Sample records for rdsd rainfall parameters

  1. Calibration of Rainfall-Runoff Parameters in Peatlands

    Walle Menberu, Meseret; Torabi Haghighi, Ali; Kløve, Bjørn


    Finland is a country where its possession of peatlands compared to the total surface area of the country puts in the leading categories globally in peatland possession having 33.5% of its total land area covered with peatlands. Recent interest has grown in using peatlands as temporary flood control barriers by taking advantage of the high water holding capacity of peat soils. Water holding capacity of peat soils enables to reduce high rate of runoff and peak flow which might endanger downstream of the flow and in the process of doing that, the rest of the water leaving the peatland areas is less polluted due to the wetlands' potential in purifying polluted water. Therefore, in order to understand how capable enough peatlands are in holding water by reducing the peak flow or slowing down the rate of runoff, this paper analyses the rainfall-runoff phenomena in peatland catchments through important runoff parameters. Among the most important runoff parameters; the initial abstraction, the curve number and lag time are selected for this paper due to their highest impact on rainfall-runoff process. For this study, two peatland catchments of drained and pristine are selected. Managing to explain the initial abstraction and curve number behaviour in the catchments will able to clearly understand and as well predict the rainfall-runoff process in the catchments. In the selected study sites, observed rainfall and runoff data are collected. The study sites are modelled with the help of Arc-GIS and Hec-GeoHMS and from that are exported to HEC-HMS (Hydrologic modelling software) for rainfall-runoff analysis. The two important parameters; the initial abstraction and curve number are used to calibrate the model. And finally, the parameters that have given the best fit between the modelled and observed rainfall-runoff process are suggested for the study sites. Having these parameters estimated eases to understand rainfall-runoff process in the catchments for whatsoever purpose

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

    José Eduardo Macedo Pezzopane


    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.

  3. Analysis of Physical Quantities and Radar Parameters about Hail Shooting and Heavy Convective Rainfall


    [Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ~(3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows: VIL value reaches 35 kg/m2 (May), 43 kg/m2 (June and July), the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km (May), 4.3 km (June) and 5.5 km (July); VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.

  4. Optimal parameters for the Green-Ampt infiltration model under rainfall conditions

    Chen Li


    Full Text Available The Green-Ampt (GA model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations has not been studied extensively. We compared calculated rainfall infiltration results for various soils obtained using existing GA parameterizations with those obtained by solving the Richards equation for variably saturated flow. Results provided an overview of GA model performance evaluated by means of a root-meansquare- error-based objective function across a large region in GA parameter space as compared to the Richards equation, which showed a need for seeking optimal GA parameters. Subsequent analysis enabled the identification of optimal GA parameters that provided a close fit with the Richards equation. The optimal parameters were found to substantially outperform the standard theoretical parameters, thus improving the utility and accuracy of the GA model for infiltration simulations under rainfall conditions. A sensitivity analyses indicated that the optimal parameters may change for some rainfall scenarios, but are relatively stable for high-intensity rainfall events.

  5. Parameter estimation in stochastic rainfall-runoff models

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


    the parameters, including the noise terms. The parameter estimation method is a maximum likelihood method (ML) where the likelihood function is evaluated using a Kalman filter technique. The ML method estimates the parameters in a prediction error settings, i.e. the sum of squared prediction error is minimized....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... 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. Regionalization parameters of conceptual rainfall-runoff model

    Osuch, M.


    Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.

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

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


    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.

  8. Conditioning rainfall-runoff model parameters to reduce prediction uncertainty in ungauged basins

    Visessri, S.; McIntyre, N.; Maksimovic, C.


    Conditioning rainfall-runoff model parameters in ungauged catchments in Thailand presents problems common to ungauged basins involving data availability, data quality, and rainfall-runoff model suitability, which all contribute to prediction uncertainty. This paper attempts to improve the estimation of streamflow in ungauged basins and reduce associated uncertainties using the approaches of conditioning the prior parameter space. 35 catchments from the upper Ping River basin, Thailand are selected as a case study. The catchments have a range of attributes e.g. catchment sizes 20-6350 km2, elevations 632-1529 m above sea level. and annual rainfall 846-1447 mm/year. For each catchment, three indices - rainfall-runoff elasticity, base flow index and runoff coefficient - are calculated using the observed rainfall-runoff data and regression equations relating these indices to the catchment attributes are identified. Uncertainty in expected indices is defined by the regression error distribution, approximated by a Gaussian model. The IHACRES model is applied for simulating streamflow. The IHACRES parameters are randomly sampled from their presumed prior parameter space. For each sampled parameter set, the streamflow and hence the three indices are modelled. The parameter sets are conditioned on the probability distributions of the regionalised indices, allowing ensemble predictions to be made. The objective function, NSE, calculated for daily and weekly time steps from the water years 1995-2000, is used to assess model performance. Ability to capture observed streamflow and the precision of the estimate is evaluated using reliability and sharpness measures. Similarity in modelled and expected indices contributes to good objective function values. Using only the regionalised runoff coefficient to condition the model yields better NSE values compared to using either only the rainfall-runoff elasticity or only the base flow index. Conditioning on the runoff coefficient

  9. Key pluvial parameters in assessing rainfall erosivity in the south-west development region, Romania

    Monica Dumitraşcu; Carmen-Sofia Dragotă; Ines Grigorescu; Costin Dumitraşcu; Alina Vlăduţ


    Located in the south-western part of Romania, the south-west development region overlaps the main relief forms: the Carpathians mountains, the Getic Subcarpathians, the Getic piedmont, the Romanian plain and the Danube valley. The study aims at providing an overview on the main pluvial parameters and their role in assessing rainfall erosivity in the study area. The authors assessed the occurrence, frequency and magnitude of some of the most significant pluvial parameters and their impact on the climatic aggressiveness in the study area. Thus, the monthly and annual mean and extreme climatic values for different rainfall related parameters (e.g., maximum amounts of precipitation/24 hr, heavy rainfall), as well as relevant indices and indicators for pluvial aggressiveness (Fournier, Fournier Modified, Angot) were calculated. The rainfall erosivity was assessed in order to provide both the spatial distribution of the triggering extreme weather phenomena and the resulted intensity classes for the analysed indices and indicators. The authors used long-term precipitation records (1961–2010) for the selected relevant meteorological stations distributed throughout all analysed relief units.

  10. Estimating hydrological parameters based on rainfall patterns in river basins with no long-term historical observations

    Shi, Haiyun; Li, Tiejian


    Small and medium river basins may frequently suffer from the destructive hydrological extremes (e.g., floods). However, the common problem in such regions is a lack of long-term historical observations. Meteorological and hydrological station networks in some river basins in China were newly-built only a few years ago, and it is infeasible to estimate hydrological parameters from calibration and validation with a long time period directly. This paper aims to develop a method to estimate the feasible hydrological parameters based on rainfall patterns in such regions. Digital Yellow River Integrated Model (DYRIM) is adopted as the hydrological model, and the feasible hydrological parameters can be estimated based on limited rainfall-runoff events. First, for each rainfall-runoff event, the parameters are independently calibrated with the observed rainfall and hydrological data using a double-layer parallel system. Then, the performances of the simulation results are comprehensively evaluated, and the value ranges of the parameters can be obtained. Finally, the statistical relationships between hydrological parameters and rainfall patterns (i.e., amount and intensity) are established, which are expressed by the statistical equations and the distribution of hydrological parameters with the rainfall patterns. From a sample demonstration, it is concluded that this parameter estimation method will be useful to estimate the feasible hydrological parameters for future rainfall-runoff events in river basins with no long-term historical observations.

  11. Downscaling site rainfall from daily to 11.25-minute resolution: event, diurnal, seasonal and decadal controls on downscaling parameters

    McIntyre, Neil; Shi, Shirley; Onof, Christian


    Downscaling site rainfall from daily to sub-daily resolution is often approached using the multiplicative discrete random cascade (MDRC) class of models, with mixed success. Questions in any application - for MDRCs or indeed other classes of downscaling model - is to what extent and in what way are model parameters functions of rainfall event type and/or large scale climate controls for example those linked to the El Nino Southern Oscillation (ENSO). These questions underlie the applicability of downscaling models for analysing rainfall and hydrological extremes, in particular for synthesising long-term historical or future sub-daily extremes conditional on historic or projected daily data. Coastal Queensland, Australia, is subject to combinations of multiple weather systems, including tropical cyclones, blocking systems, convective storms, frontal systems and ENSO influences. Using 100 years of fine resolution data from two gauges in central Brisbane, microcanonical MDRC models are fitted to data from 1 day to 11.25 minutes in seven cascade levels, each level dividing the time interval and its rainfall volume into two sub-intervals. Each cascade level involves estimating: the probabilities that all the rainfall observed in a time interval is concentrated in only the first of the two sub-intervals and that all the rainfall observed in a time interval is concentrated in only the second of the two sub-intervals; and also two beta distribution parameters that define the probability of a given division of the rainfall into both sub-intervals. These parameters are found to vary systematically with time of day, rainfall volume, event temporal structure, month of year, and ENSO anomaly. Reasonable downscaling performance is achieved (in terms of replicating extreme values of 11.25 minute rainfall given the observed daily data) by including the parameter dependence on the rainfall volume and event structure, although particular applications may justify development of more

  12. Minimizing uncertainty of daily rainfall interpolation over large catchments through realistic sampling of anisotropic correlogram parameters

    Gyasi-Agyei, Yeboah


    It has been established that daily rainfall gauged network density is not adequate for the level of hydrological modelling required of large catchments involving pollutant and sediment transport, such as the catchments draining the coastal regions of Queensland, Australia, to the sensitive Great Barrier Reef. This paper seeks to establish a link between the spatial structure of radar and gauge rainfall for improved interpolation of the limited gauged data over a grid or functional units of catchments in regions with or without radar records. The study area is within Mt. Stapylton weather radar station range, a 128 km square region for calibration and validation, and the Brisbane river catchment for validation only. Two time periods (2000-01-01 to 2008-12-31 and 2009-01-01 to 2015-06-30) were considered, the later period for calibration when radar records were available and both time periods for validation without regard to radar information. Anisotropic correlograms of both the gauged and radar data were developed and used to establish the linkage required for areas without radar records. The maximum daily temperature significantly influenced the distributional parameters of the linkage. While the gauged, radar and sampled correlogram parameters reproduced the mean estimates similarly using leave-one-out cross-validation of Ordinary Kriging, the gauged parameters overestimated the standard deviation (SD) which reflects uncertainty by over 91% of cases compared with the radar or the sampled parameter sets. However, the distribution of the SD generated by the radar and the sampled correlogram parameters could not be distinguished, with a Kolmogorov-Smirnov test p-value of 0.52. For the validation case with the catchment, the percentage overestimation of SD by the gauged parameter sets decreased to 81.2% and 87.1% for the earlier and later time periods, respectively. It is observed that the extreme wet days' parameters and statistics were fairly widely distributed

  13. A Possible Explanation for the Z -R Parameter Inconsistency when Comparing Stratiform and Convective Rainfall

    Lane, John; Kasparis, Takis; Michaelides, Silas


    The well-known Z -R power law Z = ARb uses two parameters, A and b, in order to relate rainfall rate R to measured weather radar reflectivity Z. A common method used by researchers is to compute Z and R from disdrometer data and then extract the A-bparameter pair from a log-linear line fit to a scatter plot of Z -R pairs. Even though it may seem far more truthful to extract the parameter pair from a fit of radar ZR versus gauge rainfall rate RG, the extreme difference in spatial and temporal sampling volumes between radar and rain gauge creates a slew of problems that can generally only be solved by using rain gauge arrays and long sampling averages. Disdrometer derived A - b parameters are easily obtained and can provide information for the study of stratiform versus convective rainfall. However, an inconsistency appears when comparing averaged A - b pairs from various researchers. Values of b range from 1.26 to 1.51 for both stratiform and convective events. Paradoxically the values of Afall into three groups: 150 to 200 for convective; 200 to 400 for stratiform; and 400 to 500 again for convective. This apparent inconsistency can be explained by computing the A - b pair using the gamma DSD coupled with a modified drop terminal velocity model, v(D) = αDβ - w, where w is a somewhat artificial constant vertical velocity of the air above the disdrometer. This model predicts three regions of A, corresponding to w 0, which approximately matches observed data.

  14. Performance and Probabilistic Verification of Regional Parameter Estimates for Conceptual Rainfall-runoff Models

    Franz, K.; Hogue, T.; Barco, J.


    Identification of appropriate parameter sets for simulation of streamflow in ungauged basins has become a significant challenge for both operational and research hydrologists. This is especially difficult in the case of conceptual models, when model parameters typically must be "calibrated" or adjusted to match streamflow conditions in specific systems (i.e. some of the parameters are not directly observable). This paper addresses the performance and uncertainty associated with transferring conceptual rainfall-runoff model parameters between basins within large-scale ecoregions. We use the National Weather Service's (NWS) operational hydrologic model, the SACramento Soil Moisture Accounting (SAC-SMA) model. A Multi-Step Automatic Calibration Scheme (MACS), using the Shuffle Complex Evolution (SCE), is used to optimize SAC-SMA parameters for a group of watersheds with extensive hydrologic records from the Model Parameter Estimation Experiment (MOPEX) database. We then explore "hydroclimatic" relationships between basins to facilitate regionalization of parameters for an established ecoregion in the southeastern United States. The impact of regionalized parameters is evaluated via standard model performance statistics as well as through generation of hindcasts and probabilistic verification procedures to evaluate streamflow forecast skill. Preliminary results show climatology ("climate neighbor") to be a better indicator of transferability than physical similarities or proximity ("nearest neighbor"). The mean and median of all the parameters within the ecoregion are the poorest choice for the ungauged basin. The choice of regionalized parameter set affected the skill of the ensemble streamflow hindcasts, however, all parameter sets show little skill in forecasts after five weeks (i.e. climatology is as good an indicator of future streamflows). In addition, the optimum parameter set changed seasonally, with the "nearest neighbor" showing the highest skill in the

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

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


    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

  16. Synergetic use of millimeter- and centimeter-wavelength radars for retrievals of cloud and rainfall parameters

    S. Y. Matrosov


    Full Text Available A remote sensing approach for simultaneous retrievals of cloud and rainfall parameters in the vertical column above the US Department of Energy's (DOE Climate Research Facility at the Tropical Western Pacific (TWP Darwin site in Australia is described. This approach uses vertically pointing measurements from a DOE Ka-band radar and scanning measurements from a nearby C-band radar pointing toward the TWP Darwin site. Rainfall retrieval constraints are provided by data from a surface impact disdrometer. The approach is applicable to stratiform precipitating cloud systems when a separation between the liquid hydrometeor layer, which contains rainfall and liquid water clouds, and the ice hydrometeor layer is provided by the radar bright band. Absolute C-band reflectivities and Ka-band vertical reflectivity gradients in the liquid layer are used for retrievals of the mean layer rain rate and cloud liquid water path (CLWP. C-band radar reflectivities are also used to estimate ice water path (IWP in regions above the melting layer. The retrieval uncertainties of CLWP and IWP for typical stratiform precipitation systems are about 500–800 g m−2 (for CLWP and a factor of 2 (for IWP. The CLWP retrieval uncertainties increase with rain rate, so retrievals for higher rain rates may be impractical. The expected uncertainties of layer mean rain rate retrievals are around 20%, which, in part, is due to constraints available from the disdrometer data. The applicability of the suggested approach is illustrated for two characteristic events observed at the TWP Darwin site during the wet season of 2007. A future deployment of W-band radars at the DOE tropical Climate Research Facilities can improve CLWP estimation accuracies and provide retrievals for a wider range of stratiform precipitating cloud events.

  17. Synergetic use of millimeter and centimeter wavelength radars for retrievals of cloud and rainfall parameters

    S. Y. Matrosov


    Full Text Available A remote sensing approach for simultaneous retrievals of cloud and rainfall parameters in the vertical column above the US Department of Energy's (DOE Climate Research Facility at the Tropical Western Pacific (TWP Darwin site in Australia is described. This approach uses vertically pointing measurements from a DOE Ka-band radar and scanning measurements from a nearby C-band radar pointing toward the TWP Darwin site. Rainfall retrieval constraints are provided by data from a surface impact disdrometer. The approach is applicable to stratiform precipitating cloud systems when a separation between the liquid hydrometeor layer, which contains rainfall and liquid water clouds, and the ice hydrometeor layer is provided by the radar bright band. Absolute C-band reflectivities and Ka-band vertical reflectivity gradients in the liquid layer are used for retrievals of the mean layer rain rate and cloud liquid water path (CLWP. C-band radar reflectivities are also used to estimate ice water path (IWP in regions above the melting layer. The retrieval uncertainties of CLWP and IWP for typical stratiform precipitation systems are about 500–800 g m−2 (for CLWP and a factor of 2 (for IWP. The CLWP retrieval uncertainties increase with rain rate, so retrievals for higher rain rates may be impractical. The expected uncertainties of layer mean rain rate retrievals are around 20%, which, in part, is due to constraints available from the disdrometer data. The applicability of the suggested approach is illustrated for two characteristic events observed at the TWP Darwin site during the wet season of 2007. A future deployment of W-band radars at the DOE tropical Climate Research Facilities can improve CLWP estimate accuracies and provide retrievals for a wider range of stratiform precipitating cloud events.

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

    J. D. Valiantzas


    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.

  19. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    M. Sudha


    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

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

    Yousefali Abedini


    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.

  1. A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution

    F. Uboldi


    Full Text Available Estimation of extreme event distributions and depth-duration-frequency (DDF curves is achieved at any target site by repeated sampling among all available raingauge data in the surrounding area. The estimate is computed over a gridded domain in Northern Italy, using precipitation time series from 1929 to 2011, including data from historical analog stations and from the present-day automatic observational network. The presented local regionalisation naturally overcomes traditional station-point methods, with their demand of long historical series and their sensitivity to very rare events occurring at very few stations, possibly causing unrealistic spatial gradients in DDF relations. At the same time, the presented approach allows for spatial dependence, necessary in a geographical domain such as Lombardy, complex for both its topography and its climatology. The bootstrap technique enables evaluating uncertainty maps for all estimated parameters and for rainfall depths at assigned return periods.

  2. Estimation of Model and Parameter Uncertainty For A Distributed Rainfall-runoff Model

    Engeland, K.

    The distributed rainfall-runoff model Ecomag is applied as a regional model for nine catchments in the NOPEX area in Sweden. Ecomag calculates streamflow on a daily time resolution. The posterior distribution of the model parameters is conditioned on the observed streamflow in all nine catchments, and calculated using Bayesian statistics. The distribution is estimated by Markov chain Monte Carlo (MCMC). The Bayesian method requires a definition of the likelihood of the parameters. Two alter- native formulations are used. The first formulation is a subjectively chosen objective function describing the goodness of fit between the simulated and observed streamflow as it is used in the GLUE framework. The second formulation is to use a more statis- tically correct likelihood function that describes the simulation errors. The simulation error is defined as the difference between log-transformed observed and simulated streamflows. A statistical model for the simulation errors is constructed. Some param- eters are dependent on the catchment, while others depend on climate. The statistical and the hydrological parameters are estimated simultaneously. Confidence intervals, due to the uncertainty of the Ecomag parameters, for the simulated streamflow are compared for the two likelihood functions. Confidence intervals based on the statis- tical model for the simulation errors are also calculated. The results indicate that the parameter uncertainty depends on the formulation of the likelihood function. The sub- jectively chosen likelihood function gives relatively wide confidence intervals whereas the 'statistical' likelihood function gives more narrow confidence intervals. The statis- tical model for the simulation errors indicates that the structural errors of the model are as least as important as the parameter uncertainty.

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

    Todorovic, Andrijana; Plavsic, Jasna


    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

  4. Bayesian Assessment of the Uncertainties of Estimates of a Conceptual Rainfall-Runoff Model Parameters

    Silva, F. E. O. E.; Naghettini, M. D. C.; Fernandes, W.


    This paper evaluated the uncertainties associated with the estimation of the parameters of a conceptual rainfall-runoff model, through the use of Bayesian inference techniques by Monte Carlo simulation. The Pará River sub-basin, located in the upper São Francisco river basin, in southeastern Brazil, was selected for developing the studies. In this paper, we used the Rio Grande conceptual hydrologic model (EHR/UFMG, 2001) and the Markov Chain Monte Carlo simulation method named DREAM (VRUGT, 2008a). Two probabilistic models for the residues were analyzed: (i) the classic [Normal likelihood - r ≈ N (0, σ²)]; and (ii) a generalized likelihood (SCHOUPS & VRUGT, 2010), in which it is assumed that the differences between observed and simulated flows are correlated, non-stationary, and distributed as a Skew Exponential Power density. The assumptions made for both models were checked to ensure that the estimation of uncertainties in the parameters was not biased. The results showed that the Bayesian approach proved to be adequate to the proposed objectives, enabling and reinforcing the importance of assessing the uncertainties associated with hydrological modeling.

  5. Sub-Daily Runoff Simulations with Parameters Inferred at the Daily Time Scale: Impacts of the temporal distribution of rainfall in parameter inference.

    Reynolds Puga, Jose Eduardo; Halldin, Sven; Xu, Chong-Yu; Seibert, Jan


    Flood forecasting at sub-daily time scales are commonly required in regions where sub-daily observational data are not available. This has led to approaches to estimate model parameters at sub-daily time scales from data with a lower time resolution. Reynolds et al. (2015) show that parameters inferred at one time scale (e.g., daily) may be used directly for runoff simulations at other time scales (e.g., 1 h) when the modelling time step is the same and sufficiently small during calibration and simulation periods. Their approach produced parameter distributions at daily and sub-daily time scales that were similar and relatively constant across the time scales. The transfer of parameter values across time scales resulted in small model-performance decrease as opposed to when the parameter sets inferred at their respective time scale were used. This decrease in performance may be attributed to the degree of information lost, in terms of the physical processes occurring at short time scales, when the rainfall-runoff data used during the parameter-inference phase become coarser. It is not yet fully understood how the aggregation (or disaggregation) of the rainfall-runoff data affects parameter inference. In this study we analyse the impacts of the temporal distribution of rainfall for inferring model parameters at a coarse time scale and their effects in model performance when they are used at finer time scales, where data may not be available for calibration. The motivation is to improve runoff predictions and model performance at sub-daily time scales when parameters inferred at the daily scale are used for simulating at these scales. First, we calibrated the HBV-light conceptual hydrological model at the daily scale, but modelled discharge internally in 1-h time steps using 3 disaggregation procedures of the rainfall data. This was done in an attempt to maximise the information content of the input data used for calibration at the daily scale. One disaggregation

  6. Spatial analysis of rainfall variation using variogram model parameters of X-band radar images in a small mountainous catchment

    Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Bodoque, José M.; Bermejo, Marcos; Rivero-Honegger, Carlos; Yagüe, Carlos; Monjo, Robert; Tapiador, Francisco J.


