WorldWideScience

Sample records for rdsd rainfall parameters

  1. Characterizing rainfall parameters which influence erosivity in southeastern Nigeria

    International Nuclear Information System (INIS)

    Obi, M.E.; Salako, F.K.

    1993-12-01

    An investigation was carried out to characterize some selected parameters which influence rainfall erosivity in southeastern Nigeria. Rainfall amount, distribution, duration, intensity, storm types, energy loads and frequency of rain events in the region were studied using data from stations located in three major agroecological zones. Raindrop size and detaching capacity were evaluated in one of the stations for two months. The mean annual rainfall erosivity values for southeastern Nigeria point to the fact that rainfall tend to be highly erosive. 25 refs, 6 figs, 8 tabs

  2. How is rainfall interception in urban area affected by meteorological parameters?

    Science.gov (United States)

    Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

    2017-04-01

    Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be

  3. Evaluation of intense rainfall parameters interpolation methods for the Espírito Santo State

    Directory of Open Access Journals (Sweden)

    José Eduardo Macedo Pezzopane

    2009-12-01

    Full Text Available Intense rainfalls are often responsible for the occurrence of undesirable processes in agricultural and forest areas, such as surface runoff, soil erosion and flooding. The knowledge of intense rainfall spatial distribution is important to agricultural watershed management, soil conservation and to the design of hydraulic structures. The present paper evaluated methods of spatial interpolation of the intense rainfall parameters (“K”, “a”, “b” and “c” for the Espírito Santo State, Brazil. Were compared real intense rainfall rates with those calculated by the interpolated intense rainfall parameters, considering different durations and return periods. Inverse distance to the 5th power IPD5 was the spatial interpolation method with better performance to spatial interpolated intense rainfall parameters.

  4. Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

    Science.gov (United States)

    Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

    2016-05-01

    Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

  5. Parameter estimation in stochastic rainfall-runoff models

    DEFF Research Database (Denmark)

    Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

    2006-01-01

    A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

  6. Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...

    African Journals Online (AJOL)

    IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...

  7. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds - the two-CN system approach

    Science.gov (United States)

    Soulis, K. X.; Valiantzas, J. D.

    2012-03-01

    The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

  8. Comparing a simple methodology to evaluate hydrodynamic parameters with rainfall simulation experiments

    Science.gov (United States)

    Di Prima, Simone; Bagarello, Vincenzo; Bautista, Inmaculada; Burguet, Maria; Cerdà, Artemi; Iovino, Massimo; Prosdocimi, Massimo

    2016-04-01

    Studying soil hydraulic properties is necessary for interpreting and simulating many hydrological processes having environmental and economic importance, such as rainfall partition into infiltration and runoff. The saturated hydraulic conductivity, Ks, exerts a dominating influence on the partitioning of rainfall in vertical and lateral flow paths. Therefore, estimates of Ks are essential for describing and modeling hydrological processes (Zimmermann et al., 2013). According to several investigations, Ks data collected by ponded infiltration tests could be expected to be unusable for interpreting field hydrological processes, and particularly infiltration. In fact, infiltration measured by ponding give us information about the soil maximum or potential infiltration rate (Cerdà, 1996). Moreover, especially for the hydrodynamic parameters, many replicated measurements have to be carried out to characterize an area of interest since they are known to vary widely both in space and time (Logsdon and Jaynes, 1996; Prieksat et al., 1994). Therefore, the technique to be applied at the near point scale should be simple and rapid. Bagarello et al. (2014) and Alagna et al. (2015) suggested that the Ks values determined by an infiltration experiment carried applying water at a relatively large distance from the soil surface could be more appropriate than those obtained with a low height of water pouring to explain surface runoff generation phenomena during intense rainfall events. These authors used the Beerkan Estimation of Soil Transfer parameters (BEST) procedure for complete soil hydraulic characterization (Lassabatère et al., 2006) to analyze the field infiltration experiment. This methodology, combining low and high height of water pouring, seems appropriate to test the effect of intense and prolonged rainfall events on the hydraulic characteristics of the surface soil layer. In fact, an intense and prolonged rainfall event has a perturbing effect on the soil surface

  9. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach

    Directory of Open Access Journals (Sweden)

    J. D. Valiantzas

    2012-03-01

    Full Text Available The Soil Conservation Service Curve Number (SCS-CN approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one, a clear physical reasoning for them is presented.

  10. Medical Meteorology: the Relationship between Meteorological Parameters (Humidity, Rainfall, Wind, and Temperature and Brucellosis in Zanjan Province

    Directory of Open Access Journals (Sweden)

    Yousefali Abedini

    2016-06-01

    Full Text Available Background: Brucellosis (Malta fever is a major contagious zoonotic disease, with economic and public health importance. Methods To assess the effect of meteorological (temperature, rainfall, humidity, and wind and climate parameters on incidence of brucellosis, brucellosis distribution and meteorological zoning maps of Zanjan Province were prepared using Inverse Distance Weighting (IDW and Kriging technique in Arc GIS medium. Zoning maps of mean temperature, rainfall, humidity, and wind were compared to brucellosis distribution maps. Results: Correlation test showed no relationship between the mean number of patients with brucellosis and any of the four meteorological parameters. Conclusion: It seems that in Zanjan province there is no correlation between brucellosis and meteorological parameters.

  11. Prediction of meteorological parameters - 3: Rainfall and droughts

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-11-01

    We describe two new methods by which rainfall and hence meteorological droughts at any location on the earth may be predicted. The first method is based upon well supported observations that rainfall distribution at a given location during any local sunspot-related temperature/heat cycle is approximately similar to the distribution during another cycle associated with approximately similar sunspot cycle provided that the two temperature/heat cycles involved are immediately preceded by approximately similar sunspot cycles. The second method is based upon the fact that rainfall belts or patterns seem to be closely related to certain spatial and time-dependent temperature/heat patterns in the earth-atmosphere system. Reasonable predictions of these temperature/heat patterns may be made, and hence the associated rainfall patterns or belts may correspondingly be predicted. Specific examples are given to illustrate the two prediction methods. (author). 12 refs, 11 figs, 1 tab

  12. Medical Meteorology: the Relationship between Meteorological Parameters (Humidity, Rainfall, Wind, and Temperature) and Brucellosis in Zanjan Province

    OpenAIRE

    Yousefali Abedini; Nahideh Mohammadi; Koorosh Kamali; Mohsen Ahadnejad; Mehdi Azari

    2016-01-01

    Background: Brucellosis (Malta fever) is a major contagious zoonotic disease, with economic and public health importance. Methods To assess the effect of meteorological (temperature, rainfall, humidity, and wind) and climate parameters on incidence of brucellosis, brucellosis distribution and meteorological zoning maps of Zanjan Province were prepared using Inverse Distance Weighting (IDW) and Kriging technique in Arc GIS medium. Zoning maps of mean temperature, rainfall, humidity, and win...

  13. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds. The two-CN system approach

    Science.gov (United States)

    Soulis, K. X.; Valiantzas, J. D.

    2011-10-01

    The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. They suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the novel hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behavior of the CN-rainfall function produced by the proposed two-CN system concept is approached theoretically, it is analyzed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous original method based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

  14. Parameter sensitivity analysis of the mixed Green-Ampt/Curve-Number method for rainfall excess estimation in small ungauged catchments

    Science.gov (United States)

    Romano, N.; Petroselli, A.; Grimaldi, S.

    2012-04-01

    With the aim of combining the practical advantages of the Soil Conservation Service - Curve Number (SCS-CN) method and Green-Ampt (GA) infiltration model, we have developed a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt). The basic concept is that, for a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model so as to distribute in time the information provided by the SCS-CN method. In a previous contribution, the proposed mixed procedure was evaluated on 100 observed events showing encouraging results. In this study, a sensitivity analysis is carried out to further explore the feasibility of applying the CN4GA tool in small ungauged catchments. The proposed mixed procedure constrains the GA model with boundary and initial conditions so that the GA soil hydraulic parameters are expected to be insensitive toward the net hyetograph peak. To verify and evaluate this behaviour, synthetic design hyetograph and synthetic rainfall time series are selected and used in a Monte Carlo analysis. The results are encouraging and confirm that the parameter variability makes the proposed method an appropriate tool for hydrologic predictions in ungauged catchments. Keywords: SCS-CN method, Green-Ampt method, rainfall excess, ungauged basins, design hydrograph, rainfall-runoff modelling.

  15. Temporal rainfall estimation using input data reduction and model inversion

    Science.gov (United States)

    Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

    2016-12-01

    Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a

  16. Spatial dependence of extreme rainfall

    Science.gov (United States)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

    2017-05-01

    This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

  17. Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

    Science.gov (United States)

    Gao, S.; Fang, N. Z.

    2017-12-01

    A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher

  18. Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Korup Andersen, Aske; Larsen, Anders Badsberg

    2017-01-01

    Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme...... includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions...... for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads...

  19. Simulation of daily rainfall through markov chain modeling

    International Nuclear Information System (INIS)

    Sadiq, N.

    2015-01-01

    Being an agricultural country, the inhabitants of dry land in cultivated areas mainly rely on the daily rainfall for watering their fields. A stochastic model based on first order Markov Chain was developed to simulate daily rainfall data for Multan, D. I. Khan, Nawabshah, Chilas and Barkhan for the period 1981-2010. Transitional probability matrices of first order Markov Chain was utilized to generate the daily rainfall occurrence while gamma distribution was used to generate the daily rainfall amount. In order to achieve the parametric values of mentioned cities, method of moments is used to estimate the shape and scale parameters which lead to synthetic sequence generation as per gamma distribution. In this study, unconditional and conditional probabilities of wet and dry days in sum with means and standard deviations are considered as the essential parameters for the simulated stochastic generation of daily rainfalls. It has been found that the computerized synthetic rainfall series concurred pretty well with the actual observed rainfall series. (author)

  20. Identification of homogeneous rainfall regimes in parts of Western ...

    Indian Academy of Sciences (India)

    to understand the environmental parameters pertaining to the sustenance of the region. Rainfall is one such parameter governing the hydrological processes crucial to agriculture planning, afforesta- tion and eco-system management. Therefore, it is essential to understand rainfall distribution and its variation in relevance to ...

  1. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2013-01-01

    Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

  2. Temperature Crosstalk Sensitivity of the Kummerow Rainfall Algorithm

    Science.gov (United States)

    Spencer, Roy W.; Petrenko, Boris

    1999-01-01

    Even though the signal source for passive microwave retrievals is thermal emission, retrievals of non-temperature geophysical parameters typically do not explicitly take into account the effects of temperature change on the retrievals. For global change research, changes in geophysical parameters (e.g. water vapor, rainfall, etc.) are referenced to the accompanying changes in temperature. If the retrieval of a certain parameter has a cross-talk response from temperature change alone, the retrievals might not be very useful for climate research. We investigated the sensitivity of the Kummerow rainfall retrieval algorithm to changes in air temperature. It was found that there was little net change in total rainfall with air temperature change. However, there were non-negligible changes within individual rain rate categories.

  3. Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

    Science.gov (United States)

    Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

    2013-04-01

    Taiwan is an active mountain belt created by the oblique collision between the northern Luzon arc and the Asian continental margin. The inherent complexities of geological nature create numerous discontinuities through rock masses and relatively steep hillside on the island. In recent years, the increase in the frequency and intensity of extreme natural events due to global warming or climate change brought significant landslides. The causes of landslides in these slopes are attributed to a number of factors. As is well known, rainfall is one of the most significant triggering factors for landslide occurrence. In general, the rainfall infiltration results in changing the suction and the moisture of soil, raising the unit weight of soil, and reducing the shear strength of soil in the colluvium of landslide. The stability of landslide is closely related to the groundwater pressure in response to rainfall infiltration, the geological and topographical conditions, and the physical and mechanical parameters. To assess the potential susceptibility to landslide, an effective modeling of rainfall-induced landslide is essential. In this paper, a deterministic approach is adopted to estimate the critical rainfall threshold of the rainfall-induced landslide. The critical rainfall threshold is defined as the accumulated rainfall while the safety factor of the slope is equal to 1.0. First, the process of deterministic approach establishes the hydrogeological conceptual model of the slope based on a series of in-situ investigations, including geological drilling, surface geological investigation, geophysical investigation, and borehole explorations. The material strength and hydraulic properties of the model were given by the field and laboratory tests. Second, the hydraulic and mechanical parameters of the model are calibrated with the long-term monitoring data. Furthermore, a two-dimensional numerical program, GeoStudio, was employed to perform the modelling practice. Finally

  4. Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

    Science.gov (United States)

    Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

    2017-04-01

    In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

  5. Evaluation of X-band polarimetric radar estimation of rainfall and rain drop size distribution parameters in West Africa

    Science.gov (United States)

    Koffi, A. K.; Gosset, M.; Zahiri, E.-P.; Ochou, A. D.; Kacou, M.; Cazenave, F.; Assamoi, P.

    2014-06-01

    As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH

  6. Extreme value analysis of rainfall data for Kalpakkam

    International Nuclear Information System (INIS)

    Sharma, Pramod Kumar; John Arul, A.; Ramkrishnan, M.; Bhuvana, V.

    2016-01-01

    Flood hazard evaluation is an important safety study for a Nuclear Power Plant. In the present study flood hazard at PFBR site due to rainfall is evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment is daily annual maximum rainfall (24 hrs data). The observed data points have been fitted using Gumbel, power law, and exponential distribution and return period has been estimated. The predicted 100 yrs return period rainfall for Kalpakkam ranges from 240 mm to 365 mm in a day and 1000 yrs return period rainfall ranges from 320 mm to 790 min in a day. To study the stationarity of rainfall data a moving window estimate of the parameters (exponential distribution) have also been performed. (author)

  7. RAINFALL AGGRESSIVENESS EVALUATION IN REGHIN HILLS USING FOURNIER INDEX

    Directory of Open Access Journals (Sweden)

    J. SZILAGYI

    2016-03-01

    Full Text Available Aggressiveness erosive force of rainfall is the express of kinetic energy and potential energy of rain water runoff on slopes. In the absence of a database for the analysis of parameters that define the torrencial rainfall, the rainfall erosivity factor was calculated by Fournier Index, Modified Fournier Index based on the monthly and annual precipitation.

  8. Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

    Science.gov (United States)

    Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

    2017-11-01

    Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

  9. Development and evaluation of a stochastic daily rainfall model with long-term variability

    Science.gov (United States)

    Kamal Chowdhury, A. F. M.; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony S.; Parana Manage, Nadeeka

    2017-12-01

    The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious.

  10. Derivation of critical rainfall thresholds for landslide in Sicily

    Science.gov (United States)

    Caracciolo, Domenico; Arnone, Elisa; Noto, Leonardo V.

    2015-04-01

    Rainfall is the primary trigger of shallow landslides that can cause fatalities, damage to properties and economic losses in many areas of the world. For this reason, determining the rainfall amount/intensity responsible for landslide occurrence is important, and may contribute to mitigate the related risk and save lives. Efforts have been made in different countries to investigate triggering conditions in order to define landslide-triggering rainfall thresholds. The rainfall thresholds are generally described by a functional relationship of power in terms of cumulated or intensity event rainfall-duration, whose parameters are estimated empirically from the analysis of historical rainfall events that triggered landslides. The aim of this paper is the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy, by focusing particularly on the role of the antecedent wet conditions. The creation of the appropriate landslide-rainfall database likely represents one of main efforts in this type of analysis. For this work, historical landslide events occurred in Sicily from 1919 to 2001 were selected from the archive of the Sistema Informativo sulle Catastrofi Idrogeologiche, developed under the project Aree Vulnerabili Italiane. The corresponding triggering precipitations were screened from the raingauges network in Sicily, maintained by the Osservatorio delle Acque - Agenzia Regionale per i Rifiuti e le Acque. In particular, a detailed analysis was carried out to identify and reconstruct the hourly rainfall events that caused the selected landslides. A bootstrapping statistical technique has been used to determine the uncertainties associated with the threshold parameters. The rainfall thresholds at different exceedance probability levels, from 1% to 10%, were defined in terms of cumulated event rainfall, E, and rainfall duration, D. The role of rainfall prior to the damaging events was taken into account by including in the analysis

  11. Variability of rainfall over small areas

    Science.gov (United States)

    Runnels, R. C.

    1983-01-01

    A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

  12. Analysis of rainfall distribution in Kelantan river basin, Malaysia

    Science.gov (United States)

    Che Ros, Faizah; Tosaka, Hiroyuki

    2018-03-01

    Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

  13. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds. The two-CN system approach

    OpenAIRE

    K. X. Soulis; J. D. Valiantzas

    2011-01-01

    The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. The...

  14. The impact of Amazonian deforestation on Amazon basin rainfall

    Science.gov (United States)

    Spracklen, D. V.; Garcia-Carreras, L.

    2015-11-01

    We completed a meta-analysis of regional and global climate model simulations (n = 96) of the impact of Amazonian deforestation on Amazon basin rainfall. Across all simulations, mean (±1σ) change in annual mean Amazon basin rainfall was -12 ± 11%. Variability in simulated rainfall was not explained by differences in model resolution or surface parameters. Across all simulations we find a negative linear relationship between rainfall and deforestation extent, although individual studies often simulate a nonlinear response. Using the linear relationship, we estimate that deforestation in 2010 has reduced annual mean rainfall across the Amazon basin by 1.8 ± 0.3%, less than the interannual variability in observed rainfall. This may explain why a reduction in Amazon rainfall has not consistently been observed. We estimate that business-as-usual deforestation (based on deforestation rates prior to 2004) would lead to an 8.1 ± 1.4% reduction in annual mean Amazon basin rainfall by 2050, greater than natural variability.

  15. Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

    Science.gov (United States)

    Costa, Veber; Fernandes, Wilson

    2017-11-01

    Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

  16. Rainfall intensity effects on crusting and mode of seedling ...

    African Journals Online (AJOL)

    Predicted changes in rainfall intensity due to climate change are likely to influence key soil health parameters, especially structural attributes and crop growth. Variations in rainfall intensity will impact crop ... and growth in these soils. Keywords: climate change, crusting, mineralogy, penetration resistance, soil organic matter ...

  17. The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

    Science.gov (United States)

    Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

    2013-01-01

    The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  18. An artificial neural network model for rainfall forecasting in Bangkok, Thailand

    Directory of Open Access Journals (Sweden)

    N. Q. Hung

    2009-08-01

    Full Text Available This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 rain gauge stations in the area were used to develop the ANN model. The developed ANN model is being applied for real time rainfall forecasting and flood management in Bangkok, Thailand. Aimed at providing forecasts in a near real time schedule, different network types were tested with different kinds of input information. Preliminary tests showed that a generalized feedforward ANN model using hyperbolic tangent transfer function achieved the best generalization of rainfall. Especially, the use of a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness, the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input data, advanced ANN model to apply with continuous data containing rainy and non-rainy period, allowed model to issue forecast at any moment. Additionally, forecasts by ANN model were compared to the convenient approach namely simple persistent method. Results show that ANN forecasts have superiority over the ones obtained by the persistent model. Rainfall forecasts for Bangkok from 1 to 3 h ahead were highly satisfactory. Sensitivity analysis indicated that the most important input parameter besides rainfall itself is the wet bulb temperature in forecasting rainfall.

  19. Assessment of the impact of a parameter estimation method for the Nash Model on selected parameters of a catchment discharge hydrograph

    Directory of Open Access Journals (Sweden)

    Kołodziejczyk Katarzyna

    2017-01-01

    Full Text Available An analysis of the usefulness of two parameter calculation methods (N and k parameters for the Nash Model was performed to transform effective rainfall into discharge based on two rainfall episodes gauged at the Kostrze gauging station as well as urban development data for the city of Cracow for 2014 and data obtained from a soil and agriculture map. The methods were the Rao et al. method and the Bajkiewicz-Grabowska method for regression relationships between instantaneous unit hydrograph model parameters and the physiographic parameters of a catchment. Effective rainfall was calculated for each rainfall episode using the SCS-CN method. A direct discharge hydrograph was calculated based on an effective rainfall hyetograph and using the Nash Model. Research has found that both studied methods yield comparable results, which indicates that both methods of effective rainfall transformation into discharge are useful. In addition, it has been shown that the impact of the Nash Model parameter estimation method on discharge hydrographs is minimal.

  20. Detecting Climate Variability in Tropical Rainfall

    Science.gov (United States)

    Berg, W.

    2004-05-01

    A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to

  1. Hydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin

    Directory of Open Access Journals (Sweden)

    Ansoumana Bodian

    2016-04-01

    Full Text Available The availability of climatic data, especially on a daily time step, has become very rare in West Africa over the last few years due to the high costs of climate data monitoring. This scarcity of climatic data is a huge obstacle to conduct hydrological studies over some watersheds. In this context, our study aimed to evaluate the capacity of Tropical Rainfall Measuring Mission (TRMM satellite data to simulate the observed runoffs over the Bafing (the main important tributary of the Senegal River before their potential integration in hydrological studies. The conceptual hydrological model GR4J (modèle du Génie Rural (Agricultural Engineering Model à 4 paramètres Journalier (4 parameters Daily has been used, calibrated and validated over the 1961–1997 period with rainfall and Potential Evapotranspiration (PET as inputs. Then, the parameters that best reflect the rainfall-runoff relation, obtained during the cross-calibration-validation phase, were used to simulate runoff over the 1998–2004 period using observed and TRMM rainfalls. The findings of this study show that there is a high consistency between satellite-based estimates and ground-based observations of rainfall. Over the 1998–2004 simulation period, the two rainfall data series show quite satisfactorily results. The output hydrographs from satellite-based estimates and ground-based observations of rainfall coincide quite well with the shape of observed hydrographs with Nash-Sutcliffe Efficiency coefficient (NSE of 0.88 and 0.80 for observed rainfalls and TRMM rainfalls, respectively.

  2. Impact of Uncertainty Characterization of Satellite Rainfall Inputs and Model Parameters on Hydrological Data Assimilation with the Ensemble Kalman Filter for Flood Prediction

    Science.gov (United States)

    Vergara, H. J.; Kirstetter, P.; Hong, Y.; Gourley, J. J.; Wang, X.

    2013-12-01

    The Ensemble Kalman Filter (EnKF) is arguably the assimilation approach that has found the widest application in hydrologic modeling. Its relatively easy implementation and computational efficiency makes it an attractive method for research and operational purposes. However, the scientific literature featuring this approach lacks guidance on how the errors in the forecast need to be characterized so as to get the required corrections from the assimilation process. Moreover, several studies have indicated that the performance of the EnKF is 'sub-optimal' when assimilating certain hydrologic observations. Likewise, some authors have suggested that the underlying assumptions of the Kalman Filter and its dependence on linear dynamics make the EnKF unsuitable for hydrologic modeling. Such assertions are often based on ineffectiveness and poor robustness of EnKF implementations resulting from restrictive specification of error characteristics and the absence of a-priori information of error magnitudes. Therefore, understanding the capabilities and limitations of the EnKF to improve hydrologic forecasts require studying its sensitivity to the manner in which errors in the hydrologic modeling system are represented through ensembles. This study presents a methodology that explores various uncertainty representation configurations to characterize the errors in the hydrologic forecasts in a data assimilation context. The uncertainty in rainfall inputs is represented through a Generalized Additive Model for Location, Scale, and Shape (GAMLSS), which provides information about second-order statistics of quantitative precipitation estimates (QPE) error. The uncertainty in model parameters is described adding perturbations based on parameters covariance information. The method allows for the identification of rainfall and parameter perturbation combinations for which the performance of the EnKF is 'optimal' given a set of objective functions. In this process, information about

  3. Incorporating rainfall uncertainty in a SWAT model: the river Zenne basin (Belgium) case study

    Science.gov (United States)

    Tolessa Leta, Olkeba; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

    2013-04-01

    The European Union Water Framework Directive (EU-WFD) called its member countries to achieve a good ecological status for all inland and coastal water bodies by 2015. According to recent studies, the river Zenne (Belgium) is far from this objective. Therefore, an interuniversity and multidisciplinary project "Towards a Good Ecological Status in the river Zenne (GESZ)" was launched to evaluate the effects of wastewater management plans on the river. In this project, different models have been developed and integrated using the Open Modelling Interface (OpenMI). The hydrologic, semi-distributed Soil and Water Assessment Tool (SWAT) is hereby used as one of the model components in the integrated modelling chain in order to model the upland catchment processes. The assessment of the uncertainty of SWAT is an essential aspect of the decision making process, in order to design robust management strategies that take the predicted uncertainties into account. Model uncertainty stems from the uncertainties on the model parameters, the input data (e.g, rainfall), the calibration data (e.g., stream flows) and on the model structure itself. The objective of this paper is to assess the first three sources of uncertainty in a SWAT model of the river Zenne basin. For the assessment of rainfall measurement uncertainty, first, we identified independent rainfall periods, based on the daily precipitation and stream flow observations and using the Water Engineering Time Series PROcessing tool (WETSPRO). Secondly, we assigned a rainfall multiplier parameter for each of the independent rainfall periods, which serves as a multiplicative input error corruption. Finally, we treated these multipliers as latent parameters in the model optimization and uncertainty analysis (UA). For parameter uncertainty assessment, due to the high number of parameters of the SWAT model, first, we screened out its most sensitive parameters using the Latin Hypercube One-factor-At-a-Time (LH-OAT) technique

  4. Rainfall Reliability Evaluation for Stability of Municipal Solid Waste Landfills on Slope

    Directory of Open Access Journals (Sweden)

    Fu-Kuo Huang

    2013-01-01

    Full Text Available A method to assess the reliability for the stability of municipal solid waste (MSW landfills on slope due to rainfall infiltration is proposed. Parameter studies are first done to explore the influence of factors on the stability of MSW. These factors include rainfall intensity, duration, pattern, and the engineering properties of MSW. Then 100 different combinations of parameters are generated and associated stability analyses of MSW on slope are performed assuming that each parameter is uniform distributed around its reason ranges. In the following, the performance of the stability of MSW is interpreted by the artificial neural network (ANN trained and verified based on the aforementioned 100 analysis results. The reliability for the stability of MSW landfills on slope is then evaluated and explored for different rainfall parameters by the ANN model with first-order reliability method (FORM and Monte Carlo simulation (MCS.

  5. Landslide prediction system for rainfall induced landslides in Slovenia (Masprem

    Directory of Open Access Journals (Sweden)

    Mateja Jemec Auflič

    2016-12-01

    Full Text Available In this paper we introduce a landslide prediction system for modelling the probabilities of landslides through time in Slovenia (Masprem. The system to forecast rainfall induced landslides is based on the landslide susceptibility map, landslide triggering rainfall threshold values and the precipitation forecasting model. Through the integrated parameters a detailed framework of the system, from conceptual to operational phases, is shown. Using fuzzy logic the landslide prediction is calculated. Potential landslide areas are forecasted on a national scale (1: 250,000 and on a local scale (1: 25,000 for fie selected municipalities where the exposure of inhabitants, buildings and different type of infrastructure is displayed, twice daily. Due to different rainfall patterns that govern landslide occurrences, the system for landslide prediction considers two different rainfall scenarios (M1 and M2. The landslides predicted by the two models are compared with a landslide inventory to validate the outputs. In this study we highlight the rainfall event that lasted from the 9th to the 14th of September 2014 when abundant precipitation triggered over 800 slope failures around Slovenia and caused large material damage. Results show that antecedent rainfall plays an important role, according to the comparisons of the model (M1 where antecedent rainfall is not considered. Although in general the landslides areas are over-predicted and largely do not correspond to the landslide inventory, the overall performance indicates that the system is able to capture the crucial factors in determining the landslide location. Additional calibration of input parameters and the landslide inventory as well as improved spatially distributed rainfall forecast data can further enhance the model's prediction.

  6. A space-time rainfall generator for highly convective Mediterranean rainstorms

    Directory of Open Access Journals (Sweden)

    S. Salsón

    2003-01-01

    Full Text Available Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rainstorm events. Special attention is placed on the analytical description of the spatial and temporal evolution of the rainfall intensities produced by the raincells. After deriving the necessary analytical results, the seven parameters of the model have been estimated by the method of moments, for each of the 30 selected rainfall events in the Jucar River Basin (ValenciaSpain – period 1991 to 2000, using 5-min aggregated rainfall data series from an automatic raingauge network.

  7. Modelling of extreme minimum rainfall using generalised extreme value distribution for Zimbabwe

    Directory of Open Access Journals (Sweden)

    Delson Chikobvu

    2015-09-01

    Full Text Available We modelled the mean annual rainfall for data recorded in Zimbabwe from 1901 to 2009. Extreme value theory was used to estimate the probabilities of meteorological droughts. Droughts can be viewed as extreme events which go beyond and/or below normal rainfall occurrences, such as exceptionally low mean annual rainfall. The duality between the distribution of the minima and maxima was exploited and used to fit the generalised extreme value distribution (GEVD to the data and hence find probabilities of extreme low levels of mean annual rainfall. The augmented Dickey Fuller test confirmed that rainfall data were stationary, while the normal quantile-quantile plot indicated that rainfall data deviated from the normality assumption at both ends of the tails of the distribution. The maximum likelihood estimation method and the Bayesian approach were used to find the parameters of the GEVD. The Kolmogorov-Smirnov and Anderson-Darling goodnessof- fit tests showed that the Weibull class of distributions was a good fit to the minima mean annual rainfall using the maximum likelihood estimation method. The mean return period estimate of a meteorological drought using the threshold value of mean annual rainfall of 473 mm was 8 years. This implies that if in the year there is a meteorological drought then another drought of the same intensity or greater is expected after 8 years. It is expected that the use of Bayesian inference may better quantify the level of uncertainty associated with the GEVD parameter estimates than with the maximum likelihood estimation method. The Markov chain Monte Carlo algorithm for the GEVD was applied to construct the model parameter estimates using the Bayesian approach. These findings are significant because results based on non-informative priors (Bayesian method and the maximum likelihood method approach are expected to be similar.

  8. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    Science.gov (United States)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  9. Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

    Science.gov (United States)

    Todorovic, Andrijana; Plavsic, Jasna

    2015-04-01

    A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters

  10. Effects of rainfalls variability and physical-chemical parameters on enteroviruses in sewage and lagoon in Yopougon, Côte d'Ivoire

    Science.gov (United States)

    Momou, Kouassi Julien; Akoua-Koffi, Chantal; Traoré, Karim Sory; Akré, Djako Sosthène; Dosso, Mireille

    2017-07-01

    The aim of this study was to assess the variability of the content of nutrients, oxidizable organic and particulate matters in raw sewage and the lagoon on the effect of rainfall. Then evaluate the impact of these changes in the concentration of enteroviruses (EVs) in waters. The sewage samples were collected at nine sampling points along the channel, which flows, into a tropical lagoon in Yopougon. Physical-chemical parameters (5-day Biochemical Oxygen Demand, Chemical Oxygen Demand, Suspended Particulate Matter, Total Phosphorus, Orthophosphate, Total Kjeldahl Nitrogen and Nitrate) as well as the concentration of EV in these waters were determined. The average numbers of EV isolated from the outlet of the channel were 9.06 × 104 PFU 100 ml-1. Consequently, EV was present in 55.55 and 33.33 % of the samples in the 2 brackish lagoon collection sites. The effect of rainfall on viral load at the both sewage and brackish lagoon environments is significant correlate (two-way ANOVA, P < 0.05). Furthermore, in lagoon environment, nutrients (Orthophosphate, Total Phosphorus), 5-day Biochemical Oxygen Demand, Chemical Oxygen Demand and Suspended Particulate Matter were significant correlated with EVs loads ( P < 0.05 by Pearson test). The overall results highlight the problem of sewage discharge into the lagoon and correlation between viral loads and water quality parameters in sewage and lagoon.

  11. Rainfall Stochastic models

    Science.gov (United States)

    Campo, M. A.; Lopez, J. J.; Rebole, J. P.

    2012-04-01

    This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

  12. Do we really use rainfall observations consistent with reality in hydrological modelling?

    Science.gov (United States)

    Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

    2017-04-01

    Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

  13. ANALYSIS OF EFFECTIVE RAINFALL INTENSITY AND WORKING RAINFALL FOR BASIC WARNING CRITERIA DEVELOPMENT ON LAHAR FLOW EVENT

    Directory of Open Access Journals (Sweden)

    Fitriyadi Fitriyadi

    2015-05-01

    The research results showed that the number of reviewed serial rain with total value ≥ 80 mm is 9.28% of the whole serial rain, and 12.5% of them caused lahar flow in Gendol River. Debris flow occurrence probability on total rainfall amount of ≥ 80 mm that may occur on Gendol River amounted to 1.89%. This value represents less possibility of debris flow in Gendol River, this is due to the rain conditions in the Gendol Watershed different from the situation in Japan as well as the limitations of the available data. It is recommended for further research on the limitation of total rainfall in accordance with the conditions in Gendol Watershed by considering other parameters becoming the lahar flow controller factor. Further, it is necessary to perform the analysis using rain catchment method by averaging rainfall values on each of serial rain.

  14. Regionalization of monthly rainfall erosivity patternsin Switzerland

    Science.gov (United States)

    Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

    2016-10-01

    One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

  15. Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

    OpenAIRE

    Ghazavi, Reza; Moafi Rabori, Ali; Ahadnejad Reveshty, Mohsen

    2016-01-01

    Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormw...

  16. Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

    Science.gov (United States)

    Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

    2017-04-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

  17. Monthly Rainfall Erosivity Assessment for Switzerland

    Science.gov (United States)

    Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

  18. Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

    Science.gov (United States)

    Santos, Monica; Fragoso, Marcelo

    2010-05-01

    Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

  19. Assessment of runoff contributing catchment areas in rainfall runoff modelling

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Johansen, C.; Schaarup-Jensen, Kjeld

    2006-01-01

    In numerical modelling of rainfall caused runoff in urban sewer systems an essential parameter is the hydrological reduction factor which defines the percentage of the impervious area contributing to the surface flow towards the sewer. As the hydrological processes during a rainfall are difficult...... to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literature values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literature values of the hydrological reduction factor are over-estimated for this type of catchment. In addition, different catchment descriptions...

  20. River catchment rainfall series analysis using additive Holt-Winters method

    Science.gov (United States)

    Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

    2016-03-01

    Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

  1. Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

    Science.gov (United States)

    Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

    2015-12-01

    Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

  2. Self-adaptive Green-Ampt infiltration parameters obtained from measured moisture processes

    Directory of Open Access Journals (Sweden)

    Long Xiang

    2016-07-01

    Full Text Available The Green-Ampt (G-A infiltration model (i.e., the G-A model is often used to characterize the infiltration process in hydrology. The parameters of the G-A model are critical in applications for the prediction of infiltration and associated rainfall-runoff processes. Previous approaches to determining the G-A parameters have depended on pedotransfer functions (PTFs or estimates from experimental results, usually without providing optimum values. In this study, rainfall simulators with soil moisture measurements were used to generate rainfall in various experimental plots. Observed runoff data and soil moisture dynamic data were jointly used to yield the infiltration processes, and an improved self-adaptive method was used to optimize the G-A parameters for various types of soil under different rainfall conditions. The two G-A parameters, i.e., the effective hydraulic conductivity and the effective capillary drive at the wetting front, were determined simultaneously to describe the relationships between rainfall, runoff, and infiltration processes. Through a designed experiment, the method for determining the G-A parameters was proved to be reliable in reflecting the effects of pedologic background in G-A type infiltration cases and deriving the optimum G-A parameters. Unlike PTF methods, this approach estimates the G-A parameters directly from infiltration curves obtained from rainfall simulation experiments so that it can be used to determine site-specific parameters. This study provides a self-adaptive method of optimizing the G-A parameters through designed field experiments. The parameters derived from field-measured rainfall-infiltration processes are more reliable and applicable to hydrological models.

  3. Heterogeneity of Dutch rainfall

    NARCIS (Netherlands)

    Witter, J.V.

    1984-01-01

    Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

  4. Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

    Science.gov (United States)

    Huang, Y. F.; Tsang, Y. P.

    2017-12-01

    Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

  5. Modelling rainfall amounts using mixed-gamma model for Kuantan district

    Science.gov (United States)

    Zakaria, Roslinazairimah; Moslim, Nor Hafizah

    2017-05-01

    An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

  6. Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

    Science.gov (United States)

    Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

    2009-04-01

    Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

  7. Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

    Science.gov (United States)

    Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

    2011-12-01

    In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C

  8. A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

    Science.gov (United States)

    Zorzetto, E.; Marani, M.

    2017-12-01

    The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

  9. Rainfall Erosivity in Europe

    DEFF Research Database (Denmark)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

    2015-01-01

    Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

  10. Erosivity factor in the Universal Soil Loss Equation estimated from Finnish rainfall data

    Directory of Open Access Journals (Sweden)

    Maximilian Posch

    1993-07-01

    Full Text Available Continuous rainfall data recorded for many years at 8 stations in Finland were used to estimate rainfall erosivity, a quantity needed for soil loss predictions with the Universal Soil Loss Equation (USLE. The obtained erosivity values were then used to determine the 2 parameters of a power-law function describing the relationship between daily precipitation and erosivity. This function is of importance in erosion modeling at locations where no breakpoint rainfall data are available. The parameters of the power-law were estimated both by linear regression of the log-transformed data and by non-linear least-square fitting of the original data. Results indicate a considerable seasonal (monthly variation of the erosivity, whereas the spatial variation over Finland is rather small.

  11. Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring

    Science.gov (United States)

    Zhang, Mingkai; Liu, Yanchen; Cheng, Xun; Zhu, David Z.; Shi, Hanchang; Yuan, Zhiguo

    2018-03-01

    Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously.

  12. Using rainfall simulations to understand the relationship between precipitation, soil crust and infiltration in four agricultural soils

    Science.gov (United States)

    Angulo-Martinez, Marta; Alastrué, Juan; Moret-Fernández, David; Beguería, Santiago; López, Mariví; Navas, Ana

    2017-04-01

    Rainfall simulation experiments were carried out in order to study soil crust formation and its relation with soil infiltration parameters—sorptivity (S) and hydraulic conductivity (K)—on four common agricultural soils with contrasted properties; namely, Cambisol, Gypsisol, Solonchak, and Solonetz. Three different rainfall simulations, replicated three times each of them, were performed over the soils. Prior to rainfall simulations all soils were mechanically tilled with a rototiller to create similar soil surface conditions and homogeneous soils. Rainfall simulation parameters were monitored in real time by a Thies Laser Precipitation Monitor, allowing a complete characterization of simulated rainfall microphysics (drop size and velocity distributions) and integrated variables (accumulated rainfall, intensity and kinetic energy). Once soils dried after the simulations, soil penetration resistance was measured and soil hydraulic parameters, S and K, were estimated using the disc infiltrometry technique. There was little variation in rainfall parameters among simulations. Mean intensity and mean median diameter (D50) varied in simulations 1 ( 0.5 bar), 2 ( 0.8 bar) and 3 ( 1.2 bar) from 26.5 mm h-1 and 0.43 mm (s1) to 40.5 mm h-1 and 0.54 mm (s2) and 41.1 mm h-1 and 0.56 mm for (s3), respectively. Crust formation by soil was explained by D50 and subsequently by the total precipitation amount and the percentage of silt and clay in soil, being Cambisol and Gypsisol the soils that showed more increase in penetration resistance by simulation. All soils showed similar S values by simulations which were explained by rainfall intensity. Different patterns of K were shown by the four soils, which were explained by the combined effect of D50 and intensity, together with soil physico-chemical properties. This study highlights the importance of monitoring all precipitation parameters to determine their effect on different soil processes.