    The present study deals the rainfall spatial variability of a small mountainous catchment, which includes the spatial distribution and variability of convective and stratiform events. This work focuses on the precipitation events with hydrological response in Venero-Claro Basin (Avila, Spain). In this basin of 15 square kilometers, flood events of different magnitudes have been often registered. Therefore, any improvement in understanding rainfall characteristics in the area can be of special importance in rainfall estimation and hence to calibrate and validate hydrological models. These enhancements imply more objectivity of risk studies and more predictive and preventive capacity. To separate events by origin it has been used the dimensionless index defined by Monjo (2015), according to the relative temporal distribution of maximum intensities. The main advantages of this method are that it does not require thresholds, so it can be applied for each rain gauge. The geostatistical variogram tool is used to quantify the spatial characteristics of both kinds of events. Hourly rainfall accumulations over the area are computed with observations from one of the 5 existing X-band radar in Spain and 7 rain gauges located in the zone. For each hour the rainfall variogram model has been fitted with the aid of the X-band radar images. Valuable information is extracted from the stratiform and convective ensembles of variogram models. The variogram model parameters are analyzed to determine characteristics of spatial continuity that differentiates stratiform and convective events, and quartiles of sills and ranges in both ensembles are compared.

  7. Development and testing of a large, transportable rainfall simulator for plot-scale runoff and parameter estimation

    T. G. Wilson


    Full Text Available There is increased interest in the interplay between vegetation conditions and overland flow generation. The literature is unclear on this relationship and there is little quantitative guidance for modeling efforts. Therefore, experimental efforts are needed and these call for a lightweight transportable plot-scale (>10 m2 rainfall simulator that can be deployed quickly and quickly redeployed over various vegetation cover conditions. Accordingly, a variable intensity rainfall simulator and collection system was designed and tested in the laboratory and in the field. The system was tested with three configurations of common pressure washing nozzles producing rainfall intensities of 62, 43, and 32 mm h−1 with uniformity coefficients of 76, 65, and 62, respectively, over a plot of 15.12 m2. Field tests were carried out in on a grassy field with silt-loam soil in Orroli, Sardinia in July and August 2010, and rainfall, soil moisture, and runoff data were collected. The two-term Philip infiltration model was used to find optimal values for the saturated hydraulic conductivity of the soil surface and bulk soil, soil water retention curve slope, and air entry suction head. Optimized hydraulic conductivity values were comparable to both the measured final infiltration rate and literature values for saturated hydraulic conductivity. This inexpensive rainfall simulator can therefore be used to identify field parameters needed for hydrologic modeling.

  8. How useful are Green-Ampt parameters derived from small rainfall simulation plots for modelling runoff at different plot lengths?

    Langhans, Christoph; Engels, Lien; Tegenbos, Lize; Govers, Gerard; Diels, Jan


    Rainfall simulation on small field plots is an invaluable method to derive effective field parameters for infiltration models such as Green-Ampt. Plot scales of ca. 1m² integrate much of the micro-scale variability and processes, which ring-infiltrometers or soil core measurements cannot capture. However, these parameters have to be used with caution on larger scales, because processes such as run-on infiltration can be considerable. The Green-Ampt parameters suction across the wetting front (psi) and effective hydraulic conductivity (Ke) were estimated from rainfall simulations on two ridged fields in Togo, West Africa. Additionally, rainfall events were recorded, and on plots of 1m width and lengths of 1, 4 and 16m, total runoff volume and sediment concentration were measured. The storm runoff hydrographs of the plots were modelled with Chu's Green-Ampt variable rainfall intensity infiltration model, using the field-average parameters derived from the simulations. Potential effects of runoff lag time were assumed negligible. Calculated total runoff volumes were compared to measured runoff volumes. For the 1m plots, runoff was underestimated, as patches of seal in the furrows produced runoff already at rainfall intensities much lower than the average infiltration capacity. For the longer plots, no run-on infiltration or other scale dependent processes were assumed, so the relative error due to scale effects was proportional to the average difference or runoff depth. In contrast to the 1m plots, runoff was overestimated by a factor of 1.2 and 2 for the 4m and 16m plots, respectively. It appears that the application of the Green-Ampt effective hydraulic conductivity derived from rainfall simulations faces two main problems, which are their dependence on one single rainfall intensity and scale-effects by run-on infiltration. Errors necessarily propagate into the scale dependency of erosion and sediment transport, as these processes are directly dependent on runoff

  9. Optimal parameters for the Green-Ampt infiltration model under rainfall conditions

    Chen, Li; Xiang, Long; Young, Michael H.; Yin, Jun; Yu, Zhongbo; van Genuchten, Martinus Th.


    The Green-Ampt (GA) model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations) has not been studied extensively. We compared calcu

  10. Rainfall/runoff simulation with 2D full shallow water equations: Sensitivity analysis and calibration of infiltration parameters

    Fernández-Pato, Javier; Caviedes-Voullième, Daniel; García-Navarro, Pilar


    One of the most difficult issues in the development of hydrologic models is to find a rigorous source of data and specific parameters to a given problem, on a given location that enable reliable calibration. In this paper, a distributed and physically based model (2D Shallow Water Equations) is used for surface flow and runoff calculations in combination with two infiltration laws (Horton and Green-Ampt) for estimating infiltration in a watershed. This technique offers the capability of assigning a local and time-dependent infiltration rate to each computational cell depending on the available surface water, soil type or vegetation. We investigate how the calibration of parameters is affected by transient distributed Shallow Water model and the complexity of the problem. In the first part of this work, we calibrate the infiltration parameters for both Horton and Green-Ampt models under flat ponded soil conditions. Then, by means of synthetic test cases, we perform a space-distributed sensitivity analysis in order to show that this calibration can be significantly affected by the introduction of topography or rainfall. In the second part, parameter calibration for a real catchment is addressed by comparing the numerical simulations with two different sets of experimental data, corresponding to very different events in terms of the rainfall volume. We show that the initial conditions of the catchment and the rainfall pattern have a special relevance in the quality of the adjustment. Hence, it is shown that the topography of the catchment and the storm characteristics affect the calibration of infiltration parameters.

  11. Statistical model for economic damage from pluvial floods in Japan using rainfall data and socioeconomic parameters

    Bhattarai, Rajan; Yoshimura, Kei; Seto, Shinta; Nakamura, Shinichiro; Oki, Taikan


    The assessment of flood risk is important for policymakers to evaluate damage and for disaster preparation. Large population densities and high property concentration make cities more vulnerable to floods and having higher absolute damage per year. A number of major cities in the world suffer from flood inundation damage every year. In Japan, approximately USD 1 billion in damage occurs annually due to pluvial floods only. The amount of damage was typically large in large cities, but regions with lower population density tended to have more damage per capita. Our statistical approach gives the probability of damage following every daily rainfall event and thereby the annual damage as a function of rainfall, population density, topographical slope and gross domestic product. Our results for Japan show reasonable agreement with area-averaged annual damage for the period 1993-2009. We report a damage occurrence probability function and a damage cost function for pluvial flood damage, which makes this method flexible for use in future scenarios and also capable of being expanded to different regions.

  12. A dual-polarisation radar rainfall estimation method using a multi-parameter fuzzy logic algorithm

    Hall, Will; Rico-Ramirez, Miguel Angel


    The emergence of dual-polarisation radar has resulted in a significant enhancement of quantitative precipitation estimation (QPE). It has enabled the measurement of rain drop size and shapes within a volume, the classification of hydrometeors, and the ability to more accurately account for attenuation of the radar beam. Previous methods for QPE have used only the radar reflectivity (Zh) to estimate rainfall, but more recent methods can use a combination of ZH, differential reflectivity (Zdr), specific differential phase (Kdp), and specific attenuation (Ah). The radar variables perform differently depending on rain rate, attenuation, and bright band presence. This has led to the use of fixed threshold values within which the different estimators are used, or the variables are weighted based on performance. This new method to be presented will use fuzzy logic to try to form a more robust algorithm using combinations of the rainfall estimators R(Zh), R(Kdp), and R(Ah). For this a C-band dual-polarised radar based in Hameldon Hill, near Burnley, UK, will be used, alongside a rain gauge network for calibration adn validation.

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

    Mark E. Grismer


    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

  14. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters

    Kuczera, George; Kavetski, Dmitri; Franks, Stewart; Thyer, Mark


    SummaryCalibration and prediction in conceptual rainfall-runoff (CRR) modelling is affected by the uncertainty in the observed forcing/response data and the structural error in the model. This study works towards the goal of developing a robust framework for dealing with these sources of error and focuses on model error. The characterisation of model error in CRR modelling has been thwarted by the convenient but indefensible treatment of CRR models as deterministic descriptions of catchment dynamics. This paper argues that the fluxes in CRR models should be treated as stochastic quantities because their estimation involves spatial and temporal averaging. Acceptance that CRR models are intrinsically stochastic paves the way for a more rational characterisation of model error. The hypothesis advanced in this paper is that CRR model error can be characterised by storm-dependent random variation of one or more CRR model parameters. A simple sensitivity analysis is used to identify the parameters most likely to behave stochastically, with variation in these parameters yielding the largest changes in model predictions as measured by the Nash-Sutcliffe criterion. A Bayesian hierarchical model is then formulated to explicitly differentiate between forcing, response and model error. It provides a very general framework for calibration and prediction, as well as for testing hypotheses regarding model structure and data uncertainty. A case study calibrating a six-parameter CRR model to daily data from the Abercrombie catchment (Australia) demonstrates the considerable potential of this approach. Allowing storm-dependent variation in just two model parameters (with one of the parameters characterising model error and the other reflecting input uncertainty) yields a substantially improved model fit raising the Nash-Sutcliffe statistic from 0.74 to 0.94. Of particular significance is the use of posterior diagnostics to test the key assumptions about the data and model errors

  15. Stochastic rainfall-runoff forecasting: parameter estimation, multi-step prediction, and evaluation of overflow risk

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik


    Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date, res...... in this analysis. In conclusion, further research must focus on the development of model structures that allow the proper separation of dry and wet weather uncertainties and simulate runoff uncertainties depending on the rainfall input.......Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date......, research has primarily focused on one-step-ahead flow predictions for identifying, estimating, and evaluating greybox models. For control purposes, however, stochastic predictions are required for longer forecast horizons and for the prediction of runoff volumes, rather than flows. This article therefore...

  16. Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

    Lazri, Mourad; Ameur, Zohra; Ameur, Soltane; Mohia, Yacine; Brucker, Jean Michel; Testud, Jacques


    The ultimate objective of this paper is the estimation of rainfall over an area in Algeria using data from the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager). To achieve this aim, we use a new Convective/Stratiform Rain Area Delineation Technique (CS-RADT). The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties. It uses a multispectral thresholding technique to distinguish between stratiform and convective clouds. This technique (CS-RADT) is applied to the complex situation of the Mediterranean climate of this region. The tests have been conducted during the rainy seasons of 2006/2007 and 2010/2011 where stratiform and convective precipitation is recorded. The developed scheme (CS-RADT) is calibrated by instantaneous meteorological radar data to determine thresholds, and then rain rates are assigned to each cloud type by using radar and rain gauge data. These calibration data are collocated with SEVIRI data in time and space.

  17. Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling

    Soong, David T.; Over, Thomas M.


    The Lake Michigan Diversion Accounting (LMDA) system has been developed by the U.S. Army Corps of Engineers, Chicago District (USACE-Chicago) and the State of Illinois as a part of the interstate Great Lakes water regulatory program. The diverted Lake Michigan watershed is a 673-square-mile watershed that is comprised of the Chicago River and Calumet River watersheds. They originally drained into Lake Michigan, but now flow to the Mississippi River watershed via three canals constructed in the Chicago area in the early twentieth century. Approximately 393 square miles of the diverted watershed is ungaged, and the runoff from the ungaged portion of the diverted watershed has been estimated by the USACE-Chicago using the Hydrological Simulation Program-FORTRAN (HSPF) program. The accuracy of simulated runoff depends on the accuracy of the parameter set used in the HSPF program. Nine parameter sets comprised of the North Branch, Little Calumet, Des Plaines, Hickory Creek, CSSC, NIPC, 1999, CTE, and 2008 have been developed at different time periods and used by the USACE-Chicago. In this study, the U.S. Geological Survey and the USACE-Chicago collaboratively analyzed the parameter sets using nine gaged watersheds in or adjacent to the diverted watershed to assess the predictive accuracies of selected parameter sets. Six of the parameter sets, comprising North Branch, Hickory Creek, NIPC, 1999, CTE, and 2008, were applied to the nine gaged watersheds for evaluating their simulation accuracy from water years 1996 to 2011. The nine gaged watersheds were modeled by using the three LMDA land-cover types (grass, forest, and hydraulically connected imperviousness) based on the 2006 National Land Cover Database, and the latest meteorological and precipitation data consistent with the current (2014) LMDA modeling framework.

  18. Getting a feel for parameters: using interactive parallel plots as a tool for parameter identification in the new rainfall-runoff model WALRUS

    Brauer, Claudia; Torfs, Paul; Teuling, Ryan; Uijlenhoet, Remko


    Recently, we developed the Wageningen Lowland Runoff Simulator (WALRUS) to fill the gap between complex, spatially distributed models often used in lowland catchments and simple, parametric models which have mostly been developed for mountainous catchments (Brauer et al., 2014ab). This parametric rainfall-runoff model can be used all over the world in both freely draining lowland catchments and polders with controlled water levels. The open source model code is implemented in R and can be downloaded from The structure and code of WALRUS are simple, which facilitates detailed investigation of the effect of parameters on all model variables. WALRUS contains only four parameters requiring calibration; they are intended to have a strong, qualitative relation with catchment characteristics. Parameter estimation remains a challenge, however. The model structure contains three main feedbacks: (1) between groundwater and surface water; (2) between saturated and unsaturated zone; (3) between catchment wetness and (quick/slow) flowroute division. These feedbacks represent essential rainfall-runoff processes in lowland catchments, but increase the risk of parameter dependence and equifinality. Therefore, model performance should not only be judged based on a comparison between modelled and observed discharges, but also based on the plausibility of the internal modelled variables. Here, we present a method to analyse the effect of parameter values on internal model states and fluxes in a qualitative and intuitive way using interactive parallel plotting. We applied WALRUS to ten Dutch catchments with different sizes, slopes and soil types and both freely draining and polder areas. The model was run with a large number of parameter sets, which were created using Latin Hypercube Sampling. The model output was characterised in terms of several signatures, both measures of goodness of fit and statistics of internal model variables (such as the

  19. Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis

    N. Bulygina


    Full Text Available Data scarcity and model over-parameterisation, leading to model equifinality and large prediction uncertainty, are common barriers to effective hydrological modelling. The problem can be alleviated by constraining the prior parameter space using parameter regionalisation. A common basis for regionalisation in the UK is the HOST database which provides estimates of hydrological indices for different soil classifications. In our study, Base Flow Index is estimated from the HOST database and the power of this index for constraining the parameter space is explored. The method is applied to a highly discretised distributed model of a 12.5 km2 upland catchment in Wales. To assess probabilistic predictions against flow observations, a probabilistic version of the Nash-Sutcliffe efficiency is derived. For six flow gauges with reliable data, this efficiency ranged between 0.70 and 0.81, and inspection of the results shows that the model explains the data well. Knowledge of how Base Flow Index and interception losses may change under future land use management interventions was then used to further condition the model. Two interventions are considered: afforestation of grazed areas, and soil degradation associated with increased grazing intensity. Afforestation leads to median reduction in modelled runoff volume of 24% over the simulated 3 month period; and a median peak flow reduction ranging from 12 to 15% over the six gauges for the largest simulated event. Uncertainty in all results is low compared to prior uncertainty and it is concluded that using Base Flow Index estimated from HOST is a simple and potentially powerful method of conditioning the parameter space under current and future land management.

  20. Parameter Estimation in Rainfall-Runoff Modelling Using Distributed Versions of Particle Swarm Optimization Algorithm

    Michala Jakubcová


    Full Text Available The presented paper provides the analysis of selected versions of the particle swarm optimization (PSO algorithm. The tested versions of the PSO were combined with the shuffling mechanism, which splits the model population into complexes and performs distributed PSO optimization. One of them is a new proposed PSO modification, APartW, which enhances the global exploration and local exploitation in the parametric space during the optimization process through the new updating mechanism applied on the PSO inertia weight. The performances of four selected PSO methods were tested on 11 benchmark optimization problems, which were prepared for the special session on single-objective real-parameter optimization CEC 2005. The results confirm that the tested new APartW PSO variant is comparable with other existing distributed PSO versions, AdaptW and LinTimeVarW. The distributed PSO versions were developed for finding the solution of inverse problems related to the estimation of parameters of hydrological model Bilan. The results of the case study, made on the selected set of 30 catchments obtained from MOPEX database, show that tested distributed PSO versions provide suitable estimates of Bilan model parameters and thus can be used for solving related inverse problems during the calibration process of studied water balance hydrological model.

  1. Definition and sensitivity of the conceptual MORDOR rainfall-runoff model parameters using different multi-criteria calibration strategies

    Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.


    MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.

  2. Robust Parameter Estimation Framework of a Rainfall-Runoff Model Using Pareto Optimum and Minimax Regret Approach

    Yeonjoo Kim


    Full Text Available This study developed a robust parameter set (ROPS selection framework for a rainfall-runoff model that considers multi-events using the Pareto optimum and minimax regret approach (MRA. The calibrated parameter sets based on the Nash-Sutcliffe coefficient (NSE for two events were derived using a genetic algorithm. We generated 41 combinations for weighting values between two events for the multi-event objective function and derived 41 Pareto optimum points that were considered as the ROPS candidates. Then, two different approaches for parameter selection were proposed to determine the ROPS among the candidates: one uses NSE only and the other uses four performance measures (NSE, peak flow error, root mean square error and percentage of bias. In the NSE-only method, five events, including two events from the calibration set and three events from the evaluation set, were used, and the ROPS was selected based on the regrets of both the calibration and the evaluation sets. In the multiple (i.e., four performance measure method, only three events from the evaluation set were used and the ROPS was determined based on the regrets of twelve different cases, including three events with four measures. As a result, while single- and multi-event optimizations produced satisfying results for the calibration events, the optimized parameters from the single-event calibration do not perform well for another event, even one with the same criteria, such as NSE. The results of this study suggest that the optimized parameter set from the well-weighted objective function can successfully simulate not only hydrographs in general but also others, such as peak flow. In addition, the ROPS can be selected by considering the multiple performance measures of multiple validation events, as well as the NSE only of multiple calibration and validation events. Note that the study provides a framework that could be performed reasonably well with a limited number of events. While

  3. Correcting temporal sampling error in radar-rainfall: Effect of advection parameters and rain storm characteristics on the correction accuracy

    Seo, Bong-Chul; Krajewski, Witold F.


    This study offers a method to correct for the radar temporal sampling error when determining radar-rainfall accumulations. The authors evaluate the correction effect with respect to multiple factors associated with storm advection, rainfall characteristics, and different rainfall accumulation time scales. The advection method presented in this study uses linear interpolation of static rain storm locations observed at two intermittent radar sampling times to correct for the missed rainfall accumulations. The advection correction is applied to the high space (0.5 km) and time (5-min) resolution radar-rainfall products provided by the Iowa Flood Center. We use the ground reference data from a high quality and high density rain gauge network distributed over the Turkey River basin in Iowa to evaluate the advection corrected rain fields. We base our evaluation on six rain events and examine the correction performance/improvement with respect to the advection discretization, spatial grid aggregation, rainfall basin coverage, and conditional average rainfall intensity. The results show that the 1-min advection discretization is sufficient to represent the observed distribution of storm velocities for the presented cases. Grid aggregation that is motivated by the need to expedite the computation may induce errors in estimating advection vectors. The authors found that while the advection correction tends to enhance the QPE accuracy for intense rain storms over small or isolated areas, it has little impact on the improvement of light rain estimation.

  4. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen


    Abstract: The accurate production of a rainfall environment similar to natural rainfall by a rainfall simulator (RS) is a crucial and challenging task in rainfall instrument testing or calibration. Although the spatial uniformity of rainfall accumulation is a key parameter of an RS, the spatial uniformity comparison between simulated rainfall and natural rainfall, and the spatial uniformity improvements for an RS are scant in the literature. In this study, a fine-scale natural rainfall experi...

  5. Statistical model for economic damage from pluvial flood in Japan using rainfall data and socio-economic parameters

    R. Bhattarai


    Full Text Available The assessment of flood risk is important for policy makers to evaluate damage and for disaster preparation. Large population densities and high property concentration make cities more vulnerable to floods and having higher absolute damage per year. A number of major cities in the world suffer from flood inundation damage every year. In Japan, approximately JPY 100 billion in damage occurs annually due to pluvial flood only. The amount of damage was typically large in large cities, but regions with lower population density tended to have more damage per capita. Our statistical approach gives the probability of damage following every daily rainfall event and thereby the annual damage as a function of rainfall, population density, topographical slope, and gross domestic product. Our results for Japan show reasonable agreement with area-averaged annual damage for the period 1993–2009. We report a damage occurrence probability function and a damage cost function for pluvial flood damage, which makes this method flexible for use in future scenarios and also capable of being expanded to different regions.

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

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


    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 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.

  7. Rainfall generation

    Sharma, Ashish; Mehrotra, Raj

    This chapter presents an overview of methods for stochastic generation of rainfall at annual to subdaily time scales, at single- to multiple-point locations, and in a changing climatic regime. Stochastic rainfall generators are used to provide inputs for risk assessment of natural or engineering systems that can undergo failure under sustained (high or low) extremes. As a result, generation of rainfall has evolved to provide options that adequately represent such conditions, leading to sequences that exhibit low-frequency variability of a nature similar to the observed rainfall. The chapter consists of three key sections: the first two outlining approaches for rainfall generation using endogenous predictor variables and the third highlighting approaches for generation using exogenous predictors often simulated to represent future climatic conditions. The first section presents approaches for generation of annual and seasonal rainfall and daily rainfall, both at single-point locations and multiple sites, with an emphasis on alternatives that ensure appropriate representation of low-frequency variability in the generated rainfall sequences. The second section highlights advancements in the subdaily rainfall generation procedures including commonly used approaches for daily to subdaily rainfall generation. The final section (generation using exogenous predictors) presents a range of alternatives for stochastic downscaling of rainfall for climate change impact assessments of natural and engineering systems. We conclude the chapter by outlining some of the key challenges that remain to be addressed, especially in generation under climate change conditions, with an emphasis on the importance of incorporating uncertainty present in both measurements and models, in the rainfall sequences that are generated.

  8. Comparison of parameters influencing the behavior of concentration of nitrates and phosphates during different extreme rainfall-runoff events in small watersheds

    J. Moravcová


    Full Text Available The behavior of solute concentrations during storm events is completely different from their behaviour under normal conditions, and very often results in hysteresis. This study aim is to explore the relationship between the biogeochemical and hydrological parameters describing natural conditions and the reciprocal interactions between changes in concentration of selected indicators of water quality in water and the discharge dynamics during different types of extreme rainfall-runoff events in the Jenínský stream and the Kopaninský stream catchment (Czech Republic. The relationship between concentrations and runoffs is explained by concentration-discharge hysteretic loops. As the statistical method used for cross analyzing the impact of the parameters there was chosen the RDA analysis. The relationships between the particular parameters were examined separately by conditions of spring snow melt and summer storm events. The results than confirmed the very strong relationship between parameters describing water quality and percentage of stable parts of the catchment and also of infiltration vulnerable sites.

  9. Spatial dependence of extreme rainfall

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


    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.

  10. Heterogeneity of Dutch rainfall

    Witter, J.V.


    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

  11. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP

    Bo Liu


    Full Text Available Abstract: The accurate production of a rainfall environment similar to natural rainfall by a rainfall simulator (RS is a crucial and challenging task in rainfall instrument testing or calibration. Although the spatial uniformity of rainfall accumulation is a key parameter of an RS, the spatial uniformity comparison between simulated rainfall and natural rainfall, and the spatial uniformity improvements for an RS are scant in the literature. In this study, a fine-scale natural rainfall experiment was studied using the same testing methods of an RS and the rainfall uniformity was evaluated using the Christiansen Uniformity Coefficient (CU. Simultaneously, factors influencing the spatial uniformity of natural rainfall, including the average rainfall accumulation (RA, the deviation of RA, and the area of the test zone, were analyzed. The results successfully reproduced some of the behaviors observed in natural rainfall experiments, showing that CU is dependent on these parameters. Based on these studies, we developed a rainfall simulator with a rotary platform (RSRP and found that although spatial uniformity of the RSRP was greatly improved using an appropriate rotary speed, it was not consistent with the spatial uniformity of natural rainfall. Furthermore, we tested four tipping-bucket rain gauges using this imperfect RSRP, and found that the RSRP might acquire the instrumental errors associated with RA for a tested rainfall instrument.

  12. Rainfall erosivity in New Zealand

    Klik, Andreas; Haas, Kathrin; Dvorackova, Anna; Fuller, Ian


    Rainfall and its kinetic energy expressed by the rainfall erosivity is the main driver of soil erosion processes by water. The Rainfall-Runoff Erosivity Factor (R) of the Revised Universal Soil Loss Equation is one oft he most widely used parameters describing rainfall erosivity. This factor includes the cumulative effects of the many moderate-sized storms as well as the effects oft he occasional severe ones: R quantifies the effect of raindrop impact and reflects the amopunt and rate of runoff associated with the rain. New Zealand is geologically young and not comparable with any other country in the world. Inordinately high rainfall and strong prevailing winds are New Zealand's dominant climatic features. Annual rainfall up to 15000 mm, steep slopes, small catchments and earthquakes are the perfect basis for a high rate of natural and accelerated erosion. Due to the multifacted landscape of New Zealand its location as island between the Pacific and the Tasmanian Sea there is a high gradient in precipitation between North and South Island as well as between West and East Coast. The objective of this study was to determine the R-factor for the different climatic regions in New Zealand, in order to create a rainfall erosivity map. We used rainfall data (breakpoint data in 10-min intervals) from 34 gauging stations for the calcuation of the rainfall erosivity. 15 stations were located on the North Island and 19 stations on the South Island. From these stations, a total of 397 station years with 12710 rainstorms were analyzed. The kinetic energy for each rainfall event was calculated based on the equation by Brown and Foster (1987), using the breakpoint precipitation data for each storm. On average, a mean annual precipitation of 1357 mm was obtained from the 15 observed stations on the North Island. Rainfall distribution throughout the year is relatively even with 22-24% of annual rainfall occurring in spring , fall and winter and 31% in summer. On the South Island




    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.

  14. Physical simulation of urban rainfall infiltration

    LI Jie; ZENG Bing; WANG Yan-xia; SHEN Lei


    To meet the demand of urban rainwater integrated management, we designed and complemented a physical simulation experimental system of urban rainfall infiltration regulation parameters. We discuss the feasibility of quantitative regulations of urban underlying surface rainfall infiltration conditions and a practical application of a simulated experimental system. In a comprehensive analysis of the composition of an effective rainwater harvesting system and selection of water storage material, we simulated the major parameters of an experimental area rainfall, soil moisture and water storage capacity by providing an effective regulation of the experimental area runoff coefficient, obtained from basic data.

  15. A point rainfall model and rainfall intensity-duration-frequency analysis

    Yoo, Chul-Sang; Jung, Kwang-Sik [Korea University, Jochiwon(Korea); Kim, Nam-Won [Korea Institute of Construction Technology, Koyang(Korea)


    This study proposes a theoretical methodology for deriving a rainfall intensity-duration-frequency(I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derived using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Incheon stations to check its applicability by comparing the two I-D-F curves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is found much higher than that for Incheon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration. (author). 14 refs., 6 tabs., 2 figs.

  16. Incorporation of an evolutionary algorithm to estimate transfer-functions for a parameter regionalization scheme of a rainfall-runoff model

    Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten


    This contribution presents a framework, which enables the use of an Evolutionary Algorithm (EA) for the calibration and regionalization of the hydrological model COSEROreg. COSEROreg uses an updated version of the HBV-type model COSERO (Kling et al. 2014) for the modelling of hydrological processes and is embedded in a parameter regionalization scheme based on Samaniego et al. (2010). The latter uses subscale-information to estimate model via a-priori chosen transfer functions (often derived from pedotransfer functions). However, the transferability of the regionalization scheme to different model-concepts and the integration of new forms of subscale information is not straightforward. (i) The usefulness of (new) single sub-scale information layers is unknown beforehand. (ii) Additionally, the establishment of functional relationships between these (possibly meaningless) sub-scale information layers and the distributed model parameters remain a central challenge in the implementation of a regionalization procedure. The proposed method theoretically provides a framework to overcome this challenge. The implementation of the EA encompasses the following procedure: First, a formal grammar is specified (Ryan et al., 1998). The construction of the grammar thereby defines the set of possible transfer functions and also allows to incorporate hydrological domain knowledge into the search itself. The EA iterates over the given space by combining parameterized basic functions (e.g. linear- or exponential functions) and sub-scale information layers into transfer functions, which are then used in COSEROreg. However, a pre-selection model is applied beforehand to sort out unfeasible proposals by the EA and to reduce the necessary model runs. A second optimization routine is used to optimize the parameters of the transfer functions proposed by the EA. This concept, namely using two nested optimization loops, is inspired by the idea of Lamarckian Evolution and Baldwin Effect

  17. Rainfall simulation in education

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


    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

  18. A Maximum Entropy Modelling of the Rain Drop Size Distribution

    Francisco J. Tapiador


    Full Text Available This paper presents a maximum entropy approach to Rain Drop Size Distribution (RDSD modelling. It is shown that this approach allows (1 to use a physically consistent rationale to select a particular probability density function (pdf (2 to provide an alternative method for parameter estimation based on expectations of the population instead of sample moments and (3 to develop a progressive method of modelling by updating the pdf as new empirical information becomes available. The method is illustrated with both synthetic and real RDSD data, the latest coming from a laser disdrometer network specifically designed to measure the spatial variability of the RDSD.

  19. Rainfall Fields: Estimation, Analysis, and Prediction

    The problem of predicting rainfall and its characteristics has always been one of overriding concern for both hydrologists and meteorologists. Yet, for decades the two disciplines have pursued its solution using radically different techniques and communicating relatively little about recent advances in understanding rainfall processes, new technology, and improvements in predictive skill.Meteorologists tend to publish in journals that deal almost exclusively with atmospheric processes, while hydrologists prefer media which focus on the Earth's surface and below. Meteorologists tend to concentrate on developing and improving numerical hydrodynamical models of the atmospheric processes that generate rainfall. Their approach is essentially to solve an initial value problem where the observed three-dimensional state of the atmosphere is input to the model and the rainfall is one of the output parameters.

  20. Temporal Variation of Rainfall Intensity, Rainfall Partitioning and its Correlation with Meteorological Elements of Eastern India

    Tripathi, P.; Chaturvedi, A.


    Rainfall plays a vital role in Indian agriculture hence economy of the country, but very crucial and risky due to its erratic/ unpredictable behavior and uneven distribution. Since monsoonal vagaries in eastern India are very frequent hence involve a great risk in Argil. Production and quality of atmosphere at desired level. Though prediction of onset of monsoon with total quantum of rainfall is available through different agencies but still not accurate and not in consonance of observed behavior. Therefore, surface weather data of meteorological elements needs to be critically examined for prediction of onset of monsoon, rainfall rate and its variability with space and time and strategy to cope the uncertainty of risk (drought and flood etc) needs to be evolved. In the present study an analysis of rainfall of Eastern India (Eastern U.P., Bihar and Jharkhand) has been made for rainfall partitioning, rate of rainfall and its variation with space and time. A location specific six parameter model were developed with multiple correlation technique to predict the medium and long range rainfall forecast and found 65% accurate for long range and 79% accurate to medium range. This will not only help to predict the accurate rainfall but also provides a clue for assessment of quality of rainfall under different aerosol levels of atmosphere which ultimately led to link designers with radio wave propagation. In addition, correlation of physical variables of atmosphere like vapor pressure deficit, dew point and relative humidity were also made with quantum of rainfall, rate of rainfall and its quantitative characteristics in the study area as to understand the mechanism behavior of atmosphere for space research.

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

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


    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...

  2. Estimation of rainfall using remote sensing for Riyadh climate, KSA

    AlHassoun, Saleh A.


    Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

  3. Development of Rainfall Model using Meteorological Data for Hydrological Use

    Mohd Adib Mohammad Razi


    Full Text Available Abstract At present, research on forecasting unpredictable weather such as heavy rainfall is one of the most important challenges for equipped meteorological center. In addition, the incidence of significant weather events is estimated to rise in the near future due to climate change, and this situation inspires more studies to be done. This study introduces a rainfall model that has been developed using selected rainfall parameters with the aim to recognize rainfall depth in a catchment area. This study proposes a rainfall model that utilizes the amount of rainfall, temperature, humidity and pressure records taken from selected stations in Peninsular Malaysia and they are analyzed using SPSS multiple regression model. Seven meteorological stations are selected for data collection from 1997 until 2007 in Peninsular Malaysia which are Senai, Kuantan, Melaka, Subang, Ipoh, Bayan Lepas, and Chuping. Multiple Regression analysis in Statistical Package for Social Science (SPSS software has been used to analyze a set of eleven years (1997 – 2007 meteorological data. Senai rainfall model gives an accurate result compared to observation rainfall data and this model were validating with data from Kota Tinggi station. The analysis shows that the selected meteorological parameters influence the rainfall development. As a result, the rainfall model developed for Senai proves that it can be used in Kota Tinggi catchment area within the limit boundaries, as the two stations are close from one another. Then, the amounts of rainfall at the Senai and Kota Tinggi stations are compared and the calibration analysis shows that the proposed rainfall model can be used in both areas.

  4. Spatial Variability of Rainfall

    Jensen, N.E.; Pedersen, Lisbeth


    As a part of a Local Area Weather Radar (LAWR) calibration exercise 15 km south of Århus, Denmark, the variability in accumulated rainfall within a single radar pixel (500 by 500 m) was measured using nine high-resolution rain gauges. The measured values indicate up to a 100% variation between...

  5. The Wageningen Rainfall Simulator

    Lassu, Tamas; Seeger, K.M.; Peters, P.D.; Keesstra, S.D.


    The set-up and characterisation of an indoor nozzle-type rainfall simulator (RS) at Wageningen University, the Netherlands, are presented. It is equipped with four Lechler nozzles (two nr. 460·788 and two nr. 461·008). The tilting irrigation plot is 6 m long and 2·5 m wide. An electrical pump

  6. The Winter Rainfall of Malaysia

    Chen, Tsing-Chang; Tsay, Jenq-Dar; Yen, Ming-Cheng; Matsumoto, Jun


    .... The major cause of the rainfall maximum of Peninsular Malaysia is cold surge vortices (CSVs) and heavy rainfall/flood (HRF) events propagating from the Philippine area and Borneo. In contrast, the major cause of the rainfall maximum of Borneo is these rain-producing disturbances trapped in Borneo. Disturbances of the former group are formed by the cold sur...

  7. Scale-wise evolution of rainfall probability density functions fingerprints the rainfall generation mechanism

    Molini, Annalisa; Katul, Gabriel; Porporato, Amilcare


    Possible linkages between climatic fluctuations in rainfall at low frequencies and local intensity fluctuations within single storms is now receiving significant attention in climate change research. To progress on a narrower scope of this problem, the cross-scale probabilistic structure of rainfall intensity records collected over time scales ranging from hours to decades at sites dominated by either convective or frontal systems is investigated. Across these sites, intermittency buildup from slow to fast time-scales is analyzed in terms of its heavy tailed and asymmetric signatures in the scale-wise evolution of rainfall probability density functions (pdfs). The analysis demonstrates that rainfall records dominated by convective storms develop heavier-tailed power law pdfs across finer scales when compared with their frontal systems counterpart. A concomitant marked asymmetry buildup also emerges across finer time scales necessitating skewed probability laws for quantifying the scale-wise evolution of rainfall pdfs. A scale-dependent probabilistic description of such fat tails, peakedness and asymmetry appearance is proposed and tested by using a modified q-Gaussian model, able to describe the scale wise evolution of rainfall pdfs in terms of the nonextensivity parameter q, a lacunarity (intermittency) correction γ and a tail asymmetry coefficient c, also functions of q.

  8. The asymmetry of rainfall process

    YU RuCong; YUAN WeiHua; LI Jian


    Using hourly station rain gauge data in the warm season (May-October) during 1961-2006,the climatological features of the evolution of the rainfall process are analyzed by compositing rainfall events centered on the maximum hourly rainfall amount of each event.The results reveal that the rainfall process is asymmetric,which means rainfall events usually reach the maximum in a short period and then experience a relatively longer retreat to the end of the event.The effects of rainfall intensity,duration and peak time,as well as topography,are also considered.It is found that the asymmetry is more obvious in rainfall events with strong intensity and over areas with complex terrain,such as the eastern margin of the Tibetan Plateau,the Hengduan Mountains,and the Yungui Plateau.The asymmetry in short-duration rainfall is more obvious than that in long-duration rainfall,but the regional differences are weaker.The rainfall events that reach the maximum during 14:00-02:00 LST exhibit the strongest asymmetry and those during 08:00-14:00 LST show the weakest asymmetry.The rainfall intensity at the peak time stands out,which means that the rainfall intensity increases and decreases quickly both before and after the peak.These results can improve understanding of the rainfall process and provide metrics for the evaluation of climate models.Moreover,the strong asymmetry of the rainfall process should be highly noted when taking measures to defending against geological hazards,such as collapses,landslides and debris flows throughout southwestern China.

  9. Generating monthly rainfall amount using multivariate skew-t copula

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Zanariah Satari, Siti


    This study aims to generate rainfall data in cases where the data is not available or not enough for a certain area of study. In general, the rainfall data is rightly skewed, so the multivariate skew-t copula is used as it able to model rainfall amount and capture the spatial dependence in the data. To illustrate the methodology, three rainfall stations in Kelantan are used. Firstly, the observed data is transformed to uniform unit. The Spearman’s correlation coefficient is calculated between the three stations. It is found that the correlations between the stations are significance at α = 0.05. The next step involved generating the synthetic rainfall data using the multivariate skew-t copula. The data is then transformed to uniform unit and the correlation coefficient is calculated for the generated data. Finally, the correlation coefficient of the observed and the generated data are compared. The Kolmogorov-Smirnov goodness of fit test is used to assess the fit between theoretical and empirical copula and supported by graphical representation. The results show that there is no significant difference between empirical and theoretical copula at 5% significance level. Thus, the multivariate skew-t copula is suitable to generate synthetic rainfall data that can mimic the observed rainfall data. It can also be used to present different rainfall scenarios by changing the value of the parameters in the model.

  10. Continuous rainfall generation for a warmer climate using observed temperature sensitivities

    Wasko, Conrad; Sharma, Ashish


    Continuous rainfall sequences are often used as inputs in hydrologic modeling, particularly where a probabilistic assessment is required. Continuous rainfall sequences provide a means for accounting of all aspects of rainfall that produce flooding, for example, not just the design rainfall event but also the rainfall prior to the extreme rainfall event. With the advent of climate change, higher temperatures have been associated with changes in rainfall, in particular intensifying rainfall extremes with less uniform temporal patterns. Given these demonstrated changes to extreme rainfall with temperature rise, there is a need to modify continuous rainfall generators to account for current and likely future changes in temperature. In this work we propose a novel method for simulating continuous rainfall sequences for a future warmer climate by conditioning parameters on their historical sensitivity with temperature. To demonstrate the proposed technique we use a one-dimensional Neyman-Scott Rectangular Pulses model at two locations across Australia. The statistics used in the parameter estimation are conditioned on their historical sensitivity to average monthly temperature to simulate rainfall for a change in temperature. The results are validated by comparing the simulated rainfall against observations originating from differing temperatures and it is shown that the model captures the relative difference in the mean monthly rainfall and monthly maxima. Encouraged by these results we simulate rainfall for higher temperatures and capture expected changes to annual maxima and design temporal patterns for a warmer climate. While we demonstrate our methodology in the simulation of sub-daily rainfall using a specific model, the approach presented here can be applied to all weather generation schemes for projection in a warmer climate.

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

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


    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

  12. Sensitivity of point scale runoff predictions to rainfall resolution

    A. J. Hearman


    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. The bounded random cascade model, parameterized to south western Australian rainfall, 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 partitions water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store are controlled by thresholds. For example, saturation excess is triggered when the soil water content reaches the storage capacity threshold. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and inturn, relating these to average storm intensities. By relating maximum soil infiltration capacities to saturated drainage rates (f*, we were able to split soils into two groups; those where all runoff is a result of infiltration excess alone (f*≤0.2 and those susceptible to both infiltration excess and saturation excess runoff (f*>0.2. 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 soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating saturated drainage rates to average storm intensities (g* and parameter ranges where predicted runoff was dominated by

  13. Rainfall statistics changes in Sicily

    E. Arnone


    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles which can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood prone areas.

    In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends while for longer durations the trends are mainly negative.

    Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the non parametric Mann–Kendall test.

    Particularly, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration while daily rainfall properties have been analyzed in term of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations

  14. Rainfall statistics changes in Sicily

    E. Arnone


    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann–Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall

  15. Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach

    Berti, M.; Martina, M.; Franceschini, S.; Pignone, S.; Simoni, A.; Pizziolo, M.


    resulted in landslides must be considered in the analysis. The result is a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables. The method has been applied to the historical dataset of the Emilia-Romagna Region (Italy). The dataset contains more than 9000 landslide records, for 4141 of which the date of occurrence is reported with a daily accuracy. Among these, 2741 landslides are characterized by a well-defined triggering rainfall (objectively identifiable in terms of duration and intensity) suitable for the analysis. Rainfall that non resulted in landslides account for more than 250000 events. The results clearly show that landslide triggering in the study area is strongly related to rainfall event parameters (duration, intensity, total rainfall) while antecedent rainfall seem to be less important. Moreover, the lines of equal Bayes probability in the rainfall duration- intensity chart are roughly parallel to the regional threshold proposed by Guzzetti et al. (2007), which in our case indicates a landslide probability of about 0.1. The abrupt increase of landslide probability in the duration-intensity plane indicates a radical change of state of the system, proving the existence of a real physical threshold.

  16. Prediction of stormwater particle loads from impervious urban surfaces based on a rainfall detachment index.

    Brodie, I M


    This paper makes use of Non-Coarse Particle (NCP) data collected from three different impervious surfaces in Toowoomba, Australia. NCP is defined as suspended solids less than 500 microm in size. NCP loads (in mg/m(2)) were derived for 24 storms from a galvanized iron roof, a concrete car park and a bitumen road pavement. A scatter plot analysis was used to identify potential correlations between NCP loads and basic rainfall parameters such as rainfall depth and intensity. An exponential-type trend, consistent with many washoff models, was evident between load and average rainfall intensity for all surfaces. However, load data for some storms did not fit this general trend. Various indices, comprising different combinations of basic rainfall parameters, were evaluated as an alternative to rainfall intensity. A composite index, referred to as the Rainfall Detachment Index, was found to be better than average rainfall intensity in explaining a relationship between NCP load and storm rainfall characteristics. The selected rainfall index utilizes 6-minute rainfall intensities and is a variant of the well known Rainfall Erosivity Index (EI30) used for soil erosion estimation.