  13. Real Rainfall Time Series for Storm Sewer Design

    DEFF Research Database (Denmark)

    Larsen, Torben

    The paper describes a simulation method for the design of retention storages, overflows etc. in storm sewer systems. The method is based on computer simulation with real rainfall time series as input ans with the aply of a simple transfer model of the ARMA-type (autoregressiv moving average model......) as the model of the storm sewer system. The output of the simulation is the frequency distribution of the peak flow, overflow volume etc. from the overflow or retention storage. The parameters in the transfer model is found either from rainfall/runoff measurements in the catchment or from one or a few...

  14. Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

    Directory of Open Access Journals (Sweden)

    Tingting Shi

    2015-09-01

    Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

  15. Rainfall simulation in education

    Science.gov (United States)

    Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

    2016-04-01

    Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

  16. Rainfall: State of the Science

    Science.gov (United States)

    Testik, Firat Y.; Gebremichael, Mekonnen

    Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

  17. Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

    Science.gov (United States)

    Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

    2015-12-01

    The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

  18. Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

    Directory of Open Access Journals (Sweden)

    F. Serinaldi

    2010-12-01

    Full Text Available Discrete multiplicative random cascade (MRC models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC model based on beta distribution and a discrete canonical beta-logstable (BLS, the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM model, which is used as a physically based benchmark model. Monte Carlo simulations point out

  19. Rain storm models and the relationship between their parameters

    NARCIS (Netherlands)

    Stol, P.T.

    1977-01-01

    Rainfall interstation correlation functions can be obtained with the aid of analytic rainfall or storm models. Since alternative storm models have different mathematical formulas, comparison should be based on equallity of parameters like storm diameter, mean rainfall amount, storm maximum or total

  20. Sensitivity of point scale surface runoff predictions to rainfall resolution

    Directory of Open Access Journals (Sweden)

    A. J. Hearman

    2007-01-01

    Full Text Available This paper investigates the effects of using non-linear, high resolution rainfall, compared to time averaged rainfall on the triggering of hydrologic thresholds and therefore model predictions of infiltration excess and saturation excess runoff at the point scale. The bounded random cascade model, parameterized to three locations in Western Australia, was used to scale rainfall intensities at various time resolutions ranging from 1.875 min to 2 h. A one dimensional, conceptual rainfall partitioning model was used that instantaneously partitioned water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store were controlled by thresholds. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and in turn, relating these to average storm intensities. For all soil types, we related maximum infiltration capacities to average storm intensities (k* and were able to show where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k*=0.4 and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k*>2 for all three rainfall locations tested. For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g* and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g*<2. Infiltration excess predicted from high resolution rainfall was short and intense, whereas saturation excess produced from low resolution rainfall was more constant and less intense. This has important implications for the accuracy of current hydrological models that use time

  1. [Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

    Science.gov (United States)

    Li, Yi; Shao, Ming'an

    2006-12-01

    With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

  2. Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

    Science.gov (United States)

    Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

    2017-04-01

    Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

  3. Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

    Science.gov (United States)

    Caracciolo, Clelia; Prodi, Franco; Uijlenhoet, Remko

    2006-11-01

    The performances of two couples of disdrometers based on different measuring principles are compared: a classical Joss-Waldvogel disdrometer and a recently developed device, called the Pludix tested in Ferrara, Italy, and Pludix and the two-dimensional video disdrometer (2DVD) tested in Cabauw, The Netherlands. First, the measuring principles of the different instruments are presented and compared. Secondly, the performances of the two pairs of disdrometers are analysed by comparing their rain amounts with nearby tipping bucket rain gauges and the inferred drop size distributions. The most important rainfall integral parameters (e.g. rain rate and radar reflectivity) and drop size distribution parameters are also analysed and compared. The data set for Ferrara comprises 13 rainfall events, with a total of 20 mm of rainfall and a maximum rain rate of 4 mm h - 1 . The data set for Cabauw consists of 9 events, with 25-50 mm of rainfall and a maximum rain rate of 20-40 mm h - 1 . The Pludix tends to underestimate slightly the bulk rainfall variables in less intense events, whereas it tends to overestimate with respect to the other instruments in heavier events. The correspondence of the inferred drop size distributions with those measured by the other disdrometers is reasonable, particularly with the Joss-Waldvogel disdrometer. Considering that the Pludix is still in a calibration and testing phase, the reported results are encouraging. A new signal inversion algorithm, which will allow the detection of rain drops throughout the entire diameter interval between 0.3 and 7.0 mm, is under development.

  4. Darfur: rainfall and conflict

    International Nuclear Information System (INIS)

    Kevane, Michael; Gray, Leslie

    2008-01-01

    Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972-2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa

  5. Darfur: rainfall and conflict

    Science.gov (United States)

    Kevane, Michael; Gray, Leslie

    2008-07-01

    Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

  6. The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2012-09-01

    Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

  7. Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

    Science.gov (United States)

    Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

    2017-12-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

  8. Real Rainfall Time Series for Storm Sewer Design

    DEFF Research Database (Denmark)

    Larsen, Torben

    1981-01-01

    to a storm sewer system. The output of the simulation is the frequency distribution of the peak flow, overflow volume etc. from the overflow or the retention storage. The parameters in the transfer model are found either from rainfall/runoff measurements in the catchment or from one or more simulations...

  9. Nonstationarities in Catchment Response According to Basin and Rainfall Characteristics: Application to Korean Watershed

    Science.gov (United States)

    Kwon, Hyun-Han; Kim, Jin-Guk; Jung, Il-Won

    2015-04-01

    It must be acknowledged that application of rainfall-runoff models to simulate rainfall-runoff processes are successful in gauged watershed. However, there still remain some issues that will need to be further discussed. In particular, the quantitive representation of nonstationarity issue in basin response (e.g. concentration time, storage coefficient and roughness) along with ungauged watershed needs to be studied. In this regard, this study aims to investigate nonstationarity in basin response so as to potentially provide useful information in simulating runoff processes in ungauged watershed. For this purpose, HEC-1 rainfall-runoff model was mainly utilized. In addition, this study combined HEC-1 model with Bayesian statistical model to estimate uncertainty of the parameters which is called Bayesian HEC-1 (BHEC-1). The proposed rainfall-runofall model is applied to various catchments along with various rainfall patterns to understand nonstationarities in catchment response. Further discussion about the nonstationarity in catchment response and possible regionalization of the parameters for ungauged watershed are discussed. KEYWORDS: Nonstationary, Catchment response, Uncertainty, Bayesian Acknowledgement This research was supported by a Grant (13SCIPA01) from Smart Civil Infrastructure Research Program funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and the Korea Agency for Infrastructure Technology Advancement (KAIA).

  10. Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation

    Science.gov (United States)

    Nyabeze, W. R.

    A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.

  11. Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

    Science.gov (United States)

    Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

    2017-12-01

    In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

  12. The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

    Science.gov (United States)

    Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

    2015-07-01

    This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

  13. Markov modulated Poisson process models incorporating covariates for rainfall intensity.

    Science.gov (United States)

    Thayakaran, R; Ramesh, N I

    2013-01-01

    Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.

  14. Integrating a Linear Signal Model with Groundwater and Rainfall time-series on the Characteristic Identification of Groundwater Systems

    Science.gov (United States)

    Chen, Yu-Wen; Wang, Yetmen; Chang, Liang-Cheng

    2017-04-01

    Groundwater resources play a vital role on regional supply. To avoid irreversible environmental impact such as land subsidence, the characteristic identification of groundwater system is crucial before sustainable management of groundwater resource. This study proposes a signal process approach to identify the character of groundwater systems based on long-time hydrologic observations include groundwater level and rainfall. The study process contains two steps. First, a linear signal model (LSM) is constructed and calibrated to simulate the variation of underground hydrology based on the time series of groundwater levels and rainfall. The mass balance equation of the proposed LSM contains three major terms contain net rate of horizontal exchange, rate of rainfall recharge and rate of pumpage and four parameters are required to calibrate. Because reliable records of pumpage is rare, the time-variant groundwater amplitudes of daily frequency (P ) calculated by STFT are assumed as linear indicators of puamage instead of pumpage records. Time series obtained from 39 observation wells and 50 rainfall stations in and around the study area, Pintung Plain, are paired for model construction. Second, the well-calibrated parameters of the linear signal model can be used to interpret the characteristic of groundwater system. For example, the rainfall recharge coefficient (γ) means the transform ratio between rainfall intention and groundwater level raise. The area around the observation well with higher γ means that the saturated zone here is easily affected by rainfall events and the material of unsaturated zone might be gravel or coarse sand with high infiltration ratio. Considering the spatial distribution of γ, the values of γ decrease from the upstream to the downstream of major rivers and also are correlated to the spatial distribution of grain size of surface soil. Via the time-series of groundwater levels and rainfall, the well-calibrated parameters of LSM have

  15. Rainfall interception from a lowland tropical rainforest in Brunei

    Science.gov (United States)

    Dykes, A. P.

    1997-12-01

    Results from a programme of throughfall measurements in a lowland tropical rainforest in Brunei, northwest Borneo, indicate that interception losses amount to 18% of the gross incident rainfall. The high annual rainfall experienced by the study area results in annual interception losses of around 800 mm, which may result in total annual evapotranspiration losses significantly higher than in other rainforest locations. An improved version of Gash's analytical interception model is tested on the available data using assumed values for the "forest" parameters, and is found to predict interception losses extremely well. The model predictions are based on an estimated evaporation rate during rainfall of 0.71 mm h -1. This is significantly higher than has been reported in other tropical studies. It is concluded that these results are distinctive when compared with previous results from rainforests, and that further, detailed work is required to establish whether the enhanced evaporation rate is due to advective effects associated with the maritime setting of the study area.

  16. Solar control on the cloud liquid water content and integrated water vapor associated with monsoon rainfall over India

    Science.gov (United States)

    Maitra, Animesh; Saha, Upal; Adhikari, Arpita

    2014-12-01

    A long-term observation over three solar cycles indicates a perceptible influence of solar activity on rainfall and associated parameters in the Indian region. This paper attempts to reveal the solar control on the cloud liquid water content (LWC) and integrated water vapor (IWV) along with Indian Summer Monsoon (ISM) rainfall during the period of 1977-2012 over nine different Indian stations. Cloud LWC and IWV are positively correlated with each other. An anti-correlation is observed between the Sunspot Number (SSN) and ISM rainfall for a majority of the stations and a poor positive correlation obtained for other locations. Cloud LWC and IWV possess positive correlations with Galactic Cosmic Rays (GCR) and SSN respectively for most of the stations. The wavelet analyses of SSN, ISM rainfall, cloud LWC and IWV have been performed to investigate the periodic characteristics of climatic parameters and also to indicate the varying relationship of solar activity with ISM rainfall, cloud LWC and IWV. SSN, ISM rainfall and IWV are found to have a peak at around 10.3 years whereas a dip is observed at that particular period for cloud LWC.

  17. Numerical representation of rainfall field in the Yarmouk River Basin

    Science.gov (United States)

    Shentsis, Isabella; Inbar, Nimrod; Magri, Fabien; Rosenthal, Eliyahu

    2017-04-01

    Rainfall is the decisive factors in evaluating the water balance of river basins and aquifers. Accepted methods rely on interpolation and extrapolation of gauged rain to regular grid with high dependence on the density and regularity of network, considering the relief complexity. We propose an alternative method that makes up to those restrictions by taking into account additional physical features of the rain field. The method applies to areas with (i) complex plain- and mountainous topography, which means inhomogeneity of the rainfall field and (ii) non-uniform distribution of a rain gauge network with partial lack of observations. The rain model is implemented in two steps: 1. Study of the rainfall field, based on the climatic data (mean annual precipitation), its description by the function of elevation and other factors, and estimation of model parameters (normalized coefficients of the Taylor series); 2. Estimation of rainfall in each historical year using the available data (less complete and irregular versus climatic data) as well as the a-priori known parameters (by the basic hypothesis on inter-annual stability of the model parameters). The proposed method was developed by Shentsis (1990) for hydrological forecasting in Central Asia and was later adapted to the Lake Kinneret Basin. Here this model (the first step) is applied to the Yarmouk River Basin. The Yarmouk River is the largest tributary of the Jordan River. Its transboundary basin (6,833 sq. km) extends over Syria (5,257 sq.km), Jordan (1,379 sq. km) and Israel (197 sq. km). Altitude varies from 1800 m (and more) to -235 m asl. The total number of rain stations in use is 36 (17 in Syria, 19 in Jordan). There is evidently lack and non-uniform distribution of a rain gauge network in Syria. The Yarmouk Basin was divided into five regions considering typical relationship between mean annual rain and elevation for each region. Generally, the borders of regions correspond to the common topographic

  18. Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

    Science.gov (United States)

    Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

    2017-12-01

    The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features

  19. Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

    Science.gov (United States)

    Aronica, G. T.; Candela, A.

    2007-12-01

    SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

  20. A space-time hybrid hourly rainfall model for derived flood frequency analysis

    Directory of Open Access Journals (Sweden)

    U. Haberlandt

    2008-12-01

    Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

    First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

  1. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  2. Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

    Directory of Open Access Journals (Sweden)

    S. Raia

    2014-03-01

    Full Text Available Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For this purpose, we have modified the transient rainfall infiltration and grid-based regional slope-stability analysis (TRIGRS code. The new code (TRIGRS-P adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs

  3. Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

    Science.gov (United States)

    Raia, S.; Alvioli, M.; Rossi, M.; Baum, R.L.; Godt, J.W.; Guzzetti, F.

    2013-01-01

    Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters

  4. Experimental Investigation of Rainfall Impact on Overland Flow Driven Erosion Processes and Flow Hydrodynamics on a Steep Hillslope

    Science.gov (United States)

    Tian, P.; Xu, X.; Pan, C.; Hsu, K. L.; Yang, T.

    2016-12-01

    Few attempts have been made to investigate the quantitative effects of rainfall on overland flow driven erosion processes and flow hydrodynamics on steep hillslopes under field conditions. Field experiments were performed in flows for six inflow rates (q: 6-36 Lmin-1m-1) with and without rainfall (60 mm h-1) on a steep slope (26°) to investigate: (1) the quantitative effects of rainfall on runoff and sediment yield processes, and flow hydrodynamics; (2) the effect of interaction between rainfall and overland flow on soil loss. Results showed that the rainfall increased runoff coefficients and the fluctuation of temporal variations in runoff. The rainfall significantly increased soil loss (10.6-68.0%), but this increment declined as q increased. When the interrill erosion dominated (q=6 Lmin-1m-1), the increment in the rill erosion was 1.5 times that in the interrill erosion, and the effect of the interaction on soil loss was negative. When the rill erosion dominated (q=6-36 Lmin-1m-1), the increment in the interrill erosion was 1.7-8.8 times that in the rill erosion, and the effect of the interaction on soil loss became positive. The rainfall was conducive to the development of rills especially for low inflow rates. The rainfall always decreased interrill flow velocity, decreased rill flow velocity (q=6-24 Lmin-1m-1), and enhanced the spatial uniformity of the velocity distribution. Under rainfall disturbance, flow depth, Reynolds number (Re) and resistance were increased but Froude number was reduced, and lower Re was needed to transform a laminar flow to turbulent flow. The rainfall significantly increased flow shear stress (τ) and stream power (φ), with the most sensitive parameters to sediment yield being τ (R2=0.994) and φ (R2=0.993), respectively, for non-rainfall and rainfall conditions. Compared to non-rainfall conditions, there was a reduction in the critical hydrodynamic parameters of mean flow velocity, τ, and φ by the rainfall. These findings

  5. Rainfall control of debris-flow triggering in the Réal Torrent, Southern French Prealps

    Science.gov (United States)

    Bel, Coraline; Liébault, Frédéric; Navratil, Oldrich; Eckert, Nicolas; Bellot, Hervé; Fontaine, Firmin; Laigle, Dominique

    2017-08-01

    This paper investigates the occurrence of debris flow due to rainfall forcing in the Réal Torrent, a very active debris flow-prone catchment in the Southern French Prealps. The study is supported by a 4-year record of flow responses and rainfall events, from three high-frequency monitoring stations equipped with geophones, flow stage sensors, digital cameras, and rain gauges measuring rainfall at 5-min intervals. The classic method of rainfall intensity-duration (ID) threshold was used, and a specific emphasis was placed on the objective identification of rainfall events, as well as on the discrimination of flow responses observed above the ID threshold. The results show that parameters used to identify rainfall events significantly affect the ID threshold and are likely to explain part of the threshold variability reported in the literature. This is especially the case regarding the minimum duration of rain interruption (MDRI) between two distinct rainfall events. In the Réal Torrent, a 3-h MDRI appears to be representative of the local rainfall regime. A systematic increase in the ID threshold with drainage area was also observed from the comparison of the three stations, as well as from the compilation of data from experimental debris-flow catchments. A logistic regression used to separate flow responses above the ID threshold, revealed that the best predictors are the 5-min maximum rainfall intensity, the 48-h antecedent rainfall, the rainfall amount and the number of days elapsed since the end of winter (used as a proxy of sediment supply). This emphasizes the critical role played by short intense rainfall sequences that are only detectable using high time-resolution rainfall records. It also highlights the significant influence of antecedent conditions and the seasonal fluctuations of sediment supply.

  6. Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

    Science.gov (United States)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

    2017-11-01

    This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

  7. Rainfall recharge estimation on a nation-wide scale using satellite information in New Zealand

    Science.gov (United States)

    Westerhoff, Rogier; White, Paul; Moore, Catherine

    2015-04-01

    Models of rainfall recharge to groundwater are challenged by the need to combine uncertain estimates of rainfall, evapotranspiration, terrain slope, and unsaturated zone parameters (e.g., soil drainage and hydraulic conductivity of the subsurface). Therefore, rainfall recharge is easiest to estimate on a local scale in well-drained plains, where it is known that rainfall directly recharges groundwater. In New Zealand, this simplified approach works in the policy framework of regional councils, who manage water allocation at the aquifer and sub-catchment scales. However, a consistent overview of rainfall recharge is difficult to obtain at catchment and national scale: in addition to data uncertainties, data formats are inconsistent between catchments; the density of ground observations, where these exist, differs across regions; each region typically uses different local models for estimating recharge components; and different methods and ground observations are used for calibration and validation of these models. The research described in this paper therefore presents a nation-wide approach to estimate rainfall recharge in New Zealand. The method used is a soil water balance approach, with input data from national rainfall and soil and geology databases. Satellite data (i.e., evapotranspiration, soil moisture, and terrain) aid in the improved calculation of rainfall recharge, especially in data-sparse areas. A first version of the model has been implemented on a 1 km x 1 km and monthly scale between 2000 and 2013. A further version will include a quantification of recharge estimate uncertainty: with both "top down" input error propagation methods and catchment-wide "bottom up" assessments of integrated uncertainty being adopted. Using one nation-wide methodology opens up new possibilities: it can, for example, help in more consistent estimation of water budgets, groundwater fluxes, or other hydrological parameters. Since recharge is estimated for the entire land

  8. Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

    Science.gov (United States)

    Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

    2015-04-01

    To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a

  9. Micro-Physical characterisation of Convective & Stratiform Rainfall at Tropics

    Science.gov (United States)

    Sreekanth, T. S.

    Large Micro-Physical characterisation of Convective & Stratiform Rainfall at Tropics begin{center} begin{center} Sreekanth T S*, Suby Symon*, G. Mohan Kumar (1) , and V Sasi Kumar (2) *Centre for Earth Science Studies, Akkulam, Thiruvananthapuram (1) D-330, Swathi Nagar, West Fort, Thiruvananthapuram 695023 (2) 32. NCC Nagar, Peroorkada, Thiruvananthapuram ABSTRACT Micro-physical parameters of rainfall such as rain drop size & fall speed distribution, mass weighted mean diameter, Total no. of rain drops, Normalisation parameters for rain intensity, maximum & minimum drop diameter from different rain intensity ranges, from both stratiform and convective rain events were analysed. Convective -Stratiform classification was done by the method followed by Testud et al (2001) and as an additional information electrical behaviour of clouds from Atmospheric Electric Field Mill was also used. Events which cannot be included in both types are termed as 'mixed precipitation' and identified separately. For the three years 2011, 2012 & 2013, rain events from both convective & stratiform origin are identified from three seasons viz Pre-Monsoon (March-May), Monsoon (June-September) and Post-Monsoon (October-December). Micro-physical characterisation was done for each rain events and analysed. Ground based and radar observations were made and classification of stratiform and convective rainfall was done by the method followed by Testud et al (2001). Radar bright band and non bright band analysis was done for confimation of stratifom and convective rain respectievely. Atmospheric electric field data from electric field mill is also used for confirmation of convection during convective events. Statistical analyses revealed that the standard deviation of rain drop size in higher rain rates are higher than in lower rain rates. Normalised drop size distribution is ploted for selected events from both forms. Inter relations between various precipitation parameters were analysed in three

  10. Automatic Extraction of High-Resolution Rainfall Series from Rainfall Strip Charts

    Science.gov (United States)

    Saa-Requejo, Antonio; Valencia, Jose Luis; Garrido, Alberto; Tarquis, Ana M.

    2015-04-01

    Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including climate, soil, topography, cropping and land management practices among others. Most models for soil erosion or hydrological processes need an accurate storm characterization. However, this data are not always available and in some cases indirect models are generated to fill this gap. In Spain, the rain intensity data known for time periods less than 24 hours back to 1924 and many studies are limited by it. In many cases this data is stored in rainfall strip charts in the meteorological stations but haven't been transfer in a numerical form. To overcome this deficiency in the raw data a process of information extraction from large amounts of rainfall strip charts is implemented by means of computer software. The method has been developed that largely automates the intensive-labour extraction work based on van Piggelen et al. (2011). The method consists of the following five basic steps: 1) scanning the charts to high-resolution digital images, 2) manually and visually registering relevant meta information from charts and pre-processing, 3) applying automatic curve extraction software in a batch process to determine the coordinates of cumulative rainfall lines on the images (main step), 4) post processing the curves that were not correctly determined in step 3, and 5) aggregating the cumulative rainfall in pixel coordinates to the desired time resolution. A colour detection procedure is introduced that automatically separates the background of the charts and rolls from the grid and subsequently the rainfall curve. The rainfall curve is detected by minimization of a cost function. Some utilities have been added to improve the previous work and automates some auxiliary processes: readjust the bands properly, merge bands when

  11. [Monitoring and analysis on evolution process of rainfall runoff water quality in urban area].

    Science.gov (United States)

    Dong, Wen; Li, Huai-En; Li, Jia-Ke

    2013-02-01

    In order to find the water quality evolution law and pollution characteristics of the rainfall runoff from undisturbed to the neighborhood exit, 6 times evolution process of rainfall runoff water quality were monitored and analyzed from July to October in 2011, and contrasted the clarification efficiency of the grassland to the roof runoff rudimentarily at the same time. The research showed: 1. the results of the comparison from "undisturbed, rainfall-roof, rainfall runoff-road, rainfall-runoff the neighborhood exit runoff " showed that the water quality of the undisturbed rain was better than that from the roof and the neighborhood exist, but the road rainfall runoff water quality was the worst; 2. the average concentrations of the parameters such as COD, ammonia nitrogen and total nitrogen all exceeded the Fifth Class of the Surface Water Quality Standard except for the soluble total phosphorus from undisturbed rainfall to the neighborhood exit; 3. the runoff water quality of the short early fine days was better than that of long early fine days, and the last runoff water quality was better than that of the initial runoff in the same rainfall process; 4. the concentration reduction of the grassland was notable, and the reduction rate of the grassland which is 1.0 meter wide of the roof runoff pollutants such as COD and nitrogen reached 30%.

  12. Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

    Science.gov (United States)

    Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

    2012-08-01

    This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

  13. Regional frequency analysis of short duration rainfall extremes using gridded daily rainfall data as co-variate

    DEFF Research Database (Denmark)

    Madsen, H.; Gregersen, Ida Bülow; Rosbjerg, Dan

    2017-01-01

    with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour the mean intensity is significantly...... correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both...

  14. Rainfall prediction with backpropagation method

    Science.gov (United States)

    Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

    2018-03-01

    Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

  15. Rainfall runoff and erosion in Napa Valley vineyards: effects of slope, cover and surface roughness

    Science.gov (United States)

    Battany, M. C.; Grismer, M. E.

    2000-05-01

    The effects of slope, cover and surface roughness on rainfall runoff, infiltration and erosion were determined at two sites on a hillside vineyard in Napa County, California, using a portable rainfall simulator. Rainfall simulation experiments were carried out at two sites, with five replications of three slope treatments (5%, 10% and 15%) in a randomized block design at each site (0%bsol;64 m2 plots). Prior to initiation of the rainfall simulations, detailed assessments, not considered in previous vineyard studies, of soil slope, cover and surface roughness were conducted. Significant correlations (at the 95% confidence level) between the physical characteristics of slope, cover and surface roughness, with total infiltration, runoff, sediment discharge and average sediment concentration were obtained. The extent of soil cracking, a physical characteristic not directly measured, also affected analysis of the rainfall-runoff-erosion process. Average cumulative runoff and cumulative sediment discharge from site A was 87% and 242% greater, respectively, than at site B. This difference was linked to the greater cover, extent of soil cracking and bulk density at site B than at site A. The extent of soil cover was the dominant factor limiting soil loss when soil cracking was not present. Field slopes within the range of 4-16%, although a statistically significant factor affecting soil losses, had only a minor impact on the amount of soil loss. The Horton infiltration equation fit field data better than the modified Philip's equation. Owing to the variability in the treatment parameters affecting the rainfall-runoff-erosion process, use of ANOVA methods were found to be inappropriate; multiple-factor regression analysis was more useful for identifying significant parameters. Overall, we obtained similar values for soil erosion parameters as those obtained from vineyard erosion studies in Europe. In addition, it appears that results from the small plot studies may be

  16. Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

    Science.gov (United States)

    Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

    2017-12-01

    South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31

  17. Rainfall spatiotemporal variability relation to wetlands hydroperiods

    Science.gov (United States)

    Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

    2017-04-01

    Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

  18. Prediction of Rainfall-Induced Landslides

    Science.gov (United States)

    Nadim, F.; Sandersen, F.

    2009-12-01

    -mum intensity of rain within a short period of time (1-3 hours) during a storm is most critical for triggering of debris flows. Therefore empirical methods developed for prediction of initiation of debris flows include both long-duration and short-duration rain-fall. More recent research has focused on the spatial distribution of unstable areas and on better spatial resolution of the occurrence of landslide-triggering precipitation events. Spatial distribution can be assessed by analyzing the stability conditions for shallow landslides if reasonable estimates of strength parameters are available. In general, two different approaches may be adopted for the assessment of threshold values for rainfall-induced landslides: empirical methods that are based on past observations and statistical analyses, and numerical analyses that are based on geo-mechanical modelling. The former approach together with very short-term weather forecasting (now-casting) are commonly used in the design of early warning systems for debris flows.

  19. FROM RAINFALL DATA

    Directory of Open Access Journals (Sweden)

    Sisuru Sendanayake

    2015-01-01

    Full Text Available There are many correlations developed to predict incident solar radiation at a givenlocation developed based on geographical and meteorological parameters. However, allcorrelations depend on accurate measurement and availability of weather data such assunshine duration, cloud cover, relative humidity, maximum and minimumtemperatures etc, which essentially is a costly exercise in terms of equipment andlabour. Sri Lanka being a tropical island of latitudinal change of only 30 along thelength of the country, the meteorological factors govern the amount of incidentradiation. Considering the cloud formation and wind patterns over Sri Lanka as well asthe seasonal rainfall patterns, it can be observed that the mean number of rainy dayscan be used to predict the monthly average daily global radiation which can be used forcalculations in solar related activities conveniently.

  20. Radar rainfall image repair techniques

    Directory of Open Access Journals (Sweden)

    Stephen M. Wesson

    2004-01-01

    Full Text Available There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the 'screening effect' that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

  1. Reducing bias in rainfall estimates from microwave links by considering variable drop size distribution

    Science.gov (United States)

    Fencl, Martin; Jörg, Rieckermann; Vojtěch, Bareš

    2015-04-01

    Commercial microwave links (MWL) are point-to-point radio systems which are used in backhaul networks of cellular operators. For several years, they have been suggested as rainfall sensors complementary to rain gauges and weather radars, because, first, they operate at frequencies where rain drops represent significant source of attenuation and, second, cellular networks almost completely cover urban and rural areas. Usually, path-average rain rates along a MWL are retrieved from the rain-induced attenuation of received MWL signals with a simple model based on a power law relationship. The model is often parameterized based on the characteristics of a particular MWL, such as frequency, polarization and the drop size distribution (DSD) along the MWL. As information on the DSD is usually not available in operational conditions, the model parameters are usually considered constant. Unfortunately, this introduces bias into rainfall estimates from MWL. In this investigation, we propose a generic method to eliminate this bias in MWL rainfall estimates. Specifically, we search for attenuation statistics which makes it possible to classify rain events into distinct groups for which same power-law parameters can be used. The theoretical attenuation used in the analysis is calculated from DSD data using T-Matrix method. We test the validity of our approach on observations from a dedicated field experiment in Dübendorf (CH) with a 1.85-km long commercial dual-polarized microwave link transmitting at a frequency of 38 GHz, an autonomous network of 5 optical distrometers and 3 rain gauges distributed along the path of the MWL. The data is recorded at a high temporal resolution of up to 30s. It is further tested on data from an experimental catchment in Prague (CZ), where 14 MWLs, operating at 26, 32 and 38 GHz frequencies, and reference rainfall from three RGs is recorded every minute. Our results suggest that, for our purpose, rain events can be nicely characterized based on

  2. Rainfall erosivity map for Ghana

    International Nuclear Information System (INIS)

    Oduro Afriyie, K.

    1995-10-01

    Monthly rainfall data, spanning over a period of more than thirty years, were used to compute rainfall erosivity indices for various stations in Ghana, using the Fournier index, c, defined as p 2 /P, where p is the rainfall amount in the wettest month and P is the annual rainfall amount. Values of the rainfall erosivity indices ranged from 24.5 mm at Sunyani in the mid-portion of Ghana to 180.9 mm at Axim in the south western coastal portion. The indices were used to construct a rainfall erosivity map for the country. The map revealed that Ghana may be broadly divided into five major erosion risk zones. The middle sector of Ghana is generally in the low erosion risk zone; the northern sector is in the moderate to severe erosion risk zone, while the coastal sector is in the severe to extreme severe erosion risk zone. (author). 11 refs, 1 fig., 1 tab

  3. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    OpenAIRE

    Dongkyun Kim; Francisco Olivera; Huidae Cho; Scott A. Socolofsky

    2013-01-01

    Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC) rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These...

  4. Realistic sampling of anisotropic correlogram parameters for conditional simulation of daily rainfields

    Science.gov (United States)

    Gyasi-Agyei, Yeboah

    2018-01-01

    This paper has established a link between the spatial structure of radar rainfall, which more robustly describes the spatial structure, and gauge rainfall for improved daily rainfield simulation conditioned on the limited gauged data for regions with or without radar records. A two-dimensional anisotropic exponential function that has parameters of major and minor axes lengths, and direction, is used to describe the correlogram (spatial structure) of daily rainfall in the Gaussian domain. The link is a copula-based joint distribution of the radar-derived correlogram parameters that uses the gauge-derived correlogram parameters and maximum daily temperature as covariates of the Box-Cox power exponential margins and Gumbel copula. While the gauge-derived, radar-derived and the copula-derived correlogram parameters reproduced the mean estimates similarly using leave-one-out cross-validation of ordinary kriging, the gauge-derived parameters yielded higher standard deviation (SD) of the Gaussian quantile which reflects uncertainty in over 90% of cases. However, the distribution of the SD generated by the radar-derived and the copula-derived parameters could not be distinguished. For the validation case, the percentage of cases of higher SD by the gauge-derived parameter sets decreased to 81.2% and 86.6% for the non-calibration and the calibration periods, respectively. It has been observed that 1% reduction in the Gaussian quantile SD can cause over 39% reduction in the SD of the median rainfall estimate, actual reduction being dependent on the distribution of rainfall of the day. Hence the main advantage of using the most correct radar correlogram parameters is to reduce the uncertainty associated with conditional simulations that rely on SD through kriging.

  5. Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

    Science.gov (United States)

    Poveda, Germán

    2011-02-01

    Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

  6. Rainfall erosivity in Europe.

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

    2015-04-01

    Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods

  7. Modeling of dengue occurrences early warning involving temperature and rainfall factors

    Directory of Open Access Journals (Sweden)

    Prama Setia Putra

    2017-07-01

    Full Text Available Objective: To understand dengue transmission process and its vector dynamics and to develop early warning model of dengue occurrences based on mosquito population and host-vector threshold values considering temperature and rainfall. Methods: To obtain the early warning model, mosquito population and host-vector models are developed initially. Both are developed using differential equations. Basic offspring number (R0m and basic reproductive ratio (R0d which are the threshold values are derived from the models under constant parameters assumption. Temperature and rainfall effects on mosquito and dengue are performed in entomological and disease transmission parameters. Some of parameters are set as functions of temperature or rainfall while other parameters are set to be constant. Hereafter, both threshold values are computed using those parameters. Monthly dengue occurrences data are categorized as zero and one values which one means the outbreak does occur in that month. Logistics regression is chosen to bridge the threshold values and categorized data. Threshold values are considered as the input of early warning model. Semarang city is selected as the sample to develop this early waning model. Results: The derived threshold values which are R 0 m and R 0 d show to have relation that mosquito as dengue vector affects transmission of the disease. Result of the early warning model will be a value between zero and one. It is categorized as outbreak does occur when the value is larger than 0.5 while other is categorized as outbreak does not occur. By using single predictor, the model can perform 68% accuracy approximately. Conclusions: The extinction of mosquitoes will be followed by disease disappearance while mosquitoes existence can lead to disease free or endemic states. Model simulations show that mosquito population are more affected by weather factors than human. Involving weather factors implicitly in the threshold value and linking them

  8. Nonstationary modeling of a long record of rainfall and temperature over Rome

    Science.gov (United States)

    Villarini, Gabriele; Smith, James A.; Napolitano, Francesco

    2010-10-01

    A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.

  9. Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

    Science.gov (United States)

    Kakar, Ramesh; Adler, Robert; Smith, Eric; Starr, David OC. (Technical Monitor)

    2001-01-01

    Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

  10. Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

    Science.gov (United States)

    Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

    2014-05-01

    Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

  11. Multivariate Analysis of Erosivity Indices and Rainfall Physical Characteristics Associated with Rainfall Patterns in Rio de Janeiro

    Directory of Open Access Journals (Sweden)

    Roriz Luciano Machado

    2017-12-01

    Full Text Available ABSTRACT The identification of areas with greater erosive potential is important for planning soil and water conservation. The objective of this study was to evaluate the physical characteristics of rainfall events in the state of Rio de Janeiro, Brazil, and their interactions with rainfall patterns through multivariate statistical analysis. Rainfall depth, kinetic energy, 30-min intensity (I30, duration of rainfall events, and the erosivity indices KE >10, KE >25, and EI30 in 36 locations (stations were subjected to principal component analysis (PCA and canonical discriminant analysis (CDA. Based on evaluation of the respective historical series of hyetographs, it was found that the advanced pattern occurs with highest frequency (51.8 %, followed by the delayed pattern (26.1 %, and by the intermediate pattern (22.1 %. All the evaluated rainfall characteristics have high response capacity in describing localities and rainfall patterns through PCA and CDA. In CDA, the Tukey test (p<0.05 applied to the scores of the first canonical discriminant function (CDF1 allowed differentiation of the stations with respect to the rainfall and erosivity characteristics for the advanced and delayed patterns. In the delayed pattern, the localities of Angra dos Reis, Campos, Eletrobrás, Manuel Duarte, Santa Isabel do Rio Preto, Tanguá, Teresópolis, Vila Mambucaba, and Xerém had the highest CDF1 scores, indicating that they have rainfalls with higher depth, I30, and duration because the standardized canonical coefficient (SCC and the correlation coefficient (“r” of these characteristics were positive. The rainfall events in the state of Rio de Janeiro differ from one locality to another in relation to the advanced and delayed rainfall patterns, mainly due to the physical characteristics of rainfall depth, I30, and duration, indicating a higher risk of soil loss and runoff in the localities where rainfall events with the delayed pattern prevail.

  12. A dimensionless approach for the runoff peak assessment: effects of the rainfall event structure

    Science.gov (United States)

    Gnecco, Ilaria; Palla, Anna; La Barbera, Paolo

    2018-02-01

    The present paper proposes a dimensionless analytical framework to investigate the impact of the rainfall event structure on the hydrograph peak. To this end a methodology to describe the rainfall event structure is proposed based on the similarity with the depth-duration-frequency (DDF) curves. The rainfall input consists of a constant hyetograph where all the possible outcomes in the sample space of the rainfall structures can be condensed. Soil abstractions are modelled using the Soil Conservation Service method and the instantaneous unit hydrograph theory is undertaken to determine the dimensionless form of the hydrograph; the two-parameter gamma distribution is selected to test the proposed methodology. The dimensionless approach is introduced in order to implement the analytical framework to any study case (i.e. natural catchment) for which the model assumptions are valid (i.e. linear causative and time-invariant system). A set of analytical expressions are derived in the case of a constant-intensity hyetograph to assess the maximum runoff peak with respect to a given rainfall event structure irrespective of the specific catchment (such as the return period associated with the reference rainfall event). Looking at the results, the curve of the maximum values of the runoff peak reveals a local minimum point corresponding to the design hyetograph derived according to the statistical DDF curve. A specific catchment application is discussed in order to point out the dimensionless procedure implications and to provide some numerical examples of the rainfall structures with respect to observed rainfall events; finally their effects on the hydrograph peak are examined.

  13. Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

    Directory of Open Access Journals (Sweden)

    N. Peleg

    2013-06-01

    Full Text Available Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale and increased as the timescale increased. The variance reduction factor (VRF, representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5% on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for

  14. Monsoon Rainfall and Landslides in Nepal

    Science.gov (United States)

    Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

    2009-12-01

    A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

  15. Development of a transient, lumped hydrologic model for geomorphologic units in a geomorphology based rainfall-runoff modelling framework

    Science.gov (United States)

    Vannametee, E.; Karssenberg, D.; Hendriks, M. R.; de Jong, S. M.; Bierkens, M. F. P.

    2010-05-01

    We propose a modelling framework for distributed hydrological modelling of 103-105 km2 catchments by discretizing the catchment in geomorphologic units. Each of these units is modelled using a lumped model representative for the processes in the unit. Here, we focus on the development and parameterization of this lumped model as a component of our framework. The development of the lumped model requires rainfall-runoff data for an extensive set of geomorphological units. Because such large observational data sets do not exist, we create artificial data. With a high-resolution, physically-based, rainfall-runoff model, we create artificial rainfall events and resulting hydrographs for an extensive set of different geomorphological units. This data set is used to identify the lumped model of geomorphologic units. The advantage of this approach is that it results in a lumped model with a physical basis, with representative parameters that can be derived from point-scale measurable physical parameters. The approach starts with the development of the high-resolution rainfall-runoff model that generates an artificial discharge dataset from rainfall inputs as a surrogate of a real-world dataset. The model is run for approximately 105 scenarios that describe different characteristics of rainfall, properties of the geomorphologic units (i.e. slope gradient, unit length and regolith properties), antecedent moisture conditions and flow patterns. For each scenario-run, the results of the high-resolution model (i.e. runoff and state variables) at selected simulation time steps are stored in a database. The second step is to develop the lumped model of a geomorphological unit. This forward model consists of a set of simple equations that calculate Hortonian runoff and state variables of the geomorphologic unit over time. The lumped model contains only three parameters: a ponding factor, a linear reservoir parameter, and a lag time. The model is capable of giving an appropriate

  16. Predicting watershed acidification under alternate rainfall conditions

    International Nuclear Information System (INIS)

    Huntington, T.G.

    1996-01-01

    The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, USA using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soilwater flux will result in larger increases in soil-adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

  17. Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

    Science.gov (United States)

    Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

    2009-04-01

    Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

  18. Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

    Science.gov (United States)

    van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

    2015-05-01

    Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Effect of Bias Correction of Satellite-Rainfall Estimates on Runoff Simulations at the Source of the Upper Blue Nile

    Directory of Open Access Journals (Sweden)

    Emad Habib

    2014-07-01

    Full Text Available Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances caused deterioration. Accounting for temporal variation in the bias reduced the rainfall bias by up to 50%. Additional improvements were observed when both the spatial and temporal variability in the bias was accounted for. The rainfall bias was found to have a pronounced effect on model calibration. The calibrated model parameters changed significantly when using rainfall input from gauges alone, uncorrected, and bias-corrected CMORPH estimates. Changes of up to 81% were obtained for model parameters controlling the stream flow volume.

  20. Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

    Science.gov (United States)

    Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

    2017-04-01

    Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

  1. Bayesian analysis of data and model error in rainfall-runoff hydrological models

    Science.gov (United States)

    Kavetski, D.; Franks, S. W.; Kuczera, G.

    2004-12-01

    A major unresolved issue in the identification and use of conceptual hydrologic models is realistic description of uncertainty in the data and model structure. In particular, hydrologic parameters often cannot be measured directly and must be inferred (calibrated) from observed forcing/response data (typically, rainfall and runoff). However, rainfall varies significantly in space and time, yet is often estimated from sparse gauge networks. Recent work showed that current calibration methods (e.g., standard least squares, multi-objective calibration, generalized likelihood uncertainty estimation) ignore forcing uncertainty and assume that the rainfall is known exactly. Consequently, they can yield strongly biased and misleading parameter estimates. This deficiency confounds attempts to reliably test model hypotheses, to generalize results across catchments (the regionalization problem) and to quantify predictive uncertainty when the hydrologic model is extrapolated. This paper continues the development of a Bayesian total error analysis (BATEA) methodology for the calibration and identification of hydrologic models, which explicitly incorporates the uncertainty in both the forcing and response data, and allows systematic model comparison based on residual model errors and formal Bayesian hypothesis testing (e.g., using Bayes factors). BATEA is based on explicit stochastic models for both forcing and response uncertainty, whereas current techniques focus solely on response errors. Hence, unlike existing methods, the BATEA parameter equations directly reflect the modeler's confidence in all the data. We compare several approaches to approximating the parameter distributions: a) full Markov Chain Monte Carlo methods and b) simplified approaches based on linear approximations. Studies using synthetic and real data from the US and Australia show that BATEA systematically reduces the parameter bias, leads to more meaningful model fits and allows model comparison taking

  2. The Use of Satellite Microwave Rainfall Measurements to Predict Eastern North Pacific Tropical Cyclone Intensity

    National Research Council Canada - National Science Library

    West, Derek

    1998-01-01

    .... Relationships between parameters obtained from an operational SSM/I based rainfall measuring algorithm and current intensity and ensuing 12, 24, 36, 48, 60, and 72 hour intensity changes from best...

  3. Entropy of stable seasonal rainfall distribution in Kelantan

    Science.gov (United States)

    Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

    2017-05-01

    Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

  4. Stochastic modelling of daily rainfall sequences

    NARCIS (Netherlands)

    Buishand, T.A.

    1977-01-01

    Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
    a. Seasonality. Because of seasonal variation

  5. Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

    Directory of Open Access Journals (Sweden)

    Natalie Melissa McLean

    2015-01-01

    Full Text Available End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS regional climate model (RCM under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD and extreme rainfall (R95P than consecutive dry days (CDD, wet days (R10, and maximum 5-day precipitation (RX5. Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana. Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean.

  6. Investigation of Rainfall-Runoff Processes and Soil Moisture Dynamics in Grassland Plots under Simulated Rainfall Conditions

    Directory of Open Access Journals (Sweden)

    Nana Zhao

    2014-09-01

    Full Text Available The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10 were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854–0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0–20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.

  7. Determination of Watershed Infiltration and Erosion Parameters from Field Rainfall Simulation Analyses

    Directory of Open Access Journals (Sweden)

    Mark E. Grismer

    2016-06-01

    Full Text Available Realistic modeling of infiltration, runoff and erosion processes from watersheds requires estimation of the effective hydraulic conductivity (Km of the hillslope soils and how it varies with soil tilth, depth and cover conditions. Field rainfall simulation (RS plot studies provide an opportunity to assess the surface soil hydraulic and erodibility conditions, but a standardized interpretation and comparison of results of this kind from a wide variety of test conditions has been difficult. Here, we develop solutions to the combined set of time-to-ponding/runoff and Green– Ampt infiltration equations to determine Km values from RS test plot results and compare them to the simpler calculation of steady rain minus runoff rates. Relating soil detachment rates to stream power, we also examine the determination of “erodibility” as the ratio thereof. Using data from over 400 RS plot studies across the Lake Tahoe Basin area that employ a wide range of rain rates across a range of soil slopes and conditions, we find that the Km values can be determined from the combined infiltration equation for ~80% of the plot data and that the laminar flow form of stream power best described a constant “erodibility” across a range of volcanic skirun soil conditions. Moreover, definition of stream power based on laminar flows obviates the need for assumption of an arbitrary Mannings “n” value and the restriction to mild slopes (<10%. The infiltration equation based Km values, though more variable, were on average equivalent to that determined from the simpler calculation of steady rain minus steady runoff rates from the RS plots. However, these Km values were much smaller than those determined from other field test methods. Finally, we compare RS plot results from use of different rainfall simulators in the basin and demonstrate that despite the varying configurations and rain intensities, similar erodibilities were determined across a range of

  8. Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn

    2014-01-01

    that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain...

  9. Urban rainfall estimation employing commercial microwave links

    Science.gov (United States)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

    2015-04-01

    Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

  10. On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

    Science.gov (United States)

    Mascaro, Giuseppe

    2018-04-01

    This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

  11. The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India.

    Science.gov (United States)

    Gunaseelan, Indira; Bhaskar, B Vijay; Muthuchelian, K

    2014-01-01

    Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment's impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.

  12. Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the

  13. Development of a landlside EWS based on rainfall thresholds for Tuscany Region, Italy

    Science.gov (United States)

    Rosi, Ascanio; Segoni, Samuele; Battistini, Alessandro; Rossi, Guglielmo; Catani, Filippo; Casagli, Nicola

    2017-04-01

    We present the set-up of a landslide EWS based on rainfall thresholds for the Tuscany region (central Italy), that shows a heterogeneous distribution of reliefs and precipitation. The work started with the definition of a single set of thresholds for the whole region, but it resulted unsuitable for EWS purposes, because of the heterogeneity of the Tuscan territory and non-repeatability of the analyses, that were affected by a high degree of subjectivity. To overcome this problem, the work started from the implementation of a software capable of objectively defining the rainfall thresholds, since some of the main issues of these thresholds are the subjectivity of the analysis and therefore their non-repeatability. This software, named MaCumBA, is largely automated and can analyze, in a short time, a high number of rainfall events to define several parameters of the threshold, such as the intensity (I) and the duration (D) of the rainfall event, the no-rain time gap (NRG: how many hours without rain are needed to consider two events as separated) and the equation describing the threshold. The possibility of quickly perform several analyses lead to the decision to divide the territory in 25 homogeneous areas (named alert zones, AZ), so as a single threshold for each AZ could be defined. For the definition of the thresholds two independent datasets (of joint rainfall-landslide occurrences) have been used: a calibration dataset (data from 2000 to 2007) and a validation dataset (2008-2009). Once the thresholds were defined, a WebGIS-based EWS has been implemented. In this system it is possible to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h; forecasting data are collected from LAMI (Limited Area Model Italy) rainfall forecasts. The EWS works on the basis of the threshold parameters defined by MaCumBA (I, D, NRG). An important feature of the warning system is that the visualization of the thresholds in the Web

  14. Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

    Science.gov (United States)

    Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

    2016-04-01

    Field rainfall simulators are used worldwide for many experimental purposes, such as runoff generation and soil erosion research. At CTU in Prague a laboratory simulator with swinging nozzles VeeJet has been operated since 2001. Since 2012 an additional terrain simulator is being used with 4 fixed FullJet 40WSQ nozzles with 2,4 m spacing and operating over two simultaneously sprinkled experimental plots sizing 8x2 and 1x1 m. In parallel to other research projects a specific problem was solved: improving rainfall spatial uniformity and overall intensity and surface runoff measurements. These fundamental variables significantly affect investigated processes as well as resulting water balance of the plot, therefore they need to be determined as accurately as possible. Although the original nozzles setting produced (commonly used) Christiansen uniformity index CU over 80 %, detailed measurements proved this index insufficient and showed many unrequired rainfall extremes within the plot. Moreover the number of rainfall intensity scenarios was limited and some of them required problematic multi-pressure operation of the water distribution system. Therefore the simulator was subjected to many substantial changes in 2015. Innovations ranged from pump intensification to control unit upgrade. As essential change was considered increase in number of nozzles to 9 in total and reducing their spacing to 1,2 m. However new uniformity measurements did not bring any significant improvement. Tested scenarios showed equal standard deviations of interpolated intensity rasters and equal or slightly lower CU index. Imperfections of sprinkling nozzles were found to be the limiting factor. Still many other benefits were brought with the new setup. Whole experimental plot 10x2 m is better covered with the rainfall while the water consumption is retained. Nozzles are triggered in triplets, which enables more rainfall intensity scenarios. Water distribution system is more stable due to

  15. Computation of rainfall erosivity from daily precipitation amounts.

    Science.gov (United States)

    Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

    2018-10-01

    Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

    Science.gov (United States)

    Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

    2016-12-01

    One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

  17. USING THE FOURNIER INDEXES IN ESTIMATING RAINFALL EROSIVITY. CASE STUDY - THE SECAŞUL MARE BASIN

    Directory of Open Access Journals (Sweden)

    M. COSTEA

    2012-03-01

    Full Text Available Using the Fournier Index in Estimating Rainfall Erosivity. Case Study - The Secaşul Mare Basin. Climatic aggressiveness is one of the most important factors in relief dynamic. Of all climatic parameters, rainfall is directly involved in versant dynamic, in the loss of soil quality and through pluvial denudation and the processes associated with it, through the erosivity of torrential rain. We analyzed rainfall aggressiveness based on monthly and annual average values through the Fournier's index (1970 and Fournier's index modified by Arnoldus (1980. They have the advantage that they can be used not only for evaluating the land susceptibility to erosion and the calculation of erodibility of land and soil losses, but also in assessing land susceptibility to sliding (Aghiruş, 2010. The literature illustrates the successful use of this index which provides a summary assessment of the probability of rainfall with significant erosive effects. The results obtained allow observation of differences in space and time of the distribution of this index.

  18. [Output characteristics of rainfall runoff phosphorus pollution from a typical small watershed in Yimeng mountainous area].

    Science.gov (United States)

    Yu, Xing-xiu; Li, Zhen-wei; Liu, Qian-jin; Jing, Guang-hua

    2012-08-01

    Relationships between phosphorus pollutant concentrations and precipitation-runoff were analyzed by monitoring pollutant losses at outlets of the Menglianggu watershed in 2010. A typical small watershed was selected to examine the runoff and quality parameters such as total phosphorus (TP), particle phosphorus (PP), dissolve phosphorus (DP) and dissolve inorganic phosphorus (DIP) in rainfall-runoff of 10 rainfall events. Precipitation was above 2 mm for all the 10 rainfall events. The results showed that the peak of phosphorus concentrations occurred before the peak of water flows, whereas change processes of the phosphorus fluxes were consistent with that of the water flows and the phosphorus flux also have a strong linear relationship with the water flows. The minimums of the phosphorus concentrations in every 10 natural rainfall events have small differences with each other, but the maximum and EMCs of the phosphorus concentrations have significant differences with each rainfall event. This was mainly influenced by the precipitation, maximum rainfall intensity and mean rainfall intensity (EMCs) and was less influenced by rainfall duration. DP and TP were mainly composed of DIP and PP, respectively. There were no significant correlations between DIP/DP dynamic changes and rainfall characteristics, whereas significant correlations between PP/TP dynamic changes and maximum rainfall intensity were detected. The production of DIP, DP, AND TP were mainly influenced by the direct runoff (DR) and base flow (BF). The EMCs of DIP, DP, TP and the variations of DIP/DP were all found to have significant polynomial relationships with DR/TR., but the dynamic changes of PP/ TP and the EMCS of PP were less influenced by the DR/TR.

  19. Transfer of spatio-temporal multifractal properties of rainfall to simulated surface runoff

    Science.gov (United States)

    Gires, Auguste; Giangola-Murzyn, Agathe; Richard, Julien; Abbes, Jean-Baptiste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Willinger, Bernard; Cardinal, Hervé; Thouvenot, Thomas

    2014-05-01

    In this paper we suggest to use scaling laws and more specifically Universal Multifractals (UM) to analyse in a spatio-temporal framework both the radar rainfall and the simulated surface runoff. Such tools have been extensively used to analyse and simulate geophysical fields extremely variable over wide range of spatio-temporal scales such as rainfall, but have not often if ever been applied to surface runoff. Such novel combined analysis helps to improve the understanding of the rainfall-runoff relationship. Two catchments of the chair "Hydrology for resilient cities" sponsored by Véolia, and of the European Interreg IV RainGain project are used. They are both located in the Paris area: a 144 ha flat urban area in the Seine-Saint-Denis County, and a 250 ha urban area with a significant portion of forest located on a steep hillside of the Bièvre River. A fully distributed urban hydrological model currently under development called Multi-Hydro is implemented to represent the catchments response. It consists in an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. The fully distributed model is tested with pixels of size 5, 10 and 20 m. In a first step the model is validated for three rainfall events that occurred in 2010 and 2011, for which the Météo-France radar mosaic with a resolution of 1 km in space and 5 min in time is available. These events generated significant surface runoff and some local flooding. The sensitivity of the model to the rainfall resolution is briefly checked by stochastically generating an ensemble of realistic downscaled rainfall fields (obtained by continuing the underlying cascade process which is observed on the available range of scales) and inputting them into the model. The impact is significant on both the simulated sewer flow and surface runoff. Then rainfall fields are generated with the help of discrete multifractal cascades and inputted in the

  20. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  1. Analysis of rainfall infiltration law in unsaturated soil slope.

    Science.gov (United States)

    Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

    2014-01-01

    In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.

  2. Effect of monthly areal rainfall uncertainty on streamflow simulation

    Science.gov (United States)

    Ndiritu, J. G.; Mkhize, N.

    2017-08-01

    Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

  3. Model testing on rainfall-induced landslide of loose soil in Wenchuan earthquake region

    Directory of Open Access Journals (Sweden)

    H. Fang

    2012-03-01

    Full Text Available This study investigates the formation process of rainfall-induced landslide for slopes composed of loose soil in the Wenchuan earthquake region. Experimental investigations have been performed on the landslide's formation and the variation of the controlling soil parameters under various artificial rainfall conditions. The landslide triggering mechanisms can be described in the following way. Firstly, the large porosity of the loose soil facilitated the infiltration of water, which increased the pore water pressure and reduced the shear strength of the soil significantly. In addition, the rainfalls probably caused the concentration of finer particles at a certain depth of the valley slopes. This concentration within the soil increased the pore water pressure significantly, and consequently reduced both the porosity ratio and permeability. Therefore, when the pore water pressure reached a critical state, the effective shear strength of the soil diminished, inducing the landslide's formation.

  4. Probabilistic clustering of rainfall condition for landslide triggering

    Science.gov (United States)

    Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

    2013-04-01

    Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed

  5. Hydrological model parameterization using NDVI values to account for the effects of land-cover change on the rainfall-runoff response

    Science.gov (United States)

    Classic rainfall-runoff models usually use historical data to estimate model parameters and mean values of parameters are considered for predictions. However, due to climate changes and human effects, the parameters of model change temporally. To overcome this problem, Normalized Difference Vegetati...

  6. Curve Number Estimation for a Small Urban Catchment from Recorded Rainfall-Runoff Events

    Directory of Open Access Journals (Sweden)

    Banasik Kazimierz

    2014-12-01

    Full Text Available Runoff estimation is a key component in various hydrological considerations. Estimation of storm runoff is especially important for the effective design of hydraulic and road structures, for the flood flow management, as well as for the analysis of land use changes, i.e. urbanization or low impact development of urban areas. The curve number (CN method, developed by Soil Conservation Service (SCS of the U.S. Department of Agriculture for predicting the flood runoff depth from ungauged catchments, has been in continuous use for ca. 60 years. This method has not been extensively tested in Poland, especially in small urban catchments, because of lack of data. In this study, 39 rainfall-runoff events, collected during four years (2009–2012 in a small (A=28.7 km2, urban catchment of Służew Creek in southwest part of Warsaw were used, with the aim of determining the CNs and to check its applicability to ungauged urban areas. The parameters CN, estimated empirically, vary from 65.1 to 95.0, decreasing with rainfall size and, when sorted rainfall and runoff separately, reaching the value from 67 to 74 for large rainfall events.

  7. The Indian summer monsoon rainfall: interplay of coupled dynamics, radiation and cloud microphysics

    Directory of Open Access Journals (Sweden)

    P. K. Patra

    2005-01-01

    Full Text Available The Indian summer monsoon rainfall (ISMR, which has a strong connection to agricultural food production, has been less predictable by conventional models in recent times. Two distinct years 2002 and 2003 with lower and higher July rainfall, respectively, are selected to help understand the natural and anthropogenic influences on ISMR. We show that heating gradients along the meridional monsoon circulation are reduced due to aerosol radiative forcing and the Indian Ocean Dipole in 2002. An increase in the dust and biomass-burning component of the aerosols through the zonal monsoon circulation resulted in reduction of cloud droplet growth in July 2002. These conditions were opposite to those in July 2003 which led to an above average ISMR. In this study, we have utilized NCEP/NCAR reanalyses for meteorological data (e.g. sea-surface temperature, horizontal winds, and precipitable water, NOAA interpolated outgoing long-wave radiation, IITM constructed all-India rainfall amounts, aerosol parameters as observed from the TOMS and MODIS satellites, and ATSR fire count maps. Based on this analysis, we suggest that monsoon rainfall prediction models should include synoptic as well as interannual variability in both atmospheric dynamics and chemical composition.

  8. Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

    Science.gov (United States)

    Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

    2017-12-01

    This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

  9. Extreme value analysis of meterological parameters observed at Narora during the period 1989-2001

    International Nuclear Information System (INIS)

    Varakhedkar, V.K.; Dube, B.; Gurg, R.P.

    2002-08-01

    The design of engineering structures requires an understanding of extreme weather conditions that may occur at the site of interest, which is very essential, so that the structures can be designed to withstand weather stresses. In this report an analysis of extreme values of meteorological parameters observed at Narora for the period 1989- 2001 is described. The parameters considered are maximum and minimum air temperature, minimum relative humidity, maximum wind speed, maximum rainfall in a day and month, and annual rainfall. The extreme value analysis reveals that the variables such as annual maximum air temperature, minimum relative humidity and monthly maximum rainfall obey Fisher -Tippet Type -I extreme value distribution where as annual minimum air temperature, maximum hourly wind speed, daily maximum rainfall and maximum and minimum annual rainfall, obey Fisher -Tippet Type -2 extreme value distribution function. Various distribution function parameters for each variable are determined. Extreme values corresponding to return periods of 50 years and 100 years are worked out. These derived extreme values are particularly useful for arriving at suitable design values to ensure the safety of any civil structure in Narora area with respect to stresses due to weather conditions. (author)

  10. Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

    NARCIS (Netherlands)

    Uijlenhoet, R.; Porrà, J.M.; Sempere Torres, D.; Creutin, J.D.

    2006-01-01

    A stochastic model of the microstructure of rainfall is used to derive explicit expressions for the magnitude of the sampling fluctuations in rainfall properties estimated from raindrop size measurements in stationary rainfall. The model is a marked point process, in which the points represent the

  11. Uganda rainfall variability and prediction

    Science.gov (United States)

    Jury, Mark R.

    2018-05-01

    This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

  12. Assessing Climate Variability using Extreme Rainfall and ...

    African Journals Online (AJOL)

    user1

    extreme frequency); the average intensity of rainfall from extreme events ... frequency and extreme intensity indices, suggesting that extreme events are more frequent and intense during years with high rainfall. The proportion of total rainfall from ...

  13. Soil losses from typic cambisols and red latosol as related to three erosive rainfall patterns

    Directory of Open Access Journals (Sweden)

    Regimeire Freitas Aquino

    2013-02-01

    Full Text Available Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd and a typic dystrophic Red Latosol (LVdf to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30, rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals, characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.

  14. Impacts of Rainfall Variability and Expected Rainfall Changes on Cost-Effective Adaptation of Water Systems to Climate Change

    NARCIS (Netherlands)

    Pol, van der T.D.; Ierland, van E.C.; Gabbert, S.G.M.; Weikard, H.P.; Hendrix, E.M.T.

    2015-01-01

    Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change

  15. Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China

    Directory of Open Access Journals (Sweden)

    Jun Li

    2017-01-01

    Full Text Available Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient λ, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with λ using the Soil Conservation Service curve number (SCS-CN method, with r=1/(1+λ. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r=0.833 with λ=0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.

  16. Stormwater Runoff Pollutant Loading Distributions and Their Correlation with Rainfall and Catchment Characteristics in a Rapidly Industrialized City

    Science.gov (United States)

    Li, Dongya; Wan, Jinquan; Ma, Yongwen; Wang, Yan; Huang, Mingzhi; Chen, Yangmei

    2015-01-01

    Fast urbanization and industrialization in developing countries result in significant stormwater runoff pollution, due to drastic changes in land-use, from rural to urban. A three-year study on the stormwater runoff pollutant loading distributions of industrial, parking lot and mixed commercial and residential catchments was conducted in the Tongsha reservoir watershed of Dongguan city, a typical, rapidly industrialized urban area in China. This study presents the changes in concentration during rainfall events, event mean concentrations (EMCs) and event pollution loads per unit area (EPLs). The first flush criterion, namely the mass first flush ratio (MFFn), was used to identify the first flush effects. The impacts of rainfall and catchment characterization on EMCs and pollutant loads percentage transported by the first 40% of runoff volume (FF40) were evaluated. The results indicated that the pollutant wash-off process of runoff during the rainfall events has significant temporal and spatial variations. The mean rainfall intensity (I), the impervious rate (IMR) and max 5-min intensity (Imax5) are the critical parameters of EMCs, while Imax5, antecedent dry days (ADD) and rainfall depth (RD) are the critical parameters of FF40. Intercepting the first 40% of runoff volume can remove 55% of TSS load, 53% of COD load, 58% of TN load, and 61% of TP load, respectively, according to all the storm events. These results may be helpful in mitigating stormwater runoff pollution for many other urban areas in developing countries. PMID:25774922

  17. Stormwater runoff pollutant loading distributions and their correlation with rainfall and catchment characteristics in a rapidly industrialized city.

    Science.gov (United States)

    Li, Dongya; Wan, Jinquan; Ma, Yongwen; Wang, Yan; Huang, Mingzhi; Chen, Yangmei

    2015-01-01

    Fast urbanization and industrialization in developing countries result in significant stormwater runoff pollution, due to drastic changes in land-use, from rural to urban. A three-year study on the stormwater runoff pollutant loading distributions of industrial, parking lot and mixed commercial and residential catchments was conducted in the Tongsha reservoir watershed of Dongguan city, a typical, rapidly industrialized urban area in China. This study presents the changes in concentration during rainfall events, event mean concentrations (EMCs) and event pollution loads per unit area (EPLs). The first flush criterion, namely the mass first flush ratio (MFFn), was used to identify the first flush effects. The impacts of rainfall and catchment characterization on EMCs and pollutant loads percentage transported by the first 40% of runoff volume (FF40) were evaluated. The results indicated that the pollutant wash-off process of runoff during the rainfall events has significant temporal and spatial variations. The mean rainfall intensity (I), the impervious rate (IMR) and max 5-min intensity (Imax5) are the critical parameters of EMCs, while Imax5, antecedent dry days (ADD) and rainfall depth (RD) are the critical parameters of FF40. Intercepting the first 40% of runoff volume can remove 55% of TSS load, 53% of COD load, 58% of TN load, and 61% of TP load, respectively, according to all the storm events. These results may be helpful in mitigating stormwater runoff pollution for many other urban areas in developing countries.

  18. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge

  19. Temporal and spatial variability of rainfall distribution and ...

    African Journals Online (AJOL)

    Rainfall and evapotranspiration are the two major climatic factors affecting agricultural production. This study examined the extent and nature of rainfall variability from measured data while estimation of evapotranspiration was made from recorded weather data. Analysis of rainfall variability is made by the rainfall anomaly ...

  20. Topographic relationships for design rainfalls over Australia

    Science.gov (United States)

    Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

    2016-02-01

    Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

  1. Tropical intraseasonal rainfall variability in the CFSR

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jiande [I.M. System Group Inc. at NOAA/NCEP/EMC, Camp Springs, MD (United States); Wang, Wanqiu [NOAA/NCEP/CPC, Camp Springs, MD (United States); Fu, Xiouhua [University of Hawaii at Manoa, IPRC, SOEST, Honolulu, HI (United States); Seo, Kyong-Hwan [Pusan National University, Department of Atmospheric Sciences, Busan (Korea, Republic of)

    2012-06-15

    While large-scale circulation fields from atmospheric reanalyses have been widely used to study the tropical intraseasonal variability, rainfall variations from the reanalyses are less focused. Because of the sparseness of in situ observations available in the tropics and strong coupling between convection and large-scale circulation, the accuracy of tropical rainfall from the reanalyses not only measures the quality of reanalysis rainfall but is also to some extent indicative of the accuracy of the circulations fields. This study analyzes tropical intraseasonal rainfall variability in the recently completed NCEP Climate Forecast System Reanalysis (CFSR) and its comparison with the widely used NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2). The R1 produces too weak rainfall variability while the R2 generates too strong westward propagation. Compared with the R1 and R2, the CFSR produces greatly improved tropical intraseasonal rainfall variability with the dominance of eastward propagation and more realistic amplitude. An analysis of the relationship between rainfall and large-scale fields using composites based on Madden-Julian Oscillation (MJO) events shows that, in all three NCEP reanalyses, the moisture convergence leading the rainfall maximum is near the surface in the western Pacific but is above 925 hPa in the eastern Indian Ocean. However, the CFSR produces the strongest large-scale convergence and the rainfall from CFSR lags the column integrated precipitable water by 1 or 2 days while R1 and R2 rainfall tends to lead the respective precipitable water. Diabatic heating related to the MJO variability in the CFSR is analyzed and compared with that derived from large-scale fields. It is found that the amplitude of CFSR-produced total heating anomalies is smaller than that of the derived. Rainfall variability from the other two recently produced reanalyses, the ECMWF Re-Analysis Interim (ERAI), and the Modern Era Retrospective-analysis for Research and

  2. A pair of new moisture-dynamic diagnostic parameters for heavy rain location

    Science.gov (United States)

    Yuan, Kai; Zhu, Zhiwei; Li, Ming

    2018-06-01

    In this study, the regional persistent heavy rain process occurred in the middle and lower reaches of the Yangtze River valley from 30 June 2016 to 7 July 2016 is analyzed. We find that the pure dynamic parameters [e.g., vorticity ( V) and divergence ( D)] and two-dimensional moisture-dynamic parameters [e.g., moist vorticity ( MV), moist divergence ( MD)] have difficulty in capturing the rainfall location during such a critical process. Given the poor performance of these traditional parameters, a pair of new parameters [namely, one-dimensional moist vorticity ( ODMV) and one-dimensional moist divergence ( ODMD)] based on low-level jet is proposed for diagnosing heavy rain location. The results show that (1) ODMV and ODMD have better relations with rain belt in terms of spatial distribution. Precipitation occurs in positive (negative) region of ODMV ( ODMD), and heavy rainfall accurately locates in the positive (negative) center of ODMV ( ODMD); (2) ODMV and ODMD also have good correlation with the precipitation in terms of temporal variation (significant at the 99% confidence level). When ODMV ( ODMD) is in strong positive (negative) phase, precipitation is large, and vice versa; (3) the threat score of ODMV and ODMD for the areal-mean rainfall is improved by 119% and 16%, respectively, compared to V/ D and MV/ MD. It is anticipated that the proposed new parameters would facilitate the skills of diagnosing and forecasting the heavy rainfall.

  3. Rainfall thresholds for the triggering of landslides in Slovenia

    Science.gov (United States)

    Peternel, Tina; Jemec Auflič, Mateja; Rosi, Ascanio; Segoni, Samuele; Komac, Marko; Casagli, Nicola

    2017-04-01

    Both at the worldwide level and in Slovenia, precipitation and related phenomena represent one of the most important triggering factors for the occurrence of slope mass movements. In the past decade, extreme rainfall events with a very high amount of precipitation occurs in a relatively short rainfall period have become increasingly important and more frequent, that causing numerous undesirable consequences. Intense rainstorms cause flash floods and mostly trigger shallow landslides and soil slips. On the other hand, the damage of long lasting rainstorms depends on the region's adaptation and its capacity to store or infiltrate excessive water from the rain. The amount and, consequently, the intensity of daily precipitation that can cause floods in the eastern part of Slovenia is a rather common event for the north-western part of the country. Likewise, the effect of rainfall is very dependent on the prior soil moisture, periods of full soil saturation and the creation of drifts in groundwater levels due to the slow melting of snow, growing period, etc. Landslides could be identified and to some extent also prevent with better knowledge of the relation between landslides and rainfall. In this paper the definition of rainfall thresholds for rainfall-induced landslides in Slovenia is presented. The thresholds have been calculated by collecting approximately 900 landslide data and the relative rainfall amounts, which have been collected from 41 rain gauges all over the country. The thresholds have been defined by the (1) use of an existing procedure, characterized by a high degree of objectiveness and (2) software that was developed for a test site with very different geological and climatic characteristics (Tuscany, central Italy). Firstly, a single national threshold has been defined, later the country was divided into four zones, on the basis of major the river basins and a single threshold has been calculated for each of them. Validation of the calculated

  4. Comparison of mass transport using average and transient rainfall boundary conditions

    International Nuclear Information System (INIS)

    Duguid, J.O.; Reeves, M.

    1976-01-01

    A general two-dimensional model for simulation of saturated-unsaturated transport of radionuclides in ground water has been developed and is currently being tested. The model is being applied to study the transport of radionuclides from a waste-disposal site where field investigations are currently under way to obtain the necessary model parameters. A comparison of the amount of tritium transported is made using both average and transient rainfall boundary conditions. The simulations indicate that there is no substantial difference in the transport for the two conditions tested. However, the values of dispersivity used in the unsaturated zone caused more transport above the water table than has been observed under actual conditions. This deficiency should be corrected and further comparisons should be made before average rainfall boundary conditions are used for long-term transport simulations

  5. Evolution of rainfall in the Sahel

    International Nuclear Information System (INIS)

    Diallo, M.A.

    1995-09-01

    In this note, a number of main meteorological stations has been chosen to analyse the rainfall during the last 30 years in the Sahel (1961 to 1990). Reliable climatological data have been used for this study. The concerned area is limited by the 200 mm isohyet in the north and 600 mm isohyet in the south in the Sahel countries (Senegal, Mauritania, Mali, Burkina Faso, Niger and Chad). The evolution of rainfall has pointed out some similar and significant aspects for all stations studied. Established criteria have been used to characterize the annual rainfall and to determine the years with good rainfall and years of drought in the Sahel. (author). 6 refs, 3 figs

  6. Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

    Science.gov (United States)

    Lucero, Omar A.; Rozas, Daniel

    Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of

  7. Warning Model for Shallow Landslides Induced by Extreme Rainfall

    Directory of Open Access Journals (Sweden)

    Lien-Kwei Chien

    2015-08-01

    Full Text Available In this study, the geophysical properties of the landslide-prone catchment of the Gaoping River in Taiwan were investigated using zones based on landslide history in conjunction with landslide analysis using a deterministic approach based on the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability model. Typhoon Morakot in 2009 was selected as a simulation scenario to calibrate the combination of geophysical parameters in each zone before analyzing changes in the factor of safety (FS. Considering the amount of response time required for typhoons, suitable FS thresholds for landslide warnings are proposed for each town in the catchment area. Typhoon Fanapi of 2010 was used as a test scenario to verify the applicability of the FS as well as the efficacy of the cumulative rainfall thresholds derived in this study. Finally, the amount of response time provided by the FS thresholds in cases of yellow and red alerts was determined. All five of the landslide events reported by the Soil and Water Conservation Bureau were listed among the unstable sites identified in the proposed model, thereby demonstrating its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of yellow and red alerts with the ability to reduce losses and save lives.

  8. Determining rainfall thresholds that trigger landslides in Colombia

    International Nuclear Information System (INIS)

    Mayorga Marquez, Ruth

    2003-01-01

    Considering that rainfall is the natural event that more often triggers landslides, it is important to study the relationship between this phenomenon and the occurrence of earth mass movements, by determining rainfall thresholds that trigger landslides in different zones of Colombia. The research presents a methodology that allows proposing rainfall thresholds that trigger landslides in Colombia, by means of a relationship between the accumulated rain in the soil (antecedent rainfall) and the rain that falls the day of the landslide occurrence (event rainfall)

  9. The development rainfall forecasting using kalman filter

    Science.gov (United States)

    Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

    2018-04-01

    Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

  10. [Effects of simulating acid rain on photosynthesis and chlorophyll fluorescence parameters of Quercus glauca Quercus glauca].

    Science.gov (United States)

    Wang, Sai; Yi, Li-Ta; Yu, Shu-Quan; Zhang, Chao; Shi, Jing-Jing

    2014-08-01

    At three levels of simulated acid rainfall intensities with pH values of 2.5 (severe), 40 (medium) and 5.6 (light) respectively, the responses of chlorophyll fluorescence and photosynthetic parameters of Quercus glauca seedlings were studied in three acid rainfall treatments, i. e. only the aboveground of seedlings exposed to acid rain (T1), both of the seedlings and soil exposed to acid rain (T2), only the soil exposed to acid rain (T3) compared with blank control (CK). Under the severe acid rainfall, T1 significantly inhibited chlorophyll synthesis, and thus reduced the primary photochemical efficiency of PS II ( F(v)/F(m)), potential activity of PS II (F(v)/F(o)) , apparent quantum (Y), net photosynthetic rate (P(n)), and transpiration rate (T(r)), but increased the light compensation point (LCP) and dark respiration rate (R(d)) of Q. glauca seedlings. T2 inhibited, but T3 played a little enhancement on the aforementioned parameters of Q. glauca seedlings. Under the conditions of medium and light acid rainfall intensities, the above parameters in the three treatments were higher than that of CK, except with lower R(d). The chlorophyll fluorescence and photosynthetic parameters showed a similar tendency in the three treatments, i. e. T2>T3 >T1. It indicated that T1 had the strongest inhibition on seedlings in condition of the severe acid rainfall, while T2 had the most dramatic facilitating effect on seedlings under the medium and light acid rainfall. Intensity of acid rainfall had significant influences on SPAD, F(v)/F(m), F(v)/F(o), Y, P(n), T(r), and maximum photosynthetic rate (A(max)), whereas treatments of acid rainfall affected SPAD, F(v)/F(m), Y, P(n), T(r), A(max) and light saturation point (LSP). The interaction of acid rainfall intensities and treatments played significant effects on SPAD, F(v)/F(m), Y, P(n) and A(max).

  11. Hydraulic properties for interrill erosion on steep slopes using a portable rainfall simulator

    Science.gov (United States)

    Shin, Seung Sook; Hwang, Yoonhee; Deog Park, Sang; Yun, Minu; Park, Sangyeon

    2017-04-01

    The hydraulic parameters for sheet flow on steep slopes have been not frequently measured because the shallow flow depth and slow flow velocity are difficult to measure. In this study hydraulic values of sheet flow were analyzed to evaluate interrill erosion on steep slopes. A portable rainfall simulator was used to conduct interrill erosion test. The kinetic energy of rainfall simulator was obtained by disdrometer being capable of measuring the drop size distribution and velocity of falling raindrops. The sheet flow velocity was determined by the taken time for a dye transferring fixed points using video images. Surface runoff discharge and sediment yield increased with increase of rainfall intensity and kinetic energy and slope steepness. Especially sediment yield was strongly correlated with sheet flow velocity. The maximum velocity of sheet flow was 2.3cm/s under rainfall intensity of 126.8mm/h and slope steepness of 53.2%. The sheet flow was laminar and subcritical flow as the flow Reynolds number and Froude number are respectively the ranges of 10 22 and 0.05 0.25. The roughness coefficient (Manning's n) for sheet flow on steep slopes was relatively large compared to them on the gentle slope. Keywords: Sheet flow velocity; Rainfall simulator; Interrill erosion; Steep slope This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2015R1C1A2A01055469).

  12. Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

    Science.gov (United States)

    Langousis, Andreas; Kaleris, Vassilios

    2013-04-01

    Due to its intermittent and highly variable character, daily precipitation is the least well reproduced hydrologic variable by both General Circulation Models (GCMs) and Limited Area Models (LAMs). To that extent, several statistical procedures (usually referred to as downscaling schemes) have been suggested to generate synthetic rainfall time series conditional on predictor variables that are descriptive of the atmospheric circulation at the mesoscale. In addition to be more accurately simulated by GCMs and LAMs, large-scale atmospheric predictors are important indicators of the local weather. Currently used downscaling methods simulate rainfall series using either stable statistical relationships (usually referred to as transfer functions) between certain characteristics of the rainfall process and mesoscale atmospheric predictor variables, or simple stochastic schemes (e.g. properly transformed autoregressive models) with parameters that depend on the large-scale atmospheric conditions. The latter are determined by classifying large-scale circulation patterns into broad categories of weather states, using empirical or theoretically based classification schemes, and modeled by resampling from those categories; a process usually referred to as weather generation. In this work we propose a statistical framework to generate synthetic rainfall timeseries at a daily level, conditional on large scale atmospheric predictors. The latter include the mean sea level pressure (MSLP), the magnitude and direction of upper level geostrophic winds, and the 500 hPa geopotential height, relative vorticity and divergence. The suggested framework operates in continuous time, avoiding the use of transfer functions, and weather classification schemes. The suggested downscaling approach is validated using atmospheric data from the ERA-Interim archive (see http://www.ecmwf.int/research/era/do/get/index), and daily rainfall data from Western Greece, for the 14-year period from 01 October

  13. Combined Forecasting of Rainfall Based on Fuzzy Clustering and Cross Entropy

    Directory of Open Access Journals (Sweden)

    Baohui Men

    2017-12-01

    Full Text Available Rainfall is an essential index to measure drought, and it is dependent upon various parameters including geographical environment, air temperature and pressure. The nonlinear nature of climatic variables leads to problems such as poor accuracy and instability in traditional forecasting methods. In this paper, the combined forecasting method based on data mining technology and cross entropy is proposed to forecast the rainfall with full consideration of the time-effectiveness of historical data. In view of the flaws of the fuzzy clustering method which is easy to fall into local optimal solution and low speed of operation, the ant colony algorithm is adopted to overcome these shortcomings and, as a result, refine the model. The method for determining weights is also improved by using the cross entropy. Besides, the forecast is conducted by analyzing the weighted average rainfall based on Thiessen polygon in the Beijing–Tianjin–Hebei region. Since the predictive errors are calculated, the results show that improved ant colony fuzzy clustering can effectively select historical data and enhance the accuracy of prediction so that the damage caused by extreme weather events like droughts and floods can be greatly lessened and even kept at bay.