  17. Probabilistic forecasts based on radar rainfall uncertainty

    Liguori, S.; Rico-Ramirez, M. A.


    The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at

  18. Cascade-based disaggregation of continuous rainfall time series: the influence of climate

    A. Güntner


    Full Text Available Rainfall data of high temporal resolution are required in a multitude of hydrological applications. In the present paper, a temporal rainfall disaggregation model is applied to convert daily time series into an hourly resolution. The model is based on the principles of random multiplicative cascade processes. Its parameters are dependent on (1 the volume and (2 the position in the rainfall sequence of the time interval with rainfall to be disaggregated. The aim is to compare parameters and performance of the model between two contrasting climates with different rainfall generating mechanisms, a semi-arid tropical (Brazil and a temperate (United Kingdom climate. In the range of time scales studied, the scale-invariant assumptions of the model are approximately equally well fulfilled for both climates. The model parameters differ distinctly between climates, reflecting the dominance of convective processes in the Brazilian rainfall and of advective processes associated with frontal passages in the British rainfall. In the British case, the parameters exhibit a slight seasonal variation consistent with the higher frequency of convection during summer. When applied for disaggregation, the model reproduces a range of hourly rainfall characteristics with a high accuracy in both climates. However, the overall model performance is somewhat better for the semi-arid tropical rainfall. In particular, extreme rainfall in the UK is overestimated whereas extreme rainfall in Brazil is well reproduced. Transferability of parameters in time is associated with larger uncertainty in the semi-arid climate due to its higher interannual variability and lower percentage of rainy intervals. For parameter transferability in space, no restrictions are found between the Brazilian stations whereas in the UK regional differences are more pronounced. The overall high accuracy of disaggregated data supports the potential usefulness of the model in hydrological applications

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

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


    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

  20. Downscaled TRMM Rainfall Time-Series for Catchment Hydrology Applications

    Tarnavsky, E.; Mulligan, M.


    Hydrology in semi-arid regions is controlled, to a large extent, by the spatial and temporal distribution of rainfall defined in terms of rainfall depth and intensity. Thus, appropriate representation of the space-time variability of rainfall is essential for catchment-scale hydrological models applied in semi-arid regions. While spaceborne platforms equipped with remote sensing instruments provide information on a range of variables for hydrological modelling, including rainfall, the necessary spatial and temporal detail is rarely obtained from a single dataset. This paper presents a new dynamic model of dryland hydrology, DryMOD, which makes best use of free, public-domain remote sensing data for representation of key variables with a particular focus on (a) simulation of spatial rainfall fields and (b) the hydrological response to rainfall, particularly in terms of rainfall-runoff partitioning. In DryMOD, rainfall is simulated using a novel approach combining 1-km spatial detail from a climatology derived from the TRMM 2B31 dataset (mean monthly rainfall) and 3-hourly temporal detail from time-series derived from the 0.25-degree gridded TRMM 3B42 dataset (rainfall intensity). This allows for rainfall simulation at the hourly time step, as well as accumulation of infiltration, recharge, and runoff at the monthly time step. In combination with temperature, topography, and soil data, rainfall-runoff and soil moisture dynamics are simulated over large dryland regions. In order to investigate the hydrological response to rainfall and variable catchment characteristics, the model is applied to two very different catchments in the drylands of North and West Africa. The results of the study demonstrate the use of remote sensing-based estimates of precipitation intensity and volume for the simulation of critical hydrological parameters. The model allows for better spatial planning of water harvesting activities, as well as for optimisation of agricultural activities

  1. Rainfall Characterization In An Arid Area

    Bazaraa, A. S.; Ahmed, Shamim


    The objective of this work is to characterize the rainfall in Doha which lies in an arid region. The rainfall data included daily rainfall depth since 1962 and the hyetographs of the individual storms since 1976. The rainfall is characterized by high variability and severe thunderstorms which are of limited geographical extent. Four probability distributions were used to fit the maximum rainfall in 24 hours and the annual rainfall depth. The extreme value distribution was found to have the be...

  2. On the sensitivity of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager channels to overland rainfall

    You, Yalei; Liu, Guosheng; Wang, Yu; Cao, Jie


    , and the V37 or V21 channel becomes the top responder to surface rain as the amount of hydrometeors in the atmospheric column reaches very high values. Additionally, it is found that land surface type and 2 m air temperature have significant skills in characterizing rain cloud types, so that the V19-V37 channel is more sensitive to surface rainfall for more vegetated warm surface, while the V85 channel is more sensitive to cold bare land. This finding implies that the above two parameters may be used to prioritize satellite observations at different channels, so that the channel that has the best rainfall sensitivity under a given condition receives the highest weight in retrieval algorithms.

  3. Rainfall spatiotemporal variability relation to wetlands hydroperiods

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


    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

  4. Investigation on rainfall extremes events trough a geoadditive model

    Bocci, C.; Caporali, E.; Petrucci, A.; Rossi, G.


    Rainfall can be considered a very important variable, and rainfall extreme events analysis of great concern for the enormous impacts that they may have on everyday life particularly when related to intense rainfalls and floods, and hydraulic risk management. On the catchment area of Arno River in Tuscany, Central Italy, a geoadditive mixed model of rainfall extremes is developed. Most of the territory of Arno River has suffered in the past of many severe hydro-geological events, with high levels of risk due to the vulnerability of a unique artistic and cultural heritage. The area has a complex topography that greatly influences the precipitation regime. The dataset is composed by the time series of the annual maxima of daily rainfall recorded in about 400 rain gauges, spatially distributed over the catchment area of about 8.800 km2. The record period covers mainly the second half of 20th century. The rainfall observations are assumed to follow generalized extreme value distributions whose locations are spatially dependent and where the dependence is captured using a geoadditive model. In particular, since rainfall has a natural spatial domain and a significant spatial variability, a spatial hierarchical model for extremes is used. The spatial hierarchical models, in fact, take into account data from all locations, borrowing strength from neighbouring locations when they estimate parameters and are of great interest when small set of data is available, as in the case of rainfall extreme values. Together with rain gauges location variables further physiographic variables are investigated as explanation variables. The implemented geoadditive mixed model of spatially referenced time series of rainfall extreme values, is able to capture the spatial dynamics of the rainfall extreme phenomenon. Since the model shows evidence of a spatial trend in the rainfall extreme dynamic, the temporal dynamic and the time influence can be also taken into account. The implemented

  5. Rainfall time series synthesis from queue scheduling of rain event fractals over radio links

    Alonge, Akintunde A.; Afullo, Thomas J.


    Rainfall attenuation over wireless networks stems from random fluctuations in the natural process of arriving rainfall rates over radio links. This arrival process results in discernible rainfall traffic pattern which manifests as naturally scheduled and queue-generated rain spikes. Hence, the phenomenon of rainfall process can be approached as a semi-Markovian queueing process, with event characteristics dependent on queue parameters. However, a constraint to this approach is the knowledge of the physical characteristics of queue-generated rain spikes. Therefore, this paper explores the probability theory and descriptive mathematics of rain spikes in rainfall processes. This investigation presents the synthesis of rainfall queue with rain spikes at subtropical and equatorial locations of Durban (29°52'S, 30°58'E) and Butare (2°36'S, 29°44'E), respectively. The resulting comparative analysis of rainfall distributions, using error analysis at both locations, reveals that queue-generated rainfall compares well with measured rainfall data set. This suggests that the time-varying process of rainfall, though stochastic, can be synthesized via queue scheduling with the application of relevant queue parameters at any location.

  6. Rainfall variability modelling in Rwanda

    Nduwayezu, E.; Kanevski, M.; Jaboyedoff, M.


    Support to climate change adaptation is a priority in many International Organisations meetings. But is the international approach for adaptation appropriate with field reality in developing countries? In Rwanda, the main problems will be heavy rain and/or long dry season. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). The spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front » mechanism. The torrential rainfall that occurs every year in Rwanda disturbs the circulation for many days, damages the houses and, more seriously, causes heavy losses of people. All districts are affected by bad weather (heavy rain) but the costs of such events are the highest in mountains districts. The objective of the current research is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. The research will include rainfalls variability mapping and probabilistic analyses of extreme events.

  7. Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

    Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka


    Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our

  8. Demography of Verreaux's sifaka in a stochastic rainfall environment.

    Lawler, Richard R; Caswell, Hal; Richard, Alison F; Ratsirarson, Joelisoa; Dewar, Robert E; Schwartz, Marion


    In this study, we use deterministic and stochastic models to analyze the demography of Verreaux's sifaka (Propithecus verreauxi verreauxi) in a fluctuating rainfall environment. The model is based on 16 years of data from Beza Mahafaly Special Reserve, southwest Madagascar. The parameters in the stage-classified life cycle were estimated using mark-recapture methods. Statistical models were evaluated using information-theoretic techniques and multi-model inference. The highest ranking model is time-invariant, but the averaged model includes rainfall-dependence of survival and breeding. We used a time-series model of rainfall to construct a stochastic demographic model. The time-invariant model and the stochastic model give a population growth rate of about 0.98. Bootstrap confidence intervals on the growth rates, both deterministic and stochastic, include 1. Growth rates are most elastic to changes in adult survival. Many demographic statistics show a nonlinear response to annual rainfall but are depressed when annual rainfall is low, or the variance in annual rainfall is high. Perturbation analyses from both the time-invariant and stochastic models indicate that recruitment and survival of older females are key determinants of population growth rate.

  9. Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

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


    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.


    Serkan ŞENOCAK


    Full Text Available The scope of this study is to develop a rainfall intensity-duration-frequency (IDF equation for some return periods at Erzurum rainfall station. The maximum annual rainfall values for 5, 10, 15, 30 and 60 minutes are statistically analyzed for the period 1956 – 2004 by using some statistical distributions such as the Generalized Extreme Values (GEV, Gumbel, Normal, Two-parameter Lognormal, Three-parameter Lognormal, Gamma, Pearson type III and Log-Pearson type III distributions. ?2 goodness-of-fit test was used to choose the best statistical distribution among all distributions. IDF equation constants and coefficients of correlation (R for each emprical functions are calculated using nonlinear estimation method for each return periods (T = 2, 5, 10, 25, 50, 75 and 100 years. The most suitable IDF equation is observed that ( B max i (t = A/ t + C , except for T=100 years, because of the highest coefficients of correlation.

  11. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen


    ... and the rainfall uniformity was evaluated using the Christiansen Uniformity Coefficient (CU). Simultaneously, factors influencing the spatial uniformity of natural rainfall, including the average rainfall accumulation (RA...

  12. Rainfall-runoff properties of tephra: Simulated effects of grain-size and antecedent rainfall

    Jones, Robbie; Thomas, Robert E.; Peakall, Jeff; Manville, Vern


    Rain-triggered lahars (RTLs) are a significant and often persistent secondary volcanic hazard at many volcanoes around the world. Rainfall on unconsolidated volcaniclastic material is the primary initiation mechanism of RTLs: the resultant flows have the potential for large runout distances (> 100 km) and present a substantial hazard to downstream infrastructure and communities. RTLs are frequently anticipated in the aftermath of eruptions, but the pattern, timing and scale of lahars varies on an eruption-by-eruption and even catchment-by-catchment basis. This variability is driven by a set of local factors including the grain size distribution, thickness, stratigraphy and spatial distribution of source material in addition to topography, vegetation coverage and rainfall conditions. These factors are often qualitatively discussed in RTL studies based on post-eruption lahar observations or instrumental detections. Conversely, this study aims to move towards a quantitative assessment of RTL hazard in order to facilitate RTL predictions and forecasts based on constrained rainfall, grain size distribution and isopach data. Calibrated simulated rainfall and laboratory-constructed tephra beds are used within a repeatable experimental set-up to isolate the effects of individual parameters and to examine runoff and infiltration processes from analogous RTL source conditions. Laboratory experiments show that increased antecedent rainfall and finer-grained surface tephra individually increase runoff rates and decrease runoff lag times, while a combination of these factors produces a compound effect. These impacts are driven by increased residual moisture content and decreased permeability due to surface sealing, and have previously been inferred from downstream observations of lahars but not identified at source. Water and sediment transport mechanisms differ based on surface grain size distribution: a fine-grained surface layer displayed airborne remobilisation

  13. Stochastic generation of daily rainfall events based on rainfall pattern classification and Copula-based rainfall characteristics simulation

    Xu, Y. P.; Gao, C.


    To deal with the problem of having no or insufficiently long rainfall record, developing a stochastic rainfall model is very essential. This study first proposed a stochastic model of daily rainfall events based on classification and simulation of different rainfall patterns, and copula-based joint simulation of rainfall characteristics. Compared with current stochastic rainfall models, this new model not only keeps the dependence structure of rainfall characteristics by using copula functions, but also takes various rainfall patterns that may cause different hydrological responses to watershed into consideration. In order to determine the appropriate number of representative rainfall patterns in an objective way, we also introduced clustering validation measures to the stochastic model. Afterwards, the developed stochastic rainfall model is applied to 39 gauged meteorological stations in Zhejiang province, East China, and is then extended to ungauged stations for validation by applying the self-organizing map (SOM) method. The final results show that the 39 stations can be classified into seven regions that further fall into three categories based on rainfall generation mechanisms, i.e., plum-rain control region, typhoon-rain control region and typhoon-plum-rain compatible region. Rainfall patterns of each station can be classified into five or six types based on clustering validation measures. This study shows that the stochastic rainfall model is robust and can be applied to both gauged and ungauged stations for generating long rainfall record.

  14. Satellite rainfall retrieval by logistic regression

    Chiu, Long S.


    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.

  15. Impact of rainfall temporal resolution on urban water quality modelling performance and uncertainties.

    Manz, Bastian Johann; Rodríguez, Juan Pablo; Maksimović, Cedo; McIntyre, Neil


    A key control on the response of an urban drainage model is how well the observed rainfall records represent the real rainfall variability. Particularly in urban catchments with fast response flow regimes, the selection of temporal resolution in rainfall data collection is critical. Furthermore, the impact of the rainfall variability on the model response is amplified for water quality estimates, as uncertainty in rainfall intensity affects both the rainfall-runoff and pollutant wash-off sub-models, thus compounding uncertainties. A modelling study was designed to investigate the impact of altering rainfall temporal resolution on the magnitude and behaviour of uncertainties associated with the hydrological modelling compared with water quality modelling. The case study was an 85-ha combined sewer sub-catchment in Bogotá (Colombia). Water quality estimates showed greater sensitivity to the inter-event variability in rainfall hyetograph characteristics than to changes in the rainfall input temporal resolution. Overall, uncertainties from the water quality model were two- to five-fold those of the hydrological model. However, owing to the intrinsic scarcity of observations in urban water quality modelling, total model output uncertainties, especially from the water quality model, were too large to make recommendations for particular model structures or parameter values with respect to rainfall temporal resolution.

  16. Intraseasonal Variability of Summer Monsoon Rainfall and Droughts over Central India

    Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani


    Rainfall over Madhya Pradesh (MP) in central India has large intra-seasonal variability causing droughts and floods in many years. In this study, rainfall variability in daily and monthly scale over central India has been examined using observed data. Consistency among various datasets such as rainfall, surface temperature, soil moisture and evapotranspiration has been examined. These parameters are from various different sources and critical for drought monitoring and prediction. It is found that during weak phases of monsoon, central India receives deficit rainfall with weaker monsoon circulation. This phase is characterized by an anticyclonic circulation at 850 hPa centered on MP. The EOF analysis of daily rainfall suggests that the two leading modes explain about 23-24% of rainfall variability in intraseasonal timescale. These two modes represent drought/flood conditions over MP. Relationship of weak phases of rainfall over central India with real-time multivariate (RMM) indices of Madden Julian Oscillation (MJO) has been examined. It is found that RMM-6, RMM-7, RMM-1 and RMM-2 describe the weak monsoon conditions over central India. However, frequency of drought occurrence over MP is more during RMM-7 phase. Surface temperature increases by about 0.5°-1° during weak phases of rainfall over this region. Soil moisture and evapotranspiration gradually reduce when rainfall reduces over the study region. Soil moisture and evapotranspiration anomalies have positive pattern during good rainfall events over central India and gradually reduce and become negative anomalies during weak phases.

  17. Rainfall-runoff mechanisms on a hill-island

    Frederiksen, Rasmus Rumph; Rasmussen, Keld Rømer; Christensen, Steen

    - map the shallow subsurface in more detail - choose appropriate locations for further monitoring of discharge at different spatial scales - monitor hydraulic head variations and quantify hydraulic parameters - build a model for analysis of rainfall-runoff processes in this particular hydrogeological...

  18. Physically based modelling of rainfall-runoff processes

    Diermanse, F.L.M.


    This PhD. research was set up to investigate the use of rainfall-runoff models for simulation of high water events in hillslope areas. First, dominant parameters for runoff production during high water events have been identified. Subsequently, the influence of antecedent conditions on runoff percen

  19. Preliminary results on uncertainties in rainfall interception estimation

    Muzylo, A.; Llorens, P.; Domingo, F.; Valente, Fe.; Beven, K.; Gallart, F.


    This work deals with some aspects of rainfall interception estimation uncertainty in a deciduous forest. The importance of interception loss measurement error is stressed. Confidence limits of Rutter original and sparse interception model parameters obtained from regressions for leafed and leafless period are presented, as well as free throughfall coefficient variability with event weather conditions. (Author) 8 refs.

  20. Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method

    J. Huang


    Full Text Available Rainfall-induced landslides not only cause property loss, but also kill and injure large numbers of people every year in mountainous areas in China. These losses and casualties may be avoided to some extent with rainfall threshold values used in an early warning system at a regional scale for the occurrence of landslides. However, the limited availability of data always causes difficulties. In this paper we present a method to calculate rainfall threshold values with limited data sets for the two rainfall parameters: maximum hourly rainfall intensity and accumulated precipitation. The method has been applied to the Huangshan region, in Anhui Province, China. Four early warning levels (Zero, Outlook, Attention, and Warning have been adopted and the corresponding rainfall threshold values have been defined by probability lines. A validation procedure showed that this method can significantly enhance the effectiveness of a warning system, and finally reduce the risk from shallow landslides in mountainous regions.

  1. A Case Study of Bivariate Rainfall Frequency Analysis Using Copula in South Korea

    Joo, K.; Shin, J.; Kim, W.; Heo, J.


    For a given rainfall event, it can be characterized into some properties such as rainfall depth (amount), duration, and intensity. By considering these factors simultaneously, the actual phenomenon of rainfall event can be explained better than univariate model. Using bivariate model, rainfall quantiles can be obtained for a given return period without any limitations of specific rainfall duration. For bivariate(depth and duration) frequency analysis, copula model was used in this study. Recently, copula model has been studied widely for hydrological field. And it is more flexible for marginal distribution than other conventional bivariate models. In this study, five weather stations are applied for frequency analysis from Korea Meteorological Administration (KMA) which are Seoul, Chuncheon, Gangneung, Wonju, and Chungju stations. These sites have 38 ~ 50 years of hourly precipitation data. Inter-event time definition is used for identification of rainfall events. And three copula models (Gumbel-Hougaard, Frank, and Joe) are applied in this study. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula (θ). The normal, generalized extreme value, Gumbel, 3-parameter gamma, and generalized logistic distributions are examined for marginal distribution. As a result, rainfall quantiles can be obtained for any rainfall durations for a given return period by calculating conditional probability. In addition, rainfall quantiles from copula models are compared to those from univariate model.

  2. Chapman Conference on Rainfall Fields

    Gupta, V. K.

    The Chapman Conference on Rainfall Fields, sponsored by AGU, was the first of its kind; it was devoted to strengthening scientific interaction between the North American and Latin American geophysics communities. It was hosted by Universidad Simon Bolivar and Instituto Internacional de Estudios Avanzados, in Caracas, Venezuela, during March 24-27, 1986. A total of 36 scientists from Latin America, the United States, Canada, and Europe participated. The conference, which was convened by I. Rodriguez-Iturbe (Universidad Simon Bolivar) and V. K. Gupta (University of Mississippi, University), brought together hydrologists, meteorologists, and mathematicians/statisticians in the name of enhancing an interdisciplinary focus on rainfall research.

  3. Rainfall simulation for environmental application

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


    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.

  4. Cost-effective raingauge deployment and rainfall heterogeneity effect on hydrograph simulation in mountainous watersheds

    Huang-Chuan, Jr.; Kao, Shuh-Ji; Chang, Kang-Tsung; Lin, Chuan-Yao; Chang, Pao-Liang


    To what extent hydrograph simulation was influenced by the representativeness of rainfall input were examined in meso-scale subtropical mountainous watersheds, accordingly, cost-effective raingauge deployment was suggested. Two nested watersheds in northern Taiwan and two extreme typhoons with torrential rains were undertaken as case studies. The input of radar rainfall estimates with high spatial resolution of 1.3 km2 served as a reference, which was applied onto hydrograph simulation in TOPMODEL. After calibration, optimal parameters were obtained and fixed to examine effect of deviated rainfall on hydrograph. To mimic possible raingauge networks we designed four raingauge number classes: very low (3 points/total pixels), low (10 points/total), medium (20 points/total), and high (50 points/total) based on radar rainfall for the two watersheds in different size, thus, creating wide spectrum of raingauge density. All the corresponding hydrographs were compared with the reference hydrograph to probe errors in event discharge induced by calculated rainfall input. Results showed that with the decreasing of raingauge density the biases (indicated by RMSE) of rainfall field estimates increase and the potential variability in rainfall field due to random sampling in raingauge location is exaggerated. By contrast, biases in model hydrographs are significantly smaller than that in rainfall field. When the raingauge governing area is <10 km2/gauge, the biased rainfall field shows no detectable effect on hydrographs. Incomparably lower RMSE in hydrograph indicates that surplus and deficit rainfalls at different locations were compensated in model simulation. In term of reliable hydrograph simulation, obviously, the criterion for raingauge density is not as high as that for rainfall estimate. When gauge governing is <20 km2/gauge, both the rainfall and discharge were successfully (±10% error) estimated in term of total volume. Accordingly, we suggested that covering area ~20

  5. Spatial and temporal variability of rainfall erosivity factor for Switzerland

    K. Meusburger


    Full Text Available Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution and temperature (1 h resolution data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc., aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps were significant (p<0.01 predictors. The mean value of long-term rainfall erosivity is 1330 MJ mm ha−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter months. Swiss-wide the month May to October show significantly increasing trends of rainfall erosivity for the observed period (p<0.005. Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01. The increasing trends of rainfall erosivity in May, September and October when vegetation cover is scarce are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.