  14. Urbanization Induces Nonstationarity in Extreme Rainfall Characteristics over Contiguous United States

    Science.gov (United States)

    Singh, J.; Paimazumder, D.; Mohanty, M. P.; Ghosh, S.; Karmakar, S.

    2017-12-01

    The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the perceivable impacts of climate change, urbanization and land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which in turn may affect the policy and decision-making. Also, it may no longer be reasonable to model rainfall extremes as a stationary process, yet nearly all-existing infrastructure design, water resource planning methods assume that historical extreme rainfall events will remain unchanged in the future. Therefore, a comprehensive multivariate nonstationary frequency analysis has been conducted for the CONUS to identify the precipitation characteristics (intensity, duration and depth) responsible for significant nonstationarity. We use 0.250 resolution of precipitation data for a period of 1948-2006, in a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework. A cluster of 74 GAMLSS models has been developed by considering nonstationarity in different combinations of distribution parameters through different regression techniques, and the best-fit model is further applied for bivariate analysis. Next, four demographic variables i.e. population density, housing unit, low income population and population below poverty line, have been utilized to identify the urbanizing regions through developing urbanization index. Furthermore to strengthen the analysis, Land cover map for 1992, 2001 and 2006 have been utilized to identify the location with the high change in impervious surface. The results show significant differences in the 50- and 100-year intensity, volume and duration estimated under the both stationary and nonstationary condition in urbanizing regions. Further results exhibit that rainfall duration has been decreased while, rainfall volume has been increased under nonstationary condition, which indicates increasing flood potential of

  15. Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

    Directory of Open Access Journals (Sweden)

    Ibsen Chivatá Cárdenas

    2008-05-01

    Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

  16. Impact of Erratic Rainfall from Climate Change on Pulse Production Efficiency in Lower Myanmar

    Directory of Open Access Journals (Sweden)

    Sein Mar

    2018-02-01

    Full Text Available Erratic rainfall has a detrimental impact on crop productivity but rainfall during the specific growth stage is rarely used in efficiency analysis. This study focuses on this untapped point and examines the influence of rainfall specifically encountered during the sowing stage and early vegetative growth stage and the flowering stage of pulses on productivity and efficiency in Lower Myanmar using data from 182 sample farmers. The results of a stochastic frontier production function reveal that rainfall incidence during the flowering season of pulses has a negatively significant effect on yield while replanting crops after serious damage by rain increases productivity. Controlled rainfall variables, seed rate, human labor and land preparation cost are important parameters influencing pulses yield. In the efficiency model, levels of yield loss have a negative impact while being a male household head, access to government credit, access to training, locating farms in the Bago Region and possessing a large area of pulses have a positively significant effect on technical efficiency. Policy recommendations include the establishment of a safety network, such as crop insurance to protect farmers from losses due to unpredictable weather conditions, promoting training programs on cultural practices adapted to climate change, wide coverage of extension activities, giving priority to small-scale farmers and female farmer participation in training and extension activities and increasing the rate of credit availability to farmers.

  17. Interevent Time Distribution of Renewal Point Process, Case Study: Extreme Rainfall in South Sulawesi

    Science.gov (United States)

    Sunusi, Nurtiti

    2018-03-01

    The study of time distribution of occurrences of extreme rain phenomena plays a very important role in the analysis and weather forecast in an area. The timing of extreme rainfall is difficult to predict because its occurrence is random. This paper aims to determine the inter event time distribution of extreme rain events and minimum waiting time until the occurrence of next extreme event through a point process approach. The phenomenon of extreme rain events over a given period of time is following a renewal process in which the time for events is a random variable τ. The distribution of random variable τ is assumed to be a Pareto, Log Normal, and Gamma. To estimate model parameters, a moment method is used. Consider Rt as the time of the last extreme rain event at one location is the time difference since the last extreme rainfall event. if there are no extreme rain events up to t 0, there will be an opportunity for extreme rainfall events at (t 0, t 0 + δt 0). Furthermore from the three models reviewed, the minimum waiting time until the next extreme rainfall will be determined. The result shows that Log Nrmal model is better than Pareto and Gamma model for predicting the next extreme rainfall in South Sulawesi while the Pareto model can not be used.

  18. Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

    Science.gov (United States)

    Liong, Shie-Yui; He, Shan

    2010-05-01

    Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

  19. Censored rainfall modelling for estimation of fine-scale extremes

    Science.gov (United States)

    Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

    2018-01-01

    Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

  20. Vegetation Variability And Its Effect On Monsoon Rainfall Over South East Asia: Observational and Modeling Results

    Science.gov (United States)

    Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.

    2005-12-01

    Increasing population and urbanization have created stress on developing nations. The quickly shifting patterns of vegetation change in different parts of the world have given rise to the pertinent question of feedback on the climate prevailing on local to regional scales. It is now known with some certainty, that vegetation changes can affect the climate by influencing the heat and water balance. The hydrological cycle particularly is susceptible to changes in vegetation. The Monsoon rainfall forms a vital link in the hydrological cycle prevailing over South East Asia This work examines the variability of vegetation over South East Asia and assesses its impact on the monsoon rainfall. We explain the role of changing vegetation and show how this change has affected the heat and energy balance. We demonstrate the role of vegetation one season earlier in influencing rainfall intensity over specific areas in South East Asia and show the ramification of vegetation change on the summer rainfall behavior. The vegetation variability study specifically focuses on India and China, two of the largest and most populous nations. We have done an assessment to find out the key meteorological and human induced parameters affecting vegetation over the study area through a spatial analysis of monthly NDVI values. This study highlights the role of monsoon rainfall, regional climate dynamics and large scale human induced pollution to be the crucial factors governing the vegetation and vegetation distribution. The vegetation is seen to follow distinct spatial patterns that have been found to be crucial in its eventual impact on monsoon rainfall. We have carried out a series of sensitivity experiments using a land surface hydrologic modeling scheme. The vital energy and water balance parameters are identified and the daily climatological cycles are examined for possible change in behavior for different boundary conditions. It is found that the change from native deciduous forest

  1. Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

    Science.gov (United States)

    Worku, L. Y.

    2015-12-01

    Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

  2. The Spatial Scaling of Global Rainfall Extremes

    Science.gov (United States)

    Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

    2013-12-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

  3. Forecasting and Analysis of Monthly Rainfalls in Ardabil Province by Arima, Autoregrressive, and Winters Models

    Directory of Open Access Journals (Sweden)

    B. Salahi

    2017-01-01

    precipitation in Ardabil synoptic station indicates that in May, the highest and in August, the lowest monthly total rainfall accounted in this station. Standard deviation of rainfall reached to the lowest level in August and its peak in November. Coefficients of skewness and kurtosis of total rainfall in all seasons, indicates a lack of compliance with normal distribution. From the view of the range of total monthly rainfall, October and August have highest and the lowest tolerance in these parameters, respectively. The results showed that the percentage of the mean absolute error for Arima, Winters and Autoregressive models was 61.82, 148.39 and 81.54 respectively and its R square came to be 88.28, 61.07 and 85.12 respectively. The comparison of the parameters is an indication of the fact that Arima has the highest R square and the lowest mean absolute error of 88.28 and 61.82 respectively than Winters and Autoregressive models. The presence or absence of significant changes in mean precipitation during 1977-1993 and 2010-1994 in Ardabil synoptic station shows that the difference of rainfall is not significant at the 5% error level from statistical point of view. The comparison between the monthly mean rainfall of Ardabil synoptic station in 1994-2010 and 1977-1993 indicates that rainfall has somewhat decreased in the former in recent years. Considering the low average monthly rainfall of Ardabil synoptic station in 1994-2010 compared to 1977-1993 (21.98 versus 26.11 mm, although no statistically significant difference was found in the average rainfall, low rainfall in this station would not be unexpected in the coming years. The comparison of predicted and actual values from 2011 to 2013 in Ardabil synoptic station showed that fitting real data with expected data was relatively acceptable. The observed differences between the actual and predicted values can be related to the influence of rainfalls and many local and dynamical factors of this area. Therefore, it is necessary

  4. Assessment of morphological and hydrological parameters of Oyun ...

    African Journals Online (AJOL)

    The study involves evaluation of basin area, slopes, shape of the basin as morphological parameters and analysis of flow frequencies for flood and low flows, developing unit hydrograph and analysis of rainfall intensity distribution in the study area as hydrological parameters. The morphological analysis of the basin yielded ...

  5. Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

    Directory of Open Access Journals (Sweden)

    T. P. Burt

    2014-09-01

    Full Text Available Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana, where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.

  6. Extreme Rainfall In A City

    Science.gov (United States)

    Nkemdirim, Lawrence

    Cities contain many structures and activities that are vulnerable to severe weather. Heavy precipitation cause floods which can damage structures, compromise transportation and water supply systems, and slow down economic and social activities. Rain induced flood patterns in cities must be well understood to enable effective placement of flood control and other regulatory measures. The planning goal is not to eliminate all floods but to reduce their frequency and resulting damage. Possible approaches to such planning include probability based extreme event analysis. Precipitation is normally the most variable hydrologic element over a given area. This variability results from the distribution of clouds and in cloud processes in the atmosphere, the storm path, and the distribution of topographical features on the ground along path. Some studies suggest that point rainfall patterns are also affected by urban industrial effects hence some agreement that cities are wetter than the country surrounding them. However, there are still questions regarding the intra- urban distribution of precipitation. The sealed surfaces, urban structures, and the urban heat anomaly increase convection in cities which may enhance the generation of clouds. Increased dust and gaseous aerosols loads are effective condensation and sublimation nuclei which may also enhance the generation of precipitation. Based on these associations, the greatest amount of convection type rainfall should occur at city center. A study of summer rainfall in Calgary showed that frequencies of trace amounts of rainfall and events under 0.2mm are highest downtown than elsewhere. For amounts greater than than 0.2 mm, downtown sites were not favored. The most compelling evidence for urban-industrial precipitation enhancement came from the Metromex project around St. Loius, Missouri where maximum increases of between 5 to 30 per cent in summer rainfall downwind of the city was linked to urbanization and

  7. Constraining continuous rainfall simulations for derived design flood estimation

    Science.gov (United States)

    Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

    2016-11-01

    Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

  8. Characterization of rainfall events and correlation with reported disasters: A case in Cali, Colombia

    Science.gov (United States)

    Canon, C. C.; Tischbein, B.; Bogardi, J.

    2017-12-01

    Flood maps generally display the area that a river might overflow after a rainfall event takes place, under different scenarios of climate, land use/land cover, and/or failure of dams and dikes. However, rainfall is not limited to feed runoff and enlarge the river: it also causes minor disasters outside the map's highlighted area. The city of Cali in Colombia illustrates very well this situation: its flat topography and its major critical infrastructure near the river make it flood-risk prone; a heavy rainfall event would potentially deplete drinking water, electrical power and drainage capacity, and trigger outbreaks of water-borne diseases in the whole city, not only in the flooded area. Unfortunately, the government's disaster prevention strategies focus on the floodplain and usually overlook the aftermath of these minor disasters for being milder and scattered. Predicted losses in flood maps are potentially big, while those from minor disasters over the city are small but real, and citizens, utility companies and urban maintenance funds must constantly take them over. Mitigation and prevention of such minor disasters can save money for the development of the city in other aspects. This paper characterizes hundreds of rainfall events selected from 10-min step time series from 2006 to 2017, and finds their correlation with reported rainfall-related disasters throughout Cali, identified by date and neighborhood. Results show which rainfall parameters are most likely to indicate the occurrence of such disasters and their approximate location in the urban area of Cali. These results, when coupled with real-time observations of rainfall data and simulations of drainage network response, may help citizens and emergency bodies prioritize zones to assist during heavy storms. In the long term, stakeholders may also implement low impact development solutions in these zones to reduce flood risks.

  9. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology...... necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall...... estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological...

  10. Evaluation of Surface Runoff Generation Processes Using a Rainfall Simulator: A Small Scale Laboratory Experiment

    Science.gov (United States)

    Danáčová, Michaela; Valent, Peter; Výleta, Roman

    2017-12-01

    of 5 mm/min was used to irrigate a corrupted soil sample. The experiment was undertaken for several different slopes, under the condition of no vegetation cover. The results of the rainfall simulation experiment complied with the expectations of a strong relationship between the slope gradient, and the amount of surface runoff generated. The experiments with higher slope gradients were characterised by larger volumes of surface runoff generated, and by shorter times after which it occurred. The experiments with rainfall simulators in both laboratory and field conditions play an important role in better understanding of runoff generation processes. The results of such small scale experiments could be used to estimate some of the parameters of complex hydrological models, which are used to model rainfall-runoff and erosion processes at catchment scale.

  11. Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

    Science.gov (United States)

    Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

    2017-09-01

    In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

  12. Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil

    Energy Technology Data Exchange (ETDEWEB)

    Blaustein, Ryan A., E-mail: rblauste@ufl.edu [USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, MD (United States); Department of Environmental Science and Technology, University of Maryland, College Park, MD (United States); Hill, Robert L. [Department of Environmental Science and Technology, University of Maryland, College Park, MD (United States); Micallef, Shirley A. [Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD (United States); Center for Food Safety and Security Systems, University of Maryland, College Park, MD (United States); Shelton, Daniel R.; Pachepsky, Yakov A. [USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, MD (United States)

    2016-01-01

    The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli, enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9 cm h{sup −1} of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10 cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment. - Highlights: • Release and removal of indicator bacteria from manure was evaluated in soil boxes. • Rainfall intensity did not impact runoff-removal kinetics in three tested models. • Rainfall intensity had positive/inverse effects on bacterial release to runoff

  13. Effect of an isolated elliptical terrain (Jeju Island on rainfall enhancement in a moist environment

    Directory of Open Access Journals (Sweden)

    Keun-OK Lee

    2014-03-01

    Full Text Available A series of idealised experiments using a cloud-resolving storm simulator (CReSS was performed to investigate the effects of the isolated elliptically shaped terrain of Jeju Island (oriented east–west, southern Korea, on the enhancement of pre-existing rainfall systems under the influence of prevailing southwesterly moist flows. Control parameters were the low-altitude wind speed (Froude numbers: 0.2, 0.4, 0.55 and the initial location of the elongated (oriented north–east rainfall system (off the northwestern or western shores of the island. Simulations were conducted for all combinations of initial location and wind regime. Overall, results indicate that weak southwesterlies flowing around the steep mountain on the island (height, 2 km generate two local convergences, on the northern lateral side and on the lee side of the island, both in regions of moist environments, thus producing conditions favourable for enhanced rainfall. As an eastward-moving rainfall system approaches the northwestern shore of the island, the southwesterlies at low altitudes accelerate between the system and the terrain, generating a local updraft region that causes rainfall enhancement onshore in advance of the system's arrival over the terrain. Thus, the prevailing southwesterlies at low altitudes that are parallel to the terrain are a crucial element for the enhancement. Relatively weak southwesterlies at low altitudes allow system enhancement on the lee side by generating a convergence of relatively weak go-around northwesterlies from the northern island and relatively strong moist southwesterlies from the southern island, thus producing a relatively long-lived rainfall system. As the southwesterlies strengthen, a dry descending air mass intensifies on the northeastern downwind side of the terrain, rapidly dissipating rainfall and resulting in a relatively short-lived rainfall system. A coexisting terrain-generated local convergence, combined with the absence

  14. The partitioning of litter carbon during litter decomposition under different rainfall patterns: a laboratory study

    Science.gov (United States)

    Yang, X.; Szlavecz, K. A.; Langley, J. A.; Pitz, S.; Chang, C. H.

    2017-12-01

    . Including the rainfall pattern as a parameter to the partitioning of litter carbon could help better project soil carbon cycling in the Mid-Atlantic region.

  15. Rainfall model investigation and scenario analyses of the effect of government reforestation policy on seasonal rainfalls: A case study from Northern Thailand

    Science.gov (United States)

    Duangdai, Eakkapong; Likasiri, Chulin

    2017-03-01

    In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.

  16. Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

    Science.gov (United States)

    Villafuerte, Marcelino, II; Matsumoto, Jun

    2014-05-01

    Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region

  17. Uncertainty of the Soil–Water Characteristic Curve and Its Effects on Slope Seepage and Stability Analysis under Conditions of Rainfall Using the Markov Chain Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    Weiping Liu

    2017-10-01

    Full Text Available It is important to determine the soil–water characteristic curve (SWCC for analyzing slope seepage and stability under the conditions of rainfall. However, SWCCs exhibit high uncertainty because of complex influencing factors, which has not been previously considered in slope seepage and stability analysis under conditions of rainfall. This study aimed to evaluate the uncertainty of the SWCC and its effects on the seepage and stability analysis of an unsaturated soil slope under conditions of rainfall. The SWCC model parameters were treated as random variables. An uncertainty evaluation of the parameters was conducted based on the Bayesian approach and the Markov chain Monte Carlo (MCMC method. Observed data from granite residual soil were used to test the uncertainty of the SWCC. Then, different confidence intervals for the model parameters of the SWCC were constructed. The slope seepage and stability analysis under conditions of rainfall with the SWCC of different confidence intervals was investigated using finite element software (SEEP/W and SLOPE/W. The results demonstrated that SWCC uncertainty had significant effects on slope seepage and stability. In general, the larger the percentile value, the greater the reduction of negative pore-water pressure in the soil layer and the lower the safety factor of the slope. Uncertainties in the model parameters of the SWCC can lead to obvious errors in predicted pore-water pressure profiles and the estimated safety factor of the slope under conditions of rainfall.

  18. Contribution of tropical cyclones to global rainfall

    Science.gov (United States)

    Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

    2016-04-01

    Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar

  19. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation

    Science.gov (United States)

    R. H. Hawkins; A. Barreto-Munoz

    2016-01-01

    Wildcat5 for Windows (Wildcat5) is an interactive Windows Excel-based software package designed to assist watershed specialists in analyzing rainfall runoff events to predict peak flow and runoff volumes generated by single-event rainstorms for a variety of watershed soil and vegetation conditions. Model inputs are: (1) rainstorm characteristics, (2) parameters related...

  20. Commercial application of rainfall simulation

    Science.gov (United States)

    Loch, Rob J.

    2010-05-01

    Landloch Pty Ltd is a commercial consulting firm, providing advice on a range of land management issues to the mining and construction industries in Australia. As part of the company's day-to-day operations, rainfall simulation is used to assess material erodibility and to investigate a range of site attributes. (Landloch does carry out research projects, though such are not its core business.) When treated as an everyday working tool, several aspects of rainfall simulation practice are distinctively modified. Firstly, the equipment used is regularly maintained, and regularly upgraded with a primary focus on ease, safety, and efficiency of use and on reliability of function. As well, trained and experienced technical support is considered essential. Landloch's chief technician has over 10 years experience in running rainfall simulators at locations across Australia and in Africa and the Pacific. Secondly, the specific experimental conditions established for each set of rainfall simulator runs are carefully considered to ensure that they accurately represent the field conditions to which the data will be subsequently applied. Considerations here include: • wetting and drying cycles to ensure material consolidation and/or cementation if appropriate; • careful attention to water quality if dealing with clay soils or with amendments such as gypsum; • strong focus on ensuring that the erosion processes considered are those of greatest importance to the field situation of concern; and • detailed description of both material and plot properties, to increase the potential for data to be applicable to a wider range of projects and investigations. Other important company procedures include: • For each project, the scientist or engineer responsible for analysing and reporting rainfall simulator data is present during the running of all field plots, as it is essential that they be aware of any specific conditions that may have developed when the plots were subjected

  1. Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

    OpenAIRE

    Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

    2014-01-01

    In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering t...

  2. Propagation of radar rainfall uncertainty in urban flood simulations

    Science.gov (United States)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

    hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF

  3. Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

    Science.gov (United States)

    Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

    2016-08-05

    Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

  4. Heavy daily-rainfall characteristics over the Gauteng Province

    African Journals Online (AJOL)

    2009-02-09

    Feb 9, 2009 ... the lowest number of heavy and very heavy rainfall days. The highest 24-h ... With regard to seasonal rainfall, the 1995/96 summer rainfall season had ..... The Gauteng Province is approximately 16 500 km2 in size. When the ...

  5. A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

    Science.gov (United States)

    Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

    2016-12-01

    demonstrate the model output through spatial maps of rainfall and through statistical comparisons of relevant parameters and distributions. Finally, discuss how the model can be used to understand basin-scale hydrology in terms of soil moisture, runoff, and erosion.

  6. Hydrological Effects of Historic Rainfall on the Waccamaw River

    Science.gov (United States)

    Jolly, J.; Bao, S.

    2017-12-01

    This study focuses on the overall water budget of the Waccamaw River during and after a historic rainfall event related to Hurricane Joaquin, producing a 1000-year rainfall event. While rainfall is the only input, it enters the basin through various means. Some rainwater enters the soil as soil moisture while rainfall also goes underground and enters the river channels from underground, which is defined as bucket in. Over time, the rainfall was removed from the river site through various natural processes. Those processes, including evaporation, soil storage as soil moisture, discharge runoff through the river channel, among others, were modeled and validated against the USGS gauge stations. The validated model results were then used to estimate the hydrological response of the Waccamaw River to the rainfall event and determine the overall water budget. The experiment was completed using a WRF-Hydro modeling system for the purposes of weather forecasting and meteorological analysis. Upon completion of the data analysis, the WRF-Hydro model result showed that large amounts of rainfall were variously dispersed through the aforementioned areas. It was determined that after entering the soil rainfall predominantly left the river basin by discharge, while evaporation accounted for the second most common destination of rainfall. Base flow also accounted for a destination of rainfall, though not as much as those previously mentioned.

  7. Heavy rainfall equations for Santa Catarina, Brazil

    Directory of Open Access Journals (Sweden)

    Álvaro José Back

    2011-12-01

    Full Text Available Knowledge of intensity-duration-frequency (IDF relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

  8. Rainfall interception of three trees in Oakland, California

    Science.gov (United States)

    Qingfu Xiao; E. Gregory McPherson

    2011-01-01

    A rainfall interception study was conducted in Oakland, California to determine the partitioning of rainfall and the chemical composition of precipitation, throughfall, and stemflow. Rainfall interception measurements were conducted on a gingko (Ginkgo biloba) (13.5 m tall deciduous tree), sweet gum (Liquidambar styraciflua) (8...

  9. Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

    Science.gov (United States)

    Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

    2014-09-01

    Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

  10. Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

    Directory of Open Access Journals (Sweden)

    F. Alahmadi

    2014-09-01

    Full Text Available Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC, Corrected Akaike Information Criterion (AICc, Bayesian Information Criterion (BIC and Anderson-Darling Criterion (ADC. The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

  11. Canopy rainfall partitioning across an urbanization gradient in forest structure as characterized by terrestrial LiDAR

    Science.gov (United States)

    Mesta, D. C.; Van Stan, J. T., II; Yankine, S. A.; Cote, J. F.; Jarvis, M. T.; Hildebrandt, A.; Friesen, J.; Maldonado, G.

    2017-12-01

    As urbanization expands, greater forest area is shifting from natural stand structures to urban stand structures, like forest fragments and landscaped tree rows. Changes in forest canopy structure have been found to drastically alter the amount of rainwater reaching the surface. However, stormwater management models generally treat all forest structures (beyond needle versus broadleaved) similarly. This study examines the rainfall partitioning of Pinus spp. canopies along a natural-to-urban forest gradient and compares these to canopy structural measurements using terrestrial LiDAR. Throughfall and meteorological observations were also used to estimate parameters of the commonly-used Gash interception model. Preliminary findings indicate that as forest structure changed from natural, closed canopy conditions to semi-closed canopy fragments and, ultimately, to exposed urban landscaping tree rows, the interchange between throughfall and rainfall interception also changed. This shift in partitioning between throughfall and rainfall interception may be linked to intuitive parameters, like canopy closure and density, as well as more complex metrics, like the fine-scale patterning of gaps (ie, lacunarity). Thus, results indicate that not all forests of the same species should be treated the same by stormwater models. Rather, their canopy structural characteristics should be used to vary their hydrometeorological interactions.

  12. The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

    Science.gov (United States)

    Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

    2017-11-01

    Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

  13. Satellite and gauge rainfall merging using geographically weighted regression

    Directory of Open Access Journals (Sweden)

    Q. Hu

    2015-05-01

    Full Text Available A residual-based rainfall merging scheme using geographically weighted regression (GWR has been proposed. This method is capable of simultaneously blending various satellite rainfall data with gauge measurements and could describe the non-stationary influences of geographical and terrain factors on rainfall spatial distribution. Using this new method, an experimental study on merging daily rainfall from the Climate Prediction Center Morphing dataset (CMOROH and gauge measurements was conducted for the Ganjiang River basin, in Southeast China. We investigated the capability of the merging scheme for daily rainfall estimation under different gauge density. Results showed that under the condition of sparse gauge density the merging rainfall scheme is remarkably superior to the interpolation using just gauge data.

  14. Extreme value analysis of meteorological parameters observed during the period 1994-2001 at Kakrapar Atomic Power Station

    International Nuclear Information System (INIS)

    Ramkumar, S.; Dole, M.L.; Nankar, D.P.; Rajan, M.P.; Gurg, R.P.

    2003-01-01

    In the design of engineering structures, an understanding of extreme weather conditions that may occur at the site of interest is very essential, so that the structures can be designed to withstand such situations. In this report an analysis of extreme values of meteorological parameters observed at Kakrapar Atomic Power Station site for the period 1994 -2001 is described. The parameters considered are maximum and minimum air temperature, maximum wind speed and gust, and maximum rainfall in a month, in a day, in an hour and annual rainfall. The extreme value analysis reveals that annual rainfall, maximum monthly rainfall, minimum air temperature and maximum wind speed at 10 m obey Fisher-Tippet Type -1 distribution whereas maximum daily rainfall, maximum hourly rainfall, maxinlum air temperature and maximum wind speed at 30 m obey Fisher-Tippet Type -2 distribution function. There is no difference in correlation coefficients and fit both extreme value distribution function. Co-efficients of the distribution functions for each variable are established. Extreme values of parameters corresponding to return periods of 50 and 100 years are derived. These derived extreme values are particularly useful for arriving at suitable design basis values to ensure the safety of any civil structure in and around Kakrapar Atomic Power Station site with respect to stresses due to weather conditions. (author)

  15. Automated reconstruction of rainfall events responsible for shallow landslides

    Science.gov (United States)

    Vessia, G.; Parise, M.; Brunetti, M. T.; Peruccacci, S.; Rossi, M.; Vennari, C.; Guzzetti, F.

    2014-04-01

    Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.

  16. Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

    Directory of Open Access Journals (Sweden)

    Assumpta Mukabutera

    2016-08-01

    Full Text Available Abstract Background Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. Methods We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Results Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff but had no impact among children in household with improved toilets. Conclusion Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

  17. Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert.

    Science.gov (United States)

    Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

    2016-05-17

    In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

  18. THE IMPACT OF SPATIAL AND TEMPORAL RESOLUTIONS IN TROPICAL SUMMER RAINFALL DISTRIBUTION: PRELIMINARY RESULTS

    Directory of Open Access Journals (Sweden)

    Q. Liu

    2017-10-01

    Full Text Available The abundance or lack of rainfall affects peoples’ life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007, accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG. However, the models’ resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days and monthly resolutions. The probability distributions (PDF and cumulative distribution functions(CDF of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

  19. The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

    Science.gov (United States)

    Liu, Q.; Chiu, L. S.; Hao, X.

    2017-10-01

    The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

  20. A Poisson Cluster Stochastic Rainfall Generator That Accounts for the Interannual Variability of Rainfall Statistics: Validation at Various Geographic Locations across the United States

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2014-01-01

    Full Text Available A novel approach for a Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations in the United States. The suggested novel approach, The Hybrid Model (THM, as compared to the traditional Poisson cluster rainfall modeling approaches, has an additional capability to account for the interannual variability of rainfall statistics. THM and a traditional approach of Poisson cluster rainfall model (modified Bartlett-Lewis rectangular pulse model were compared in their ability to reproduce the characteristics of extreme rainfall and watershed response variables such as runoff and peak flow. The results of the comparison indicate that THM generally outperforms the traditional approach in reproducing the distributions of peak rainfall, peak flow, and runoff volume. In addition, THM significantly outperformed the traditional approach in reproducing extreme rainfall by 2.3% to 66% and extreme flow values by 32% to 71%.

  1. A regional and nonstationary model for partial duration series of extreme rainfall

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

    2017-01-01

    as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...

  2. A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

    Science.gov (United States)

    Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

    2018-01-01

    Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

  3. Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

    Science.gov (United States)

    Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

    2013-04-01

    Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is

  4. A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale

    Directory of Open Access Journals (Sweden)

    Yaokui Cui

    2014-04-01

    Full Text Available Rainfall interception loss of forest is an important component of water balance in a forested ecosystem. The Gash analytical model has been widely used to estimate the forest interception loss at field scale. In this study, we proposed a simple model to estimate rainfall interception loss of heterogeneous forest at regional scale with several reasonable assumptions using remote sensing observations. The model is a modified Gash analytical model using easily measured parameters of forest structure from satellite data and extends the original Gash model from point-scale to the regional scale. Preliminary results, using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS products, field measured rainfall data, and meteorological data of the Automatic Weather Station (AWS over a picea crassifolia forest in the upper reaches of the Heihe River Basin in northwestern China, showed reasonable accuracy in estimating rainfall interception loss at both the Dayekou experimental site (R2 = 0.91, RMSE = 0.34 mm∙d −1 and the Pailugou experimental site (R2 = 0.82, RMSE = 0.6 mm∙d −1, compared with ground measurements based on per unit area of forest. The interception loss map of the study area was shown to be strongly heterogeneous. The modified model has robust physics and is insensitive to the input parameters, according to the sensitivity analysis using numerical simulations. The modified model appears to be stable and easy to be applied for operational estimation of interception loss over large areas.

  5. Accuracy of rainfall measurement for scales of hydrological interest

    Directory of Open Access Journals (Sweden)

    S. J. Wood

    2000-01-01

    Full Text Available The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a 'true value' of rainfall against which the 2 km radar grid and a single 'typical gauge' estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the 'true catchment rainfall' and the accuracy of a radar estimate (an area-weighted average of radar pixel values and a single 'typical gauge' estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000 considers the accuracy of rainfall estimates obtained using raingauge and radar in combination. Keywords: rainfall, accuracy, raingauge, radar

  6. Potential of deterministic and geostatistical rainfall interpolation under high rainfall variability and dry spells: case of Kenya's Central Highlands

    Science.gov (United States)

    Kisaka, M. Oscar; Mucheru-Muna, M.; Ngetich, F. K.; Mugwe, J.; Mugendi, D.; Mairura, F.; Shisanya, C.; Makokha, G. L.

    2016-04-01

    Drier parts of Kenya's Central Highlands endure persistent crop failure and declining agricultural productivity. These have, in part, attributed to high temperatures, prolonged dry spells and erratic rainfall. Understanding spatial-temporal variability of climatic indices such as rainfall at seasonal level is critical for optimal rain-fed agricultural productivity and natural resource management in the study area. However, the predominant setbacks in analysing hydro-meteorological events are occasioned by either lack, inadequate, or inconsistent meteorological data. Like in most other places, the sole sources of climatic data in the study region are scarce and only limited to single stations, yet with persistent missing/unrecorded data making their utilization a challenge. This study examined seasonal anomalies and variability in rainfall, drought occurrence and the efficacy of interpolation techniques in the drier regions of eastern Kenyan. Rainfall data from five stations (Machang'a, Kiritiri, Kiambere and Kindaruma and Embu) were sourced from both the Kenya Meteorology Department and on-site primary recording. Owing to some experimental work ongoing, automated recording for primary dailies in Machang'a have been ongoing since the year 2000 to date; thus, Machang'a was treated as reference (for period of record) station for selection of other stations in the region. The other stations had data sets of over 15 years with missing data of less than 10 % as required by the world meteorological organization whose quality check is subject to the Centre for Climate Systems Modeling (C2SM) through MeteoSwiss and EMPA bodies. The dailies were also subjected to homogeneity testing to evaluate whether they came from the same population. Rainfall anomaly index, coefficients of variance and probability were utilized in the analyses of rainfall variability. Spline, kriging and inverse distance weighting interpolation techniques were assessed using daily rainfall data and

  7. Isotopic composition of rainfall and runoff in a small arid basin with implications for deep percolation

    International Nuclear Information System (INIS)

    Dody, A.

    1995-08-01

    The aim of this work was to characterize the isotopic composition of potential recharge in an arid rocky watershed. Unique field observations were obtained from an arid watershed in the Negev Highlands, Israel, through utilization of the dynamic variations in the isotopic composition of rainfall and runoff. The hydrological system's inputs are rainfall and its isotopic composition. Rainfall and runoff were sampled in eight storms. High variability in the isotopic composition of rainfall was observed during any single rainstorm. The isotopic distribution in the runoff at the outlet of the basin appeared often not to be correlated to the isotopic patterns of the associated rain storm. A new mathematical model was developed to describe these physical processes. The model called A Double-Component Kinematic Wave Flow and Transport Approach, was designated to assess the dynamic isotopic distribution in arid rain storms and runoff. This model simulates the transport of rainfall into overland flow and runoff in an arid rocky watershed with uniformly distributed shallow depression storage. A numerical solution for the problem was developed, to estimate the depression storage parameters. The model also reflects the isotopic memory effect due to the depression storage between sequential rain showers. A good agreement between the observed and computed hydrograph and the change of the δ 18O values in runoff in time confirms the validity of the model. (author) 138 figs., 125 refs

  8. Rainfall erosivity factor estimation in Republic of Moldova

    Science.gov (United States)

    Castraveš, Tudor; Kuhn, Nikolaus

    2017-04-01

    Rainfall erosivity represents a measure of the erosive force of rainfall. Typically, it is expressed as variable such as the R factor in the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1965, 1978) or its derivates. The rainfall erosivity index for a rainfall event (EI30) is calculated from the total kinetic energy and maximum 30 minutes intensity of individual events. However, these data are often unavailable for wide regions and countries. Usually, there are three issues regarding precipitation data: low temporal resolution, low spatial density and limited access to the data. This is especially true for some of postsoviet countries from Eastern Europe, such as Republic of Moldova, where soil erosion is a real and persistent problem (Summer, 2003) and where soils represents the main natural resource of the country. Consequently, researching and managing soil erosion is particularly important. The purpose of this study is to develop a model based on commonly available rainfall data, such as event, daily or monthly amounts, to calculate rainfall erosivity for the territory of Republic of Moldova. Rainfall data collected during 1994-2015 period at 15 meteorological stations in the Republic of Moldova, with 10 minutes temporal resolution, were used to develop and calibrate a model to generate an erosivity map of Moldova. References 1. Summer, W., (2003). Soil erosion in the Republic of Moldova — the importance of institutional arrangements. Erosion Prediction in Ungauged Basins: Integrating Methods and Techniques (Proceedings of symposium HS01 held during IUGG2003 at Sapporo. July 2003). IAHS Publ. no. 279. 2. Wischmeier, W.H., and Smith, D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains. Agr. Handbook No. 282, U.S. Dept. Agr., Washington, DC 3. Wischmeier, W.H., and Smith, D.D. (1978). Predicting rainfall erosion losses. Agr. handbook No. 537, U.S. Dept. of Agr., Science and Education Administration.

  9. Rainfall reliability, drought and flood vulnerability in Botswana ...

    African Journals Online (AJOL)

    Rainfall data from 14 stations (cities, towns and major villages) spanning 26 years (1970 to 1995) were used to calculate reliability and vulnerability of rainfall in Botswana. Time series data for 72 years were generated from the long-term rainfall gauging stations and the number of wet and dry years determined. Apart from ...

  10. Projected changes of rainfall event characteristics for the Czech Republic

    Directory of Open Access Journals (Sweden)

    Svoboda Vojtěch

    2016-12-01

    Full Text Available Projected changes of warm season (May–September rainfall events in an ensemble of 30 regional climate model (RCM simulations are assessed for the Czech Republic. Individual rainfall events are identified using the concept of minimum inter-event time and only heavy events are considered. The changes of rainfall event characteristics are evaluated between the control (1981–2000 and two scenario (2020–2049 and 2070–2099 periods. Despite a consistent decrease in the number of heavy rainfall events, there is a large uncertainty in projected changes in seasonal precipitation total due to heavy events. Most considered characteristics (rainfall event depth, mean rainfall rate, maximum 60-min rainfall intensity and indicators of rainfall event erosivity are projected to increase and larger increases appear for more extreme values. Only rainfall event duration slightly decreases in the more distant scenario period according to the RCM simulations. As a consequence, the number of less extreme heavy rainfall events as well as the number of long events decreases in majority of the RCM simulations. Changes in most event characteristics (and especially in characteristics related to the rainfall intensity depend on changes in radiative forcing and temperature for the future periods. Only changes in the number of events and seasonal total due to heavy events depend significantly on altitude.

  11. Temporal and spatial variations of rainfall erosivity in Southern Taiwan

    Science.gov (United States)

    Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

    2014-05-01

    Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

  12. Performance of bias corrected MPEG rainfall estimate for rainfall-runoff simulation in the upper Blue Nile Basin, Ethiopia

    Science.gov (United States)

    Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.

    2018-01-01

    In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.

  13. Mixing the Green-Ampt model and Curve Number method as an empirical tool for rainfall excess estimation in small ungauged catchments.

    Science.gov (United States)

    Grimaldi, S.; Petroselli, A.; Romano, N.

    2012-04-01

    The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS-CN is a simple and valuable approach to estimate the total stream-flow volume generated by a storm rainfall, but it was developed to be used with daily rainfall data. To overcome this drawback, we propose to include the Green-Ampt (GA) infiltration model into a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt), aiming to distribute in time the information provided by the SCS-CN method so as to provide estimation of sub-daily incremental rainfall excess. For a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model. The proposed procedure was evaluated by analyzing 100 rainfall-runoff events observed in four small catchments of varying size. CN4GA appears an encouraging tool for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, a better agreement with observed hydrographs than that of the classic SCS-CN method.

  14. Temporal characteristics of rainfall events under three climate types in Slovenia

    Science.gov (United States)

    Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

    2016-10-01

    Temporal rainfall distribution can often have significant influence on other hydrological processes such as runoff generation or rainfall interception. High-frequency rainfall data from 30 stations in Slovenia were analysed in order to improve the knowledge about the temporal rainfall distribution within a rainfall event. Using the pre-processed rainfall data Huff curves were determined and the binary shape code (BSC) methodology was applied. Although Slovenia covers only about 20,000 km2, results indicate large temporal and spatial variability in the precipitation pattern of the analysed stations, which is in agreement with the different Slovenian climate types: sub-Mediterranean, temperate continental, and mountain climate. Statistically significant correlation was identified between the most frequent BSC types, mean annual precipitation, and rainfall erosivity for individual rainfall stations. Moreover, different temporal rainfall distributions were observed for rainfall events with shorter duration (less than 12 h) than those with longer duration (more than 24 h). Using the analysis of the Huff curves it was shown that the variability in the Huff curves decreases with increasing rainfall duration. Thus, it seems that for shorter duration convective storms a more diverse temporal rainfall distribution can be expected than for the longer duration frontal precipitation where temporal rainfall distribution shows less variability.

  15. Application of the rainfall infiltration breakthrough (RIB) model for groundwater recharge estimation in west coastal South Africa

    CSIR Research Space (South Africa)

    Sun, X

    2013-04-01

    Full Text Available level fluctuations (WLF) on a monthly basis was proposed in the rainfall infiltration breakthrough (RIB) model for the purpose of groundwater recharge estimation. In this paper, the physical meaning of parameters in the CRD and previous RIB models...

  16. How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

    Science.gov (United States)

    Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

    2017-12-01

    Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

  17. Classification of rainfall events for weather forecasting purposes in andean region of Colombia

    Science.gov (United States)

    Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

    2016-04-01

    This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main

  18. Validation and evaluation of epistemic uncertainty in rainfall thresholds for regional scale landslide forecasting

    Science.gov (United States)

    Gariano, Stefano Luigi; Brunetti, Maria Teresa; Iovine, Giulio; Melillo, Massimo; Peruccacci, Silvia; Terranova, Oreste Giuseppe; Vennari, Carmela; Guzzetti, Fausto

    2015-04-01

    Prediction of rainfall-induced landslides can rely on empirical rainfall thresholds. These are obtained from the analysis of past rainfall events that have (or have not) resulted in slope failures. Accurate prediction requires reliable thresholds, which need to be validated before their use in operational landslide warning systems. Despite the clear relevance of validation, only a few studies have addressed the problem, and have proposed and tested robust validation procedures. We propose a validation procedure that allows for the definition of optimal thresholds for early warning purposes. The validation is based on contingency table, skill scores, and receiver operating characteristic (ROC) analysis. To establish the optimal threshold, which maximizes the correct landslide predictions and minimizes the incorrect predictions, we propose an index that results from the linear combination of three weighted skill scores. Selection of the optimal threshold depends on the scope and the operational characteristics of the early warning system. The choice is made by selecting appropriately the weights, and by searching for the optimal (maximum) value of the index. We discuss weakness in the validation procedure caused by the inherent lack of information (epistemic uncertainty) on landslide occurrence typical of large study areas. When working at the regional scale, landslides may have occurred and may have not been reported. This results in biases and variations in the contingencies and the skill scores. We introduce two parameters to represent the unknown proportion of rainfall events (above and below the threshold) for which landslides occurred and went unreported. We show that even a very small underestimation in the number of landslides can result in a significant decrease in the performance of a threshold measured by the skill scores. We show that the variations in the skill scores are different for different uncertainty of events above or below the threshold. This

  19. Effects of Hydrological Parameters on Palm Oil Fresh Fruit Bunch Yield)

    Science.gov (United States)

    Nda, M.; Adnan, M. S.; Suhadak, M. A.; Zakaria, M. S.; Lopa, R. T.

    2018-04-01

    Climate change effects and variability have been studied by many researchers in diverse geophysical fields. Malaysia produces large volume of palm oil, the effects of climate change on hydrological parameters (rainfall and precipitation) could have adverse effects on palm oil fresh fruit bunch (FFB) production with implications at both local and international market. It is important to understand the effects of climate change on crop yield to adopt new cultivation techniques and guaranteeing food security globally. Based on this background, the paper’s objective is to investigate the effects of rainfall and temperature pattern on crop yield (FFB) within five years period (2013 - 2017) at Batu Pahat District. The Man - Kendall rank technique (trend test) and statistical analyses (correlation and regression) were applied to the dataset used for the study. The results reveal that there are variabilities in rainfall and temperature from one month to the other and the statistical analysis reveals that the hydrological parameters have an insignificant effect on crop yield.

  20. Evaluation of short-period rainfall estimates from Kalpana-1 satellite

    Indian Academy of Sciences (India)

    The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study ...

  1. Regional rainfall thresholds for landslide occurrence using a centenary database

    Science.gov (United States)

    Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

    2018-04-01

    This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

  2. Extreme Rainfall Mechanisms Exhibited by Typhoon Morakot (2009

    Directory of Open Access Journals (Sweden)

    Ching-Yuang Huang

    2011-01-01

    Full Text Available Moderate Typhoon Morakot (2009 became the most catastrophic typhoon in Taiwan on record. The MM5 numerical experiments with and without bogus data assimilation (BDA were used to investigate the extreme rainfall mechanisms in Taiwan associated with the westbound typhoon. The BDA, based on 4DVAR, helps MM5 to maintain a more consolidated typhoon vortex and better predict the observed track after landfall, thus producing realistic extreme rainfall (about 2400 mm at the southern and Central Mountain Range (CMR of Taiwan. Severe rainfall in Taiwan is dominated by the CMR that hence modulates rainfall predictability.

  3. Rainfall and Development of Zika Virus

    African Journals Online (AJOL)

    2017-11-01

    Nov 1, 2017 ... between rainfall and incidence of arbovirus disease such as dengue is well demonstrated (2). For Zika virus an infection, a similar observation can be expected. A recent report from Thailand can also show the expected pattern of the prevalence of Zika virus infection in the areas with high rainfall (3).

  4. A comprehensive continent-wide regionalisation investigation for daily design rainfall

    OpenAIRE

    F. Johnson; J. Green

    2018-01-01

    Study region: Australia. Study focus: Design rainfalls, in the form of Intensity Duration Frequency curves, are the standard input for most flood studies. Methods to combine rainfall data across space are required to provide optimal estimates of design rainfalls and constrain their uncertainty. This paper robustly investigates the use of a variety of regionalization methods to provide Australia wide design rainfall estimates using 8619 high quality rainfall stations. The influence of an indiv...

  5. Rainfall leaching is critical for long-term use of recycled water in the Salinas Valley

    Directory of Open Access Journals (Sweden)

    Belinda E. Platts

    2014-07-01

    Full Text Available In 1998, Monterey County Water Recycling Projects began delivering water to 12,000 acres in the northern Salinas Valley. Two years later, an ongoing study began assessing the effects of the recycled water on soil salinity. Eight sites are receiving recycled water and a control site is receiving only well water. In data collected from 2000 to 2012, soil salinity of the 36-inch-deep profile was on average approximately double that of the applied water, suggesting significant leaching from applied water (irrigation or rainfall. In this study, we investigated some of the soil water hydrology factors possibly controlling the soil salinity results. Using soil water balance modeling, we found that rainfall had more effect on soil salinity than did leaching from irrigation. Increasing applied water usually only correlated significantly with soil salinity parameters in the shallow soil profile (1 to 12 inches depth and at 24 to 36 inches at sites receiving fairly undiluted recycled water. Winter rains, though, had a critical effect. Increasing rainfall depths were significantly correlated with decreasing soil salinity of the shallow soil at all test sites, though this effect also diminished with increased soil depth. When applied water had high salinity levels, winter rainfall in this area was inadequate to prevent soil salinity from increasing.

  6. Rainfall mediations in the spreading of epidemic cholera

    Science.gov (United States)

    Righetto, L.; Bertuzzo, E.; Mari, L.; Schild, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2013-10-01

    Following the empirical evidence of a clear correlation between rainfall events and cholera resurgence that was observed in particular during the recent outbreak in Haiti, a spatially explicit model of epidemic cholera is re-examined. Specifically, we test a multivariate Poisson rainfall generator, with parameters varying in space and time, as a driver of enhanced disease transmission. The relevance of the issue relates to the key insight that predictive mathematical models may provide into the course of an ongoing cholera epidemic aiding emergency management (say, in allocating life-saving supplies or health care staff) or in evaluating alternative management strategies. Our model consists of a set of dynamical equations (SIRB-like i.e. subdivided into the compartments of Susceptible, Infected and Recovered individuals, and including a balance of Bacterial concentrations in the water reservoir) describing a connected network of human communities where the infection results from the exposure to excess concentrations of pathogens in the water. These, in turn, are driven by rainfall washout of open-air defecation sites or cesspool overflows, hydrologic transport through waterways and by mobility of susceptible and infected individuals. We perform an a posteriori analysis (from the beginning of the epidemic in October 2010 until December 2011) to test the model reliability in predicting cholera cases and in testing control measures, involving vaccination and sanitation campaigns, for the ongoing epidemic. Even though predicting reliably the timing of the epidemic resurgence proves difficult due to rainfall inter-annual variability, we find that the model can reasonably quantify the total number of reported infection cases in the selected time-span. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate conditions for further resurgences and endemicity of cholera in the region with a view to policies which may bring to

  7. Application of random number generators in genetic algorithms to improve rainfall-runoff modelling

    Science.gov (United States)

    Chlumecký, Martin; Buchtele, Josef; Richta, Karel

    2017-10-01

    The efficient calibration of rainfall-runoff models is a difficult issue, even for experienced hydrologists. Therefore, fast and high-quality model calibration is a valuable improvement. This paper describes a novel methodology and software for the optimisation of a rainfall-runoff modelling using a genetic algorithm (GA) with a newly prepared concept of a random number generator (HRNG), which is the core of the optimisation. The GA estimates model parameters using evolutionary principles, which requires a quality number generator. The new HRNG generates random numbers based on hydrological information and it provides better numbers compared to pure software generators. The GA enhances the model calibration very well and the goal is to optimise the calibration of the model with a minimum of user interaction. This article focuses on improving the internal structure of the GA, which is shielded from the user. The results that we obtained indicate that the HRNG provides a stable trend in the output quality of the model, despite various configurations of the GA. In contrast to previous research, the HRNG speeds up the calibration of the model and offers an improvement of rainfall-runoff modelling.

  8. Interannual rainfall variability over the Cape south coast of South Africa linked to cut-off low associated rainfall

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2014-10-01

    Full Text Available The influence of cut-off low (COL) associated rainfall on interannual rainfall variability over the Cape south coast region of South Africa for the period 1979-2011 is investigated. COLs are objectively identified and tracked on daily average 500 h...

  9. Effect of raingage density, position and interpolation on rainfall-discharge modelling

    Science.gov (United States)

    Ly, S.; Sohier, C.; Charles, C.; Degré, A.

    2012-04-01

    Precipitation traditionally observed using raingages or weather stations, is one of the main parameters that have direct impact on runoff production. Precipitation data require a preliminary spatial interpolation prior to hydrological modeling. The accuracy of modelling result depends on the accuracy of the interpolated spatial rainfall which differs according to different interpolation methods. The accuracy of the interpolated spatial rainfall is usually determined by cross-validation method. The objective of this study is to assess the different interpolation methods of daily rainfall at the watershed scale through hydrological modelling and to explore the best methods that provide a good long term simulation. Four versions of geostatistics: Ordinary Kriging (ORK), Universal Kriging (UNK), Kriging with External Dridft (KED) and Ordinary Cokriging (OCK) and two types of deterministic methods: Thiessen polygon (THI) and Inverse Distance Weighting (IDW) are used to produce 30-year daily rainfall inputs for a distributed physically-based hydrological model (EPIC-GRID). This work is conducted in the Ourthe and Ambleve nested catchments, located in the Ardennes hilly landscape in the Walloon region, Belgium. The total catchment area is 2908 km2, lies between 67 and 693 m in elevation. The multivariate geostatistics (KED and OCK) are also used by incorporating elevation as external data to improve the rainfall prediction. This work also aims at analysing the effect of different raingage densities and position used for interpolation, on the stream flow modelled to get insight in terms of the capability and limitation of the geostatistical methods. The number of raingage varies from 70, 60, 50, 40, 30, 20, 8 to 4 stations located in and surrounding the catchment area. In the latter case, we try to use different positions: around the catchment and only a part of the catchment. The result shows that the simple method like THI fails to capture the rainfall and to produce

  10. prediction of rainfall in the southern highlands of tanzania

    African Journals Online (AJOL)

    User

    distribution at different places in the world. A study to ... climate indices influence rainfall. It has been observed .... Table 4: Summary of Predictors entered MLR and PCR models for MAM and OND rainfalls. .... from the cumulus clouds; rainfall is.

  11. Characteristics of the event mean concentration (EMC) from rainfall runoff on an urban highway

    International Nuclear Information System (INIS)

    Lee, Ju Young; Kim, Hyoungjun; Kim, Youngjin; Han, Moo Young

    2011-01-01

    The purpose of this study was to investigate the characterization of the event mean concentration (EMC) of runoff during heavy precipitation events on highways. Highway runoff quality data were collected from the 7th highway, in South Korea during 2007-2009. The samples were analyzed for runoff quantity and quality parameters such as COD cr , TSS, TPHs, TKN, NO 3 , TP, PO 4 and six heavy metals, e.g., As, Cu, Cd, Ni, Pb and Zn. Analysis of resulting hydrographs and pollutant graphs indicates that the peak of the pollutant concentrations in runoff occurs 20 min after the first rainfall runoff occurrence. The first flush effect depends on the preceding dry period and the rainfall intensity. The results of this study can be used as a reference for water quality management of urban highways. - Research highlights: → Field test on urban highway were performed to 50 of 100 storm events for 3 years. → The peak pollutant concentrations occurs 20 min after the first runoff. → The first flush effect depends on the preceding dry period and rainfall intensity. → Relationship between runoff and event mean concentration for SS and COD. → A crest of the EMC by 70-80 m 3 /event and decreasing EMC after 70-80 m 3 /event. - This study investigate the characterization of the EMC of runoff during rainfall event on highway.

  12. Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

    Science.gov (United States)

    Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

    2018-03-01

    The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

  13. Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    Hassan Zulkarnain

    2018-01-01

    Full Text Available The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015 data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM, as compared to Southwest monsoon (SWM. Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

  14. A Semi Risk-Based Approach for Managing Urban Drainage Systems under Extreme Rainfall

    Directory of Open Access Journals (Sweden)

    Carlos Salinas-Rodriguez

    2018-03-01

    Full Text Available Conventional design standards for urban drainage systems are not set to deal with extreme rainfall events. As these events are becoming more frequent, there is room for proposing new planning approaches and standards that are flexible enough to cope with a wide range of rainfall events. In this paper, a semi risk-based approach is presented as a simple and practical way for the analysis and management of rainfall flooding at the precinct scale. This approach uses various rainfall events as input parameters for the analysis of the flood hazard and impacts, and categorises the flood risk in different levels, ranging from very low to very high risk. When visualised on a map, the insight into the risk levels across the precinct will enable engineers and spatial planners to identify and prioritise interventions to manage the flood risk. The approach is demonstrated for a sewer district in the city of Rotterdam, the Netherlands, using a one-dimensional (1D/two-dimensional (2D flood model. The risk level of this area is classified as being predominantly very low or low, with a couple of locations with high and very high risk. For these locations interventions, such as disconnection and lowering street profiles, have been proposed and analysed with the 1D/2D flood model. The interventions were shown to be effective in reducing the risk levels from very high/high risk to medium/low risk.

  15. Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

    Science.gov (United States)

    Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

    2018-01-01

    Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

  16. Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

    Science.gov (United States)

    Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

    2013-04-01

    Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

  17. Duration-frequency relationships of heavy rainfall in Santa Catarina, Brazil

    Directory of Open Access Journals (Sweden)

    Álvaro José Back

    2012-06-01

    Full Text Available The purpose of this study was to adjust equations that establish relationships between rainfall events with different duration and data from weather stations in the state of Santa Catarina, Brazil. In this study, the relationships between different duration heavy rainfalls from 13 weather stations of Santa Catarina were analyzed. From series of maximum annual rainfalls, and using the Gumbel-Chow distribution, the maximum rainfall for durations between 5 min and 24 h were estimated considering return periods from 2 to 100 years. The data fit to the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test at 5 % significance. The coefficients of Bell's equation were adjusted to estimate the relationship between rainfall duration t (min and the return period T (y in relation to the maximum rainfall with a duration of 1 hour and a 10 year return period. Likewise, the coefficients of Bell's equation were adjusted based on the maximum rainfall with a duration of 1 day and a 10 year return period. The results showed that these relationships are viable to estimate short-duration rainfall events at locations where there are no rainfall records.

  18. Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

    Science.gov (United States)

    Barman, S.; Bhattacharjya, R. K.

    2017-12-01

    The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

  19. Rainfall-threshold conditions for landslides in a humid-tropical system

    Science.gov (United States)

    Larsen, Matthew C.; Simon, Andrew

    1993-01-01

    Landslides are triggered by factors such as heavy rainfall, seismic activity, and construction on hillslopes. The leading cause of landslides in Puerto Rico is intense and/or prolonged rainfall. A rainfall threshold for rainfall-triggered landsliding is delimited by 256 storms that occurred between 1959 and 1991 in the central mountains of Puerto Rico, where mean annual rainfall is close to or in excess of 2,000 mm. Forty one of the 256 storms produced intense and/or prolonged rainfall that resulted in tens to hundreds of landslides. A threshold fitted to the lower boundary of the field defined by landslide-triggering storms is expressed as

  20. Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

    Science.gov (United States)

    Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

    2015-02-01

    In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

  1. The rainfall plot: its motivation, characteristics and pitfalls.

    Science.gov (United States)

    Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

    2017-05-18

    A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

  2. Statistical Analysis of 30 Years Rainfall Data: A Case Study

    Science.gov (United States)

    Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

    2017-07-01

    Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

  3. Non-parametric characterization of long-term rainfall time series

    Science.gov (United States)

    Tiwari, Harinarayan; Pandey, Brij Kishor

    2018-03-01

    The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

  4. Performance and efficiency of geotextile-supported erosion control measures during simulated rainfall events

    Science.gov (United States)

    Obriejetan, Michael; Rauch, Hans Peter; Florineth, Florin

    2013-04-01

    Erosion control systems consisting of technical and biological components are widely accepted and proven to work well if installed properly with regard to site-specific parameters. A wide range of implementation measures for this specific protection purpose is existent and new, in particular technical solutions are constantly introduced into the market. Nevertheless, especially vegetation aspects of erosion control measures are frequently disregarded and should be considered enhanced against the backdrop of the development and realization of adaptation strategies in an altering environment due to climate change associated effects. Technical auxiliaries such as geotextiles typically used for slope protection (nettings, blankets, turf reinforcement mats etc.) address specific features and due to structural and material diversity, differing effects on sediment yield, surface runoff and vegetational development seem evident. Nevertheless there is a knowledge gap concerning the mutual interaction processes between technical and biological components respectively specific comparable data on erosion-reducing effects of technical-biological erosion protection systems are insufficient. In this context, an experimental arrangement was set up to study the correlated influences of geotextiles and vegetation and determine its (combined) effects on surface runoff and soil loss during simulated heavy rainfall events. Sowing vessels serve as testing facilities which are filled with top soil under application of various organic and synthetic geotextiles and by using a reliable drought resistant seed mixture. Regular vegetational monitoring as well as two rainfall simulation runs with four repetitions of each variant were conducted. Therefore a portable rainfall simulator with standardized rainfall intensity of 240 mm h-1 and three minute rainfall duration was used to stress these systems on different stages of plant development at an inclination of 30 degrees. First results show

  5. Regional rainfall thresholds for landslide occurrence using a centenary database

    Science.gov (United States)

    Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Quaresma, Ivânia

    2017-04-01

    Rainfall is one of the most important triggering factors for landslides occurrence worldwide. The relation between rainfall and landslide occurrence is complex and some approaches have been focus on the rainfall thresholds identification, i.e., rainfall critical values that when exceeded can initiate landslide activity. In line with these approaches, this work proposes and validates rainfall thresholds for the Lisbon region (Portugal), using a centenary landslide database associated with a centenary daily rainfall database. The main objectives of the work are the following: i) to compute antecedent rainfall thresholds using linear and potential regression; ii) to define lower limit and upper limit rainfall thresholds; iii) to estimate the probability of critical rainfall conditions associated with landslide events; and iv) to assess the thresholds performance using receiver operating characteristic (ROC) metrics. In this study we consider the DISASTER database, which lists landslides that caused fatalities, injuries, missing people, evacuated and homeless people occurred in Portugal from 1865 to 2010. The DISASTER database was carried out exploring several Portuguese daily and weekly newspapers. Using the same newspaper sources, the DISASTER database was recently updated to include also the landslides that did not caused any human damage, which were also considered for this study. The daily rainfall data were collected at the Lisboa-Geofísico meteorological station. This station was selected considering the quality and completeness of the rainfall data, with records that started in 1864. The methodology adopted included the computation, for each landslide event, of the cumulative antecedent rainfall for different durations (1 to 90 consecutive days). In a second step, for each combination of rainfall quantity-duration, the return period was estimated using the Gumbel probability distribution. The pair (quantity-duration) with the highest return period was

  6. Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

    Directory of Open Access Journals (Sweden)

    Renato Fontes Guimarães

    2017-10-01

    Full Text Available Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a creating the digital elevation model (DEM and deriving attributes such as slope and contributing area; (b incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.

  7. Apply data mining to analyze the rainfall of landslide

    Directory of Open Access Journals (Sweden)

    Lee Chou-Yuan

    2018-01-01

    Full Text Available Taiwan is listed as extremely dangerous country which suffers from many disasters. The disasters from the landslide result in the loss of agricultural productions, life and property and so on. Many researchers concern about the disasters of landslide, but there are few discussions for the threshold of rainfall for landslide. In this paper, data mining is applied to establish rules and the threshold of rainfall for landslide in Huafan University, Taiwan. These used variables include rainfall, insolation, insolation rate, averaged humidity, averaged temperature, wind speed, and the tilt of inclinometer. The inclinometer is an important instrument for measuring tilt, elevation or depression of an object with respect to gravity. There are 26 inclinometers in Talun mountain area of Huafan University. In this research, the used data were collected from January 2008 to July 2014. In the proposed approach, the regression analysis is used to predict rainfall first. Then, decision tree is used to obtain decision rules and set the threshold of rainfall for landslide. The output of this approach can provide more information for understanding the change of rainfall. The threshold of rainfall could also provide useful information to maintain the security for Huafan University.

  8. Predicting rainfall erosivity by momentum and kinetic energy in Mediterranean environment

    Science.gov (United States)

    Carollo, Francesco G.; Ferro, Vito; Serio, Maria A.

    2018-05-01

    Rainfall erosivity is an index that describes the power of rainfall to cause soil erosion and it is used around the world for assessing and predicting soil loss on agricultural lands. Erosivity can be represented in terms of both rainfall momentum and kinetic energy, both calculated per unit time and area. Contrasting results on the representativeness of these two variables are available: some authors stated that momentum and kinetic energy are practically interchangeable in soil loss estimation while other found that kinetic energy is the most suitable expression of rainfall erosivity. The direct and continuous measurements of momentum and kinetic energy by a disdrometer allow also to establish a relationship with rainfall intensity at the study site. At first in this paper a comparison between the momentum-rainfall intensity relationships measured at Palermo and El Teularet by an optical disdrometer is presented. For a fixed rainfall intensity the measurements showed that the rainfall momentum values measured at the two experimental sites are not coincident. However both datasets presented a threshold value of rainfall intensity over which the rainfall momentum assumes a quasi-constant value. Then the reliability of a theoretically deduced relationship, linking momentum, rainfall intensity and median volume diameter, is positively verified using measured raindrop size distributions. An analysis to assess which variable, momentum or kinetic energy per unit area and time, is the best predictor of erosivity in Italy and Spain was also carried out. This investigation highlighted that the rainfall kinetic energy per unit area and time can be substituted by rainfall momentum as index for estimating the rainfall erosivity, and this result does not depend on the site where precipitation occurs. Finally, rainfall intensity measurements and soil loss data collected from the bare plots equipped at Sparacia experimental area were used to verify the reliability of some

  9. Distributional changes in rainfall and river flow in Sarawak, Malaysia

    Science.gov (United States)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

    2017-11-01

    Climate change may not change the rainfall mean, but the variability and extremes. Therefore, it is required to explore the possible distributional changes of rainfall characteristics over time. The objective of present study is to assess the distributional changes in annual and northeast monsoon rainfall (November-January) and river flow in Sarawak where small changes in rainfall or river flow variability/distribution may have severe implications on ecology and agriculture. A quantile regression-based approach was used to assess the changes of scale and location of empirical probability density function over the period 1980-2014 at 31 observational stations. The results indicate that diverse variation patterns exist at all stations for annual rainfall but mainly increasing quantile trend at the lowers, and higher quantiles for the month of January and December. The significant increase in annual rainfall is found mostly in the north and central-coastal region and monsoon month rainfalls in the interior and north of Sarawak. Trends in river flow data show that changes in rainfall distribution have affected higher quantiles of river flow in monsoon months at some of the basins and therefore more flooding. The study reveals that quantile trend can provide more information of rainfall change which may be useful for climate change mitigation and adaptation planning.

  10. Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator

    Science.gov (United States)

    Polyakov, Viktor; Stone, Jeffry; Holifield Collins, Chandra; Nearing, Mark A.; Paige, Ginger; Buono, Jared; Gomez-Pond, Rae-Landa

    2018-01-01

    This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583).

  11. The influence of the net rainfall mixed Curve Number – Green Ampt procedure in flood hazard mapping: a case study in Central Italy

    Directory of Open Access Journals (Sweden)

    Andrea Petroselli

    2013-09-01

    Full Text Available A net rainfall estimation procedure, referred to as Curve-Number For Green-Ampt (CN4GA, combining the Soil Conservation Service - Curve Number (SCS-CN method and the Green and Ampt (GA infiltration equation was recently developed, aiming to distribute at subdaily time resolution the information provided by the SCS-CN method. The initial abstraction and the total volume of rainfall provided by the SCS-CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation, whereas the GA infiltration model distributes the total volume of the rainfall excess provided by the SCS-CN method. In this study we evaluate the proposed procedure with reference to a real case comparing the flood mapping obtained applying the event-based approach for two different net rainfall scenarios: the proposed CN4GA and the common SCS-CN. Results underline that the net rainfall estimation step can affect the final flood mapping result.

  12. Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

    Science.gov (United States)

    Ali, H.; Mishra, V.

    2017-12-01

    Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

  13. Mathematical and physical modeling of rainfall in centrifuge

    OpenAIRE

    CAICEDO, Bernardo; THOREL, Luc; TRISTANCHO, Julian

    2015-01-01

    Rainfall simulation in centrifuge models is important for modelling soil-atmosphere interactions. However, the presence of Coriolis force, drag forces, evaporation and wind within the centrifuge may affect the distribution of rainfall over the model. As a result, development of appropriate centrifuge rain simulators requires a demanding process of experimental trial and error. This paper highlights the key factors involved in controlling rainfall in centrifuge simulations, develops a mathemat...

  14. Impact of Rainfall on Multilane Roundabout Flowrate Contraction

    Science.gov (United States)

    PARKSHIR, Amir; BEN-EDIGBE, Johnnie

    2017-08-01

    In this study, roundabouts at two sites in the Malaysia were investigated under rainy and dry weather conditions. Two automatic traffic counters per roundabout arm as well as two rain gauge stations were used to collect data at each surveyed site. Nearly one million vehicles were investigated at four sites. Vehicle volume, speeds and headways for entry and circulating flows were collected continuously at each roundabout about arm for six weeks between November 2013 and January 2014. Empirical regression technique and gap-acceptance models were modified and used to analyze roundabout capacity. Good fits to the data were obtained; the results also fit models developed in other countries. It was assumed that entry capacity depends on the geometric characteristics of the roundabout, particularly the diameter of the outside circle of the intersection. It was also postulated that geometric characteristics determine the speed of vehicles around the central island and, therefore, have an impact on the gap-acceptance process and consequently the capacity. Only off-peak traffic data per light, moderate or heavy rainfall were analysed. Peak traffic data were not used because of the presence of peak traffic flow. Passenger car equivalent values being an instrument of conversion from traffic volume to flow were modified. Results show that, average entry capacity loss is about 22.6% under light rainfall, about 18.1% under moderate rainfall and about 5.6% under heavy rainfall. Significant entry capacity loss would result from rainfall irrespective of their intensity. It can be postulated that entry capacity loss under heavy rainfall is lowest because the advantage enjoyed by circulating flow would be greatly reduced with increased rainfall intensity. The paper concluded that rainfall has significant impact of flowrate contraction at roundabouts.

  15. Isotopic composition of rainfall and runoff in a small arid basin with implications for deep percolation

    Energy Technology Data Exchange (ETDEWEB)

    Dody, A [Ben-Gurion Univ. of the Negev, Beersheba (Israel)

    1995-08-01

    The aim of this work was to characterize the isotopic composition of potential recharge in an arid rocky watershed. Unique field observations were obtained from an arid watershed in the Negev Highlands, Israel, through utilization of the dynamic variations in the isotopic composition of rainfall and runoff. The hydrological system`s inputs are rainfall and its isotopic composition. Rainfall and runoff were sampled in eight storms. High variability in the isotopic composition of rainfall was observed during any single rainstorm. The isotopic distribution in the runoff at the outlet of the basin appeared often not to be correlated to the isotopic patterns of the associated rain storm. A new mathematical model was developed to describe these physical processes. The model called A Double-Component Kinematic Wave Flow and Transport Approach, was designated to assess the dynamic isotopic distribution in arid rain storms and runoff. This model simulates the transport of rainfall into overland flow and runoff in an arid rocky watershed with uniformly distributed shallow depression storage. A numerical solution for the problem was developed, to estimate the depression storage parameters. The model also reflects the isotopic memory effect due to the depression storage between sequential rain showers. A good agreement between the observed and computed hydrograph and the change of the {delta}{sup 18O} values in runoff in time confirms the validity of the model. (author) 138 figs., 125 refs.

  16. Rainfall Simulator Experiments to Investigate Macropore Impacts on Hillslope Hydrological Response

    Directory of Open Access Journals (Sweden)

    Yvonne Smit

    2016-11-01

    Full Text Available Understanding hillslope runoff response to intense rainfall is an important topic in hydrology, and is key to correct prediction of extreme stream flow, erosion and landslides. Although it is known that preferential flow processes activated by macropores are an important phenomena in understanding runoff processes inside a hillslope, hydrological models have generally not embraced the concept of an extra parameter that represents ‘macropores’ because of the complexity of the phenomenon. Therefore, it is relevant to investigate the influence of macropores on runoff processes in an experimental small artificial hillslope. Here, we report on a controlled experiment where we could isolate the influence of macropores without the need for assumptions regarding their characteristics. Two identical hillslopes were designed, of which one was filled with artificial macropores. Twelve artificial rainfall events were applied to the two hillslopes and results of drainage and soil moisture were investigated. After the experiments, it could be concluded that the influence of macropores on runoff processes was minimal. The S90 sand used for this research caused runoff to respond fast to rainfall, leading to little or no development of saturation near the macropores. In addition, soil moisture data showed a large amount of pendular water in the hillslopes, which implies that the soil has a low air entry value, and, in combination with the lack of vertical flow, could have caused the pressure difference between the matrix and the macropores to vanish sooner and result in equilibrium being reached in a relatively short time. Nevertheless, a better outline is given to determine a correct sand type for these types of experiments and, by using drainage recession analysis to investigate the influences of macropores on runoff, heterogeneity in rainfall intensity can be overcome. This study is a good point of reference to start future experiments from concerning

  17. Multi-catchment rainfall-runoff simulation for extreme flood estimation

    Science.gov (United States)

    Paquet, Emmanuel

    2017-04-01

    The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the

  18. Rainfall simulation for environmental application

    Energy Technology Data Exchange (ETDEWEB)

    Shriner, D.S.; Abner, C.H.; Mann, L.K.

    1977-08-01

    Rain simulation systems have been designed for field and greenhouse studies which have the capability of reproducing the physical and chemical characteristics of natural rainfall. The systems permit the simulation of variations in rainfall and droplet size similar to that of natural precipitation. The systems are completely automatic and programmable, allowing unattended operation for periods of up to one week, and have been used to expose not only vegetation but also soils and engineering materials, making them versatile tools for studies involving simulated precipitation.

  19. Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

    Science.gov (United States)

    Rahimi, A.; Zhang, L.

    2012-12-01

    Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further

  20. Characterizing rainfall in the Tenerife island

    Science.gov (United States)

    Díez-Sierra, Javier; del Jesus, Manuel; Losada Rodriguez, Inigo

    2017-04-01

    In many locations, rainfall data are collected through networks of meteorological stations. The data collection process is nowadays automated in many places, leading to the development of big databases of rainfall data covering extensive areas of territory. However, managers, decision makers and engineering consultants tend not to extract most of the information contained in these databases due to the lack of specific software tools for their exploitation. Here we present the modeling and development effort put in place in the Tenerife island in order to develop MENSEI-L, a software tool capable of automatically analyzing a complete rainfall database to simplify the extraction of information from observations. MENSEI-L makes use of weather type information derived from atmospheric conditions to separate the complete time series into homogeneous groups where statistical distributions are fitted. Normal and extreme regimes are obtained in this manner. MENSEI-L is also able to complete missing data in the time series and to generate synthetic stations by using Kriging techniques. These techniques also serve to generate the spatial regimes of precipitation, both normal and extreme ones. MENSEI-L makes use of weather type information to also provide a stochastic three-day probability forecast for rainfall.

  1. Rainfall intensity characteristics at coastal and high altitude stations ...

    Indian Academy of Sciences (India)

    a given amount of rain occurs is important because heavier rainfall leads to greater runoff, greater soil erosion and less infiltration into the water table. A knowledge of rainfall intensity therefore becomes. Keywords. Rainfall intensity; Kerala; cumulative distribution. J. Earth Syst. Sci. 116, No. 5, October 2007, pp. 451–463.

  2. A Stochastic Fractional Dynamics Model of Rainfall Statistics

    Science.gov (United States)

    Kundu, Prasun; Travis, James

    2013-04-01

    Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

  3. Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

    Science.gov (United States)

    Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

    2017-01-01

    Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

  4. A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

    Science.gov (United States)

    Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

    2018-01-01

    RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

  5. Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the

  6. Analysis of rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province

    Science.gov (United States)

    Pan, Huali; Hu, Mingjian; Ou, Guoqiang

    2017-04-01

    According to the geological investigation in Fujian province, the total number of geological disasters was 9513, in which the number of landslide, collapse, unstable slope and surface collapse was 5816, 1888, 1591, 103 and 115 respectively. The main geological disaster was the landslide with 61.1% of total geological disasters. Among all these geological disasters, only 6.0% was relative stable, 17.0% was basic stable, nearly 76.0% was unstable. The slope disaster was the main geological disaster, if the unstable slope was the potential landslide or collapse; the slope collapse was 98.0% of all geological disasters. The rainfall, in particular the heavy rain, was direct dynamic factor for geological disasters, but the occurrence probability of geological disasters was different because of the sensitivity of the geological environment though of the same intensity rainfall. To obtain the characteristics of soil erosion under the rainfall condition, the rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province was analyzed by the meteorological and rainfall data. According to the distribution of monitoring stations of hydrological and rainfall in Longyan city of Fujian province and the location of gold-copper deposit, the Shanghang monitoring station of hydrological and rainfall was chosen, which is the nearest one to the gold-copper deposit. Then main parameters of the prediction model, the antecedent precipitation, the rainfall on the day and the rainfall threshold, were calculated by using the rainfall data from 2002 to 2010. And the relationship between geological disasters and the rainfall characteristics were analyzed. The results indicated that there was high risk for the debris flow with landslide collapse when either the daily rainfall was more than 100.0 mm, or the total rainfall was more than 136.0mm in the gold-copper deposit and the Shanghang region. At the same time, although there was few

  7. Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

    Science.gov (United States)

    Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

    2018-05-01

    Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

  8. Relationship between rainfall and shallow landslides in the southern Apuan Alps (Italy

    Directory of Open Access Journals (Sweden)

    R. Giannecchini

    2006-01-01

    Full Text Available The Apuan Alps region is one of the rainiest areas in Italy (more than 3000 mm/year, in which frequently heavy and concentrated rainfall occurs. This is particularly due to its geographical position and conformation: the Apuan chain is located along the northern Tuscan coast, close to the Ligurian Sea, and the main peaks reach almost 2000 m. In several cases, the storms that hit the area have triggered many shallow landslides (soil slip-debris flows, which exposed the population to serious risks (during the 19 June 1996 rainstorm about 1000 landslides were triggered and 14 people died. The assessment of the rainfall thresholds is very important in order to prepare efficient alarm systems in a region particularly dedicated to tourism and marble activities. With the aim of contributing to the landslide hazard evaluation of the southern Apuan Alps territory (upper Versilia area, a detailed analysis of the main pluviometric events was carried out. The data recorded at the main rain gauge of the area from 1975 to 2002 were analysed and compared with the occurrence of soil slips, in order to examine the relationship between soil slip initiation and rainfall. The most important rainstorms which triggered shallow landslides occurred in 1984, 1992, 1994, 1996, 1998 and 2000. Many attempts were made to obtain a possible correlation between rainfall parameters and the occurrence of soil slip phenomena and to identify the local rainfall threshold for triggering shallow landslides. A threshold for soil slip activity in terms of mean intensity, duration and mean annual precipitation (MAP was defined for the study area. The thresholds obtained for the southern Apuan Alps were also compared with those proposed by other authors for several regions in the world. This emphasized the high value of the rain threshold for shallow landslide activity in the Apuan area. The high threshold is probably also linked to the high mean annual precipitation and to the high

  9. Soil erosion under multiple time-varying rainfall events

    Science.gov (United States)

    Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

    2010-05-01

    Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

  10. Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

    Science.gov (United States)

    Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.

    2018-06-01

    Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

  11. Mapping monthly rainfall erosivity in Europe.

    Science.gov (United States)

    Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

    2017-02-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

  12. Persistence Characteristics of Australian Rainfall Anomalies

    Science.gov (United States)

    Simmonds, Ian; Hope, Pandora

    1997-05-01

    Using 79 years (1913-1991) of Australian monthly precipitation data we examined the nature of the persistence of rainfall anomalies. Analyses were performed for four climate regions covering the country, as well as for the entire Australian continent. We show that rainfall over these regions has high temporal variability and that annual rainfall amounts over all five sectors vary in phase and are, with the exception of the north-west region, significantly correlated with the Southern Oscillation Index (SOI). These relationships were particularly strong during the spring season.It is demonstrated that Australian rainfall exhibits statistically significant persistence on monthly, seasonal, and (to a limited extent) annual time-scales, up to lags of 3 months and one season and 1 year. The persistence showed strong seasonal dependence, with each of the five regions showing memory out to 4 or 5 months from winter and spring. Many aspects of climate in the Australasian region are known to have undergone considerable changes about 1950. We show this to be true for persistence also; its characteristics identified for the entire record were present during the 1951--1980 period, but virtually disappeared in the previous 30-year period.Much of the seasonal distribution of rainfall persistence on monthly time-scales, particularly in the east, is due to the influence of the SOI. However, most of the persistence identified in winter and spring in the north-west is independent of the ENSO phenomenon.Rainfall anomalies following extreme dry and wet months, seasons and years (lowest and highest two deciles) persisted more than would be expected by chance. For monthly extreme events this was more marked in the winter semester for the wet events, except in the south-east region. In general, less persistence was found for the extreme seasons. Although the persistence of dry years was less than would have been expected by chance, the wet years appear to display persistence.

  13. Relationship between rainfall and microbiological contamination of ...

    African Journals Online (AJOL)

    Outbreaks of contamination events in many developing countries occur during periods of peak rainfall. This study presents evidence of direct pulse response of shallow groundwater contamination events to rainfall in Northern Mozambique. The objective of the paper is to establish both a statistical relationship between ...

  14. Developing empirical relationship between interrill erosion, rainfall ...

    African Journals Online (AJOL)

    In order to develop an empirical relationship for interrill erosion based on rainfall intensity, slope steepness and soil types, an interrill erosion experiment was conducted using laboratory rainfall simulator on three soil types (Vertisols, Cambisols and Leptosols) for the highlands of North Shewa Zone of Oromia Region.