  6. Synthesis of rainfall time series in a high temporal resolution

    Callau Poduje, Ana Claudia; Haberlandt, Uwe


    In order to optimize the design and operation of urban drainage systems, long and continuous rain series in a high temporal resolution are essential. As the length of the rainfall records is often short, particularly the data available with the temporal and regional resolutions required for urban hydrology, it is necessary to find some numerical representation of the precipitation phenomenon to generate long synthetic rainfall series. An Alternating Renewal Model (ARM) is applied for this purpose, which consists of two structures: external and internal. The former is the sequence of wet and dry spells, described by their durations which are simulated stochastically. The internal structure is characterized by the amount of rain corresponding to each wet spell and its distribution within the spell. A multivariate frequency analysis is applied to analyze the internal structure of the wet spells and to generate synthetic events. The stochastic time series must reproduce the statistical characteristics of observed high resolution precipitation measurements used to generate them. The spatio-temporal interdependencies between stations are addressed by resampling the continuous synthetic series based on the Simulated Annealing (SA) procedure. The state of Lower-Saxony and surrounding areas, located in the north-west of Germany is used to develop the ARM. A total of 26 rainfall stations with high temporal resolution records, i.e. rainfall data every 5 minutes, are used to define the events, find the most suitable probability distributions, calibrate the corresponding parameters, simulate long synthetic series and evaluate the results. The length of the available data ranges from 10 to 20 years. The rainfall series involved in the different steps of calculation are compared using a rainfall-runoff model to simulate the runoff behavior in urban areas. The EPA Storm Water Management Model (SWMM) is applied for this evaluation. The results show a good representation of the

  7. Spatial and temporal variability of rainfall erosivity factor for Switzerland

    A. Steel


    Full Text Available Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity (R-factor in Switzerland. Time series of 22 yr for rainfall (10 min resolution and temperature (1 h resolution data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Multiple regression was used to interpolate the erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc., aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Alps were significant predictors. The mean value of long-term rainfall erosivity is 1323 MJ mm ha−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter month. Swiss-wide the month May to October show significantly increasing trends of erosivity (p<0.005. Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01. The increasing trends of erosivity in May, September and October when vegetation cover is susceptible are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.

  8. Where do forests influence rainfall?

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


    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.

  9. Long range prediction of Indian summer monsoon rainfall

    A A Munot; K Krishna Kumar


    The search for new parameters for predicting the all India summer monsoon rainfall (AISMR) has been an important aspect of long range prediction of AISMR. In recent years NCEP/NCAR reanalysis has improved the geographical coverage and availability of the data and this can be easily updated. In this study using NCEP/NCAR reanalysis data on temperature, zonal and meridional wind at different pressure levels, few predictors are identified and a prediction scheme is developed for predicting AISMR. The regression coeffcients are computed by stepwise multiple regression procedure. The final equation explained 87% of the variance with multiple correlation coeffcient (MCC), 0.934. The estimated rainfall in the El-Nino year of 1997 was -1.7% as against actual of 4.4%. The estimated rainfall deficiency in both the recent deficient years of 2002 and 2004 were -19.5% and -8.5% as against observed -20.4% and -11.5% respectively.

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

    Thayakaran, R; Ramesh, N I


    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.

  11. Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees)

    Abancó, Clàudia; Hürlimann, Marcel; Moya, José; Berenguer, Marc


    Torrential flows like debris flows or debris floods are fast movements formed by a mix of water and different amounts of unsorted solid material. They generally occur in steep torrents and pose high risk in mountainous areas. Rainfall is their most common triggering factor and the analysis of the critical rainfall conditions is a fundamental research task. Due to their wide use in warning systems, rainfall thresholds for the triggering of torrential flows are an important outcome of such analysis and are empirically derived using data from past events. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, rainfall data of 25 torrential flows ("TRIG rainfalls") were recorded, with a 5-min sampling frequency. Other 142 rainfalls that did not trigger torrential flows ("NonTRIG rainfalls") were also collected and analyzed. The goal of this work was threefold: (i) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential flows and others that did not; (ii) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment by with different techniques; (iii) analyze how the criterion used for defining the rainfall duration and the spatial variability of rainfall influences the value obtained for the thresholds. The statistical analysis of the rainfall characteristics showed that the parameters that discriminate better the TRIG and NonTRIG rainfalls are the rainfall intensities, the mean rainfall and the total rainfall amount. The antecedent rainfall was not significantly different between TRIG and NonTRIG rainfalls, as it can be expected when the source material is very pervious (a sandy glacial soil in the study site). Thresholds were derived from data collected at one rain gauge located inside the catchment. Two different methods were applied to calculate the duration and intensity of rainfall: (i) using total duration, Dtot

  12. Prediction of Rainfall-Induced Landslides

    Nadim, F.; Sandersen, F.


    -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.

  13. Comparison of different types of medium scale field rainfall simulators

    Dostál, Tomáš; Strauss, Peter; Schindewolf, Marcus; Kavka, Petr; Schmidt, Jürgen; Bauer, Miroslav; Neumann, Martin; Kaiser, Andreas; Iserloh, Thomas


    Rainfall simulators are used in numerous experiments to study runoff and soil erosion characteristics. However, they usually differ in their construction details, rainfall generation, plot size and other technical parameters. As field experiments using medium to large scale rainfall simulators (plot length 3 - 8 m) are very much time and labor consuming, close cooperation of individual teams and comparability of results is highly desirable to enlarge the database of results. Two experimental campaigns were organized to compare three field rainfall simulators of similar scale (plot size), but with different technical parameters. The results were then compared, to identify parameters that are crucial for soil loss and surface runoff formation and test if results from individual devices can be reliably compared. The rainfall simulators compared were: field rainfall simulator of CTU Prague (the Czech Republic) (Kavka et al., 2012; EGU2015-11025), field simulator of BAW (Austria) (Strauss et al., 2002) and field simulator of TU Bergakademie Freiberg (Germany) (Schindewolf & Schmidt 2012). The device of CTU Prague is usually applied to a plot size of 9,5 x 2 m employing 4 nozzles SS Full Jet 40WSQ mounted on folding arm, working pressure is 0.8 bar, height of nozzles is 2.65 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The rainfall simulator of BAW is constructed as a modular system, which is usually applied for a length of 5 m (area 2 x 5 m), using 6 nozzles SS Full Jet 40WSQ. Usual working pressure is 0.25 bar. Elevation of nozzles is 2.6 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The device of TU Bergakademie Freiberg is also standard modular system, working usually with a plot size of 3 x 1 m, using 3 oscillating VeeJet 80/100 nozzles with an usual operating pressure of 0.5 bar. Intensity is regulated by the frequency of sweeps above

  14. Rainfall intensity characteristics at coastal and high altitude stations in Kerala

    V Sasi Kumar; S Sampath; P V S S K Vinayak; R Harikumar


    Rainfall intensities measured at a few stations in Kerala during 2001 –2005 using a disdrometer were found to be in reasonable agreement with the total rainfall measured using a manual rain gauge. The temporal distributions of rainfall intensity at different places and during different months show that rainfall is of low intensity (> 10 mm/hr),65%to 90%of the time.This could be an indication of the relative prevalence of stratiform and cumuliform clouds.Rainfall was of intensity > 5 mm/hr for more than 95%of the time in Kochi in July 2002,which was a month seriously deficient in rainfall,indicating that the deficiency was probably due to the relative absence of cumuliform clouds.Cumulative distribution graphs are also plotted and fitted with the Weibull distribution.The fit parameters do not appear to have any consistent pattern. The higher intensities also contributed signi ficantly to total rainfall most of the time,except in Munnar (a hill station). In this analysis also,the rainfall in Kochi in July 2002 was found to have less presence of high intensities. This supports the hypothesis that the rainfall de ficiency was probably caused by the absence of conditions that favoured the formation of cumuliform clouds.

  15. Applying satellite remote sensing technique in disastrous rainfall systems around Taiwan

    Liu, Gin-Rong; Chen, Kwan-Ru; Kuo, Tsung-Hua; Liu, Chian-Yi; Lin, Tang-Huang; Chen, Liang-De


    Many people in Asia regions have been suffering from disastrous rainfalls year by year. The rainfall from typhoons or tropical cyclones (TCs) is one of their key water supply sources, but from another perspective such TCs may also bring forth unexpected heavy rainfall, thereby causing flash floods, mudslides or other disasters. So far we cannot stop or change a TC route or intensity via present techniques. Instead, however we could significantly mitigate the possible heavy casualties and economic losses if we can earlier know a TC's formation and can estimate its rainfall amount and distribution more accurate before its landfalling. In light of these problems, this short article presents methods to detect a TC's formation as earlier and to delineate its rainfall potential pattern more accurate in advance. For this first part, the satellite-retrieved air-sea parameters are obtained and used to estimate the thermal and dynamic energy fields and variation over open oceans to delineate the high-possibility typhoon occurring ocean areas and cloud clusters. For the second part, an improved tropical rainfall potential (TRaP) model is proposed with better assumptions then the original TRaP for TC rainfall band rotations, rainfall amount estimation, and topographic effect correction, to obtain more accurate TC rainfall distributions, especially for hilly and mountainous areas, such as Taiwan.

  16. Multivariate Analysis of Joint Probability of Different Rainfall Frequencies Based on Copulas

    Yang Wang


    Full Text Available The performance evaluation of a city’s flood control system is essentially based on accurate storm designs, where a particular challenge is the development of the joint distributions of dependent rainfall variables. When it comes to the research design for consecutive rainfall, the analytical investigation is only focused on the maximum of consecutive rainfalls, and it does not consider the probabilistic relations between the first day of rainfall and the overall rainfall included in consecutive rainfall events. In this study, the copula method is used to separate the dependence structure of multi-day rainfall from its marginal distribution and analyse the different impacts of the dependence structure and marginal distribution on system performance. Three one-parameter Archimedean copulas, including the Clayton, Gumbel, and Frank families, are fitted and compared for different combinations of marginal distributions that cannot be rejected by statistical tests. The fitted copulas are used to generate rainfall events for a system performance analysis, including the conditional probability and design values for different return periods. The results obtained in this study highlight the importance of taking into account the dependence structure of one-day and multi-day rainfall in the context of storm design evaluations and reveal the different impacts of the dependence structure and the marginal distributions on the probability.

  17. Stochastic modelling of daily rainfall sequences

    Buishand, T.A.


    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

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

    N. Q. Hung


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

    N. Q. Hung


    Full Text Available The present study developed an artificial neural network (ANN model to overcome the difficulties in training the ANN models with continuous data consisting of rainy and non-rainy days. Among the six models analyzed the ANN model which used generalized feedforward type network and a hyperbolic tangent function and a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness, and the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input for training of the model was found most satisfactory in forecasting rainfall in Bangkok, Thailand. The developed ANN model was applied to derive rainfall forecast from 1 to 6 h ahead at 75 rain gauge stations in the study area as forecast point from the data of 3 consecutive years (1997–1999. Results were highly satisfactory for rainfall forecast 1 to 3 h ahead. Sensitivity analysis indicated that the most important input parameter beside rainfall itself is the wet bulb temperature in forecasting rainfall. Based on these results, it is recommended that the developed ANN model can be used for real-time rainfall forecasting and flood management in Bangkok, Thailand.

  20. Spatial variability and rainfall characteristics of Kerala

    Anu Simon; K Mohankumar


    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 receive more rainfall than stations south of 10°N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period, whereas stations falling in Group II receive 25-30% of annual rainfall during the pre-monsoon and the north-east monsoon periods. The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also clearly brought out by the study.

  1. Simulation of mosquitoes population dynamic based on rainfall and average daily temperature

    Widayani, H.; Seprianus, Nuraini, N.; Arum, J.


    This paper proposed rainfall and average daily temperature approximation functions using least square method with trigonometry polynomial. Error value from this method is better than Fast Fourier Transform method. This approximation is used to accommodate climatic factors into deterministic model of mosquitoes population by constructing a carrying capacity function which contains rainfall and average daily temperature functions. We develop a mathematical model for mosquitoes population dynamic which formulated by Yang et al (2010) with dynamic parameter of a daily rainfall as well as temperature on that model. Two fixed points, trivial and non-trivial, are obtained when constant entomological parameters assumed. Basic offspring number, Q0 as mosquitoes reproduction parameter is constructed. Non-trivial fixed point is stable if and only if Q0 > 1. Numerical simulation shown the dynamics of mosquitoes population significantly affected by rainfall and average daily temperature function.

  2. Rainfall estimation using raingages and radar — A Bayesian approach: 1. Derivation of estimators

    Seo, D.-J.; Smith, J. A.


    Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field. The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily evaluated by numerically integrating two single integrals. To reduce computational burden associated with evaluating sufficient statistics for the likelihood function, an approximate form of parameter updating is given. Also, as a further approximation, the parameters are updated using raingage measurements only, yielding closed-form expressions for estimate and estimation variance in the Gaussian domain. With a reduction in the number of radar rainfall data in constructing covariance matrices, computational requirements for the estimation procedures are not significantly greater than those for simple co-kriging. Given their generality, the estimation procedures constructed in this work are considered to be applicable in various estimation problems involving an undersampled main variable and a densely sampled auxiliary variable.

  3. [Local sensitivity and its stationarity analysis for urban rainfall runoff modelling].

    Lin, Jie; Huang, Jin-Liang; Du, Peng-Fei; Tu, Zhen-Shun; Li, Qing-Sheng


    Sensitivity analysis of urban-runoff simulation is a crucial procedure for parameter identification and uncertainty analysis. Local sensitivity analysis using Morris screening method was carried out for urban rainfall runoff modelling based on Storm Water Management Model (SWMM). The results showed that Area, % Imperv and Dstore-Imperv are the most sensitive parameters for both total runoff volume and peak flow. Concerning total runoff volume, the sensitive indices of Area, % Imperv and Dstore-Imperv were 0.46-1.0, 0.61-1.0, -0.050(-) - 5.9, respectively; while with respect to peak runoff, they were 0.48-0.89, 0.59-0.83, 0(-) -9.6, respectively. In comparison, the most sensitive indices (Morris) for all parameters with regard to total runoff volume and peak flow appeared in the rainfall event with least rainfall; and less sensitive indices happened in the rainfall events with heavier rainfall. Furthermore, there is considerable variability in sensitive indices for each rainfall event. % Zero-Imperv's coefficient variations have the largest values among all parameters for total runoff volume and peak flow, namely 221.24% and 228.10%. On the contrary, the coefficient variations of conductivity among all parameters for both total runoff volume and peak flow are the smallest, namely 0.

  4. Development of a Compound Distribution Markov Chain Model for Stochastic Generation of Rainfall with Long Term Persistence

    Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George


    One of the overriding issues in the rainfall simulation is the underestimation of observed rainfall variability in longer timescales (e.g. monthly, annual and multi-year), which usually results into under-estimation of reservoir reliability in urban water planning. This study has developed a Compound Distribution Markov Chain (CDMC) model for stochastic generation of daily rainfall. We used two parameters of Markov Chain process (transition probabilities of wet-to-wet and dry-to-dry days) for simulating rainfall occurrence and two parameters of gamma distribution (calculated from mean and standard deviation of wet-day rainfall) for simulating wet-day rainfall amounts. While two models with deterministic parameters underestimated long term variability, our investigation found that the long term variability of rainfall in the model is predominantly governed by the long term variability of gamma parameters, rather than the variability of Markov Chain parameters. Therefore, in the third approach, we developed the CDMC model with deterministic parameters of Markov Chain process, but stochastic parameters of gamma distribution by sampling the mean and standard deviation of wet-day rainfall from their log-normal and bivariate-normal distribution. We have found that the CDMC is able to replicate both short term and long term rainfall variability, when we calibrated the model at two sites in east coast of Australia using three types of daily rainfall data - (1) dynamically downscaled, 10 km resolution gridded data produced by NSW/ACT Regional Climate Modelling project, (2) 5 km resolution gridded data by Australian Water Availability Project and (3) point scale raingauge stations data by Bureau of Meteorology, Australia. We also examined the spatial variability of parameters and their link with local orography at our field site. The suitability of the model in runoff generation and urban reservoir-water simulation will be discussed.

  5. Interannual variation in root production in grasslands affected by artificially modified amount of rainfall.

    Fiala, Karel; Tůma, Ivan; Holub, Petr


    The effect of different amounts of rainfall on the below-ground plant biomass was studied in three grassland ecosystems. Responses of the lowland (dry Festuca grassland), highland (wet Cirsium grassland), and mountain (Nardus grassland) grasslands were studied during five years (2006-2010). A field experiment based on rainout shelters and gravity irrigation simulated three climate scenarios: rainfall reduced by 50% (dry), rainfall increased by 50% (wet), and the natural rainfall of the current growing season (ambient). The interannual variation in root increment and total below-ground biomass reflected the experimentally manipulated amount of precipitation and also the amount of current rainfall of individual years. The effect of year on these below-ground parameters was found significant in all studied grasslands. In comparison with dry Festuca grassland, better adapted to drought, submontane wet Cirsium grassland was more sensitive to the different water inputs forming rather lower amount of below-ground plant matter at reduced precipitation.

  6. Interannual Variation in Root Production in Grasslands Affected by Artificially Modified Amount of Rainfall

    Karel Fiala


    Full Text Available The effect of different amounts of rainfall on the below-ground plant biomass was studied in three grassland ecosystems. Responses of the lowland (dry Festuca grassland, highland (wet Cirsium grassland, and mountain (Nardus grassland grasslands were studied during five years (2006–2010. A field experiment based on rainout shelters and gravity irrigation simulated three climate scenarios: rainfall reduced by 50% (dry, rainfall increased by 50% (wet, and the natural rainfall of the current growing season (ambient. The interannual variation in root increment and total below-ground biomass reflected the experimentally manipulated amount of precipitation and also the amount of current rainfall of individual years. The effect of year on these below-ground parameters was found significant in all studied grasslands. In comparison with dry Festuca grassland, better adapted to drought, submontane wet Cirsium grassland was more sensitive to the different water inputs forming rather lower amount of below-ground plant matter at reduced precipitation.

  7. Variability of raindrop size distributions in a squall line and implications for radar rainfall estimation

    Uijlenhoet, R.; Steiner, M.; Smith, J.A.


    The intrastorm variability of raindrop size distributions as a source of uncertainty in single-parameter and dual-parameter radar rainfall estimates is studied using time series analyses of disdrometer observations. Two rain-rate (R) estimators are considered: the traditional single-parameter

  8. Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

    Friedel, M.J.


    A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

  9. Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System

    Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum


    ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i

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

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


    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%.

  11. Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

    Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.


    In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

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

    Zakaria, Roslinazairimah; Moslim, Nor Hafizah


    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.

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

    S. Salsón


    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.

  14. First flush characteristics of rainfall runoff from a paddy field in the Taihu Lake watershed, China.

    Li, Songmin; Wang, Xiaoling; Qiao, Bin; Li, Jiansheng; Tu, Jiamin


    Nonpoint storm runoff remains a major threat to surface water quality in China. As a paddy matures, numerous fertilizers are needed, especially in the rainy seasons; the concentration of nitrogen and phosphorus in rainfall runoff from farmland is much higher than at other times, and this poses a great threat to water bodies and is the main reason for water eutrophication, especially in high concentration drainages. To date, most studies regarding the characteristics of pollutants in rainfall runoff have mainly been concentrated on urban runoff and watershed runoff; therefore, it is particularly important to investigate the characteristics of nitrogen and phosphorus loss in rainfall runoff from paddy fields. To study the characteristics of nitrogen and phosphorus loss and whether the first flush effect exists, continuous monitoring of the rainfall runoff process of six rainfall events was conducted in 2013, of which four rainfall events during storm, high, middle, and low intensity rainfalls were analyzed, and runoff and quality parameters, such as suspended solids (SS), total nitrogen (TN), ammonium nitrogen (NH4(+)-N), nitrate nitrogen (NO3(-)-N), total phosphorus (TP), and phosphate (PO4(3-)-P), were analyzed to determine the relationship between runoff and water quality. The paddy field is located north of Wuxi Lake Basin along the Hejia River upstream in Zhoutie town, Yixing city. An analysis of the load distribution during rainfall runoff was conducted. Event mean concentration (EMC) was used to evaluate the pollution situation of the paddy field's rainfall runoff. A curve of the dimensionless normalized cumulative load (L) vs. normalized cumulative flow (F) (L-F curve), the probability of the mass first flush (MFFn), and the pollutants carried by the initial 25% of runoff (FF25) were used to analyze the first flush effect of the paddy field runoff, and different contaminants show different results: the concentration of nitrogen and phosphorus fluctuate and

  15. Exploring Aerosol Effects on Rainfall for Brisbane, Australia

    Michael Hewson


    Full Text Available The majority of studies assessing aerosol effects on rainfall use coarse spatial scale (1° latitude/longitude or more and multi-seasonal or decadal data sets. Here, we present results from a spatial correlation of aerosol size distribution and rain rate for selected stratiform and cumuliform precipitation events. The chemistry transport version of the Weather Research and Forecasting model was used to estimate aerosol parameters during rain events Aerosol maps were then compared with observations of rainfall using geostatistics for the first time. The cross-variogram analysis showed that anthropogenic aerosol was associated with areas of less intense rain within the stratiform system studied. For cumuliform systems, cross-variogram analysis found that anthropogenic emissions may be associated with enhanced rain downwind of aerosol emissions. We conclude that geostatistics provides a promising new technique to investigate relationships between aerosols and rainfall at spatial scales of 1 km which complements more commonly used methods to study aerosol effects on rainfall.