  15. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)

    2012-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  16. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)

    2013-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  17. Rainfall thresholds for the possible occurrence of landslides in Italy

    Directory of Open Access Journals (Sweden)

    M. T. Brunetti

    2010-03-01

    Full Text Available In Italy, rainfall is the primary trigger of landslides that frequently cause fatalities and large economic damage. Using a variety of information sources, we have compiled a catalogue listing 753 rainfall events that have resulted in landslides in Italy. For each event in the catalogue, the exact or approximate location of the landslide and the time or period of initiation of the slope failure is known, together with information on the rainfall duration D, and the rainfall mean intensity I, that have resulted in the slope failure. The catalogue represents the single largest collection of information on rainfall-induced landslides in Italy, and was exploited to determine the minimum rainfall conditions necessary for landslide occurrence in Italy, and in the Abruzzo Region, central Italy. For the purpose, new national rainfall thresholds for Italy and new regional rainfall thresholds for the Abruzzo Region were established, using two independent statistical methods, including a Bayesian inference method and a new Frequentist approach. The two methods proved complementary, with the Bayesian method more suited to analyze small data sets, and the Frequentist method performing better when applied to large data sets. The new regional thresholds for the Abruzzo Region are lower than the new national thresholds for Italy, and lower than the regional thresholds proposed in the literature for the Piedmont and Lombardy Regions in northern Italy, and for the Campania Region in southern Italy. This is important, because it shows that landslides in Italy can be triggered by less severe rainfall conditions than previously recognized. The Frequentist method experimented in this work allows for the definition of multiple minimum rainfall thresholds, each based on a different exceedance probability level. This makes the thresholds suited for the design of probabilistic schemes for the prediction of rainfall-induced landslides. A scheme based on four

  18. Ostrich recruitment dynamics in relation to rainfall in the Mara ...

    African Journals Online (AJOL)

    Ostrich recruitment dynamics in relation to rainfall in the Mara–Serengeti ... To understand how rainfall influences ostriches, we related changes in ostrich recruitment in the Mara–Serengeti ecosystem to rainfall. ... AJOL African Journals Online.

  19. A mathematical model for soil solute transfer into surface runoff as influenced by rainfall detachment.

    Science.gov (United States)

    Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhao, Guangxu; Liu, Yanli; Zhang, Pengyu

    2016-07-01

    Nutrients transport is a main source of water pollution. Several models describing transport of soil nutrients such as potassium, phosphate and nitrate in runoff water have been developed. The objectives of this research were to describe the nutrients transport processes by considering the effect of rainfall detachment, and to evaluate the factors that have greatest influence on nutrients transport into runoff. In this study, an existing mass-conservation equation and rainfall detachment process were combined and augmented to predict runoff of nutrients in surface water in a Loess Plateau soil in Northwestern Yangling, China. The mixing depth is a function of time as a result of rainfall impact, not a constant as described in previous models. The new model was tested using two different sub-models of complete-mixing and incomplete-mixing. The complete-mixing model is more popular to use for its simplicity. It captured the runoff trends of those high adsorption nutrients, and of nutrients transport along steep slopes. While the incomplete-mixing model predicted well for the highest observed concentrations of the test nutrients. Parameters inversely estimated by the models were applied to simulate nutrients transport, results suggested that both models can be adopted to describe nutrients transport in runoff under the impact of rainfall. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. How El-Nino affects Ethiopian summer rainfall

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel; Viste, Ellen

    2016-04-01

    Ethiopian economy and society are strongly dependent on agriculture and therefore rainfall. Reliable forecasts for the rainy seasons are important to allow for agricultural planning and drought preparations. The operational seasonal forecasts for Ethiopia are based on analogue methods relying mainly on sea surface temperature (SST) indices. A better understanding of the physical links between Ethiopian rainfall and SST may help to improve forecasts. The highest rainfall rates are observed in the Kiremt season (defined as JJAS), which is the rainy season in Central and Northwestern Ethiopia. Kiremt rainfall shows clear negative correlation with Central Pacific SST, linking dry Ethiopian summers with ENSO-like warm SST anomalies. We use the atmosphere general circulation model Echam5.3 to investigate the physical link between Pacific SST anomalies and Kiremt rainfall. We compare a historical simulation with a T106 horizontal resolution (~ 1.125°), forced with reconstructed SST data, to gauge-based rainfall observations for the time period of 1961 to 2009. Composite analysis for model and observations show warm SST anomalies in the Central Pacific and a corresponding large-scale circulation anomaly with subsidence over Ethiopia in dry Kiremt seasons. Horizontal wind fields show a slow-down of the whole Indian monsoon system with a weaker Tropical Easterly Jet (TEJ) and a weaker East African Low-Level Jet (EALLJ) in these summers. We conducted a sensitivity experiment with El Nino like SST anomalies in the Central Pacific with the same Echam version. Its results show that warm Pacific SST anomalies cause dry summer conditions over Ethiopia. While the large-scale subsidence over East Africa is present in the experiment, there is no significant weakening of the Indian monsoon system. We rather find an anomalous circulation cell over Northern Africa with westerlies at 100-200 hPa and easterlies below 500 hPa. The anomalous easterly flow in the lower and middle

  1. Flood risk reduction and flow buffering as ecosystem services - Part 2: Land use and rainfall intensity effects in Southeast Asia

    Science.gov (United States)

    van Noordwijk, Meine; Tanika, Lisa; Lusiana, Betha

    2017-05-01

    Watersheds buffer the temporal pattern of river flow relative to the temporal pattern of rainfall. This ecosystem service is inherent to geology and climate, but buffering also responds to human use and misuse of the landscape. Buffering can be part of management feedback loops if salient, credible and legitimate indicators are used. The flow persistence parameter Fp in a parsimonious recursive model of river flow (Part 1, van Noordwijk et al., 2017) couples the transmission of extreme rainfall events (1 - Fp), to the annual base-flow fraction of a watershed (Fp). Here we compare Fp estimates from four meso-scale watersheds in Indonesia (Cidanau, Way Besai and Bialo) and Thailand (Mae Chaem), with varying climate, geology and land cover history, at a decadal timescale. The likely response in each of these four to variation in rainfall properties (including the maximum hourly rainfall intensity) and land cover (comparing scenarios with either more or less forest and tree cover than the current situation) was explored through a basic daily water-balance model, GenRiver. This model was calibrated for each site on existing data, before being used for alternative land cover and rainfall parameter settings. In both data and model runs, the wet-season (3-monthly) Fp values were consistently lower than dry-season values for all four sites. Across the four catchments Fp values decreased with increasing annual rainfall, but specific aspects of watersheds, such as the riparian swamp (peat soils) in Cidanau reduced effects of land use change in the upper watershed. Increasing the mean rainfall intensity (at constant monthly totals for rainfall) around the values considered typical for each landscape was predicted to cause a decrease in Fp values by between 0.047 (Bialo) and 0.261 (Mae Chaem). Sensitivity of Fp to changes in land use change plus changes in rainfall intensity depends on other characteristics of the watersheds, and generalisations made on the basis of one or two

  2. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    Science.gov (United States)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

  3. Simulation of Tropical Rainfall Variability

    Science.gov (United States)

    Bader, J.; Latif, M.

    2002-12-01

    The impact of sea surface temperature (SST) - especially the role of the tropical Atlantic meridional SST gradient and the El Nino-Southern Oscillation - on precipitation is investigated with the atmospheric general circulation model ECHAM4/T42. Ensemble experiments - driven with observed SST - show that Atlantic SST has a significant influence on precipitation over West Africa and northeast Brazil. SST sensitivity experiments were performed in which the climatological SST was enhanced or decreased by one Kelvin in certain ocean areas. Changing SST in the eastern tropical Atlantic caused only significant changes along the Guinea Coast, with a positive anomaly (SSTA) increasing rainfall and a negative SSTA reducing it. The response was nearly linear. Changing SST in other ocean areas caused significant changes over West Africa, especially in the Sahel area. The response is found to be non linear, with only negative SSTA leading to significant reduction in Sahel rainfall. Also, the impact of the SSTAs from the different ocean regions was not additive with respect to the rainfall. The influence of SST on precipitation over northeast Brazil (Nordeste) was also investigated. Three experiments were performed in which the climatological SST was enhanced/decreased or decreased/enhanced by one Kelvin in the North/South Atlantic and increased by two Kelvin in the Nino3 ocean area. All experiments caused significant changes over Nordeste, with an enhanced/reduced SST gradient in the Atlantic increasing/reducing rainfall. The response was nearly linear. The main effect of the Atlantic SST gradient was a shift of the ITCZ, caused by trade wind changes. The ''El Nino'' event generates a significant reduction in Nordeste rainfall. A significant positive SLP anomaly occurs in northeast Brazil which may be associated with the descending branch of the Walker circulation. Also a significant positive SLP over the Atlantic from 30S to 10N north occurs. This results in a reduced SLP

  4. Understanding road surface pollutant wash-off and underlying physical processes using simulated rainfall.

    Science.gov (United States)

    Egodawatta, Prasanna; Goonetilleke, Ashantha

    2008-01-01

    Pollutant wash-off is one of the key pollutant processes that detailed knowledge is required in order to develop successful treatment design strategies for urban stormwater. Unfortunately, current knowledge relating to pollutant wash-off is limited. This paper presents the outcomes of a detailed investigation into pollutant wash-off on residential road surfaces. The investigations consisted of research methodologies formulated to overcome the physical constraints due to the heterogeneity of urban paved surfaces and the dependency on naturally occurring rainfall. This entailed the use of small road surface plots and artificially simulated rainfall. Road surfaces were selected due to its critical importance as an urban stormwater pollutant source. The study results showed that the influence of initially available pollutants on the wash-off process was limited. Furthermore, pollutant wash-off from road surfaces can be replicated using an exponential equation. However, the typical version of the exponential wash-off equation needs to be modified by introducing a non dimensional factor referred to as 'capacity factor' CF. Three rainfall intensity ranges were identified where the variation of CF can be defined. Furthermore, it was found that particulate density rather than size is the critical parameter that influences the process of pollutant wash-off. (c) IWA Publishing 2008.

  5. Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

    Directory of Open Access Journals (Sweden)

    Elena Tarnavsky

    2013-12-01

    Full Text Available This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR. Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

  6. A Physically-based Model For Rainfall-triggered Landslides At A Regional Scale

    Science.gov (United States)

    Teles, V.; Capolongo, D.; Bras, R. L.

    Rainfall has long been recognized as a major cause of landslides. Historical records have shown that large rainfall can generate hundreds of landslides over hundreds of square kilometers. Although a great body of work has documented the morphology and mechanics of individual slope failure, few studies have considered the process at basin and regional scale. A landslide model is integrated in the landscape evolution model CHILD and simulates rainfall-triggered events based on a geotechnical index, the factor of safety, which takes into account the slope, the soil effective cohesion and weight, the friction angle, the regolith thickness and the saturated thickness. The stat- urated thickness is represented by the wetness index developed in the TOPMODEL. The topography is represented by a Triangulated Irregular Network (TIN). The factor of safety is computed at each node of the TIN. If the factor of safety is lower than 1, a landslide is intiated at this node. The regolith is then moved downstream. We applied the model to the Fortore basin whose valley cuts the flysch terrain that constitute the framework of the so called "sub-Apennines" chain that is the most eastern part of the Southern Apennines (Italy). We will discuss its value according to its sensitivity to the used parameters and compare it to the actual data available for this basin.

  7. Engineering of an Extreme Rainfall Detection System using Grid Computing

    Directory of Open Access Journals (Sweden)

    Olivier Terzo

    2012-10-01

    Full Text Available This paper describes a new approach for intensive rainfall data analysis. ITHACA's Extreme Rainfall Detection System (ERDS is conceived to provide near real-time alerts related to potential exceptional rainfalls worldwide, which can be used by WFP or other humanitarian assistance organizations to evaluate the event and understand the potentially floodable areas where their assistance is needed. This system is based on precipitation analysis and it uses rainfall data from satellite at worldwide extent. This project uses the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis dataset, a NASA-delivered near real-time product for current rainfall condition monitoring over the world. Considering the great deal of data to process, this paper presents an architectural solution based on Grid Computing techniques. Our focus is on the advantages of using a distributed architecture in terms of performances for this specific purpose.

  8. Fluvial signatures of modern and paleo orographic rainfall gradients

    Science.gov (United States)

    Schildgen, Taylor; Strecker, Manfred

    2016-04-01

    The morphology of river profiles is intimately linked to both climate and tectonic forcing. While much interest recently has focused on how river profiles can be inverted to derive uplift histories, here we show how in regions of strong orographic rainfall gradients, rivers may primarily record spatial patterns of precipitation. As a case study, we examine the eastern margin of the Andean plateau in NW Argentina, where the outward (eastward) growth of a broken foreland has led to a eastward shift in the main orographic rainfall gradient over the last several million years. Rivers influenced by the modern rainfall gradient are characterized by normalized river steepness values in tributary valleys that closely track spatial variations in rainfall, with higher steepness values in drier areas and lower steepness values in wetter areas. The same river steepness pattern has been predicted in landscape evolution models that apply a spatial gradient in rainfall to a region of uniform erosivity and uplift rate (e.g., Han et al., 2015). Also, chi plots from river networks on individual ranges affected by the modern orographic rainfall reveal patterns consistent with assymmetric precipitation across the range: the largest channels on the windward slopes are characterized by capture, while the longest channels on the leeward slopes are dominated by beheadings. Because basins on the windward side both lengthen and widen, tributary channels in the lengthening basins are characterized by capture, while tributary channels from neighboring basins on the windward side are dominated by beheadings. These patterns from the rivers influenced by the modern orographic rainfall gradient provide a guide for identifying river morphometric signatures of paleo orographic rainfall gradients. Mountain ranges to the west of the modern orographic rainfall have been interpreted to mark the location of orographic rainfall in the past, but these ranges are now in spatially near-uniform semi-arid to

  9. Stochastic Modeling of Rainfall in Peninsular Malaysia Using Bartlett Lewis Rectangular Pulses Models

    Directory of Open Access Journals (Sweden)

    Ibrahim Suliman Hanaish

    2011-01-01

    Full Text Available Three versions of Bartlett Lewis rectangular pulse rainfall models, namely, the Original Bartlett Lewis (OBL, Modified Bartlett Lewis (MBL, and 2N-cell-type Bartlett Lewis model (BL2n, are considered. These models are fitted to the hourly rainfall data from 1970 to 2008 obtained from Petaling Jaya rain gauge station, located in Peninsular Malaysia. The generalized method of moments is used to estimate the model parameters. Under this method, minimization of two different objective functions which involve different weight functions, one weight is inversely proportional to the variance and another one is inversely proportional to the mean squared, is carried out using Nelder-Mead optimization technique. For the purpose of comparison of the performance of the three different models, the results found for the months of July and November are used for illustration. This performance is assessed based on the goodness of fit of the models. In addition, the sensitivity of the parameter estimates to the choice of the objective function is also investigated. It is found that BL2n slightly outperforms OBL. However, the best model is the Modified Bartlett Lewis MBL, particularly when the objective function considered involves weight which is inversely proportional to the variance.

  10. Integration and calibration of a conceptual rainfall-runoff model in the framework of a decision support system for river basin management

    Directory of Open Access Journals (Sweden)

    J. Götzinger

    2005-01-01

    Full Text Available Water balance models provide significant input to integrated models that are used to simulate river basin processes. However, one of the primary problems involves the coupling and simultaneous calibration of rainfall-runoff and groundwater models. This problem manifests itself through circular arguments - the hydrologic model is modified to calculate highly discretized groundwater recharge rates as input to the groundwater model which provides modeled base flow for the flood-routing module of the rainfall-runoff model. A possibility to overcome this problem using a modified version of the HBV Model is presented in this paper. Regionalisation and optimization methods lead to objective and efficient calibration despite large numbers of parameters. The representation of model parameters by transfer functions of catchment characteristics enables consistent parameter estimation. By establishing such relationships, models are calibrated for the parameters of the transfer functions instead of the model parameters themselves. Simulated annealing, using weighted Nash-Sutcliffe-coefficients of variable temporal aggregation, assists in efficient parameterisations. The simulations are compared to observed discharge and groundwater recharge modeled by the State Institute for Environmental Protection Baden-Württemberg using the model TRAIN-GWN.

  11. The Interdependence between Rainfall and Temperature: Copula Analyses

    DEFF Research Database (Denmark)

    Cong, Ronggang; Brady, Mark

    2012-01-01

    possible approach to this problem, five families of copula models are employed to model the interdependence between rainfall and temperature. Scania is a leading agricultural province in Sweden and is affected by a maritime climate. Historical climatic data for Scania is used to demonstrate the modeling...... process. Heteroscedasticity and autocorrelation of sample data are also considered to eliminate the possibility of observation error. The results indicate that for Scania there are negative correlations between rainfall and temperature for the months from April to July and September. The student copula...... is found to be most suitable to model the bivariate distribution of rainfall and temperature based on the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Using the student copula, we simulate temperature and rainfall simultaneously. The resulting models can be integrated...

  12. Rainfall: Features and Variations over Saudi Arabia, A Review

    Directory of Open Access Journals (Sweden)

    Hosny Hasanean

    2015-08-01

    Full Text Available The Saudi Arabia (SA climate varies greatly, depending on the geography and the season. According to K ppen and Geiger, the climates of SA is “desert climate”. The analysis of the seasonal rainfall detects that spring and winter seasons have the highestrainfall incidence, respectively. Through the summer,small quantities of precipitation are observed, while autumn received more precipitation more than summer season considering the total annual rainfall. In all seasons, the SW area receives rainfall, with a maximum in spring, whereas in the summer season, the NE and NW areas receive very little quantities of precipitation. The Rub Al-Khali (the SE region is almost totally dry. The maximum amount of annual rainfall does not always happen at the highest elevation. Therefore, the elevation is not the only factor in rainfall distribution.A great inter-annual change in the rainfall over the SA for the period (1978–2009 is observed. In addition, in the same period, a linear decreasing trend is found in the observed rainfall, whilst in the recent past (1994–2009 a statistically significant negative trend is observed. In the Southern part of the Arabian Peninsula (AP and along the coast of the Red Sea, it is interesting to note that rainfall increased, whilst it decreased over most areas of SA during the 2000–2009 decade, compared to 1980–1989.Statistical and numerical models are used to predict rainfall over Saudi Arabia (SA. The statistical models based on stochastic models of ARIMA and numerical models based on Providing Regional Climates for Impact Studies of Hadley Centre (PRECIS. Climate and its qualitative character and quantified range of possible future changes are investigated. The annual total rainfall decreases in most regions of the SA and only increases in the south. The summertime precipitation will be the highest between other seasons over the southern, the southwestern provinces and Asir mountains, while the wintertime

  13. The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

    OpenAIRE

    Suseno, Dwi Prabowo Yuga

    2013-01-01

    The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...

  14. Inter-Annual Variability Of Rainfall In Some States Of Southern Nigeria

    Directory of Open Access Journals (Sweden)

    Egor

    2015-08-01

    Full Text Available Abstract The study inter-annual variability of rainfall in some states in Southern Nigeria focuses on analyzing the trends and fluctuations in annual rainfall over six states in Southern Nigeria covering a period of 1972 2012. In order to ascertain the variabilitys and to model the annual rainfall for future prediction to enhance policy implementation the quantitative and descriptive analysis techniques was employed. The rainfall series were analyzed for fluctuations using Standardized Anomaly Index SAI whereas the trends were examined using Statistical Package for Social Science Software SPSS 17.0. At 95 percent confidence level observations in the stations may be signals that the wetter period dominates the drier periods in this study. Each of the series contains two distinct periods when the rainfall anomalies negative and positive of a particular type were most significant. The period where the annual rainfall is above one standard deviation from the mean annual rainfall is considered Wet and the period below one standard deviation from the mean annual rainfall is considered Dry for each station. The results of the linear trend lines revealed an increase in rainfall supply over the period of study especially of recent. The annual rate of increase in rainfall over the period of investigation 1972 - 2012 were 15.21mmyear for Calabar 2.18mmyear for Port Harcourt 22.23mmyear for Owerri 3.25mmyear for Benin City 5.08mmyear for Enugu and 16.29mmyear for Uyo respectively. The variability in amount of annual rainfall revealed that in 2012 Calabar received the highest amount of rainfall of about 4062.70mm and the least value of 2099.4mm in 1973. In Porthacourt the highest amount of rainfall occurred in 1993 with a value of 3911.70mm and the least value in 1983 with a value of 1816.4mm. Owerri recorded the highest amount of rainfall of about 3064.0mm in 2011 and the least value occurred in 1986 with a value of 1228.4mm. In 1976 Benin received the

  15. Spatial variability and rainfall characteristics of Kerala

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10◦N (north. Kerala) fall into one group and they ...

  16. Where do forests influence rainfall?

    Science.gov (United States)

    Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

    2017-04-01

    Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

  17. Probabilistic Analysis of Cut-Slope Stability for Tropical Red Clay of Depok, West Java as an Effect of Rainfall Duration and Intensity

    Directory of Open Access Journals (Sweden)

    Hakim Sagitaningrum Fathiyah

    2018-01-01

    Full Text Available Landslide in Indonesia, specifically in Java island, occurs during rainy seasons. In Java island, it is known that the tropical red clay has the ability to stand at steep angles, while in stability analysis due to rainfall, practitioners only consider the rise of groundwater table. Previous studies states that one of the factor affecting factor of safety (FS for tropical red clay slopes is the formation of saturated zones due to matric suction. This research studies the effect of rainfall intensity and duration to FS of cut-slopes as parametric study with probabilistic analysis for different height of 10m, 20m, and 30m also slope angles of 27°, 45°, 55°, and 70°. Rainfall parameter are taken from FTUI rainfall station for advanced pattern and three-days duration of rain. Analysis of seepage uses SEEP/W and slope stability uses SLOPE/W. It is known that the significant increase of probability of failure due to the three-days rainfall is achieved at the 10m height and 70°-angled slope. Increase of the probability of failure is mainly due to rainfall infiltration which saturates the surface and pore water pressure increase until certain time where infiltration stops and turn into surface run-off.

  18. Extreme values of meteorological parameters observed at Kalpakkam during the period 1968-1999

    International Nuclear Information System (INIS)

    Balagurunathan, M.R.; Chandresekharan, E.; Rajan, M.P.; Gurg, R.P.

    2001-05-01

    In the design phase of engineering structures, an understanding of extreme weather conditions that may occur at the site of interest is very essential, so that the structures can be designed to withstand climatological stresses during its life time. In this report an analysis of extreme values of meteorological parameters at Kalpakkam for the period 1968-99, which provide an insight into such situations is described. The extreme value analysis reveals that all the variables obey Fisher-Tippet Type-I extreme value distribution function. Parameter values of extreme value analysis functions are presented for the variables studied and the 50- and 100- year return period extreme values are arrived at. Frequency distribution of rainfall parameters is investigated. Time series of annual rainfall data suggests a cycle of 2-3 years period. (author)

  19. Effect of variations in rainfall intensity on slope stability in Singapore

    Directory of Open Access Journals (Sweden)

    Christofer Kristo

    2017-12-01

    Full Text Available Numerous scientific evidence has given credence to the true existence and deleterious impacts of climate change. One aspect of climate change is the variations in rainfall patterns, which affect the flux boundary condition across ground surface. A possible disastrous consequence of this change is the occurrence of rainfall-induced slope failures. This paper aims to investigate the variations in rainfall patterns in Singapore and its effect on slope stability. Singapore's historical rainfall data from Seletar and Paya Lebar weather stations for the period of 1985–2009 were obtained and analysed by duration using linear regression. A general increasing trend was observed in both weather stations, with a possible shift to longer duration rainfall events, despite being statistically insignificant according to the Mann-Kendall test. Using the derived trends, projected rainfall intensities in 2050 and 2100 were used in the seepage and slope stability analyses performed on a typical residual soil slope in Singapore. A significant reduction in factor of safety was observed in the next 50 years, with only a marginal decrease in factor of safety in the subsequent 50 years. This indicates a possible detrimental effect of variations in rainfall patterns on slope stability in Singapore, especially in the next 50 years. The statistical analyses on rainfall data from Seletar and Paya Lebar weather stations for the period of 1985–2009 indicated that rainfall intensity tend to increase over the years, with a possible shift to longer duration rainfall events in the future. The stability analyses showed a significant decrease in factor of safety from 2003 to 2050 due to increase in rainfall intensity, suggesting that a climate change might have existed beyond 2009 with possibly detrimental effects to slope stability. Keywords: Climate change, Rainfall, Seepage, Slope stability

  20. A protocol for conducting rainfall simulation to study soil runoff.

    Science.gov (United States)

    Kibet, Leonard C; Saporito, Louis S; Allen, Arthur L; May, Eric B; Kleinman, Peter J A; Hashem, Fawzy M; Bryant, Ray B

    2014-04-03

    Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

  1. Modern proposal of methodology for retrieval of characteristic synthetic rainfall hyetographs

    Science.gov (United States)

    Licznar, Paweł; Burszta-Adamiak, Ewa; Łomotowski, Janusz; Stańczyk, Justyna

    2017-11-01

    Modern engineering workshop of designing and modelling complex drainage systems is based on hydrodynamic modelling and has a probabilistic character. Its practical application requires a change regarding rainfall models accepted at the input. Previously used artificial rainfall models of simplified form, e.g. block precipitation or Euler's type II model rainfall are no longer sufficient. It is noticeable that urgent clarification is needed as regards the methodology of standardized rainfall hyetographs that would take into consideration the specifics of local storm rainfall temporal dynamics. The aim of the paper is to present a proposal for innovative methodology for determining standardized rainfall hyetographs, based on statistical processing of the collection of actual local precipitation characteristics. Proposed methodology is based on the classification of standardized rainfall hyetographs with the use of cluster analysis. Its application is presented on the example of selected rain gauges localized in Poland. Synthetic rainfall hyetographs achieved as a final result may be used for hydrodynamic modelling of sewerage systems, including probabilistic detection of necessary capacity of retention reservoirs.

  2. Investigation into increasing short-duration rainfall intensities in ...

    African Journals Online (AJOL)

    2015-04-03

    Apr 3, 2015 ... This study explores this expectation by using historical short-duration ... weather station 5-min rainfall data were combined to extend the effective ... evidence was found of trends or indications of changes in rainfall intensities.

  3. The Effect of Rainfall Patterns on the Mechanisms of Shallow Slope Failure

    Directory of Open Access Journals (Sweden)

    Muhammad Suradi

    2014-04-01

    Full Text Available This paper examines how rainfall patterns affect the mechanisms of shallow slope failure. Numerical modelling, utilising the commercial software SVFlux and SVSlope, was carried out for a coupled analysis of rainfall-induced slope seepage and instability, with reference to a shallow landslide took place in Jabiru, Northern Territory (NT Australia in 2007. Rainfall events were varied in terms of pattern in this analysis. The results revealed that slopes are sensitive to rainfall pattern when the rainfall intensity has a high degree of fluctuation at around the same value as that of saturated hydraulic conductivity. Average rainfall intensity at the beginning of a rainfall period plays a primary role in determining the rate of decrease in initial factor of safety (Fi towards minimum factor of safety (Fmin. The effect of rainfall events on the slope instability is attributed to the amount of rainwater infiltration into slope associated with rainfall pattern.

  4. Impact of climate change on extreme rainfall events and flood risk

    Indian Academy of Sciences (India)

    The analysis of the frequency of rainy days, rain days and heavy rainfall days as well as one-day extreme rainfall and return period has been carried out in this study to observe the impact of climate change on extreme rainfall events and flood risk in India. The frequency of heavy rainfall events are decreasing in major parts ...

  5. Indonesian Rainfall Characteristic Based on the EAR and WPR Data Analysis

    Science.gov (United States)

    Hermawan, Eddy

    2010-05-01

    As one of the most real product of the joint research between RISH (Research Institute for Sustainable Humanosphere) of Kyoto University, Japan with the National Institute of Aeronautics and Space (LAPAN), is being applied the Equatorial Atmosphere Radar (EAR) at Kototabang, Bukittinggi, West Sumatera that has already operated since June, 2001. The other one, since March 2007, has also operated the other radar that called as WPR (Wind Profiling Radar) at Pontianak and Biak station under the JAMSTEC (Japan Marine Science Technology), Japan. Those radars give a good chance for the Indonesian young scientist to apply those data in applicable research for many people. One of them is the behavior of Indonesian rainfall variability over Kototabang, Pontianak, and Biak, respectively. This is very important, since rainfall is one of the most important parameter that has direct effect to daily living, not only in wet season (suspected related to flooding) or dry season (suspected related to drought) than normal condition. We understood that until now, no many significant result obtained from those data, especially from WPR, not only since that data is still new one, but also related well to the limitation of the other suppport data, facility (hardware and software), also the man power (reseracher) working on that data analysis. Based on this condition, the main purpose of this study is to investigate the Indonesian rainfall behavior, especially over Kototabang, Pontianak, and Biak, respectively. The others are we would like to investigate the pattern of zonal wind variation along the Indian Ocean passing away to Indonesia region, to investigate the MJO (Madden Julian Oscillation) phenomenon, and to investigate the relationship or correlation between rainfall and zonal wind variation. The results show that in the wet season (DJF=December-January-February), Kototabang and surrounded area is dominated by the Westerly wind that mostly contains of water vapor. While, in the dry

  6. Spatial Scaling of Global Rainfall and Flood Extremes

    Science.gov (United States)

    Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

    2014-05-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

  7. What aspects of future rainfall changes matter for crop yields in West Africa?

    Science.gov (United States)

    Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

    2015-10-01

    How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

  8. Hydrological similarity approach and rainfall satellite utilization for mini hydro power dam basic design (case study on the ungauged catchment at West Borneo, Indonesia)

    Science.gov (United States)

    Prakoso, W. G.; Murtilaksono, K.; Tarigan, S. D.; Purwanto, Y. J.

    2018-05-01

    An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

  9. Meteorology Assessment of Historic Rainfall for Los Alamos During September 2013

    Energy Technology Data Exchange (ETDEWEB)

    Bruggeman, David Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dewart, Jean Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-02-12

    DOE Order 420.1, Facility Safety, requires that site natural phenomena hazards be evaluated every 10 years to support the design of nuclear facilities. The evaluation requires calculating return period rainfall to determine roof loading requirements and flooding potential based on our on-site rainfall measurements. The return period rainfall calculations are done based on statistical techniques and not site-specific meteorology. This and future studies analyze the meteorological factors that produce the significant rainfall events. These studies provide the meteorology context of the return period rainfall events.

  10. Critical Phenomena of Rainfall in Ecuador

    Science.gov (United States)

    Serrano, Sh.; Vasquez, N.; Jacome, P.; Basile, L.

    2014-02-01

    Self-organized criticality (SOC) is characterized by a power law behavior over complex systems like earthquakes and avalanches. We study rainfall using data of one day, 3 hours and 10 min temporal resolution from INAMHI (Instituto Nacional de Meteorologia e Hidrologia) station at Izobamba, DMQ (Metropolitan District of Quito), satellite data over Ecuador from Tropical Rainfall Measure Mission (TRMM,) and REMMAQ (Red Metropolitana de Monitoreo Atmosferico de Quito) meteorological stations over, respectively. Our results show a power law behavior of the number of rain events versus mm of rainfall measured for the high resolution case (10 min), and as the resolution decreases this behavior gets lost. This statistical property is the fingerprint of a self-organized critical process (Peter and Christensen, 2002) and may serve as a benchmark for models of precipitation based in phase transitions between water vapor and precipitation (Peter and Neeling, 2006).

  11. An Atlantic influence on Amazon rainfall

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Jin-Ho [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Zeng, Ning [University of Maryland, Earth System Science Interdisciplinary Center, College Park, MD (United States); University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States)

    2010-02-15

    Rainfall variability over the Amazon basin has often been linked to variations in Pacific sea surface temperature (SST), and in particular, to the El Nino/Southern Oscillation (ENSO). However, only a fraction of Amazon rainfall variability can be explained by ENSO. Building upon the recent work of Zeng (Environ Res Lett 3:014002, 2008), here we provide further evidence for an influence on Amazon rainfall from the tropical Atlantic Ocean. The strength of the North Atlantic influence is found to be comparable to the better-known Pacific ENSO connection. The tropical South Atlantic Ocean also shows some influence during the wet-to-dry season transition period. The Atlantic influence is through changes in the north-south divergent circulation and the movement of the ITCZ following warm SST. Therefore, it is strongest in the southern part of the Amazon basin during the Amazon's dry season (July-October). In contrast, the ENSO related teleconnection is through anomalous east-west Walker circulation with largely concentrated in the eastern (lower) Amazon. This ENSO connection is seasonally locked to boreal winter. A complication due to the influence of ENSO on Atlantic SST causes an apparent North Atlantic SST lag of Amazon rainfall. Removing ENSO from North Atlantic SST via linear regression resolves this causality problem in that the residual Atlantic variability correlates well and is in phase with the Amazon rainfall. A strong Atlantic influence during boreal summer and autumn is particularly significant in terms of the impact on the hydro-ecosystem which is most vulnerable during the dry season, as highlighted by the severe 2005 Amazon drought. Such findings have implications for both seasonal-interannual climate prediction and understanding the longer-term changes of the Amazon rainforest. (orig.)

  12. Multiscaling properties of tropical rainfall: Analysis of rain gauge datasets in Lesser Antilles island environment

    Science.gov (United States)

    Bernard, Didier C.; Pasquier, Raphaël; Cécé, Raphaël; Dorville, Jean-François

    2014-05-01

    Changes in rainfall seem to be the main impact of climate change in the Caribbean area. The last conclusions of IPCC (2013), indicate that the end of this century will be marked by a rise of extreme rainfalls in tropical areas, linked with increase of the mean surface temperature. Moreover, most of the Lesser Antilles islands are characterized by a complex topography which tends to enhance the rainfall from synoptic disturbances by orographic effects. In the past five years, out of hurricanes passage, several extreme rainy events (approx. 16 mm in 6 minutes), including fatal cases, occurred in the Lesser Antilles Arc: in Guadeloupe (January 2011, May 2012 and 2013), in Martinique (May 2009, April 2011 and 2013), in Saint-Lucia (December 2013). These phenomena inducing floods, loss of life and material damages (agriculture sector and public infrastructures), inhibit the development of the islands. At this time, numerical weather prediction models as WRF, which are based on the equations of the atmospheric physics, do not show great results in the focused area (Bernard et al., 2013). Statistical methods may be used to examine explicitly local rainy updrafts, thermally and orographically induced at micro-scale. The main goal of the present insular tropical study is to characterize the multifractal symmetries occurring in the 6-min rainfall time series, registered since 2006 by the French Met. Office network weather stations. The universal multifractal model (Schertzer and Lovejoy, 1991) is used to define the statistical properties of measured rainfalls at meso-scale and micro-scale. This model is parametrized by a fundamental exponents set (H,a,C1,q) which are determined and compared with values found in the literature. The first three parameters characterize the mean pattern and the last parameter q, the extreme pattern. The occurrence ranges of multifractal regime are examined. The suggested links between the internal variability of the tropical rainy events and the

  13. Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

    Directory of Open Access Journals (Sweden)

    Bolívar Erazo

    2018-02-01

    Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

  14. Testing the Effect of Cropping Practices on Soil Erosion Rates - Application of Field Rainfall Simulator

    Science.gov (United States)

    Dostál, Tomáš; Zumr, David; Krása, Josef; Kavka, Petr; Strouhal, Luděk

    2017-04-01

    C factor, the protection effect of the vegetation cover, is a key parameter which is introduced in the basic empirical soil erosion relationships (e.g. USLE). The C factor values for various crops in various grow stages are usually estimated based on the catalogue values. As these values often do not fit to the observed data from the plot experiments or do not represent actually grown crops, we decided to validate and extend the database. We present a methodology and primary results of tens of the field rainfall simulation experiments conducted on several agricultural crops with different BBCH. The rainfall simulations were done with the mobile field rainfall simulator of the Czech Technical University. The tested plots of the size 2 x 8,7 m were repeatedly exposed to the artificial rainfalls with intensity of 60 mm/h and duration of 30 to 60 minutes. The experiments were always performed twice on a bare soil and twice on the vegetated plots (to mimic dry and wet initial soil conditions). The tests were done on several slopes in the Czech Republic, the soils were mostly Cambisols with various organic matter content and stoniness. Based on the results we will be able to correct and validate the C factor values for the currently most widely grown crops in the conditions of the Central Europe. The presentation is funded by Ministry of Agriculture of the Czech Republic (research project QJ1530181) and an internal student CTU grant.

  15. Nonmonotonic and spatial-temporal dynamic slope effects on soil erosion during rainfall-runoff processes

    Science.gov (United States)

    Wu, Songbai; Yu, Minghui; Chen, Li

    2017-02-01

    The slope effect on flow erosivity and soil erosion still remains a controversial issue. This theoretical framework explained and quantified the direct slope effect by coupling the modified Green-Ampt equation accounting for slope effect on infiltration, 1-D kinematic wave overland flow routing model, and WEPP soil erosion model. The flow velocity, runoff rate, shear stress, interrill, and rill erosion were calculated on 0°-60° isotropic slopes with equal horizontal projective length. The results show that, for short-duration rainfall events, the flow erosivity and erosion amounts exhibit a bell-shaped trend which first increase with slope gradient, and then decrease after a critical slope angle. The critical slope angles increase significantly or even vanish with increasing rainfall duration but are nearly independent of the slope projective length. The soil critical shear stress, rainfall intensity, and temporal patterns have great influences on the slope effect trend, while the other soil erosion parameters, soil type, hydraulic conductivity, and antecedent soil moisture have minor impacts. Neglecting the slope effect on infiltration would generate smaller erosion and reduce critical slope angles. The relative slope effect on soil erosion in physically based model WEPP was compared to those in the empirical models USLE and RUSLE. The trends of relative slope effect were found quite different, but the difference may diminish with increasing rainfall duration. Finally, relatively smaller critical slope angles could be obtained with the equal slope length and the range of variation provides a possible explanation for the different critical slope angles reported in previous studies.

  16. Fine-tuning satellite-based rainfall estimates

    Science.gov (United States)

    Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

    2018-05-01

    Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

  17. Application of isotopic information for estimating parameters in Philip infiltration model

    Directory of Open Access Journals (Sweden)

    Tao Wang

    2016-10-01

    Full Text Available Minimizing parameter uncertainty is crucial in the application of hydrologic models. Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system, provide additional information for parameter estimation, and improve parameter identifiability. This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model. Two approaches to parameter estimation were compared: (a using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity, and (b using hydrologic information to determine the soil water transmission and the soil sorptivity. Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions. Experimental results showed that approach (a, using isotopic and hydrologic information, estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well. The results of parameter estimation of approach (a were better than those of approach (b. It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.

  18. Effects of Rainfall Characteristics on the Stability of Tropical Residual Soil Slope

    Directory of Open Access Journals (Sweden)

    Rahardjo Harianto

    2016-01-01

    Full Text Available Global climate change has a significant impact on rainfall characteristics, sea water level and groundwater table. Changes in rainfall characteristics may affect stability of slopes and have severe impacts on sustainable urban living. Information on the intensity, frequency and duration of rainfall is often required by geotechnical engineers for performing slope stability analyses. Many seepage analyses are commonly performed using the most extreme rainfall possible which is uneconomical in designing a slope repair or slope failure preventive measure. In this study, the historical rainfall data were analyzed and investigated to understand the characteristics of rainfall in Singapore. The frequency distribution method was used to estimate future rainfall characteristics in Singapore. New intensity-duration-frequency (IDF curves for rainfall in Singapore were developed for six different durations (10, 20, 30 min and 1, 2 and 24 h and six frequencies (2, 5, 10, 25, 50 and 100 years. The new IDF curves were used in the seepage and slope stability analyses to determine the variation of factor of safety of residual soil slopes under different rainfall intensities in Singapore.