  16. Identification of homogeneous rainfall regimes in parts of Western Ghats region of Karnataka

    B Venkatesh; Mathew K Jose


    In view of the ongoing environmental and ecological changes in the Western Ghats, it is important 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, afforestation and eco-system management. Therefore, it is essential to understand rainfall distribution and its variation in relevance to such activities. The present study is an attempt to gain in-depth understanding in this direction. The study area comprises of one coastal district and its adjoining areas in Karnataka State. Mean annual rainfall data of 93 rain gauge stations distributed over the study area for a period of 10–50 years are used for the study. In order to assess the variation of rainfall across the ghats, several bands were constructed parallel to the latitudes to facilitate the analysis. The statistical analyses conducted included cluster analysis and analysis of variance. The study revealed that there exist three distinct zones of rainfall regimes in the study area, namely, Coastal zone, Transition zone and Malanad zone. It is observed that, the maximum rainfall occurs on the windward side ahead of the geographical peak. Further, mean monthly rainfall distribution over the zones has been depicted to enable agricultural planning in the study area.

  17. Urban rainfall estimation employing commercial microwave links

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


    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.

  18. A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

    Lazri, Mourad; Ameur, Soltane


    In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

  19. The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

    Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.


    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

  20. Generation of future high-resolution rainfall time series with a disaggregation model

    Müller, Hannes; Haberlandt, Uwe


    High-resolution rainfall data are needed in many fields of hydrology and water resources management. For analyzes of future rainfall condition climate scenarios exist with hourly values of rainfall. However, the direct usage of these data is associated with uncertainties which can be indicated by comparisons of observations and C20 control runs. An alternative is the derivation of changes of rainfall behavior over the time from climate simulations. Conclusions about future rainfall conditions can be drawn by adding these changes to observed time series. A multiplicative cascade model is used in this investigation for the disaggregation of daily rainfall amounts to hourly values. Model parameters can be estimated by REMO rainfall time series (UBA-, BfG- and ENS-realization), based on ECHAM5. Parameter estimation is carried out for C20 period as well as near term and long term future (2021-2050 and 2071-2100). Change factors for both future periods are derived by parameter comparisons and added to the parameters estimated from observed time series. This enables the generation of hourly rainfall time series from observed daily values with respect to future changes. The investigation is carried out for rain gauges in Lower Saxony. Generated Time series are analyzed regarding statistical characteristics, e.g. extreme values, event-based (wet spell duration and amounts, dry spell duration, …) and continuum characteristics (average intensity, fraction of dry intervals,…). The generation of the time series is validated by comparing the changes in the statistical characteristics from the REMO data and from the disaggregated data.

  1. Investigating and predicting landslides using a rainfall-runoff model in Southern Norway

    Kråbøl, Eline Haga


    Landslides are amongst the most destructive natural hazards, causing damage to infrastructures, such as roads, railways and houses, and can, in a worst-case scenario, take lives. By studying the effect and response of rainfall using the temporal and spatial distribution of the storage and discharge, a better understanding of landslide processes and a more detailed prediction can be possible. This study employs a parameter-parsimonious rainfall-runoff model, the Distance Distribution model (DD...

  2. Rainfall Climatology of the US Based on a Multifractal Storm Model

    Lepore, C.; Molini, A.; Veneziano, D.; Yoon, S.


    Whether the multifractal properties of rainfall are impacted by climatology and therefore deviate from universality is a vexing question in both hydrology and the climate sciences and a crucial issue for rainfall downscaling applications. In a recent paper, Veneziano and Lepore (The Scaling of Temporal Rainfall, WRR, 2012) suggested a rainfall model with alternating storms and dry inter-storm periods and beta-lognormal multifractal rainfall intensity inside the storms. The parameters of the model are the rate of storm arrivals λ , the mean value mD and coefficient of variation VD of storm duration, the mean rainfall intensity inside the storms mI, and the multifractal parameters Cβ (lacunarity), CLN (intermittency), and dmax (outer limit of the scaling range). We use this model and 200 hourly rainfall records from NOAA to describe the variability of intense rainfall over the continental US. The records are selected based on length (at least 25 years) and data quality (quantization, fraction of unavailable values, periods when rainfall is reported as aggregated total depth…). We conclude that CLN and dmax display large systematic variations in space and with season. In particular, CLN decreases as latitude increases, from 0.20-0.25 along the Gulf of Mexico to about 0.12 in New England and 0.08 in the Northwest. This spatial variation is captured in approximation by partitioning the continental US into 11 climatic regions. Seasonal analysis shows that in most regions CLN is highest in the summer and lowest in the winter, following similar variations in the frequency and intensity of convective rainfall. An exception is the Northwest region, where CLN is almost constant throughout the year. The outer scale dmax is negatively correlated with CLN and follows opposite trends. The lacunarity parameter Cβ is lowest (around 0.04) in the Northeast and highest (around 0.07) in Florida and the Midwestern region. Lacunarity tends to be higher in the spring and summer

  3. Empirical rainfall thresholds and copula based IDF curves for shallow landslides and flash floods

    Bezak, Nejc; Šraj, Mojca; Brilly, Mitja; Mikoš, Matjaž


    rainfall data with 5-minute time step where the data series ranged from 11 to 66 years. Gumbel and Gamma distributions were selected to model annual maximums of rainfall intensities and durations, respectively. Method of L-moments was used to estimate the marginal distributions parameters and method of moments was chosen to estimate the Frank copula parameter. Comparison between ID curves and IDF curves constructed using copula approach was also made.

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

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


    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.

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

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


    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.

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

    U. Haberlandt


    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

  7. On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution

    G. Bruni


    Full Text Available Cities are increasingly vulnerable to floods generated by intense rainfall, because of their high degree of imperviousness, implementation of infrastructures, and changes in precipitation patterns due to climate change. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction. In this paper, a detailed study of the sensitivity of urban hydrological response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar for four rainstorms were used as input into a detailed hydrodynamic sewer model for an urban catchment in Rotterdam, the Netherlands. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size, catchment sampling number (rainfall resolution vs. catchment size, runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively. Results show catchment smearing effect for rainfall resolution approaching half the catchment size, i.e. for catchments sampling numbers greater than 0.5 averaged rainfall volumes decrease about 20%. Moreover, deviations in maximum water depths, form 10 to 30% depending on the storm, occur for rainfall resolution close to storm size, describing storm smearing effect due to rainfall coarsening. Model results also show the sensitivity of modelled runoff peaks and maximum water depths to the resolution of the runoff areas and sewer density respectively. Sensitivity to temporal resolution of rainfall input seems low compared to spatial resolution, for the storms analysed in this study. Findings are in agreement with previous studies on natural catchments

  8. An Analysis of Thermally-Related Surface Rainfall Budgets Associated with Convective and Stratiform Rainfall

    ZHOU Yushu; Xiaofan LI


    Both water vapor and heat processes play key roles in producing surface rainfall.While the water vapor effects of sea surface temperature and cloud radiative and microphysical processes on surface rainfall have been investigated in previous studies,the thermal effects on rainfall are analyzed in this study using a series of two-dimensional equilibrium cloud-resolving model experiments forced by zonally-uniform,constant,large-scale zonal wind and zero large-scale vertical velocity.The analysis of thermally-related surface rainfall budget reveals that the model domain mean surface rain rate is primarily associated with the mean infrared cooling rate.Convective rainfall and transport of hydrometeor concentration from convective regions to raining stratiform regions corresponds to the heat divergence over convective regions,whereas stratiform rainfall corresponds to the transport of hydrometeor concentration from convective regions and heat divergence over raining stratiform regions.The heat divergence over convective regions is mainly balanced by the heat convergence over rainfall-free regions,which is,in turn,offset by the radiative cooling over rainfall-free regions.The sensitivity experiments of rainfall to the effects of sea surface temperature and cloud radiative and microphysical processes show that the sea surface temperature and cloud processes affect convective rainfall through the changes in infrared cooling rate over rainfall-free regions and transport rate of heat from convective regions to rainfall-free regions.

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

    Engelbrecht, CJ


    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...

  10. The impacts of the Indian summer rainfall on North China summer rainfall

    Wu, Renguang; Jiao, Yang


    Previous studies have indicated a connection between interannual variations of the Indian and North China summer rainfall. An atmospheric circulation wave pattern over the mid-latitude Asia plays an important role in the connection. The present study compares the influence of the above-normal and below-normal Indian summer rainfall on the North China summer rainfall variations. Composite analysis shows that the mid-latitude Asian atmospheric circulation and the North China rainfall anomalies during summer tend to be anti-symmetric in above-normal and below-normal Indian rainfall years. Analysis indicates that the Indian-North China summer rainfall relation tends to be stronger when larger Indian rainfall anomaly occurs during a higher mean rainfall period. The observed long-term change in the Indian-North China summer rainfall relationship cannot be explained by the impact of the El Niño-Southern Oscillation (ENSO). The present study evaluates the Indian-North China summer rainfall relationship in climate models. Analysis shows that the Indian-North China summer rainfall relationship differs largely among different climate models and among different simulations of a specific model. The relationship also displays obvious temporal variations in both individual and ensemble mean model simulations. This suggests an important role of the atmospheric internal variability in the change of the Indian-North China summer rainfall relationship.

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

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


    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, 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

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

    Ansoumana Bodian


    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.

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

    Blaustein, Ryan A., E-mail: [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)


    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

  14. Uncertainties on the definition of critical rainfall patterns for debris-flows triggering. Results from the Rebaixader monitoring site (Central Pyrenees)

    Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc


    Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the

  15. Calibration of Conceptual Rainfall-Runoff Models Using Global Optimization

    Chao Zhang


    Full Text Available Parameter optimization for the conceptual rainfall-runoff (CRR model has always been the difficult problem in hydrology since watershed hydrological model is high-dimensional and nonlinear with multimodal and nonconvex response surface and its parameters are obviously related and complementary. In the research presented here, the shuffled complex evolution (SCE-UA global optimization method was used to calibrate the Xinanjiang (XAJ model. We defined the ideal data and applied the method to observed data. Our results show that, in the case of ideal data, the data length did not affect the parameter optimization for the hydrological model. If the objective function was selected appropriately, the proposed method found the true parameter values. In the case of observed data, we applied the technique to different lengths of data (1, 2, and 3 years and compared the results with ideal data. We found that errors in the data and model structure lead to significant uncertainties in the parameter optimization.

  16. The impact of model and rainfall forcing errors on characterizing soil moisture uncertainty in land surface modeling

    V. Maggioni


    Full Text Available 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.

  17. Simulating atmospheric free-space optical propagation: rainfall attenuation

    Achour, Maha


    With recent advances and interest in Free-Space Optics (FSO) for commercial deployments, more attention has been placed on FSO weather effects and the availability of global weather databases. The Meteorological Visual Range (Visibility) is considered one of the main weather parameters necessary to estimate FSO attenuation due to haze, fog and low clouds. Proper understanding of visibility measurements conducted throughout the years is essential. Unfortunately, such information is missing from most of the databases, leaving FSO players no choice but to use the standard visibility equation based on 2% contrast and other assumptions on the source luminance and its background. Another challenge is that visibility is measured using the visual wavelength of 550 nm. Extrapolating the measured attenuations to longer infrared wavelengths is not trivial and involves extensive experimentations. Scattering of electromagnetic waves by spherical droplets of different sizes is considered to simulate FSO scattering effects. This paper serves as an introduction to a series of publications regarding simulation of FSO atmospheric propagation. This first part focuses on attenuation due to rainfall. Additional weather parameters, such as rainfall rate, temperature and relative humidity are considered to effectively build the rain model. Comparison with already published experimental measurement is performed to validate the model. The scattering cross section due to rain is derived from the density of different raindrop sizes and the raindrops fall velocity is derived from the overall rainfall rate. Absorption due the presence of water vapor is computed using the temperature and relative humidity measurements.

  18. Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

    Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara


    Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the

  19. Mapping monthly rainfall erosivity in Europe

    Ballabio, C; Meusburger, K; Klik, A


    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...

  20. Weather radar rainfall data in urban hydrology

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick


    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...

  1. Modelling persistence in annual Australia point rainfall

    J. P. Whiting


    Full Text Available Annual rainfall time series for Sydney from 1859 to 1999 is analysed. Clear evidence of nonstationarity is presented, but substantial evidence for persistence or hidden states is more elusive. A test of the hypothesis that a hidden state Markov model reduces to a mixture distribution is presented. There is strong evidence of a correlation between the annual rainfall and climate indices. Strong evidence of persistence of one of these indices, the Pacific Decadal Oscillation (PDO, is presented together with a demonstration that this is better modelled by fractional differencing than by a hidden state Markov model. It is shown that conditioning the logarithm of rainfall on PDO, the Southern Oscillation index (SOI, and their interaction provides realistic simulation of rainfall that matches observed statistics. Similar simulation models are presented for Brisbane, Melbourne and Perth. Keywords: Hydrological persistence,hidden state Markov models, fractional differencing, PDO, SOI, Australian rainfall

  2. Beyond Rainfall Multipliers: Describing Input Uncertainty as an Autocorrelated Stochastic Process Improves Inference in Hydrology

    Del Giudice, D.; Albert, C.; Reichert, P.; Rieckermann, J.


    Rainfall is the main driver of hydrological systems. Unfortunately, it is highly variable in space and time and therefore difficult to observe accurately. This poses a serious challenge to correctly estimate the catchment-averaged precipitation, a key factor for hydrological models. As biased precipitation leads to biased parameter estimation and thus to biased runoff predictions, it is very important to have a realistic description of precipitation uncertainty. Rainfall multipliers (RM), which correct each observed storm with a random factor, provide a first step into this direction. Nevertheless, they often fail when the estimated input has a different temporal pattern from the true one or when a storm is not detected by the raingauge. In this study we propose a more realistic input error model, which is able to overcome these challenges and increase our certainty by better estimating model input and parameters. We formulate the average precipitation over the watershed as a stochastic input process (SIP). We suggest a transformed Gauss-Markov process, which is estimated in a Bayesian framework by using input (rainfall) and output (runoff) data. We tested the methodology in a 28.6 ha urban catchment represented by an accurate conceptual model. Specifically, we perform calibration and predictions with SIP and RM using accurate data from nearby raingauges (R1) and inaccurate data from a distant gauge (R2). Results show that using SIP, the estimated model parameters are "protected" from the corrupting impact of inaccurate rainfall. Additionally, SIP can correct input biases during calibration (Figure) and reliably quantify rainfall and runoff uncertainties during both calibration (Figure) and validation. In our real-word application with non-trivial rainfall errors, this was not the case with RM. We therefore recommend SIP in all cases where the input is the predominant source of uncertainty. Furthermore, the high-resolution rainfall intensities obtained with this

  3. Multilayer perceptron neural network for downscaling rainfall in arid region: A case study of Baluchistan, Pakistan

    Kamal Ahmed; Shamsuddin Shahid; Sobri Bin Haroon; Wang Xiao-Jun


    Downscaling rainfall in an arid region is much challenging compared to wet region due to erratic and infrequent behaviour of rainfall in the arid region. The complexity is further aggregated due to scarcity of data in such regions. A multilayer perceptron (MLP) neural network has been proposed in the present study for the downscaling of rainfall in the data scarce arid region of Baluchistan province of Pakistan, which is considered as one of the most vulnerable areas of Pakistan to climate change. The National Center for Environmental Prediction (NCEP) reanalysis datasets from 20 grid points surrounding the study area were used to select the predictors using principal component analysis. Monthly rainfall data for the time periods 1961–1990 and 1991–2001 were used for the calibration and validation of the MLP model, respectively. The performance of the model was assessed using various statistics including mean, variance, quartiles, root mean square error (RMSE), mean bias error (MBE), coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE). Comparisons of mean monthly time series of observed and downscaled rainfall showed good agreement during both calibration and validation periods, while the downscaling model was found to underpredict rainfall variance in both periods. Other statistical parameters also revealed good agreement between observed and downscaled rainfall during both calibration and validation periods in most of the stations.

  4. River catchment rainfall series analysis using additive Holt–Winters method

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


    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 rainfalltrends 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.

  5. Effect of rainfall seasonality on carbon storage in tropical dry ecosystems

    Rohr, Tyler; Manzoni, Stefano; Feng, Xue; Menezes, Rômulo S. C.; Porporato, Amilcare


    seasonally dry conditions are typical of large areas of the tropics, their biogeochemical responses to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Seasonal moisture availability positively affects both productivity and soil respiration, resulting in a delicate balance between C deposition as litterfall and C loss through heterotrophic respiration. To understand how rainfall seasonality (i.e., duration of the wet season and rainfall distribution) affects this balance and to provide estimates of long-term C sequestration, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, related C inputs through litterfall, and soil C dynamics. A drought-deciduous caatinga ecosystem in northeastern Brazil is used as a case study to parameterize the model. When extended to different patterns of rainfall seasonality, the results indicate that for fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall is a critical driver of this relationship, leading at times to distinct optima in both production and C storage. These theoretical predictions are discussed in the context of parameter uncertainties and possible changes in rainfall regimes in tropical dry ecosystems.

  6. Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

    S. Yin


    Full Text Available Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. The purpose of this study was to develop models that relate more commonly available rainfall data resolutions, such as daily or monthly totals, to rainfall erosivity. Eleven stations with one-minute temporal resolution rainfall data collected from 1961 through 2000 in the eastern water-erosion areas of China were used to develop and calibrate 21 models. Seven independent stations, also with one-minute data, were utilized to validate those models, together with 20 previously published equations. Results showed that models in this study performed better or similar to models from previous research to estimate rainfall erosivity for these data. Prediction capabilities, as determined using symmetric mean absolute percentage errors and Nash–Sutcliffe model efficiency coefficients, were demonstrated for the 41 models including those for estimating erosivity at event, daily, monthly, yearly, average monthly and average annual time scales. Prediction capabilities were generally better using higher resolution rainfall data as inputs. For example, models with rainfall amount and maximum 60 min rainfall amount as inputs performed better than models with rainfall amount and maximum daily rainfall amount, which performed better than those with only rainfall amount. Recommendations are made for choosing the appropriate estimation equation, which depend on objectives and data availability.

  7. Hydro-mechanical mechanism and thresholds of rainfall-induced unsaturated landslides

    Yang, Zongji; Lei, Xiaoqin; Huang, Dong; Qiao, Jianping


    The devastating Ms 8 Wenchuan earthquake in 2008 created the greatest number of co-seismic mountain hazards ever recorded in China. However, the dynamics of rainfall induced mass remobilization and transport deposits after giant earthquake are not fully understood. Moreover, rainfall intensity and duration (I-D) methods are the predominant early warning indicators of rainfall-induced landslides in post-earthquake region, which are a convenient and straight-forward way to predict the hazards. However, the rainfall-based criteria and thresholds are generally empirical and based on statistical analysis,consequently, they ignore the failure mechanisms of the landslides. This study examines the mechanism and hydro-mechanical behavior and thresholds of these unsaturated deposits under the influence of rainfall. To accomplish this, in situ experiments were performed in an instrumented landslide deposit, The field experimental tests were conducted on a natural co-seismic fractured slope to 1) simulate rainfall-induced shallow failures in the depression channels of a debris flow catchment in an earthquake-affected region, 2)explore the mechanisms and transient processes associated with hydro-mechanical parameter variations in response to the infiltration of rainfall, and 3) identify the hydrologic parameter thresholds and critical criteria of gravitational erosion in areas prone to mass remobilization as a source of debris flows. These experiments provided instrumental evidence and directly proved that post-earthquake rainfall-induced mass remobilization occurred under unsaturated conditions in response to transient rainfall infiltration, and revealed the presence of transient processes and the dominance of preferential flow paths during rainfall infiltration. A hydro-mechanical method was adopted for the transient hydrologic process modelling and unsaturated slope stability analysis. and the slope failures during the experimental test were reproduced by the model

  8. Heavy daily-rainfall characteristics over the Gauteng Province


    Feb 9, 2009 ... Department of Geography, Geoinformatics and Meteorology, Geography Building 2-12, University of .... An example of heavy rainfall 'climatology' in the scientific .... rainfall stations in the calculation of the area-average rainfall.

  9. Spatiotemporal monthly rainfall forecasting for south-eastern and eastern Australia using climatic indices

    Montazerolghaem, Maryam; Vervoort, Willem; Minasny, Budiman; McBratney, Alex


    from the result of this study that climate classification can improve the result of monthly spatiotemporal rainfall forecast models in South-eastern and eastern Australia. Also, the number of sub-regions is one of the important parameters in ranking predictors at the modeling stage, and allows elucidation of climate influences for different sub regions. Classification of stations helps FRA to capture variations in Australian rainfall in space without influence of the rainfall seasonal cycle and regimes.

  10. A New Method for Radar Rainfall Estimation Using Merged Radar and Gauge Derived Fields

    Hasan, M. M.; Sharma, A.; Johnson, F.; Mariethoz, G.; Seed, A.


    Accurate estimation of rainfall is critical for any hydrological analysis. The advantage of radar rainfall measurements is their ability to cover large areas. However, the uncertainties in the parameters of the power law, that links reflectivity to rainfall intensity, have to date precluded the widespread use of radars for quantitative rainfall estimates for hydrological studies. There is therefore considerable interest in methods that can combine the strengths of radar and gauge measurements by merging the two data sources. In this work, we propose two new developments to advance this area of research. The first contribution is a non-parametric radar rainfall estimation method (NPZR) which is based on kernel density estimation. Instead of using a traditional Z-R relationship, the NPZR accounts for the uncertainty in the relationship between reflectivity and rainfall intensity. More importantly, this uncertainty can vary for different values of reflectivity. The NPZR method reduces the Mean Square Error (MSE) of the estimated rainfall by 16 % compared to a traditionally fitted Z-R relation. Rainfall estimates are improved at 90% of the gauge locations when the method is applied to the densely gauged Sydney Terrey Hills radar region. A copula based spatial interpolation method (SIR) is used to estimate rainfall from gauge observations at the radar pixel locations. The gauge-based SIR estimates have low uncertainty in areas with good gauge density, whilst the NPZR method provides more reliable rainfall estimates than the SIR method, particularly in the areas of low gauge density. The second contribution of the work is to merge the radar rainfall field with spatially interpolated gauge rainfall estimates. The two rainfall fields are combined using a temporally and spatially varying weighting scheme that can account for the strengths of each method. The weight for each time period at each location is calculated based on the expected estimation error of each method

  11. Topographic relationships for design rainfalls over Australia

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


    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

  12. Regionalized rainfall-runoff model to estimate low flow indices

    Garcia, Florine; Folton, Nathalie; Oudin, Ludovic


    Estimating low flow indices is of paramount importance to manage water resources and risk assessments. These indices are derived from river discharges which are measured at gauged stations. However, the lack of observations at ungauged sites bring the necessity of developing methods to estimate these low flow indices from observed discharges in neighboring catchments and from catchment characteristics. Different estimation methods exist. Regression or geostatistical methods performed on the low flow indices are the most common types of methods. Another less common method consists in regionalizing rainfall-runoff model parameters, from catchment characteristics or by spatial proximity, to estimate low flow indices from simulated hydrographs. Irstea developed GR2M-LoiEau, a conceptual monthly rainfall-runoff model, combined with a regionalized model of snow storage and melt. GR2M-LoiEau relies on only two parameters, which are regionalized and mapped throughout France. This model allows to cartography monthly reference low flow indices. The inputs data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data from everywhere in the French territory. To exploit fully these data and to estimate daily low flow indices, a new version of GR-LoiEau has been developed at a daily time step. The aim of this work is to develop and regionalize a GR-LoiEau model that can provide any daily, monthly or annual estimations of low flow indices, yet keeping only a few parameters, which is a major advantage to regionalize them. This work includes two parts. On the one hand, a daily conceptual rainfall-runoff model is developed with only three parameters in order to simulate daily and monthly low flow indices, mean annual runoff and seasonality. On the other hand, different regionalization methods, based on spatial proximity and similarity, are tested to estimate the model parameters and to simulate

  13. The within-day behaviour of 6 minute rainfall intensity in Australia

    A. W. Western


    Full Text Available The statistical behaviour and distribution of high-resolution (6 min rainfall intensity within the wet part of rainy days (total rainfall depth >10 mm is investigated for 42 stations across Australia. This paper compares nine theoretical distribution functions (TDFs in representing these data. Two goodness-of-fit statistics are reported: the Root Mean Square Error (RMSE between the fitted and observed within-day distribution; and the coefficient of efficiency for the fit to the highest rainfall intensities (average intensity of the 5 highest intensity intervals across all days at a site. The three-parameter Generalised Pareto distribution was clearly the best performer. Good results were also obtained from Exponential, Gamma, and two-parameter Generalized Pareto distributions, each of which are two parameter functions, which may be advantageous when predicting parameter values. Results of different fitting methods are compared for different estimation techniques. The behaviour of the statistical properties of the within-day intensity distributions was also investigated and trends with latitude, Köppen climate zone (strongly related to latitude and daily rainfall amount were identified. The latitudinal trends are likely related to a changing mix of rainfall generation mechanisms across the Australian continent.

  14. The within-day behaviour of 6 minute rainfall intensity in Australia

    Western, A. W.; Anderson, B.; Siriwardena, L.; Chiew, F. H. S.; Seed, A.; Blöschl, G.


    The statistical behaviour and distribution of high-resolution (6 min) rainfall intensity within the wet part of rainy days (total rainfall depth >10 mm) is investigated for 42 stations across Australia. This paper compares nine theoretical distribution functions (TDFs) in representing these data. Two goodness-of-fit statistics are reported: the Root Mean Square Error (RMSE) between the fitted and observed within-day distribution; and the coefficient of efficiency for the fit to the highest rainfall intensities (average intensity of the 5 highest intensity intervals) across all days at a site. The three-parameter Generalised Pareto distribution was clearly the best performer. Good results were also obtained from Exponential, Gamma, and two-parameter Generalized Pareto distributions, each of which are two parameter functions, which may be advantageous when predicting parameter values. Results of different fitting methods are compared for different estimation techniques. The behaviour of the statistical properties of the within-day intensity distributions was also investigated and trends with latitude, Köppen climate zone (strongly related to latitude) and daily rainfall amount were identified. The latitudinal trends are likely related to a changing mix of rainfall generation mechanisms across the Australian continent.

  15. The within-day behaviour of 6 minute rainfall intensity in Australia

    A. W. Western


    Full Text Available The statistical behaviour and distribution of high-resolution (6 min rainfall intensity within the wet part of rainy days (total rainfall depth >10 mm is investigated for 42 stations across Australia. This paper compares nine theoretical distribution functions (TDFs in representing these data. Two goodness-of-fit statistics are reported: the Root Mean Square Error (RMSE between the fitted and observed within-day distribution; and the efficiency of prediction of the highest rainfall intensities (average intensity of the 5 highest intensity intervals. The three-parameter Generalised Pareto distribution was clearly the best performer. Good results were also obtained from Exponential, Gamma, and two-parameter Generalized Pareto distributions, each of which are two parameter functions, which may be advantageous when predicting parameter values. Results of different fitting methods are compared for different estimation techniques. The behaviour of the statistical properties of the within-day intensity distributions was also investigated and trends with latitude, Köppen climate zone (strongly related to latitude and daily rainfall amount were identified. The latitudinal trends are likely related to a changing mix of rainfall generation mechanisms across the Australian continent.

  16. Coupled Numerical Analysis of the Stability Behaviour of Unsaturated Soil Slopes Under Rainfall Conditions

    WANG Cheng-hua(王成华); THOMAS H R


    The stability behaviour of unsaturated soil slopes under rainfall conditions is investigated via a parametric finite element analysis, which is a fully coupled flow and deformation approach linked to a dynamic programming technique for determining the minimum factor of safety as well as its corresponding critical slip surface based on the stress fields from the numerical computation. The effects of rainfall features, soil strength parameters and permeability properties on slope stability are studied. The analyses revealed that the soil matric suction decreased during rainfall, especially in slopes with high permeability and/or with high suction angles of unsaturated soils. The influence of rainfall conditions on such slopes is quite obvious, and soil suction drops rapidly, which leads to a consequent quick reduction in the factor of safety.

  17. Rainfall Simulation: methods, research questions and challenges

    Ries, J. B.; Iserloh, T.


    In erosion research, rainfall simulations are used for the improvement of process knowledge as well as in the field for the assessment of overland flow generation, infiltration, and erosion rates. In all these fields of research, rainfall experiments have become an indispensable part of the research methods. In this context, small portable rainfall simulators with small test-plot sizes of one square-meter or even less, and devices of low weight and water consumption are in demand. Accordingly, devices with manageable technical effort like nozzle-type simulators seem to prevail against larger simulators. The reasons are obvious: lower costs and less time consumption needed for mounting enable a higher repetition rate. Regarding the high number of research questions, of different fields of application, and not least also due to the great technical creativity of our research staff, a large number of different experimental setups is available. Each of the devices produces a different rainfall, leading to different kinetic energy amounts influencing the soil surface and accordingly, producing different erosion results. Hence, important questions contain the definition, the comparability, the measurement and the simulation of natural rainfall and the problem of comparability in general. Another important discussion topic will be the finding of an agreement on an appropriate calibration method for the simulated rainfalls, in order to enable a comparison of the results of different rainfall simulator set-ups. In most of the publications, only the following "nice" sentence can be read: "Our rainfall simulator generates a rainfall spectrum that is similar to natural rainfall!". The most substantial and critical properties of a simulated rainfall are the drop-size distribution, the fall velocities of the drops, and the spatial distribution of the rainfall on the plot-area. In a comparison of the most important methods, the Laser Distrometer turned out to be the most up

  18. Heavy rainfall equations for Santa Catarina, Brazil

    Álvaro José Back


    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.

  19. Spatial Coherence of Tropical Rainfall

    Ratan, Ram; Venugopal, V.; Sukhatme, Jai; Murtugudde, Raghu


    We characterise the spatial coherence of tropical rain and its wet spells from observations (TRMM) and assess if models (CMIP5) are able to reproduce the observed features. Based on 15 years (1998-2012) of TRMM 3B42 (V7) 1-degree, daily rainfall, we estimate the spatial decorrelation scale (e-folding distance) of rain at each location in the tropics. A ratio of zonal to meridional spatial scales clearly illustrates that while rain patterns tend to be anisotropic (ratio of 4) over tropical ocean regions (particularly over Pacific ITCZ); over land regions, rain tends to be mostly isotropic. This contrast between ocean and land appears to be reasonably well captured by CMIP5 models, although the anisotropy (ratio) over ocean is much higher than in observations. A very curious behaviour in observations is the presence of a coherent band of spatial decorrelation lengths straddling the equator, in the East Pacific, reminiscent of a double ITCZ that some models tend to simulate. A similar analysis of wet spells of different durations suggests that the decorrelation scale is largely independent of the duration of wet spell.

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

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


    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 rainfallrelated 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.

  1. Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya

    M. Oscar Kisaka


    Full Text Available This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall values and the observed daily rainfall data using root mean square errors and mean absolute errors statistics. Results showed 90% chance of below cropping threshold rainfall (500 mm exceeding 258.1 mm during short rains in Embu for one year return period. Rainfall variability was found to be high in seasonal amounts (CV = 0.56, 0.47, and 0.59 and in number of rainy days (CV = 0.88, 0.49, and 0.53 in Machang’a, Kiritiri, and Kindaruma, respectively. Monthly rainfall variability was found to be equally high during April and November (CV = 0.48, 0.49, and 0.76 with high probabilities (0.67 of droughts exceeding 15 days in Machang’a and Kindaruma. Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60% in Kiambere, Kindaruma, Machang’a, and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.

  2. Detecting Rainfall Onset Using Sky Images

    Dev, Soumyabrata; Lee, Yee Hui; Winkler, Stefan


    Ground-based sky cameras (popularly known as Whole Sky Imagers) are increasingly used now-a-days for continuous monitoring of the atmosphere. These imagers have higher temporal and spatial resolutions compared to conventional satellite images. In this paper, we use ground-based sky cameras to detect the onset of rainfall. These images contain additional information about cloud coverage and movement and are therefore useful for accurate rainfall nowcast. We validate our results using rain gauge measurement recordings and achieve an accuracy of 89% for correct detection of rainfall onset.

  3. The Climatology of Taiwan extreme rainfall events and the attributions

    Su, S. H.; Kuo, H. C.; Chen, Y. H.; Chu, J. L.; Lin, L. Y.


    Taiwan is located in the East-Asian monsoon region with average 2,500mm annual precipitation. Most significant Meteorological disasters are related to extreme precipitation which is associated with a complex terrain. Therefore, the long-term trends or climate variations in precipitation due to climate change are our major concern. We studied the climatology of extreme rainfall (ER, 95thpercentile) events in Taiwan using hourly precipitation data form 21 surface stations during 1960-2014. ER contributes about 40% of the total rain amount. It was found that approximately 68% of ER is related to typhoon (TY) and 22% associated with the Mei-Yu (MY) frontal system. The total ER amount annual variation is strongly related to TY, with correlation coefficient of 0.89 for rainfall amount and 0.86 for frequency. There is a significant increasing trend of TY-ER in past 55 years, but also has large variations over the annual and decadal time scales. The inter-annual variation of astounding extreme rainfall (AER, 99.9thpercentile) is increased significantly, especially in the past 15 years. It implies that the increasing of AER rainfall amount majorly caused by the increasing of frequency instead of average rain intensity of TY-AER. The MY-ER events are also highly correlated with the frontal system. The correlation is 0.84 for the rainfall amount and 0.83 of the frequency with the frontal days. There are also strong inter-annual variations of MY-ER, but the long-term trends are not as significant as TY-ER. The variation of frontal system number is another parameter may impact the MY-ER. The observational frontal system numbers had positive correlation with the MY-ER. The attribution of Taiwan TY-ER changes was debated in the research community. In general, the public acceptance of Taiwan extreme precipitation events is affected by multi-scale systems. According to observational data, the increasing of TY-ER amount is 37 % (48% )in Taiwan and some resent studies (Wang et al

  4. Warning Model for Shallow Landslides Induced by Extreme Rainfall

    Lien-Kwei Chien


    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.

  5. Recent Improvements in Estimating Convective and Stratiform Rainfall in Amazonia

    Negri, Andrew J.


    In this paper we present results from the application of a satellite infrared (IR) technique for estimating rainfall over northern South America. Our main objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. We apply the technique of Anagnostou et al (1999). In simple functional form, the estimated rain area A(sub rain) may be expressed as: A(sub rain) = f(A(sub mode),T(sub mode)), where T(sub mode) is the mode temperature of a cloud defined by 253 K, and A(sub mode) is the area encompassed by T(sub mode). The technique was trained by a regression between coincident microwave estimates from the Goddard Profiling (GPROF) algorithm (Kummerow et al, 1996) applied to SSM/I data and GOES IR (11 microns) observations. The apportionment of the rainfall into convective and stratiform components is based on the microwave technique described by Anagnostou and Kummerow (1997). The convective area from this technique was regressed against an IR structure parameter (the Convective Index) defined by Anagnostou et al (1999). Finally, rainrates are assigned to the proportional to (253-temperature), with different rates for the convective and stratiform

  6. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall severity

    Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios; Zoccatelli, Davide; Creutin, Jean-Dominique; Borga, Marco


    Forecasting the occurrence of landslides and debris flows (collectively termed 'debris flows' hereinafter) is fundamental for issuing hazard warnings, and focuses largely on rainfall as a triggering agent. Debris flow forecasting relies very often on the identification of combinations of depth and duration of rainfall - rainfall thresholds - that trigger widespread debris flows. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (debris-flow triggering rainfall events that occurred in the study area between 2005 and 2014. The selected events are among the most severe in the region during this period and triggered a total of 99 debris flows that caused significant damage to people and infrastructures. We show that the spatial rainfall organisation depends on the severity (measured via the estimated return time-RT) of the debris flow-triggering rainfall. For more frequent events (RTdebris flow location coincides with a local minimum, whereas for less frequent events (RT>20 yrs) the triggering rainfall presents a local peak corresponding to the debris flow initiation point. Dependence of these features on rainfall duration is quite limited. The characteristics of the spatial rainfall organisation are exploited to understand the performances and results of three different rainfall interpolation techniques: nearest neighbour (NN), inverse distance weighting (IDW) and ordinary kriging (OK). We show that the features of the spatial organization of the debris flow triggering rainfall explain the biases in the

  7. Conditional probability of rainfall extremes across multiple durations

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


    The conditional probability that extreme rainfall will occur at one location given that it is occurring at another location is critical in engineering design and management circumstances including planning of evacuation routes and the sitting of emergency infrastructure. A challenge with this conditional simulation is that in many situations the interest is not so much the conditional distributions of rainfall of the same duration at two locations, but rather the conditional distribution of flooding in two neighbouring catchments, which may be influenced by rainfall of different critical durations. To deal with this challenge, a model that can consider both spatial and duration dependence of extremes is required. The aim of this research is to develop a model that can take account both spatial dependence and duration dependence into the dependence structure of extreme rainfalls. To achieve this aim, this study is a first attempt at combining extreme rainfall for multiple durations within a spatial extreme model framework based on max-stable process theory. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, this study proposes a new approach that includes addition elements representing duration dependence of extremes to the covariance matrix of max-stable model. To improve the efficiency of calculation, a re-parameterization proposed by Koutsoyiannis et al. (1998) is used to reduce the number of parameters necessary to be estimated. This re-parameterization enables the GEV parameters to be represented as a function of timescale. A stepwise framework has been adopted to achieve the overall aims of this research. Firstly, the re-parameterization is used to define a new set of common parameters for marginal distribution across multiple durations. Secondly, spatial interpolation of the new parameter set is used to

  8. Rainfall mechanisms for the dominant rainfall mode over Zimbabwe relative to ENSO and/or IODZM.

    Manatsa, Desmond; Mukwada, Geoffrey


    Zimbabwe's homogeneous precipitation regions are investigated by means of principal component analysis (PCA) with regard to the underlying processes related to ENSO and/or Indian Ocean Dipole zonal mode (IODZM). Station standardized precipitation index rather than direct rainfall values represent the data matrix used in the PCA. The results indicate that the country's rainfall is highly homogeneous and is dominantly described by the first principal mode (PC1). This leading PC can be used to represent the major rainfall patterns affecting the country, both spatially and temporarily. The current practice of subdividing the country into the two seasonal rainfall forecast zones becomes irrelevant. Partial correlation analysis shows that PC1 is linked more to the IODZM than to the traditional ENSO which predominantly demonstrates insignificant association with PC1. The pure IODZM composite is linked to the most intense rainfall suppression mechanisms, while the pure El Niño composite is linked to rainfall enhancing mechanisms.

  9. Free fall of water drops in laboratory rainfall simulations

    Chowdhury, M. Nasimul; Testik, Firat Y.; Hornack, Mathew C.; Khan, Abdul A.


    Motivated by various hydrological and meteorological applications, this paper investigates the free fall of water drops to provide guidance in laboratory simulations of natural rainfall and to elucidate drop morphodynamics. Drop fall velocity and shape parameters such as axis ratio (ratio of the maximum vertical and horizontal chords of the drop), chord ratio [ratio of the two orthogonal chords where one chord (cl) is the longest chord in the drop and the other one (cs) is the longest chord that is orthogonal to cl], canting angle (angle between the longest chord of the drop and the horizontal axis), and relative fluctuation of chords (difference between vertical and horizontal chord fluctuations) were investigated for three selected water drop sizes (2.6, 3.7, and 5.1 mm spherical volume equivalent diameter) using high speed imaging. Based upon experimental observations, three distinct fall zones were identified: Zone I, in which source-induced oscillations and shape adjustment take place; Zone II, in which equilibrium-shaped drops accelerate to achieve terminal velocity; and Zone III, in which equilibrium-shaped drops fall at terminal velocity. Our results revealed that the fall distance values of approximately 6 m and 12 m can be used as conservative reference values for rainfall experiments with oscillation-free fall of drops (i.e. end of Zone I and onset of Zone II) and with equilibrium-shaped drops falling at terminal velocities (i.e. end of Zone II and onset of Zone III), respectively, for the entire raindrop size spectrum in natural rainfall. These required fall distance values are smaller than the distances discussed in the literature. Methodology and results presented here will facilitate optimum experimental laboratory simulations of natural rainfall.

  10. Maximum daily rainfall in South Korea

    Saralees Nadarajah; Dongseok Choi


    Annual maxima of daily rainfall for the years 1961–2001 are modeled for five locations in South Korea (chosen to give a good geographical representation of the country). The generalized extreme value distribution is fitted to data from each location to describe the extremes of rainfall and to predict its future behavior. We find evidence to suggest that the Gumbel distribution provides the most reasonable model for four of the five locations considered. We explore the possibility of trends in the data but find no evidence suggesting trends. We derive estimates of 10, 50, 100, 1000, 5000, 10,000, 50,000 and 100,000 year return levels for daily rainfall and describe how they vary with the locations. This paper provides the first application of extreme value distributions to rainfall data from South Korea.




    Oct 13, 2011 ... annual total amount, and frequency of fall, kinetic energy and ... annual rainfall increases from the northern frontier of the region ... Nigeria Meteorological Agency, Lagos for the ..... Estimation for Australia's Tropics. Aust. J. Soil.

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


    As noted by the Bureau of Meteorology, Canada, to examine whether such ... their local climate, a threshold considered extreme in one part of Australia could be ... (extreme frequency); the average intensity of rainfall from extreme events.

  13. Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

    Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath


    Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

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

    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

  15. Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

    Hasan, Mohammad Mahadi; Sharma, Ashish; Mariethoz, Gregoire; Johnson, Fiona; Seed, Alan


    While the value of correcting raw radar rainfall estimates using simultaneous ground rainfall observations is well known, approaches that use the complete record of both gauge and radar measurements to provide improved rainfall estimates are much less common. We present here two new approaches for estimating radar rainfall that are designed to address known limitations in radar rainfall products by using a relatively long history of radar reflectivity and ground rainfall observations. The first of these two approaches is a radar rainfall estimation algorithm that is nonparametric by construction. Compared to the traditional gauge adjusted parametric relationship between reflectivity (Z) and ground rainfall (R), the suggested new approach is based on a nonparametric radar rainfall estimation method (NPR) derived using the conditional probability distribution of reflectivity and gauge rainfall. The NPR method is applied to the densely gauged Sydney Terrey Hills radar network, where it reduces the RMSE in rainfall estimates by 10%, with improvements observed at 90% of the gauges. The second of the two approaches is a method to merge radar and spatially interpolated gauge measurements. The two sources of information are combined using a dynamic combinatorial algorithm with weights that vary in both space and time. The weight for any specific period is calculated based on the error covariance matrix that is formulated from the radar and spatially interpolated rainfall errors of similar reflectivity periods in a cross-validation setting. The combination method reduces the RMSE by about 20% compared to the traditional Z-R relationship method, and improves estimates compared to spatially interpolated point measurements in sparsely gauged areas.

  16. Weather radar rainfall data in urban hydrology

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick; Ellerbæk Nielsen, Jesper; ten Veldhuis, Marie-Claire; Arnbjerg-Nielsen, Karsten; Rasmussen, Michael R.; Molnar, Peter


    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 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 to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

  17. Humidity Profiles' Effect On The Relationship Between Ice Scattering And Rainfall In Microwave Rainfall Retrievals

    Petkovic, V.; Kummerow, C. D.