  19. Rainfall estimation for hydrology using volumetric weather radar

    NARCIS (Netherlands)

    Hazenberg, P.

    2013-01-01

    This thesis focuses specifically on weather radar rainfall measurements in strati form precipitation. In North-Western Europe this type of precipitation is most dominant in winter and leads to the largest hydro logical response of catchments. Unfortunately, the quality of uncorrected radar rainfall

  20. Urban rainfall estimation employing commercial microwave links (poster)

    NARCIS (Netherlands)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.; Ten Veldhuis, J.A.E.

    2015-01-01

    In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Urban areas often lack rainfall information. Hence, new rainfall measurement techniques are important. E.g., the number of

  1. Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models

    Directory of Open Access Journals (Sweden)

    A. P. Jacquin

    2009-01-01

    Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.

  2. Monsoon rainfall behaviour in recent times on local/regional scale in India

    International Nuclear Information System (INIS)

    Singh, Surender; Rao, V.U.M.; Singh, Diwan

    2002-08-01

    An attempt has been made here to investigate the local/regional monsoon rainfall behaviour in the meteorological sub-division no. 13 comprising the areas of Haryana, Delhi and Chandigarh in India. The monthly monsoon rainfall data of 30 years (1970-99) of different locations in the region were used for the investigation. All locations except Delhi received more rainfall in monsoon season during the decade (1990-99) showing general increasing trend in the rainfall behaviour in recent times. The mean monsoon rainfall at various locations ranged between 324.8 mm at Sirsa and 974.9 mm at Chandigarh. The major amount of monsoon rainfall occurred during the month of July and August in the entire region. Monthly mean rainfall ranged between 37.5 to 144.9 mm (June), 130.6 to 298.2 mm (July), 92.6 to 313.6 mm (August) and 44.0 to 149.4mm (September) at different locations. All the locations in the region exhibited overall increasing trend in monsoon rainfall over the period under study. All locations in the region received their lowest monsoon rainfall in the year 1987 which was a drought year and the season's rainfall ranged between 56.1 mm (Sirsa) and 290.0 mm (Delhi) during this year. Many of the locations observed clusters of fluctuations in their respective monsoon rainfall. The statistical summaries of historical data series (1970-99) gave rainfall information on various time scale. Such information acquires value through its influence on the decision making of the ultimate users. (author)

  3. Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

    Science.gov (United States)

    Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

    2010-05-01

    The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day

  4. TIME SERIES CHARACTERISTIC ANALYSIS OF RAINFALL, LAND USE AND FLOOD DISCHARGE BASED ON ARIMA BOX-JENKINS MODEL

    Directory of Open Access Journals (Sweden)

    Abror Abror

    2014-01-01

    Full Text Available Indonesia located in tropic area consists of wet season and dry season. However, in last few years, in river discharge in dry season is very little, but in contrary, in wet season, frequency of flood increases with sharp peak and increasingly great water elevation. The increased flood discharge may occur due to change in land use or change in rainfall characteristic. Both matters should get clarity. Therefore, a research should be done to analyze rainfall characteristic, land use and flood discharge in some watershed area (DAS quantitatively from time series data. The research was conducted in DAS Gintung in Parakankidang, DAS Gung in Danawarih, DAS Rambut in Cipero, DAS Kemiri in Sidapurna and DAS Comal in Nambo, located in Tegal Regency and Pemalang Regency in Central Java Province. This research activity consisted of three main steps: input, DAS system and output. Input is DAS determination and selection and searching secondary data. DAS system is early secondary data processing consisting of rainfall analysis, HSS GAMA I parameter, land type analysis and DAS land use. Output is final processing step that consisting of calculation of Tadashi Tanimoto, USSCS effective rainfall, flood discharge, ARIMA analysis, result analysis and conclusion. Analytical calculation of ARIMA Box-Jenkins time series used software Number Cruncher Statistical Systems and Power Analysis Sample Size (NCSS-PASS version 2000, which result in time series characteristic in form of time series pattern, mean square errors (MSE, root mean square ( RMS, autocorrelation of residual and trend. Result of this research indicates that composite CN and flood discharge is proportional that means when composite CN trend increase then flood discharge trend also increase and vice versa. Meanwhile, decrease of rainfall trend is not always followed with decrease in flood discharge trend. The main cause of flood discharge characteristic is DAS management characteristic, not change in

  5. High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events

    Directory of Open Access Journals (Sweden)

    Tomasz Berezowski

    2018-01-01

    Full Text Available Discharge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River. The forcing data are delivered by Weather Research and Forecasting (WRF model in 1 h temporal and 4 × 4 km spatial resolutions. The discharge forecasting models are set in two scenarios with snowmelt and rainfall and rainfall only predictors in order to highlight the effect of snowmelt on the results (both scenarios use also pre-forecast discharge based predictors. We show that inclusion of snowmelt decrease the forecast errors for longer forecasts’ lead times. Moreover, importance of discharge based predictors is higher in the rainfall only models then in the snowmelt and rainfall models. We conclude that the role of snowmelt for discharge forecasting in mixed snowmelt and rainfall environments is in accounting for nonlinear physical processes, such as initial wetting and rain on snow, which cannot be properly modelled by rainfall only.

  6. Observed magnified runoff response to rainfall intensification under global warming

    International Nuclear Information System (INIS)

    Huang, Jr-Chuan; Lee, Tsung-Yu; Lee, Jun-Yi

    2014-01-01

    Runoff response to rainfall intensification under global warming is crucial, but is poorly discussed due to the limited data length and human alteration. Historical rainfall and runoff records in pristine catchments in Taiwan were investigated through trend analysis and cross temperature difference analysis. Trend analysis showed that both rainfall and runoff in the 99.9-percentile have been significantly increasing in terms of frequency and intensity over the past four decades. Cross temperature difference analysis quantified that the rainfall and runoff extremes (including the 99.0–99.9-percentiles) may increase by 69.5% and 99.8%, respectively, under a future scenario of 1  ° C increase in temperature. This increase in intensity resembles the increase in intensity observed between 1971–1990 and 1991–2010. The amplified runoff response can be related to the limited catchment storage capacity being preoccupied by rainfall extremes. The quantified temperature effect on rainfall and runoff intensification can be a strong basis for designing scenarios, confirming and fusing GCMs’ results. In addition, the runoff amplification should be a warning for other regions with significant rainfall intensification. Appropriate strategies are indispensable and urgently needed to maintain and protect the development of societies. (paper)

  7. Urban Run-off Volumes Dependency on Rainfall Measurement Method

    DEFF Research Database (Denmark)

    Pedersen, L.; Jensen, N. E.; Rasmussen, Michael R.

    2005-01-01

    Urban run-off is characterized with fast response since the large surface run-off in the catchments responds immediately to variations in the rainfall. Modeling such type of catchments is most often done with the input from very few rain gauges, but the large variation in rainfall over small areas...... resolutions and single gauge rainfall was fed to a MOUSE run-off model. The flow and total volume over the event is evaluated....

  8. Error threshold inference from Global Precipitation Measurement (GPM) satellite rainfall data and interpolated ground-based rainfall measurements in Metro Manila

    Science.gov (United States)

    Ampil, L. J. Y.; Yao, J. G.; Lagrosas, N.; Lorenzo, G. R. H.; Simpas, J.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission is a group of satellites that provides global observations of precipitation. Satellite-based observations act as an alternative if ground-based measurements are inadequate or unavailable. Data provided by satellites however must be validated for this data to be reliable and used effectively. In this study, the Integrated Multisatellite Retrievals for GPM (IMERG) Final Run v3 half-hourly product is validated by comparing against interpolated ground measurements derived from sixteen ground stations in Metro Manila. The area considered in this study is the region 14.4° - 14.8° latitude and 120.9° - 121.2° longitude, subdivided into twelve 0.1° x 0.1° grid squares. Satellite data from June 1 - August 31, 2014 with the data aggregated to 1-day temporal resolution are used in this study. The satellite data is directly compared to measurements from individual ground stations to determine the effect of the interpolation by contrast against the comparison of satellite data and interpolated measurements. The comparisons are calculated by taking a fractional root-mean-square error (F-RMSE) between two datasets. The results show that interpolation improves errors compared to using raw station data except during days with very small amounts of rainfall. F-RMSE reaches extreme values of up to 654 without a rainfall threshold. A rainfall threshold is inferred to remove extreme error values and make the distribution of F-RMSE more consistent. Results show that the rainfall threshold varies slightly per month. The threshold for June is inferred to be 0.5 mm, reducing the maximum F-RMSE to 9.78, while the threshold for July and August is inferred to be 0.1 mm, reducing the maximum F-RMSE to 4.8 and 10.7, respectively. The maximum F-RMSE is reduced further as the threshold is increased. Maximum F-RMSE is reduced to 3.06 when a rainfall threshold of 10 mm is applied over the entire duration of JJA. These results indicate that

  9. An investigation of wash-off controlling parameters at urban and commercial monitoring sites.

    Science.gov (United States)

    Berretta, C; Gnecco, I; Lanza, L G; La Barbera, P

    2007-01-01

    The relationship between the parameters of the wash-off function and the controlling hydrologic variables are investigated in this paper, assuming that the pollutant generation process basically depends on the watershed rainfall-runoff response characteristics. Data collected during an intense monitoring program carried out by the Department of Environmental Engineering of the University of Genova (Italy) within a residential area, an auto dismantler facility, a tourism terminal and a urban waste truck depot are used to this aim. The observed runoff events are classified into different TSS mass delivery processes and the occurrence of the first flush phenomenon is also investigated. The correlation between the mathematical parameters describing the exponential process and the hydrological parameters of the corresponding rainfall-runoff event is analysed: runoff parameters and in particular the maximum flow discharge over the time of concentration of the drainage network are proposed as the controlling factor for the total mass of pollutant that is made available for wash-off during each runoff event.

  10. Seasonal variation and climate change impact in Rainfall Erosivity across Europe

    Science.gov (United States)

    Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine; Ballabio, Cristiano

    2017-04-01

    Rainfall erosivity quantifies the climatic effect on water erosion and is of high importance for soil scientists, land use planners, agronomists, hydrologists and environmental scientists in general. The rainfall erosivity combines the influence of rainfall duration, magnitude, frequency and intensity. Rainfall erosivity is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minute rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years). The European Commission's Joint Research Centr(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,675 stations. The interpolation of those point erosivity values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511: 801-815). In 2016, REDES extended with a monthly component, which allowed developing monthly and seasonal erosivity maps and assessing rainfall erosivity both spatially and temporally for European Union and Switzerland. The monthly erosivity maps have been used to develop composite indicators that map both intra-annual variability and concentration of erosive events (Science of the Total Environment, 579: 1298-1315). Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Finally, the identification of the most erosive month allows recommending certain agricultural management practices (crop

  11. Prediction of Rainfall-Induced Landslides in Tegucigalpa, Honduras, Using a Hydro-Geotechnical Model

    Science.gov (United States)

    Garcia Urquia, Elias; Axelsson, K.

    2010-05-01

    parameters based on the existing information (i.e. rainfall data, soil testing data, land-use data). In addition, the spatial data management and manipulation is done by means of a Geographic Information System (GIS). For such purpose, maps of land-use, topography and geology provided by JICA have bee manually digitized and converted into GIS raster maps. The resulting safety map is then validated by comparing it with existing slope-failure-maps that have been created to show the affected areas during Hurricane Mitch. This safety map represents a useful tool in the prevention of landslide-related disasters, as it would be able to point out which segments of the population are at risk as a consequence of the rainfall-slope interaction in Tegucigalpa.

  12. Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

    Science.gov (United States)

    Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

    2015-04-01

    The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

  13. Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

    Science.gov (United States)

    Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

    2017-04-01

    Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

  14. Multifractal rainfall extremes: Theoretical analysis and practical estimation

    International Nuclear Information System (INIS)

    Langousis, Andreas; Veneziano, Daniele; Furcolo, Pierluigi; Lepore, Chiara

    2009-01-01

    We study the extremes generated by a multifractal model of temporal rainfall and propose a practical method to estimate the Intensity-Duration-Frequency (IDF) curves. The model assumes that rainfall is a sequence of independent and identically distributed multiplicative cascades of the beta-lognormal type, with common duration D. When properly fitted to data, this simple model was found to produce accurate IDF results [Langousis A, Veneziano D. Intensity-duration-frequency curves from scaling representations of rainfall. Water Resour Res 2007;43. (doi:10.1029/2006WR005245)]. Previous studies also showed that the IDF values from multifractal representations of rainfall scale with duration d and return period T under either d → 0 or T → ∞, with different scaling exponents in the two cases. We determine the regions of the (d, T)-plane in which each asymptotic scaling behavior applies in good approximation, find expressions for the IDF values in the scaling and non-scaling regimes, and quantify the bias when estimating the asymptotic power-law tail of rainfall intensity from finite-duration records, as was often done in the past. Numerically calculated exact IDF curves are compared to several analytic approximations. The approximations are found to be accurate and are used to propose a practical IDF estimation procedure.

  15. Radioactive pollution in rainfall

    International Nuclear Information System (INIS)

    Jemtland, R.

    1985-01-01

    Routine measurements of radioactivity in rainfall are carried out at the National Institute for Radiation Hygiene, Norway. The report discusses why the method of ion exchange was selected and gives details on how the measurements are performed

  16. Preliminary Investigation on the Behavior of Pore Air Pressure During Rainfall Infiltration

    Science.gov (United States)

    Ashraf Mohamad Ismail, Mohd; Min, Ng Soon; Hasliza Hamzah, Nur; Hazreek Zainal Abidin, Mohd; Madun, Aziman; Tajudin, Saiful Azhar Ahmad

    2018-04-01

    This paper focused on the preliminary investigation of pore air pressure behaviour during rainfall infiltration in order to substantiate the mechanism of rainfall induced slope failure. The actual behaviour or pore air pressure during infiltration is yet to be clearly understood as it is regularly assumed as atmospheric. Numerical modelling of one dimensional (1D) soil column was utilized in this study to provide a preliminary insight of this highlighted uncertainty. Parametric study was performed by using rainfall intensities of 1.85 x 10-3m/s and 1.16 x 10-4m/s applied on glass beads to simulate intense and modest rainfall conditions. Analysis results show that the high rainfall intensity causes more development of pore air pressure compared to low rainfall intensity. This is because at high rainfall intensity, the rainwater cannot replace the pore air smoothly thus confining the pore air. Therefore, the effect of pore air pressure has to be taken into consideration particularly during heavy rainfall.

  17. Impact of the Rainfall Duration and Temporal Rainfall Distribution Defined Using the Huff Curves on the Hydraulic Flood Modelling Results

    Directory of Open Access Journals (Sweden)

    Nejc Bezak

    2018-02-01

    Full Text Available In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the possible approaches involves using a hydrological model where one can calculate the design hydrograph through the design of a rainfall event. This study investigates the impact of the design rainfall on the combined one-dimensional/two-dimensional (1D/2D hydraulic modelling results. The Glinščica Stream catchment located in Slovenia (central Europe is used as a case study. Ten different design rainfall events were compared for 10 and 100-year return periods, where we used Huff curves for the design rainfall event definition. The results indicate that the selection of the design rainfall event should be regarded as an important step, since the hydraulic modelling results for different scenarios differ significantly. In the presented experimental case study, the maximum flooded area extent was twice as large as the minimum one, and the maximum water velocity over flooded areas was more than 10 times larger than the minimum one. This can lead to the production of very different flood hazard maps, and consequently planning very different flood protection schemes.

  18. Multisite rainfall downscaling and disaggregation in a tropical urban area

    Science.gov (United States)

    Lu, Y.; Qin, X. S.

    2014-02-01

    A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

  19. RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

    Directory of Open Access Journals (Sweden)

    Celso A. G. Santos

    2016-01-01

    Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

  20. Rainfall measurement based on in-situ storm drainage flow sensors

    DEFF Research Database (Denmark)

    Ahm, Malte; Rasmussen, Michael Robdrup

    2017-01-01

    Data for adjustment of weather radar rainfall estimations are mostly obtained from rain gauge observations. However, the density of rain gauges is often very low. Yet in many urban catchments, runoff sensors are typically available which can measure the rainfall indirectly. By utilising these sen......Data for adjustment of weather radar rainfall estimations are mostly obtained from rain gauge observations. However, the density of rain gauges is often very low. Yet in many urban catchments, runoff sensors are typically available which can measure the rainfall indirectly. By utilising...... these sensors, it may be possible to improve the ground rainfall estimate, and thereby improve the quantitative precipitation estimation from weather radars for urban drainage applications. To test the hypothesis, this paper presents a rainfall measurement method based on flow rate measurements from well......-defined urban surfaces. This principle was used to design a runoff measurement system in a parking structure in Aalborg, Denmark, where it was evaluated against rain gauges. The measurements show that runoff measurements from well-defined urban surfaces perform just as well as rain gauges. This opens up...

  1. Towards flash flood prediction in the dry Dead Sea region utilizing radar rainfall information

    Science.gov (United States)

    Morin, E.; Jacoby, Y.; Navon, S.; Bet-Halachmi, E.

    2009-04-01

    Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model utilizing radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on five years of data for one of the catchments. Validation was performed for a subsequent five-year period for the same catchment and then for an entire ten year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood-warning model is feasible for catchments in the area studied.

  2. Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

    Science.gov (United States)

    Morin, Efrat; Jacoby, Yael; Navon, Shilo; Bet-Halachmi, Erez

    2009-07-01

    Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Validation was performed for a subsequent 5-year period for the same catchment and then for an entire 10-year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.

  3. Deforestation alters rainfall: a myth or reality

    Science.gov (United States)

    Hanif, M. F.; Mustafa, M. R.; Hashim, A. M.; Yusof, K. W.

    2016-06-01

    To cope with the issue of food safety and human shelter, natural landscape has gone through a number of alterations. In the coming future, the expansion of urban land and agricultural farms will likely disrupt the natural environment. Researchers have claimed that land use change may become the most serious issue of the current century. Thus, it is necessary to understand the consequences of land use change on the climatic variables, e.g., rainfall. This study investigated the impact of deforestation on local rainfall. An integrated methodology was adopted to achieve the objectives. Above ground biomass was considered as the indicator of forest areas. Time series data of a Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were obtained for the year of 2000, 2005, and 2010. Rainfall data were collected from the Department of Irrigation and Drainage, Malaysia. The MODIS time series data were classified and four major classes were developed based on the Normalised Difference Vegetation Index (NDVI) ranges. The results of the classification showed that water, and urban and agricultural lands have increased in their area by 2, 3, and 6%, respectively. On the other hand, the area of forest has decreased 10% collectively from 2000 to 2010. The results of NDVI and rainfall data were analysed by using a linear regression analysis. The results showed a significant relationship at a 90% confidence interval between rainfall and deforestation (t = 1.92, p = 0.06). The results of this study may provide information about the consequences of land use on the climate on the local scale.

  4. Drought-avoiding plants with low water use can achieve high rainfall retention without jeopardising survival on green roofs.

    Science.gov (United States)

    Szota, Christopher; Farrell, Claire; Williams, Nicholas S G; Arndt, Stefan K; Fletcher, Tim D

    2017-12-15

    Green roofs are increasingly being used among the suite of tools designed to reduce the volume of surface water runoff generated by cities. Plants provide the primary mechanism for restoring the rainfall retention capacity of green roofs, but selecting plants with high water use is likely to increase drought stress. Using empirically-derived plant physiological parameters, we used a water balance model to assess the trade-off between rainfall retention and plant drought stress under a 30-year climate scenario. We compared high and low water users with either drought avoidance or drought tolerance strategies. Green roofs with low water-using, drought-avoiding species achieved high rainfall retention (66-81%) without experiencing significant drought stress. Roofs planted with other strategies showed high retention (72-90%), but they also experienced >50days of drought stress per year. However, not all species with the same strategy behaved similarly, therefore selecting plants based on water use and drought strategy alone does not guarantee survival in shallow substrates where drought stress can develop quickly. Despite this, it is more likely that green roofs will achieve high rainfall retention with minimal supplementary irrigation if planted with low water users with drought avoidance strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Simulation of heavy, long-term rainfall over low mountain ranges; Simulation von Starkniederschlaegen mit langer Andauer ueber Mittelgebirgen

    Energy Technology Data Exchange (ETDEWEB)

    Kunz, M.

    2003-03-01

    A diagnostic model for the estimation of orographic precipitation during large-scale upslide motions is presented. It is based on linear theory for 3-D mountain overflow. From the simulated vertical velocities rain intensities at the ground are calculated using a model for precipitation formation. Due to the small number of free parameters and because of the simple initialisation method, e.g. with single radiosonde data, the model is used for regionalisation of precipitation from rain gauge observations as well as for deriving its statistics under dynamical constraints. For Southwest Germany and Eastern France, with the low mountain ranges of the Vosges, Black Forest and Swabian Alb, model simulations are performed for individual events with heavy rainfall. Thereby it is evaluated, how realistic rainfall patterns can be obtained with a combination of model simulations and measurement data. Mean rainfall distributions are derived from simulations of all extreme events with 24-h totals over 60 mm at selected rain gauge stations between 1971 and 2000. Furthermore the calculation of rain sums for different return periods is performed using extreme value statistics. So it is possible to quantify the hazard potential of heavy rainfall, which may cause flooding or landslides, in high spatial resolution (2.5 x 2.5 km). (orig.)

  6. Rainfall estimation with TFR model using Ensemble Kalman filter

    Science.gov (United States)

    Asyiqotur Rohmah, Nabila; Apriliani, Erna

    2018-03-01

    Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

  7. Effect of variations in rainfall intensity on slope stability in Singapore

    OpenAIRE

    Christofer Kristo; Harianto Rahardjo; Alfrendo Satyanaga

    2017-01-01

    Numerous scientific evidence has given credence to the true existence and deleterious impacts of climate change. One aspect of climate change is the variations in rainfall patterns, which affect the flux boundary condition across ground surface. A possible disastrous consequence of this change is the occurrence of rainfall-induced slope failures. This paper aims to investigate the variations in rainfall patterns in Singapore and its effect on slope stability. Singapore's historical rainfall d...

  8. Spatial and temporal variability of rainfall in the Tocantins-Araguaia hydrographic region

    Directory of Open Access Journals (Sweden)

    Glauber Epifanio Loureiro

    2015-01-01

    Full Text Available Current paper examines the space-time dynamics of yearly rainfall of the Tocantins-Araguaia Hydrographic Region (TAHR, foregrounded on rainfall volume from isohyet maps and interpolated by Kriging geo-statistical method.  Rainfall space dynamics was undertaken by the analysis of descriptive statistics, Index of Meteorological Irregularity (IMI and Variation Coefficient. Temporal dynamics was analyzed through the distribution of total annual volume precipitation for each TAHR sub-basin by the Standardized Anomaly Index, trend and magnitude test provided by Mann-Kendall and Sen Tests. Results correlated with meteorological anomalies of the Atlantic (Dipole and Pacific (ENOS Oceans show a highly heterogeneous rainfall behavior with temporal variability. Or rather, a decrease of rainfall extensiveness during years of intense meteorological anomaly with a rainfall increase south of the High Tocantins and Araguaia sub-basins and a decrease of rainfall in the Lower Tocantins sub-basin, with El Niño features. Although the Mann-Kendall test does not show statistically a significant trend for rainfall in the TAHR region, Sen’s estimator reveals a decrease in rainfall in the High Tocantins (-1.24 km³ year-1 and Araguaia (-1.13 km³ year-1 sub-basins and a rainfall increase in the Lower Tocantins sub-basin (0.53 km³ year-1 and in the TAHR region (-1.5 km³ year-1.

  9. Stochastic modeling of hourly rainfall times series in Campania (Italy)

    Science.gov (United States)

    Giorgio, M.; Greco, R.

    2009-04-01

    Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil

  10. Spatio-temporal trends of rainfall across Indian river basins

    Science.gov (United States)

    Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

    2018-04-01

    Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

  11. Should seasonal rainfall forecasts be used for flood preparedness?

    Directory of Open Access Journals (Sweden)

    E. Coughlan de Perez

    2017-09-01

    Full Text Available In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.

  12. Rainfall Modification by Urban Areas: New Perspectives from TRMM

    Science.gov (United States)

    Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

    2002-01-01

    Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

  13. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  14. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

    estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological...... applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value......Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology...

  15. Location-Based Rainfall Nowcasting Service for Public

    Science.gov (United States)

    Woo, Wang-chun

    2013-04-01

    The Hong Kong Observatory has developed the "Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)", a radar-based rainfall nowcasting system originally to support forecasters in rainstorm warning and severe weather forecasting such as hail, lightning and strong wind gusts in Hong Kong. The system has since been extended to provide rainfall nowcast service direct for the public in recent years. Following the launch of "Rainfall Nowcast for the Pearl River Delta Region" service provided via a Geographical Information System (GIS) platform in 2008, a location-based rainfall nowcast service served through "MyObservatory", a smartphone app for iOS and Android developed by the Observatory, debuted in September 2012. The new service takes advantage of the capability of smartphones to detect own locations and utilizes the quantitative precipitation forecast (QPF) from SWIRLS to provide location-based rainfall nowcast to the public. The conversion of radar reflectivity data (at 2 or 3 km above ground) to rainfall in SWIRLS is based on the Z-R relationship (Z=aRb) with dynamical calibration of the coefficients a and b determined using real-time rain gauge data. Adopting the "Multi-scale Optical-flow by Variational Analysis (MOVA)" scheme to track the movement of radar echoes and Semi-Lagrangian Advection (SLA) scheme to extrapolate their movement, the system is capable of producing QPF for the next six hours in a grid of 480 x 480 that covers a domain of 256 km x 256 km once every 6 minutes. Referencing the closest point in a resampled 2-km grid over the territory of Hong Kong, a prediction as to whether there will be rainfall exceeding 0.5 mm in every 30 minute intervals for the next two hours at users' own or designated locations are made available to the users in both textual and graphical format. For those users who have opted to receive notifications, a message would pop up on the user's phone whenever rain is predicted in the next two hours in a user

  16. Wheat yield vulnerability: relation to rainfall and suggestions for adaptation

    Directory of Open Access Journals (Sweden)

    Khalid Tafoughalti

    2018-04-01

    Full Text Available Wheat production is of paramount importance in the region of Meknes, which is mainly produced under rainfed conditions. It is the dominant cereal, the greater proportion being the soft type. During the past few decades, rainfall flaws have caused a number of cases of droughts. These flaws have seriously affecting wheat production. The main objective of this study is the assessment of rainfall variability at monthly, seasonal and annual scales and to determine their impact on wheat yields. To reduce this impact we suggested some mechanisms of adaptation. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model to evaluate the impact of rainfall on wheat yields. Data analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that soft wheat and hard wheat are strongly correlated with the period of January to March than with the whole growing-season. While they are adversely correlated with the mid-spring. This investigation concluded that synchronizing appropriate adaptation with the period of January to March was crucial to achieving success yield of wheat.

  17. Effect of Variations in Long-Duration Rainfall Intensity on Unsaturated Slope Stability

    Directory of Open Access Journals (Sweden)

    Hsin-Fu Yeh

    2018-04-01

    Full Text Available In recent years, many scientific methods have been used to prove that the Earth’s climate is changing. Climate change can affect rainfall patterns, which can in turn affect slope safety. Therefore, this study analyzed the effects of climate change on rainfall patterns from the perspective of rainfall intensity. This analysis was combined with numerical model analysis to examine the rainfall patterns of the Zengwen reservoir catchment area and its effects on slope stability. In this study, the Mann–Kendall test and the Theil–Sen estimator were used to analyze the rainfall records of rainfall stations at Da-Dong-Shan, Ma-To-Shan, and San-Jiao-Nan-Shan. The rainfall intensity of the Zengwen reservoir catchment area showed an increasing trend from 1990–2016. In addition, the analysis results of rainfall intensity trends were used for qualitative analysis of seepage and slope stability. The trend analysis result showed that in the future, from 2017–2100, if the amount of rainfall per hour continues to rise at about 0.1 mm per year, the amount of seepage will increase at the slope surface boundary and significantly change pore water pressure in the soil. As a result, the time of the occurrence of slope instability after the start of rainfall will decrease from 20 to 13 h, and the reduction in the safety coefficient will increase from 32 to 41%. Therefore, to decrease the effects of slope disasters on the safety of the Zengwen reservoir and its surrounding areas, changes in rainfall intensity trends should be considered for slope safety in this region. However, the results of trend analyses were weak and future research is needed using a wider range of precipitation data and detailed hydrological analysis to better predict rainfall pattern variations.

  18. Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

    Directory of Open Access Journals (Sweden)

    Carolien Toté

    2015-02-01

    Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  19. Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

    Science.gov (United States)

    Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  20. Effect of rainfall on cropping pattern in mid Himalayan region ...

    African Journals Online (AJOL)

    The analysis of effect of rainfall during the last 20 years is needed to evaluate cropping pattern in the rain-fed region. In this study, trends in annual, seasonal and monthly rainfall of district of Himachal Pradesh in India over the past 20 years were examined. The annual rainfall varies from 863.3 to 1470.0 mm. During the ...

  1. Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

    Science.gov (United States)

    Narulita, Ida; Ningrum, Widya

    2018-02-01

    Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

  2. Rainfall estimation in the context of post-event flash flood analysis

    Science.gov (United States)

    Delrieu, Guy; Boudevillain, Brice; Bouilloud, Ludovic

    2010-05-01

    Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology was developed within the EC-funded HYDRATE project to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically

  3. Exploring the potential of multivariate depth-damage and rainfall-damage models

    DEFF Research Database (Denmark)

    van Ootegem, Luc; van Herck, K.; Creten, T.

    2018-01-01

    In Europe, floods are among the natural catastrophes that cause the largest economic damage. This article explores the potential of two distinct types of multivariate flood damage models: ‘depth-damage’ models and ‘rainfall-damage’ models. We use survey data of 346 Flemish households that were...... victim of pluvial floods complemented with rainfall data from both rain gauges and weather radars. In the econometrical analysis, a Tobit estimation technique is used to deal with the issue of zero damage observations. The results show that in the ‘depth-damage’ models flood depth has a significant...... impact on the damage. In the ‘rainfall-damage’ models there is a significant impact of rainfall accumulation on the damage when using the gauge rainfall data as predictor, but not when using the radar rainfall data. Finally, non-hazard indicators are found to be important for explaining pluvial flood...

  4. Influence of southern oscillation on autumn rainfall in Iran (1951-2011)

    Science.gov (United States)

    Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

    2016-04-01

    This study aimed to investigate the relationships between southern oscillation and autumn (October-December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July-September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Niño (negative) and La Niña (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean's pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Niño and La Niña years over Iran. During the El Niño years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Niña years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Niño conditions increased autumn rainfall in Iran, the opposite conditions during the La Niña phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

  5. A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

    Science.gov (United States)

    Tan, H.; Chandrasekar, V.; Chen, H.

    2017-12-01

    Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products

  6. Rainfall influence on plot-scale runoff and soil loss from repeated burning in a Mediterranean-shrub ecosystem, Valencia, Spain

    Science.gov (United States)

    González-Pelayo, O.; Andreu, V.; Gimeno-García, E.; Campo, J.; Rubio, J. L.

    2010-06-01

    The effect of a repeated burning on soil hydrology and erosive parameters was studied on a Mediterranean forest soil (Rendzic leptosol) with the aim of identifying the effects of the fire and climatic parameters related to the post-fire runoff and soil loss. The study was carried out in an Experimental Permanent Field Station (La Concordia), close to Valencia (Spain). This field station is located on a calcareous hillside facing SSE, and is composed of nine erosion plots (20 × 4 m). Firstly, experimental fires were performed in June 1995 with two fire treatments (T1 or high severity fire and T2 or moderate severity fire) and a control one (unburnt, T3). The repeated fire (low severity) was carried out in July 2003. The studied period was focused from 18 months before the repeated fire (July 2003) until 18 months after it. Rainfall characteristics of each single event were recorded, which allowed us to statistically distinguish four time periods according to the rainfall intensity and duration: periods I (March 2002 to May 2003) and III (December 2003 to early May 2004) with low intensity and long duration rainfalls, and periods II (June 2003 to November 2003) and IV (late May 2004 to December 2004) with high intensity and short duration rainfalls. Before the 2003 fire, the partial recovery of soil and vegetation from the previous burning in 1995 led to a diminution in the runoff rates (6.5 L m - 2 in burned plots and 1.8 L m - 2 in unburnt ones). Six months later (period II), runoff increased in one order of magnitude (23.9 L m - 2 in burnt plots and 1.1 L m - 2 in the unburnt ones) due, in part, to the short time elapsed from fire until high intensity rainfalls. These differences in runoff production were maintained during the whole post-fire period. Fire effects were reflected in the erosion rates. Soil losses prior to the 2003 fire, in both fire treatments and in the control one, were scant relative to post-fire levels. However, six months after the repeated

  7. Statistical downscaling of rainfall: a non-stationary and multi-resolution approach

    Science.gov (United States)

    Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

    2016-05-01

    A novel downscaling technique is proposed in this study whereby the original rainfall and reanalysis variables are first decomposed by wavelet transforms and rainfall is modelled using the semi-parametric additive model formulation of Generalized Additive Model in Location, Scale and Shape (GAMLSS). The flexibility of the GAMLSS model makes it feasible as a framework for non-stationary modelling. Decomposition of a rainfall series into different components is useful to separate the scale-dependent properties of the rainfall as this varies both temporally and spatially. The study was conducted at the Onkaparinga river catchment in South Australia. The model was calibrated over the period 1960 to 1990 and validated over the period 1991 to 2010. The model reproduced the monthly variability and statistics of the observed rainfall well with Nash-Sutcliffe efficiency (NSE) values of 0.66 and 0.65 for the calibration and validation periods, respectively. It also reproduced well the seasonal rainfall over the calibration (NSE = 0.37) and validation (NSE = 0.69) periods for all seasons. The proposed model was better than the tradition modelling approach (application of GAMLSS to the original rainfall series without decomposition) at reproducing the time-frequency properties of the observed rainfall, and yet it still preserved the statistics produced by the traditional modelling approach. When downscaling models were developed with general circulation model (GCM) historical output datasets, the proposed wavelet-based downscaling model outperformed the traditional downscaling model in terms of reproducing monthly rainfall for both the calibration and validation periods.

  8. Some observations of the variations in natural gamma radiation due to rainfall

    International Nuclear Information System (INIS)

    Minato, S.

    1980-01-01

    Results of observations of variations in natural gamma-radiation flux densities due to rainfall are presented and discussed in relation to rate of rainfall. Variations of fluences with amounts of rainfall are also described. It is concluded that the frequency distribution of the ratio of the fluence to the amount of rainfall has a trend to be lognormal

  9. EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

    Directory of Open Access Journals (Sweden)

    A. Cilek

    2016-06-01

    Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

  10. Damaging Rainfall and Flooding. The Other Sahel Hazards

    Energy Technology Data Exchange (ETDEWEB)

    Tarhule, A. [Department of Geography, University of Oklahoma, 100 East Boyd Street, Norman, OK, 73079 (United States)

    2005-10-01

    Damaging rainfall and rain-induced flooding occur from time to time in the drought-prone Sahel savannah zone of Niger in West Africa but official records of these events and their socioeconomic impacts do not exist. This paper utilized newspaper accounts between 1970 and 2000 to survey and illustrate the range of these flood hazards in the Sahel. During the study interval, 53 newspaper articles reported 79 damaging rainfall and flood events in 47 different communities in the Sahel of Niger. Collectively, these events destroyed 5,580 houses and rendered 27,289 people homeless. Cash losses and damage to infrastructure in only three events exceeded $4 million. Sahel residents attribute these floods to five major causes including both natural and anthropogenic, but they view the flood problem as driven primarily by land use patterns. Despite such awareness, traditional coping strategies appear inadequate for dealing with the problems in part because of significant climatic variability. Analysis of several rainfall measures indicates that the cumulative rainfall in the days prior to a heavy rain event is an important factor influencing whether or not heavy rainfall results in flooding. Thus, despite some limitations, newspaper accounts of historical flooding are largely consistent with measured climatic variables. The study demonstrates that concerted effort is needed to improve the status of knowledge concerning flood impacts and indeed other natural and human hazards in the Sahel.

  11. Event-based rainfall-runoff modelling of the Kelantan River Basin

    Science.gov (United States)

    Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

    2014-02-01

    Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

  12. Event-based rainfall-runoff modelling of the Kelantan River Basin

    International Nuclear Information System (INIS)

    Basarudin, Z; Adnan, N A; Latif, A R A; Syafiqah, N; Tahir, W

    2014-01-01

    Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area

  13. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  14. Improvement of Statistical Typhoon Rainfall Forecasting with ANN-Based Southwest Monsoon Enhancement

    Directory of Open Access Journals (Sweden)

    Tsung-Yi Pan

    2011-01-01

    Full Text Available Typhoon Morakot 2009, with significant southwest monsoon flow, produced a record-breaking rainfall of 2361 mm in 48 hours. This study hopes to improve a statistical typhoon rainfall forecasting method used over the mountain region of Taiwan via an artificial neural network based southwest monsoon enhancement (ANNSME model. Rainfall data collected at two mountain weather stations, ALiShan and YuShan, are analyzed to establish the relation to the southwest monsoon moisture flux which is calculated at a designated sea area southwest of Taiwan. The results show that the moisture flux, with southwest monsoon flow, transported water vapor during the landfall periods of Typhoons Mindulle, Bilis, Fungwong, Kalmaegi, Haitaing and Morakot. Based on the moisture flux, a linear regression is used to identify an effective value of moisture flux as the threshold flux which can enhance mountain rainfall in southwestern Taiwan. In particular, a feedforward neural network (FNN is applied to estimate the residuals from the linear model to the differences between simulated rainfalls by a typhoon rainfall climatology model (TRCM and observations. Consequently, the ANNSME model integrates the effective moisture flux, linear rainfall model and the FNN for residuals. Even with very limited training cases, our results indicate that the ANNSME model is robust and suitable for improvement of TRCM rainfall prediction. The improved prediction of the total rainfall and of the multiple rainfall peaks is important for emergency operation.

  15. Projections of West African summer monsoon rainfall extremes from two CORDEX models

    Science.gov (United States)

    Akinsanola, A. A.; Zhou, Wen

    2018-05-01

    Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

  16. High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2016-04-01

    Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

  17. Parametric study on the effect of rainfall pattern to slope stability

    Directory of Open Access Journals (Sweden)

    Hakim Sagitaningrum Fathiyah

    2017-01-01

    Full Text Available Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also observed. The analyses were conducted with SEEP/W for the seepage and SLOPE/W for the slope stability. It is found that the lowest FS for gentle slope is reached under the application of advanced rainfall pattern and the lowest FS for steep slope is reached under the application of delayed rainfall pattern. Reduction of FS is known to be the largest for gentle slope rather than steep slope due to negative pore water pressure reduction and the rising of ground water level. The largest FS reduction caused by rainfall was achieved for gentle slope under advanced rainfall pattern.

  18. Ten-Year Climatology of Summertime Diurnal Rainfall Rate Over the Conterminous U.S.

    Science.gov (United States)

    Matsui, Toshihisa; Mocko, David; Lee, Myong-In; Tao, Wei-Kuo; Suarez, Max J.; Pielke, Roger A., Sr.

    2010-01-01

    Diurnal cycles of summertime rainfall rates are examined over the conterminous United States, using radar-gauge assimilated hourly rainfall data. As in earlier studies, rainfall diurnal composites show a well-defined region of rainfall propagation over the Great Plains and an afternoon maximum area over the south and eastern portion of the United States. Zonal phase speeds of rainfall in three different small domains are estimated, and rainfall propagation speeds are compared with background zonal wind speeds. Unique rainfall propagation speeds in three different regions can be explained by the evolution of latent-heat theory linked to the convective available potential energy, than by gust-front induced or gravity wave propagation mechanisms.

  19. Influence of rainfall observation network on model calibration and application

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-01-01

    Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

  20. An Investigation on the Sensitivity of the Parameters of Urban Flood Model

    Science.gov (United States)

    M, A. B.; Lohani, B.; Jain, A.

    2015-12-01

    Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a

  1. The Use of Rainfall Variability in Flood Countermeasure Planning

    Directory of Open Access Journals (Sweden)

    Iis Catur Wulan Dhari

    2017-09-01

    Full Text Available One of the impacts of climate change is the unpredictable shifting of seasons and rainfall patterns which caused flooding. Rejoso Watershed in Pasuruan Regency is one of the watersheds that suffer from flooding almost every year due to watershed degradation characterized by land conversion and changes in the hydrological behavior including the extreme rainfall pattern. This research was aimed to investigate the effect of rainfall variability on runoff and floodwater level profile along the river channel to provide technical and non-technical recommendation for handling flood problems. The hydrological analysis was performed using HEC-HMS version 4.0 software and the hydraulic analysis was conducted using HEC-RAS version 5.0.3 software. Several variations of extreme rainfall pattern were applied in the rainfall-runoff calculation to determine the representative flood discharges that will be used as input to the hydraulic simulation for evaluating the characteristics of flood water level. The result of the research shows that rainfall with the same depth yet varies in duration and starting time generate different flood hydrographs. Rejoso River could not store flood discharge with return period of 2 years with peak discharge of 201.46 m3/s that causing overflow along the stream. The recommendation to handle flood problems is by normalization, which could reduce the overtopping at several river reaches of 4,927 m, while the combination of normalization and embankment could reduce 7,843 m from the existing river length of 12,396 m.

  2. A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

    Science.gov (United States)

    Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

  3. Analysis of Rainfall Intensity in Madiun Watershed, East Java

    Directory of Open Access Journals (Sweden)

    Muttaqin Muttaqin

    2004-01-01

    Full Text Available The aim of the reasearch in the area of Madiun River Basin is to make and to analyze the Intensity Duration Curve (IDC i.e. the curve describing graphically the relation between rainfall intensity and rainfall duration in a certain frequent period. Formulation used in the research was Talbot Formula and Ishiguro’s. In the drafting of Intensity Duration Curve it was used specific coefficient i.e by using the rainfall data of fifteen and sixty duration for both applied formulations. The IDC recorded has not mean difference because in both formulation was used coefficient of the same value. The pattern of the rainfall intensity occured directed toward Nort East. It was happened because of the moving clouds directed toward that course. Depression occured at the backward of Mount Lawu, exactly toward East.

  4. A comparative study of mixed exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process

    Science.gov (United States)

    Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah

    2014-11-01

    A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.

  5. Incident rainfall in Rome and its relation to biodeterioration of buildings

    Energy Technology Data Exchange (ETDEWEB)

    Caneva, G; Gori, E; Danin, A [Instituto Centrale per il Restauro, Rome (Italy)

    1992-06-01

    A discussion is presented of the intensity and distribution of incident rainfall in Rome, and the degree of lithobiont cover of building walls. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. The results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water. 31 refs., 4 figs., 2 tabs.

  6. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

    Directory of Open Access Journals (Sweden)

    S. Zhang

    2018-03-01

    Full Text Available Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

  7. Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

    Directory of Open Access Journals (Sweden)

    Sungwon Kim

    2015-06-01

    Full Text Available The objective of this study is to develop artificial neural network (ANN models, including multilayer perceptron (MLP and Kohonen self-organizing feature map (KSOFM, for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop and 11-3-1 (Levenberg-Marquardt were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop and 1-3-11 (Levenberg–Marquardt, which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts.

  8. Positive response of Indian summer rainfall to Middle East dust

    KAUST Repository

    Jin, Qinjian

    2014-06-02

    Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

  9. Congo Basin rainfall climatology: can we believe the climate models?

    Science.gov (United States)

    Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

    2013-01-01

    The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

  10. Positive response of Indian summer rainfall to Middle East dust

    KAUST Repository

    Jin, Qinjian; Wei, Jiangfeng; Yang, Zong-Liang

    2014-01-01

    Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

  11. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-01-01

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

  12. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-06-15

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  13. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Directory of Open Access Journals (Sweden)

    Haris Akram Bhatti

    2016-06-01

    Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  14. What rainfall events trigger landslides on the West Coast US?

    Science.gov (United States)

    Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

    2016-04-01

    A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

  15. NEXRAD Rainfall Data: Eureka, California

    Data.gov (United States)

    National Aeronautics and Space Administration — Next-Generation Radar (NEXRAD) Weather Surveillance Radar 1988 (WSR-88D) measurements were used to support AMSR-E rainfall validation efforts in Eureka, California,...

  16. Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

    Science.gov (United States)

    Muhammed, B. U.; Kaduk, J.; Balzter, H.

    2012-12-01

    In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

  17. Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

    Directory of Open Access Journals (Sweden)

    K C Gouda

    2017-10-01

    Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

  18. frequency analysis of rainfall for flood control in patani, delta state

    African Journals Online (AJOL)

    user

    The Niger Delta Region of Nigeria is within the mangrove forest region and is crisscrossed by ... especially in Forcados, some oil wells have been lost to ... rainfall depths and the assessment of the rarity of .... hydrological data shows that peak rainfall occurs around .... magnitude and as output the observed maximum rainfall.

  19. Long range prediction of Indian summer monsoon rainfall

    Indian Academy of Sciences (India)

    to the performance of summer monsoon rain- fall over India. Variations in the total amount of rainfall have strong socio-economic consequences. Parthasarathy et al .... deviation of rainfall for training period 1961–1995, are 838.4 mm and 89.3 mm respectively. The period. 1949–1960 and 1996–2005 is used for independent.

  20. How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands.

    Science.gov (United States)

    Cobb, Alexander R; Hoyt, Alison M; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su'ut, Nur Salihah; Harvey, Charles F

    2017-06-27

    Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage.

  1. How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands

    Science.gov (United States)

    Hoyt, Alison M.; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su’ut, Nur Salihah; Harvey, Charles F.

    2017-01-01

    Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage. PMID:28607068

  2. Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

    Science.gov (United States)

    Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

    2018-01-01

    Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

  3. Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

    Science.gov (United States)

    Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

  4. Analysis of rainfall-induced shallow landslides and debris flows in the Eastern Pyrenees

    Science.gov (United States)

    Portilla Gamboa, M.; Hürlimann, M.; Corominas, J.

    2009-09-01

    The inventory of rainfall-induced mass movements, rainfall data, and slope characteristics are considered the basis of the analysis determining appropriate rainfall thresholds for mass movements in a specific region. The rainfall-induced landslide thresholds established in the literature for the Catalan Pyrenees have been formulated referring to the rainfall events of November 1982, September 1992, December 1997, and others occurred after 1999. It has been shown that a rainfall intensity greater than 190 mm in 24 hours without antecedent rainfall would be necessary to produce mass movements (Corominas and Moya, 1999; Corominas et al, 2002) or 51mm in 24h with 61 mm of accumulated rainfall (Marco, 2007). Short duration-high intensity rainfalls have brought about several mass movements in some Catalonian regions throughout the course of twenty-first century (Berga, Bonaigua, Saldes, Montserrat, Port-Ainé, Riu Runer, and Sant Nicolau). Preliminary analysis of these events shows that it is necessary to review the thresholds defined so far and redo the existing inventory of mass movements for the Catalan Pyrenees. The present work shows the usefulness of aerial photographs in the reconstruction of the inventory of historic mass movements (Molló-Queralbs, 1940; Arties-Vielha, 1963; Barruera-Senet, 1940 and 1963, and Berga-Cercs, 1982, 1997 and 2008). Also, it highlights the treatment given to scarce and scattered rainfall data available inside these Catalonia’s regions, and the application of Geographic Information Systems (ArcGIS) in the management of the gathered information. The results acquired until now show that the historic rainfall events occurred in the Eastern Pyrenees have yielded many more mass movements than those reported in the literature. Besides, it can be said that the thresholds formulated for the Pyrenees are valid for longstanding regional rainfalls, and not for local downpours. In the latter cases it should be necessary to take into account the

  5. Rainfall simulation experiments in the Southwestern USA using the Walnut Gulch rainfall simulator

    Science.gov (United States)

    The dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semi-arid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30% of the plots simulations were conducted up to five time...

  6. Understanding extreme rainfall events in Australia through historical data

    Science.gov (United States)

    Ashcroft, Linden; Karoly, David John

    2016-04-01

    Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

  7. TRMM Applications for Rainfall-Induced Landslide Early Warning

    Science.gov (United States)

    Dok, A.; Fukuoka, H.; Hong, Y.

    2012-04-01

    Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall

  8. A method for predicting monthly rainfall patterns

    International Nuclear Information System (INIS)

    Njau, E.C.

    1987-11-01

    A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

  9. Rainfall Climatology over Asir Region, Saudi Arabia

    Science.gov (United States)

    Sharif, H.; Furl, C.; Al-Zahrani, M.

    2012-04-01

    Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

  10. Water storage and evaporation as constituents of rainfall interception

    NARCIS (Netherlands)

    Klaassen, W; Bosveld, F; de Water, E

    1998-01-01

    Intercepted rainfall may be evaporated during or after the rain event. Intercepted rain is generally determined as the difference between rainfall measurements outside and inside the forest. Such measurements are often used to discriminate between water storage and evaporation during rain as well.

  11. Effects of Rainfall Characteristics on the Stability of Tropical Residual Soil Slope

    OpenAIRE

    Rahardjo Harianto; Satyanaga Alfrendo; Leong Eng Choon

    2016-01-01

    Global climate change has a significant impact on rainfall characteristics, sea water level and groundwater table. Changes in rainfall characteristics may affect stability of slopes and have severe impacts on sustainable urban living. Information on the intensity, frequency and duration of rainfall is often required by geotechnical engineers for performing slope stability analyses. Many seepage analyses are commonly performed using the most extreme rainfall possible which is uneconomical in d...

  12. Research on the Relationship between Landslide of Farming Terraces and the Intensity of Rainfall and Slope Angle Based on the Indoor Rainfall Slide Slope Model

    Directory of Open Access Journals (Sweden)

    Dongqin Chen

    2016-03-01

    Full Text Available Due to the increase of geographical disaster in China, it is necessary to study the formation mechanism to make a preparation for the future prevention of geological disasters and effectively reduce the unnecessary financial loss and casualties. We found there is a powerful connection between heavy rainfall and landslide slope. Thus, this article takes the accumulation of gravel soil as the research material to set up indoor rainfall and landslide model test. By comparing the rules of pore water pressure and soil pressure responding to different rainfall intensity and slope angle, we discussed over the effects of rainfall intensity and slope angle on the sliding of accumulation gravelly soil.

  13. Rainfall distribution and change detection across climatic zones in Nigeria

    OpenAIRE

    Stephen Bunmi Ogungbenro; Tobi Eniolu Morakinyo

    2014-01-01

    Nigerian agriculture is mainly rain-fed and basically dependent on the vagaries of weather especially rainfall. Nigeria today has about forty-four (44) weather observation stations which provide measurement of rainfall amount for different locations across the country. Hence, this study investigates change detection in rainfall pattern over each climatic zone of Nigeria. Data were collected for 90 years (1910–1999) period for all the weather observation stations in Nigeria, while a subdivisio...

  14. The Impact of Amazonian Deforestation on Dry-Season Rainfall

    Science.gov (United States)

    Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming; Surratt, Jason; Starr, David OC. (Technical Monitor)

    2002-01-01

    Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

  15. Saturated and unsaturated stability analysis of slope subjected to rainfall infiltration

    Directory of Open Access Journals (Sweden)

    Gofar Nurly

    2017-01-01

    Full Text Available This paper presents results of saturated and unsaturated stability analysis of typical residual slopes subjected to rainfall infiltration corresponds to 50 years rainfall return period. The slope angles considered were 45° and 70°. The saturated stability analyses were carried out for original and critical ground water level commonly considered by practicing engineer. The analyses were conducted using limit equilibrium method. Unsaturated stability analyses used combination of coupled stress–pore-water pressure analysis to evaluate the effect of rainfall infiltration on the deformation and transient pore-water pressure on slope stability. Slope stability analyses were performed at some times during and after rainfall infiltration. Results show that the critical condition for slope made by sandy material was at the end of rainfall while for clayey material was at some specified times after the rainfall ceased. Unsaturated stability analysis on sandy soil gives higher factor of safety because the soil never reached saturation. Transient analysis using unsaturated soil concept could predict more critical condition of delayed failure of slopes made up of clayey soil.

  16. Rainfall is a risk factor for sporadic cases of Legionella pneumophila pneumonia.

    Directory of Open Access Journals (Sweden)

    Carolina Garcia-Vidal

    Full Text Available It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011. Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5% had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases, antigenuria (206 and serology (98. Daily rainfall average was 0.556 liters/m(2 in the Legionella pneumonia group vs. 0.328 liters/m(2 for non-Legionella pneumonia cases (p = 0.04. A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54. Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03. Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003. No relationship was found between rainfall average and non-Legionella pneumonia cases (-0.06; p = 0.24. As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

  17. Characteristics of rainfall triggering of debris flows in the Chenyulan watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    J. C. Chen

    2013-04-01

    Full Text Available This paper reports the variation in rainfall characteristics associated with debris flows in the Chenyulan watershed, central Taiwan, between 1963 and 2009. The maximum hourly rainfall Im, the maximum 24 h rainfall Rd, and the rainfall index RI (defined as the product RdIm were analysed for each rainfall event that triggered a debris flow within the watershed. The corresponding number of debris flows initiated by each rainfall event (N was also investigated via image analysis and/or field investigation. The relationship between N and RI was analysed. Higher RI of a rainfall event would trigger a larger number of debris flows. This paper also discusses the effects of the Chi-Chi earthquake (CCE on this relationship and on debris flow initiation. The results showed that the critical RI for debris flow initiation had significant variations and was significantly lower in the years immediately following the CCE of 1999, but appeared to revert to the pre-earthquake condition about five years later. Under the same extreme rainfall event of RI = 365 cm2 h−1, the value of N in the CCE-affected period could be six times larger than that in the non-CCE-affected periods.

  18. Some analysis on the diurnal variation of rainfall over the Atlantic Ocean

    Science.gov (United States)

    Gill, T.; Perng, S.; Hughes, A.

    1981-01-01

    Data collected from the GARP Atlantic Tropical Experiment (GATE) was examined. The data were collected from 10,000 grid points arranged as a 100 x 100 array; each grid covered a 4 square km area. The amount of rainfall was measured every 15 minutes during the experiment periods using c-band radars. Two types of analyses were performed on the data: analysis of diurnal variation was done on each of grid points based on the rainfall averages at noon and at midnight, and time series analysis on selected grid points based on the hourly averages of rainfall. Since there are no known distribution model which best describes the rainfall amount, nonparametric methods were used to examine the diurnal variation. Kolmogorov-Smirnov test was used to test if the rainfalls at noon and at midnight have the same statistical distribution. Wilcoxon signed-rank test was used to test if the noon rainfall is heavier than, equal to, or lighter than the midnight rainfall. These tests were done on each of the 10,000 grid points at which the data are available.

  19. Analysis of Spatiotemporal Statistical Properties of Rainfall in the Phoenix Metropolitan Area

    Science.gov (United States)

    Mascaro, G.

    2016-12-01

    The analysis of the rainfall statistical properties at multiple spatiotemporal scales is a necessary preliminary step to support modeling of urban hydrology, including flood prediction and simulation of impacts of land use changes. In this contribution, the rainfall statistical properties are analyzed in the Phoenix Metropolitan area and its surroundings ( 29600 km2) in Arizona using observations from 310 gauges of the Flood Control District of the Maricopa County network. Different techniques are applied to investigate the rainfall properties at temporal scales from 1 min to years and to quantify the associated spatial variability. Results reveal the following. The rainfall regime is characterized by high interannual variability, which is partially explained by teleconnections with El Niño Southern Oscillation, and marked seasonality, with two maxima in the monsoon season from July to September and in winter from November to March. Elevation has a significant control on seasonal rainfall accumulation, strength of thermal convective activity during the monsoon, and peak occurrence of the rainfall diurnal cycle present in summer. The spatial correlation of wintertime rainfall is high even at short aggregation times (cells).

  20. Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

    Science.gov (United States)

    Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

    2018-02-01

    There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of

  1. Spatial Interpolation of Rainfall Erosivity Using Artificial Neural Networks for Southern Brazil Conditions

    Directory of Open Access Journals (Sweden)

    Michel Castro Moreira

    Full Text Available ABSTRACT Water erosion is the process of disaggregation and transport of sediments, and rainfall erosivity is a numerical value that expresses the erosive capacity of rain. The scarcity of information on rainfall erosivity makes it difficult or impossible to use to estimate losses occasioned by the erosive process. The objective of this study was to develop Artificial Neural Networks (ANNs for spatial interpolation of the monthly and annual values of rainfall erosivity at any location in the state of Rio Grande do Sul, and a software that enables the use of these networks in a simple and fast manner. This experiment used 103 rainfall stations in Rio Grande do Sul and their surrounding area to generate synthetic rainfall series on the software ClimaBR 2.0. Rainfall erosivity was determined by summing the values of the EI30 and KE >25 indexes, considering two methodologies for obtaining the kinetic energy of rainfall. With these values of rainfall erosivity and latitude, longitude, and altitude of the stations, the ANNs were trained and tested for spatializations of rainfall erosivity. To facilitate the use of the ANNs, a computer program was generated, called netErosividade RS, which makes feasible the use of ANNs to estimate the values of rainfall erosivity for any location in the state of Rio Grande do Sul.

  2. A stochastic assessment of the effect of global warming on rainfall ...

    African Journals Online (AJOL)

    Crop production depends on rainfall, and rainfall is affected by extreme weather conditions. Markov chain and time series model are adapted for the study of the pattern of rainfall in the North Central Region of Nigeria. Results reveal the long run distributions of the dry and wet days to be 0.7841, and 0.2159 respectively.

  3. Evaluating the Effect of Rainfall Infiltration on the Slope Stability of T16 tower of Taipei Mao-kong Gondola by Numerical Methods

    Science.gov (United States)

    RUNG, J.

    2013-12-01

    In this study, a series of rainfall-stability analyses were performed to simulate the failure mechanism and the function of remediation works of the down slope of T-16 tower pier, Mao-Kong gondola (or T-16 Slope) at the hillside of Taipei City using two-dimensional finite element method. The failure mechanism of T-16 Slope was simulated using the rainfall hyetograph of Jang-Mi typhoon in 2008 based on the field investigation data, monitoring data, soil/rock mechanical testing data and detail design plots of remediation works. Eventually, the numerical procedures and various input parameters in the analysis were verified by comparing the numerical results with the field observations. In addition, 48 hrs design rainfalls corresponding to 5, 10, 25 and 50 years return periods were prepared using the 20 years rainfall data of Mu-Zha rainfall observation station, Central Weather Bureau for the rainfall-stability analyses of T-16 Slope to inspect the effect of the compound stabilization works on the overall stability of the slope. At T-16 Slope, without considering the longitudinal and transverse drainages on the ground surface, there totally 4 types of stabilization works were installed to stabilize the slope. From the slope top to the slope toe, the stabilization works of T-16 Slope consists of RC-retaining wall with micro-pile foundation at the up-segment, earth anchor at the up-middle-segment, soil nailing at the middle-segment and retaining pile at the down-segment of the slope. The effect of each individual stabilization work on the slope stability under rainfall condition was examined and evaluated by raising field groundwater level.

  4. Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

    Science.gov (United States)

    Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

    2016-09-01

    The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rain rate. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e., RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance but also for use in hydrological modeling. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.

  5. Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

    OpenAIRE

    Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

  6. Correlations between the air pollution and the rainfall composition in Jiului Valley area

    Directory of Open Access Journals (Sweden)

    Traistă Eugen

    2003-09-01

    Full Text Available Rainfall composition is conditional on the air quality. If the air is polluted, the rainfall will be also polluted. In fact, rainfall contains the same compounds like the air as nitrites, nitrates, sulphites, sulphates, ammonia etc. Some cations like calcium, magnesium, sodium and potassium are present in rainfall because of dust. This paper presents the air qualities and the soil composition influenced by the rainfall in one of the most polluted mining areas from our country, Jiului Valley.

  7. Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

    Science.gov (United States)

    Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

    2012-04-01

    During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

  8. Linking landscape structure and rainfall runoff behaviour in a thermodynamic optimality context

    Science.gov (United States)

    Zehe, Erwin; Ehret, Uwe; Blume, Theresa; Kleidon, Axel; Scherer, Ulrike; Westhoff, Martijn

    2015-04-01

    order polynomial of the wetting rate, which depends on macropore density, the slope of the soil water retention curve, topography and depth to groundwater. An uncalibrated long term simulation of the water balance of the 3.5 km² Weiherbach catchment based on the first optimum macroporosity performed almost as well as the best fit when macroporosity was calibrated to match rainfall runoff. In the other regime called potential- or p-regime, free energy dynamics of soil water is dominated by changes in its potential energy, which applies to non-cohesive soils and a pronounced topography. Soil wetting during rainfall in the p-regime implies to push the system away from LTE. This can be compensated by preferential pathways which connect directly to the riparian zone or the groundwater body, because these drainage structures enhance export of potential energy from the critical zone. However, in the p-regime no local optimum exists because potential energy reduction rates scale linearly with the drainage rate (there is at best an optimum at the margin of the parameter space). Nevertheless, in this case one can define a "distinguished" density of vertical and lateral preferential flow paths that assures steady state conditions of the potential energy balance of the soil. This applies when average storage of potential energy is compensated by average potential export . When applying this idea to the Mallalcahuello catchment in Chile model, which is characterized by non-cohesive soils, high annual rainfall and steep terrain, simulations performed close to the value that yielded the best fit of rainfall runoff behaviour obtained during a calibration exercise. Secondly this idea allowed a robust a priory estimate of the annual runoff coefficient in accordance with long term observations.

  9. TEMPORAL AND SPATIAL ANALYSIS OF EXTREME RAINFALL ON THE SLOPE AREA OF MT. MERAPI

    Directory of Open Access Journals (Sweden)

    Dhian Dharma Prayuda

    2015-02-01

    Full Text Available Rainfall has temporal and spatial characteristics with certain pattern which are affected by topographic variations and climatology of an area. The intensity of extreme rainfall is one of important characteristics related to the trigger factors for debris flow. This research will discuss the result of analysis on short duration rainfall data in the south and west slope of Mt. Merapi. Measured hourly rainfall data in 14 rainfall stations for the last 27 years were used as analysis input. The rainfall intensity-duration-frequency relationship (IDF was derived using empirical formula of Sherman, Kimijima, Haspers, and Mononobe method. The analysis on the characteristics of extreme rainfall intensity was performed by conducting spatial interpolation using Inverse Distance Weighted (IDW method. Result of analysis shows that IDF of rainfall in the research area fits to Sherman’s formula. Besides, the spatial distribution pattern of maximum rainfall intensity was assessed on the basis of area rainfall. Furthermore, the difference on the result of spatial map for one hour extreme rainfall based on isolated event and non-isolated event method can be evaluated. The result of this preliminary research is expected to be inputs in the establishment of debris flow early warning in Mt. Merapi slope area.

  10. Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

    Science.gov (United States)

    Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

    2017-10-01

    This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

  11. Application of the rainfall infiltration breakthrough (RIB) model for ...

    African Journals Online (AJOL)

    Application of the rainfall infiltration breakthrough (RIB) model for groundwater recharge estimation in west coastal South Africa. ... the data from Oudebosch with different rainfall and groundwater abstraction inputs are simulated to explore individual effects on water levels as well as recharge rate estimated on a daily basis.

  12. Scale invariance properties of rainfall in AMMA-CATCH observatory ...

    African Journals Online (AJOL)

    1International Chair in Physics Mathematics and Applications (CIPMA-Chair Unesco) , University of .... modeling the distribution of rainfall intensities, in time and space. There is particular lack of knowledge about rainfall variability at different scales [1].The knotty problem of .... Lovejoy [6] have provided the definition of.

  13. A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

    Science.gov (United States)

    Bhattacharjya, Rajib Kumar

    2018-05-01

    The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

  14. Effect of Variations in Long-Duration Rainfall Intensity on Unsaturated Slope Stability

    OpenAIRE

    Hsin-Fu Yeh; Yi-Jin Tsai

    2018-01-01

    In recent years, many scientific methods have been used to prove that the Earth’s climate is changing. Climate change can affect rainfall patterns, which can in turn affect slope safety. Therefore, this study analyzed the effects of climate change on rainfall patterns from the perspective of rainfall intensity. This analysis was combined with numerical model analysis to examine the rainfall patterns of the Zengwen reservoir catchment area and its effects on slope stability. In this study, the...

  15. Downscaling of rainfall in Peru using Generalised Linear Models

    Science.gov (United States)

    Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.

    2012-04-01

    The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the downscaling model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim downscaling model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim downscaling model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.

  16. Reclaimed mineland curve number response to temporal distribution of rainfall

    Science.gov (United States)

    Warner, R.C.; Agouridis, C.T.; Vingralek, P.T.; Fogle, A.W.

    2010-01-01

    The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound. ?? 2010 American Water Resources Association.

  17. Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

    Science.gov (United States)

    Chang, P.; Saravanan, R.; Giannini, A.

    2003-04-01

    The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

  18. Stochastic bias-correction of daily rainfall scenarios for hydrological applications

    Directory of Open Access Journals (Sweden)

    I. Portoghese

    2011-09-01

    Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.

    In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.

  19. Developing Methods For Linking Surficial Aquifers With Localized Rainfall Data

    Science.gov (United States)

    Lafrenz, W. B.; van Gaalen, J. F.

    2008-12-01

    Water level hydrographs of the surficial aquifer can be evaluated to identify both the cause and consequence of water supply development. Rainfall, as a source of direct recharge and as a source of delayed or compounded recharge, is often the largest influence on surficial aquifer water level responses. It is clear that proximity of the rain gauge to the observation well is a factor in the degree of correlation, but in central Florida, USA, rainfall patterns change seasonally, with latitude, and with distance from the coast . Thus, for a location in central Florida, correlation of rain events with observed hydrograph responses depends on both distance and direction from an observation well to a rain gauge. In this study, we examine the use of extreme value analysis as a method of selecting the best rainfall data set for describing a given surficial aquifer monitor well. A surficial aquifer monitor well with a substantial suite of data is compared to a series of rainfall data sets from gauges ranging from meters to tens of kilometers in distance from the monitor well. The gauges vary in a wide range of directions from the monitor well in an attempt to identify both a method for rainfall gauge selection to be associated with the monitor well. Each rainfall gauge is described by a correlation coefficient with respect to the surficial aquifer water level data.

  20. Convective Cloud and Rainfall Processes Over the Maritime Continent: Simulation and Analysis of the Diurnal Cycle

    Science.gov (United States)

    Gianotti, Rebecca L.

    The Maritime Continent experiences strong moist convection, which produces significant rainfall and drives large fluxes of heat and moisture to the upper troposphere. Despite the importance of these processes to global circulations, current predictions of climate change over this region are still highly uncertain, largely due to inadequate representation of the diurnally-varying processes related to convection. In this work, a coupled numerical model of the land-atmosphere system (RegCM3-IBIS) is used to investigate how more physically-realistic representations of these processes can be incorporated into large-scale climate models. In particular, this work improves simulations of convective-radiative feedbacks and the role of cumulus clouds in mediating the diurnal cycle of rainfall. Three key contributions are made to the development of RegCM3-IBIS. Two pieces of work relate directly to the formation and dissipation of convective clouds: a new representation of convective cloud cover, and a new parameterization of convective rainfall production. These formulations only contain parameters that can be directly quantified from observational data, are independent of model user choices such as domain size or resolution, and explicitly account for subgrid variability in cloud water content and nonlinearities in rainfall production. The third key piece of work introduces a new method for representation of cloud formation within the boundary layer. A comprehensive evaluation of the improved model was undertaken using a range of satellite-derived and ground-based datasets, including a new dataset from Singapore's Changi airport that documents diurnal variation of the local boundary layer height. The performance of RegCM3-IBIS with the new formulations is greatly improved across all evaluation metrics, including cloud cover, cloud liquid water, radiative fluxes and rainfall, indicating consistent improvement in physical realism throughout the simulation. This work

  1. Erosivity of rainfall in Lages, Santa Catarina, Brazil

    Directory of Open Access Journals (Sweden)

    Jefferson Schick

    2014-12-01

    Full Text Available The erosive capacity of rainfall can be expressed by an index and knowing it allows recommendation of soil management and conservation practices to reduce water erosion. The objective of this study was to calculate various indices of rainfall erosivity in Lages, Santa Catarina, Brazil, identify the best one, and discover its temporal distribution. The study was conducted at the Center of Agricultural and Veterinary Sciences, Lages, Santa Catarina, using daily rainfall charts from 1989 to 2012. Using the computer program Chuveros , 107 erosivity indices were obtained, which were based on maximum intensity in 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 70, 80, 90, 100, 110, 120, 135, 150, 165, 180, 210, and 240 min of duration and on the combination of these intensities with the kinetic energy obtained by the equations of Brown & Foster, Wagner & Massambani, and Wischmeier & Smith. The indices of the time period from 1993 to 2012 were correlated with the respective soil losses from the standard plot of the Universal Soil Loss Equation (USLE in order to select the erosivity index for the region. Erosive rainfall accounted for 83 % of the mean annual total volume of 1,533 mm. The erosivity index (R factor of rainfall recommended for Lages is the EI30, whose mean annual value is 5,033 MJ mm ha-1 h-1, and of this value, 66 % occurs from September to February. Mean annual erosivity has a return period estimated at two years with a 50 % probability of occurrence.

  2. Modeling rainfall-runoff relationship using multivariate GARCH model

    Science.gov (United States)

    Modarres, R.; Ouarda, T. B. M. J.

    2013-08-01

    The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

  3. [Infiltration characteristics of soil water on loess slope land under intermittent and repetitive rainfall conditions].

    Science.gov (United States)

    Li, Yi; Shao, Ming-An

    2008-07-01

    Based on the experiments of controlled intermittent and repetitive rainfall on slope land, the infiltration and distribution characteristics of soil water on loess slope land were studied. The results showed that under the condition of intermittent rainfall, the cumulative runoff during two rainfall events increased linearly with time, and the wetting front also increased with time. In the interval of the two rainfall events, the wetting front increased slowly, and the infiltration rate was smaller on steeper slope than on flat surface. During the second rainfall event, there was an obvious decreasing trend of infiltration rate with time. The cumulative infiltration on 15 degrees slope land was larger than that of 25 degrees slope land, being 178 mm and 88 mm, respectively. Under the condition of repetitive rainfall, the initial infiltration rate during each rainfall event was relatively large, and during the first rainfall, both the infiltration rate and the cumulative infiltration at various stages were larger than those during the other three rainfall events. However, after the first rainfall, there were no obvious differences in the infiltration rate among the next three rainfall events. The more the rainfall event, the deeper the wetting front advanced.

  4. Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

    International Nuclear Information System (INIS)

    Reddy, R.S.; Mukherjee, B.K.; Ramana Murty, Bh.V.

    1976-01-01

    An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant. (author)

  5. Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, R S; Mukherjee, B K; Ramana Murty, Bh V [Indian Inst. of Tropical Meteorology, Pune

    1976-12-01

    An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant.

  6. Predictability of Seasonal Rainfall over the Greater Horn of Africa

    Science.gov (United States)

    Ngaina, J. N.

    2016-12-01

    The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the

  7. PDS-Modelling and Regional Bayesian Estimation of Extreme Rainfalls

    DEFF Research Database (Denmark)

    Madsen, Henrik; Rosbjerg, Dan; Harremoës, Poul

    1994-01-01

    rainfalls. The method is applied to two variables: the total precipitation depth and the maximum 10-minute rain intensity of individual storms. On the basis of the atsite modelling a regional analysis is carried out. It is shown that the previous assumption of spatial homogeneity of extreme rainfalls...

  8. Gridded daily Indian monsoon rainfall for 14 seasons: Merged ...

    Indian Academy of Sciences (India)

    Indian monsoon is an important component of earth's climate system. Daily rainfall data for longer period is vital to study components and processes related to Indian monsoon. Daily observed gridded rainfall data covering both land and adjoining oceanic regions are required for numerical model vali- dation and model ...

  9. Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

    Science.gov (United States)

    Haberlandt, U.; Radtke, I.

    2014-01-01

    Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the

  10. Soil erodibility variability in laboratory and field rainfall simulations

    Science.gov (United States)

    Szabó, Boglárka; Szabó, Judit; Jakab, Gergely; Centeri, Csaba; Szalai, Zoltán

    2017-04-01

    Rainfall simulation experiments are the most common way to observe and to model the soil erosion processes in in situ and ex situ circumstances. During modelling soil erosion, one of the most important factors are the annual soil loss and the soil erodibility which represent the effect of soil properties on soil loss and the soil resistance against water erosion. The amount of runoff and soil loss can differ in case of the same soil type, while it's characteristics determine the soil erodibility factor. This leads to uncertainties regarding soil erodibility. Soil loss and soil erodibility were examined with the investigation of the same soil under laboratory and field conditions with rainfall simulators. The comparative measurement was carried out in a laboratory on 0,5 m2, and in the field (Shower Power-02) on 6 m2 plot size where the applied slope angles were 5% and 12% with 30 and 90 mm/h rainfall intensity. The main idea was to examine and compare the soil erodibility and its variability coming from the same soil, but different rainfall simulator type. The applied model was the USLE, nomograph and other equations which concern single rainfall events. The given results show differences between the field and laboratory experiments and between the different calculations. Concerning for the whole rainfall events runoff and soil loss, were significantly higher at the laboratory experiments, which affected the soil erodibility values too. The given differences can originate from the plot size. The main research questions are that: How should we handle the soil erodibility factors and its significant variability? What is the best solution for soil erodibility determination?

  11. Multivariate analysis applied to monthly rainfall over Rio de Janeiro state, Brazil

    Science.gov (United States)

    Brito, Thábata T.; Oliveira-Júnior, José F.; Lyra, Gustavo B.; Gois, Givanildo; Zeri, Marcelo

    2017-10-01

    Spatial and temporal patterns of rainfall were identified over the state of Rio de Janeiro, southeast Brazil. The proximity to the coast and the complex topography create great diversity of rainfall over space and time. The dataset consisted of time series (1967-2013) of monthly rainfall over 100 meteorological stations. Clustering analysis made it possible to divide the stations into six groups (G1, G2, G3, G4, G5 and G6) with similar rainfall spatio-temporal patterns. A linear regression model was applied to a time series and a reference. The reference series was calculated from the average rainfall within a group, using nearby stations with higher correlation (Pearson). Based on t-test ( p River (G5) and the metropolitan area of the city of Rio de Janeiro (G6). The driest months in all regions were June, July and August, while November, December and January were the rainiest months. Sharp transitions occurred when considering monthly accumulated rainfall: from January to February, and from February to March, likely associated with episodes of "veranicos", i.e., periods of 4-15 days of duration with no rainfall.

  12. Effect of confinement area on production, physiological parameters ...

    African Journals Online (AJOL)

    Cows in the small camp stood for longer periods (P < 0.01) to avoid lying down in wet areas. Cows in the large camp spent more time (P < 0.01) lying down. Although no difference in production parameters was observed in both trials, an earthen mound and camps of at least 100 m2/cow may be necessaryin high rainfall ...

  13. Seasonal variation of meteorological factors on air parameters and ...

    African Journals Online (AJOL)

    user

    Onna. Air quality parameters (Cl-, SPM and SO2) were found to have positive correlation with vapour pressure, humidity and rainfall values in the study areas. It was also established that a positive correlation exits between NO2, H2S, SO2, SPM, chloride, carbon monoxide and wind speed relative humidity, temperature and ...

  14. Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method

    Directory of Open Access Journals (Sweden)

    Yuhan Jia

    2017-01-01

    Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.

  15. Rainfall characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

    Science.gov (United States)

    Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

    2018-02-01

    The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

  16. Analysis of Rainfall Variations and Trends in Coastal Tanzania

    African Journals Online (AJOL)

    Ocean Dipole, Pacific Decadal Oscillation ... island of Mafia receives the highest amount of rainfall (1879 mm p.a.) while Kilwa. Masoko receives the ... However, the effects of the Pacific .... an important role in terrestrial and marine .... and ENSO, the largest coefficient being .... rainfall on the small islands of Southeast Asia.

  17. Fractal analysis of rainfall occurrence observed in the synoptic ...

    African Journals Online (AJOL)

    Fractal analysis is important for characterizing and modeling rainfall's space-time variations in hydrology. The purpose of this study consists on determining, in a mono-fractal framework, the scale invariance of rainfall series in Benin synopticstations located in two main geographical area: Cotonou, Bohicon , Savè in a sub ...

  18. Seasonal rainfall predictability over the Lake Kariba catchment area ...

    African Journals Online (AJOL)

    Retroactive forecasts are produced for lead times of up to 5 months and probabilistic forecast performances evaluated for extreme rainfall thresholds of the 25th and 75th percentile values of the climatological record. The verification of the retroactive forecasts shows that rainfall over the catchment is predictable at extended ...

  19. Influence of atmospheric rainfall to γ radiation Kerma rate in surface air

    International Nuclear Information System (INIS)

    Xu Zhe; Wan Jun; Yu Rongsheng

    2009-01-01

    Objective: To investigate the influence rule of the atmospheric Rainfall to the γ radiation Kerma rate in surface air in order to revise the result of its measurement during rainfall. Methods: The influence factors of rainfall to the measurement of the γ radiation Kerma rate in air were analyzed and then the differential equation of the correlation factors was established theoretically, and by resolving the equation, the mathematical model Was obtained. The model was discussed through several practical examples. Results: The mathematical model was coincided with the tendency of curve about the measured data on the influence rule of rainfall to the γ radiation Kerma rate in surface air. Conclusion: By using the theoretical formula in this article which is established to explain the relationship between the rainfall and the γ radiation Kerma rate in surface air, the influence of rainfall to the γ radiation Kerma rate in surface air could be correctly revised. (authors)

  20. A Cumulative Rainfall Function for Subhourly Design Storm in Mediterranean Urban Areas

    Directory of Open Access Journals (Sweden)

    Marco Carbone

    2015-01-01

    Full Text Available Design storms are very useful in many hydrological and hydraulic practices and are obtained from statistical analysis of precipitation records. However considering design storms, which are often quite unlike the natural rainstorms, may result in designing oversized or undersized drainage facilities. For these reasons, in this study, a two-parameter double exponential function is proposed to parameterize historical storm events. The proposed function has been assessed against the storms selected from 5-year rainfall time series with a 1-minute resolution, measured by three meteorological stations located in Calabria, Italy. In particular, a nonlinear least square optimization has been used to identify parameters. In previous studies, several evaluation methods to measure the goodness of fit have been used with excellent performances. One parameter is related to the centroid of the rain distribution; the second one is related to high values of the standard deviation of the kurtosis for the selected events. Finally, considering the similarity between the proposed function and the Gumbel function, the two parameters have been computed with the method of moments; in this case, the correlation values were lower than those computed with nonlinear least squares optimization but sufficiently accurate for designing purposes.