    Currently, satellite microwave rainfall retrievals base their algorithm on an observed global average of the relationship between high frequency brightness temperature (Tb) depression and rainfall rate. This makes them very sensitive to differences in the ratio of ice to liquid in the cloud, resulting in regional biases of rainfall estimates. To address this problem we investigate how the environmental conditions that precede raining systems influence the ice to rainfall relationship. The vertical profile of humidity was found to be a key variable in predicting this ratio. We found that dry over moist air conditions are favorable for developing intense, well organized systems such as MCSs in West Africa and the Sahel, characterized by strong Tb depressions and amounts of ice aloft significantly above the globally observed average value. As a consequence, microwave retrieval algorithms misinterpret these systems assigning them unrealistically high rainfall rates. The opposite is true in the Amazon region, where observed raining systems exhibit very little ice while producing high rainfall rates. These regional differences correspond well with a map of radar to radiometer biases of rainfall. Deeper understanding of the influence of environmental conditions on this ice to rain ratio provides a foundation for mapping a global ice-scattering to rainfall rate relationship that will improve satellite microwave rainfall retrievals and our understanding of cloud microphysics globally.

  18. A multi-scale analysis of Namibian rainfall over the recent decade – comparing TMPA satellite estimates and ground observations

    Xuefei Lu


    New hydrological insights for the region: The agreement between ground and satellite rainfall data was generally good at annual/monthly scales but large variations were observed at the daily scale. Results showed a spatial variability of rainfall trends across the rainfall gradient. We observed significant changes in frequency along with insignificant changes in intensity and no changes in total amount for the driest location, but no changes in any of the rainfall parameters were observed for the three wetter locations. The results also showed increased rainfall variability for the driest location. This study provided a useful approach of using TMPA data associated with trend analysis to extend the data record for ecohydrological studies for similar data scarce conditions. The results of this study will also help constrain IPCC predictions in this region.

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

    Blaustein, Ryan A; Hill, Robert L; Micallef, Shirley A; Shelton, Daniel R; Pachepsky, Yakov A


    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 9cmh(-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 10cm 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.

  20. Effect of forest clear-cutting on landslide occurrences: Analysis of rainfall thresholds at Mt. Ichifusa, Japan

    Saito, Hitoshi; Murakami, Wataru; Daimaru, Hiromu; Oguchi, Takashi


    Vegetation cover is an important factor for rainfall-induced landslides. We analyzed the effect of forest clear-cutting on the initiation of landslides using empirical rainfall intensity-duration (I-D) thresholds at Mt. Ichifusa, Japan, which is characterized by granitic rocks. Extensive clear-cutting was conducted for the forest industry during the late 1960s in the northern part of Mt. Ichifusa. This single episode of clear-cutting caused frequent shallow landslides triggered by rainfall. We interpreted orthorectified aerial photographs from 1969, 1976, 1980, 1985, 1990, 1995, 1999, and 2005 using GIS and mapped landslides based on these photographs. We then analyzed all rainfall events of the warm seasons (Apr.-Oct.) of 1952-2011 (60 years) based on hourly rain gauge data. We used basic rainfall parameters such as mean rainfall intensity (I, mm/h) and duration (D, h) and estimated the return periods of these rainfall conditions. We investigated rainfall I-D thresholds for landslide occurrences in each period represented by the aerial photographs and assessed the relationships between landslide occurrences and topographic characteristics from 10-m DEMs. The results show that several landslides occurred after clear-cutting before 1976 but that they have occurred most frequently during the periods 1976-1980, 1980-1985, and 1990-1995. Numerous landslides occurred in these years at steeper and gentler slopes in the clear-cut area, but few landslides occurred in the non-clear-cut area. Rainfall analysis demonstrates that rainfall I-D thresholds after clear-cutting declined to half of those of the non-clear-cut area. The return periods of these rainfall I-D thresholds also declined to 1 year for short durations of < 12 h and to < 3 years for 72 h in the clear-cut area. Our findings underscore the substantial hysteresis effects between clear-cutting and landslide occurrences at Mt. Ichifusa.

  1. Satellite-based estimation of rainfall erosivity for Africa

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


    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 data.

  2. Precipitation top heights of orographic heavy rainfall in the Asian monsoon regions

    Shige, Shoichi; Kummerow, Christian


    In contrast to the dominant view that heavy rainfall results from deep clouds, the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) frequently observed heavy, but shallow orographic rainfall over coastal mountain ranges of the Asian monsoon regions. The low-level horizontal winds, leading to topographic forced upward motion on the windward slopes, are dynamically important for its occurrence. This paper focuses on the thermodynamic character of the atmospheric environment associated with shallow orographic heavy rainfall. The precipitation-top heights of orographic heavy rainfall generally decrease with low- and mid-level relative humidity especially for coastal mesoscale mountain ranges during summer monsoon. This differs from what has been observed for convection over the tropical ocean in previous studies, but is consistent with abundant shallow convection during the moist summer monsoon season. In contrast, the precipitation-top heights over Annam Cordillera during the transition phase from boreal summer to winter monsoon seasons, facing the prevailing northeasterly, increase with low-level and mid-level relative humidity, demonstrating that convection depth is not a simple function of humidity. The precipitation-top heights of orographic heavy rainfall decrease with the low-level stability for all regions considered in this study as well as Annam Cordillera during the transition phase from boreal summer to winter monsoon seasons. Therefore, low-level static stability, which inhibits cloud growth and promotes cloud detrainment, is inferred to be an equally important parameter in determining the precipitation-top heights.

  3. Determination of seasonal rainfall variability, onset and cessation in semi-arid Tharaka district, Kenya

    Recha, C. W.; Makokha, G. L.; Traore, P. S.; Shisanya, C.; Lodoun, T.; Sako, A.


    The study quantified rainfall variability for March-May (MAM) and October-December (OND) seasons in Tharaka district, Kenya. The parameters analysed were inter-annual variability of seasonal rainfall, onset and cessation using daily rainfall data in three agro-ecological zones' stations. Percentage mean cumulative method was used to determine onset and cessation, and seasonal variability was estimated using rainfall variability indices. Although both seasons are highly variable, OND has been persistently below mean over time while MAM shows high within-season variability. Despite the near uniformity in the mean onset and cessation dates, the former is highly variable on an inter-annual scale. The two rainfall seasons are inherently dissimilar and therefore require specific cropping in agro-ecological zone LM4 and LM4-5. It is possible that farmers in IL5 are missing an opportunity by under-utilising MAM rainfall. The results should be incorporated in implications of climate variability and vulnerability assessment in semi-arid Tharaka district.

  4. Method for generating spatial and temporal synthetic hourly rainfall in the Valley of Mexico

    Mendoza-Resendiz, Alejandro; Arganis-Juarez, Maritza; Dominguez-Mora, Ramon; Echavarria, Bernardo


    Hydrological risk analyses require a dense pluviometer network and a long period of records with an adequate time resolution; usually pluviometer networks have short periods of simultaneous records, so it is required to extend the number of records by means of synthetically generated rainfall events. This paper describes the development and implementation of a method based on a daily rainfall disaggregation for generating synthetic rainfall events distributed spatially and temporally. It uses the information recorded in 49 rain-gauge stations in the network of the basin of the Valley of Mexico during the rainy season from 1988 to 2006. Within various methods found in the literature, we consider that this one provides a greater simplicity for a practical implementation. The tests carried out showed that rainfall events generated with this method properly reproduce the statistical parameters of the historical records, including those that are not implicitly incorporated in the model, as is the case of the synthetic hourly rainfall, whose statistical values are virtually identical to the historical ones despite that the proposed method only uses the probability distribution of maximum daily rainfall.

  5. Temporal analysis (1940-2010) of rainfall aggressiveness in the Iberian Peninsula basins

    García-Barrón, L.; Camarillo, J. M.; Morales, J.; Sousa, A.


    Rainfall aggressiveness causes environmental impacts and it is related to several natural hazards. Therefore, this parameter has been chosen as an environmental indicator. The present study is based on the monthly estimated rainfall using the Precipitation Runoff Integrated Model (SIMPA) for each Spanish hydrographic basin from 1940 to 2010. The main aim is to analyse temporal irregularity of rainfall aggressiveness in large geographic areas and to extract spatio-temporal patterns. For each year the rainfall aggressiveness was calculated using the Modified Fournier Index (IFM) and Oliver's Index of Precipitation Concentration (IPC). The temporal variability of the annual series of these indices was analysed for each zone delimited. The results obtained made it possible to characterize the rainfall aggressiveness in the Iberian Peninsula and to determine its evolution over the past decades. They also reveal that the general pattern of the rainfall aggressiveness is determined by the dual effect of latitude (north-south) and longitude (east-west) as a result of the different maritime influences of the Atlantic and the Mediterranean watersheds. Finally a new variable is proposed, the Annual Aggressiveness Risk RA, which summarizes the information provided by IFM and IPC.

  6. Remote sensing of rainfall for debris-flow hazard assessment

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,


    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

  7. Climate information based streamflow and rainfall forecasts for Huai River Basin using Hierarchical Bayesian Modeling

    X. Chen


    Full Text Available A Hierarchal Bayesian model for forecasting regional summer rainfall and streamflow season-ahead using exogenous climate variables for East Central China is presented. The model provides estimates of the posterior forecasted probability distribution for 12 rainfall and 2 streamflow stations considering parameter uncertainty, and cross-site correlation. The model has a multilevel structure with regression coefficients modeled from a common multivariate normal distribution results in partial-pooling of information across multiple stations and better representation of parameter and posterior distribution uncertainty. Covariance structure of the residuals across stations is explicitly modeled. Model performance is tested under leave-10-out cross-validation. Frequentist and Bayesian performance metrics used include Receiver Operating Characteristic, Reduction of Error, Coefficient of Efficiency, Rank Probability Skill Scores, and coverage by posterior credible intervals. The ability of the model to reliably forecast regional summer rainfall and streamflow season-ahead offers potential for developing adaptive water risk management strategies.

  8. Long Range Forecast on South West Monsoon Rainfall using Artificial Neural Networks based on Clustering Approach

    Maya L. Pai


    Full Text Available The purpose of this study is to forecast Southwest Indian Monsoon rainfall based on sea surface temperature, sea level pressure, humidity and zonal (u and meridional (v winds. With the aforementioned parameters given as input to an Artificial Neural Network (ANN, the rainfall within 10x10 grids of southwest Indian regions is predicted by means of one of the most efficient clustering methods, namely the Kohonen Self-Organizing Maps (SOM. The ANN is trained with input parameters spanning for 36 years (1960-1995 and tested and validated for a period of 9 years (1996-2004. It is further used to predict the rainfall for 6 years (2005-2010. The results show reasonably good accuracy for the summer monsoon periods June, July, August and September (JJAS of the validation years.

  9. Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

    Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.


    Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results

  10. A multiplier-based method of generating stochastic areal rainfall from point rainfalls

    Ndiritu, J. G.

    Catchment modelling for water resources assessment is still mainly based on rain gauge measurements as these are more easily available and cover longer periods than radar and satellite-based measurements. Rain gauges however measure the rain falling on an extremely small proportion of the catchment and the areal rainfall obtained from these point measurements are consequently substantially uncertain. These uncertainties in areal rainfall estimation are generally ignored and the need to assess their impact on catchment modelling and water resources assessment is therefore imperative. A method that stochastically generates daily areal rainfall from point rainfall using multiplicative perturbations as a means of dealing with these uncertainties is developed and tested on the Berg catchment in the Western Cape of South Africa. The differences in areal rainfall obtained by alternately omitting some of the rain gauges are used to obtain a population of plausible multiplicative perturbations. Upper bounds on the applicable perturbations are set to prevent the generation of unrealistically large rainfall and to obtain unbiased stochastic rainfall. The perturbations within the set bounds are then fitted into probability density functions to stochastically generate the perturbations to impose on areal rainfall. By using 100 randomly-initialized calibrations of the AWBM catchment model and Sequent Peak Analysis, the effects of incorporating areal rainfall uncertainties on storage-yield-reliability analysis are assessed. Incorporating rainfall uncertainty is found to reduce the required storage by up to 20%. Rainfall uncertainty also increases flow-duration variability considerably and reduces the median flow-duration values by an average of about 20%.

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

    Villafuerte, Marcelino, II; Matsumoto, Jun


    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

  12. Extreme Rainfall Impacts in Fractured Permeable Catchments

    Ireson, A. M.; Butler, A. P.


    Serious groundwater flooding events have occurred on Chalk catchments in both the UK and north west Europe in the last decade, causing substantial amounts of disruption and economic damage. These fractured, permeable catchments are characterized by low surface runoff, high baseflow indices and strongly attenuated streamflow hydrographs. They have a general resilience to drought and pluvial/fluvial flooding. The small pore size of the Chalk matrix (~ 1 µm) exerts a high suction, such that dynamic storage is primarily due to the fractures, and amounts to ~ 1% of the total volume. As a result, under sustained rainfall the water table can rise up to exceptional levels leading to surface water emergence from springs and valleys. Floodwater may slowly drain with the topography, or, in localized depressions, it may simply pond until the groundwater levels decline. In winter 2000/1, a sequence of individually unexceptional rainfall events over several months led to large scale flooding in the Pang catchment, Berkshire, UK. By contrast, an extreme rainfall event on 20th July 2007 in the same catchment caused a very rapid response at the water table, but due to the antecedent conditions did not lead to flooding. The objective of this study is to quantify how the water table in a fractured permeable catchment responds to different types of rainfall, and the implications of this for groundwater flooding. We make use of measurements from the Pang catchment, including: rainfall (tipping bucket gauges); actual evaporation (eddy flux correlation); soil water content (profile probes and neutron probes); near surface matric potential (tensiometers and equitensiometers); deep (>10m) matric potential (deep jacking tensiometers); and water table elevation (piezometers). Conventional treatment of recharge in Chalk aquifers considers a fixed bypass component of rainfall, normally 15%, to account for the role of the fractures. However, interpretation of the field data suggest three modes

  13. Changes in rainfall seasonality in the tropics

    Feng, X.; Porporato, A. M.; Rodriguez-Iturbe, I.


    Climate change has altered not only the overall magnitude of rainfall but also their seasonal distribution and interannual variability across the world. Such changes in the rainfall regimes will be most keenly felt in arid and semiarid regions, where the availability and timing of water are key factors controlling biogeochemical cycles, primary productivity, and phenology, in addition to regulating regional agricultural production and economic output. Nevertheless, due to the inherent complexity of the signals, a comprehensive framework to understand seasonal rainfall profiles across multiple timescales and geographical regions is still lacking. Here, we formulate a global measure of seasonality and investigate changes in the seasonal rainfall regime across the tropics in the past century. The seasonality index, which captures the effects of both the magnitude and concentration of the rainy season, is highest in the northeast region of Brazil, western and central Africa, northern Australia, and parts of the Caribbean and Southeast Asia (the seasonally dry tropics). Further decomposing rainfall seasonality into its magnitude, duration, and timing components using spectral techniques and information theory, we find marked increase in the interannual variability of seasonality over most of the dry tropics, implying increasing uncertainty in the intensity, duration, and arrival of seasonal rainfall over the past century. We also show that such increase in variability has occurred in conjunction with shifts in the seasonal timing and changes in its overall magnitude. Thus, it is importance to place the analysis of rainfall regimes in these regions into a seasonal context that is most relevant to local ecological and social processes. These changes, if sustained into the next century, will portend significant shifts in the timing of plant activities and ecosystem composition and distribution, with consequences for water and carbon cycling and water resource management in

  14. Modeling the Distribution of Rainfall Intensity using Hourly Data

    Salisu Dan'azumi; Supiah Shamsudin; Azmi Aris


    Problem statement: Design of storm water best management practices to control runoff and water pollution can be achieved if a prior knowledge of the distribution of rainfall characteristics is known. Rainfall intensity, particularly in tropical climate, plays a major role in the design of runoff conveyance and erosion control systems. This study is aimed to explore the statistical distribution of rainfall intensity for Peninsular Malaysia using hourly rainfall data. Approach: Hourly rainfall ...

  15. The role of observation uncertainty in the calibration of hydrologic rainfall-runoff models

    T. Ghizzoni


    Full Text Available Hydrologic rainfall-runoff models are usually calibrated with reference to a limited number of recorded flood events, for which rainfall and runoff measurements are available. In this framework, model's parameters consistency depends on the number of both events and hydrograph points used for calibration, and on measurements reliability. Recently, to make users aware of application limits, major attention has been devoted to the estimation of uncertainty in hydrologic modelling. Here a simple numerical experiment is proposed, that allows the analysis of uncertainty in hydrologic rainfall-runoff modelling associated to both quantity and quality of available data.

    A distributed rainfall-runoff model based on geomorphologic concepts has been used. The experiment involves the analysis of an ensemble of model runs, and its overall set up holds if the model is to be applied in different catchments and climates, or even if a different hydrologic model is used. With reference to a set of 100 synthetic rainfall events characterized by a given rainfall volume, the effect of uncertainty in parameters calibration is studied. An artificial truth – perfect observation – is created by using the model in a known configuration. An external source of uncertainty is introduced by assuming realistic, i.e. uncertain, discharge observations to calibrate the model. The range of parameters' values able to "reproduce" the observation is studied. Finally, the model uncertainty is evaluated and discussed. The experiment gives useful indications about the number of both events and data points needed for a careful and stable calibration of a specific model, applied in a given climate and catchment. Moreover, an insight on the expected and maximum error in flood peak discharge simulations is given: errors ranging up to 40% are to be expected if parameters are calibrated on insufficient data sets.

  16. A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate

    Lima, Carlos H. R.; Kwon, Hyun-Han; Kim, Jin-Young


    The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.

  17. Scaling statistics in a critical, nonlinear physical model of tropical oceanic rainfall

    K. M. Nordstrom


    Full Text Available Over the last two decades, concepts of scale invariance have come to the fore in both modeling and data analysis in hydrological precipitation research. With the advent of the use of the multiplicative random cascade model, these concepts have become increasingly more important. However, unifying this statistical view of the phenomenon with the physics of rainfall has proven to be a rather nontrivial task. In this paper, we present a simple model, developed entirely from qualitative physical arguments, without invoking any statistical assumptions, to represent tropical atmospheric convection over the ocean. The model is analyzed numerically. It shows that the data from the model rainfall look very spiky, as if generated from a random field model. They look qualitatively similar to real rainfall data sets from Global Atmospheric Research Program (GARP Atlantic Tropical Experiment (GATE. A critical point is found in a model parameter corresponding to the Convective Inhibition (CIN, at which rainfall changes abruptly from non-zero to a uniform zero value over the entire domain. Near the critical value of this parameter, the model rainfall field exhibits multifractal scaling determined from a fractional wetted area analysis and a moment scaling analysis. It therefore must exhibit long-range spatial correlations at this point, a situation qualitatively similar to that shown by multiplicative random cascade models and GATE rainfall data sets analyzed previously (Over and Gupta, 1994; Over, 1995. However, the scaling exponents associated with the model data are different from those estimated with real data. This comparison identifies a new theoretical framework for testing diverse physical hypotheses governing rainfall based in empirically observed scaling statistics.

  18. Scaling statistics in a critical, nonlinear physical model of tropical oceanic rainfall

    Nordstrom, K. M.; Gupta, V. K.

    Over the last two decades, concepts of scale invariance have come to the fore in both modeling and data analysis in hydrological precipitation research. With the advent of the use of the multiplicative random cascade model, these concepts have become increasingly more important. However, unifying this statistical view of the phenomenon with the physics of rainfall has proven to be a rather nontrivial task. In this paper, we present a simple model, developed entirely from qualitative physical arguments, without invoking any statistical assumptions, to represent tropical atmospheric convection over the ocean. The model is analyzed numerically. It shows that the data from the model rainfall look very spiky, as if generated from a random field model. They look qualitatively similar to real rainfall data sets from Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE). A critical point is found in a model parameter corresponding to the Convective Inhibition (CIN), at which rainfall changes abruptly from non-zero to a uniform zero value over the entire domain. Near the critical value of this parameter, the model rainfall field exhibits multifractal scaling determined from a fractional wetted area analysis and a moment scaling analysis. It therefore must exhibit long-range spatial correlations at this point, a situation qualitatively similar to that shown by multiplicative random cascade models and GATE rainfall data sets analyzed previously (Over and Gupta, 1994; Over, 1995). However, the scaling exponents associated with the model data are different from those estimated with real data. This comparison identifies a new theoretical framework for testing diverse physical hypotheses governing rainfall based in empirically observed scaling statistics.

  19. Laboratory experiments on rainfall-induced flowslide from pore pressure and moisture content measurements

    M. R. Hakro


    Full Text Available During or immediately after rainfall many slope failures have been observed. The slope failure occurred due to rainfall infiltration that rapidly increase the pore pressure and trigger the slope failure. Numerous studies have been conducted to investigate the rainfall-induced slope failure, but the mechanism of slope failure is still not well clarified. To investigate mechanism of rainfall-induced slope failure laboratory experiments have been conducted in flume. The slope was prepared with sandy soil in flume with constant inclination of 45°, because most of rainfall-induced slope failure occurred in sandy soil and on steep slope. The hydrological parameters such as pore pressure and moisture content were measured with piezometers and advanced Imko TDRs respectively. The slope failure occurred due to increase in moisture content and rise in pore pressure. During the flowslide type of slope failure the sudden increase in pore pressure was observed. The higher moisture content and pore pressure was at the toe of the slope. The pore pressure was higher at the toe of the slope and smaller at the upper part of the slope. After the saturation the run-off was observed at the toe of the slope that erodes the toe and forming the gullies from toe to upper part of the slope. In the case antecedent moisture conditions the moisture content and the pore pressure increased quickly and producing the surface runoff at the horizontal part of the slope. The slope having less density suffer from flowslide type of the failure, however in dense slope no major failure was occurred even at higher rainfall intensity. The antecedent moisture accompanied with high rainfall intensity also not favors the initiation of flowslide in case of dense slope. The flowslide type of failure can be avoided by controlling the density of soil slope. Knowing such parameters that controls the large mass movement helpful in developing the early warning system for flowslide type of

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

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


    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.

  1. Downscaling summer rainfall in the UK from North Atlantic ocean temperatures

    R. L. Wilby


    Full Text Available Annual series of three stochastic rainfall model parameters — the seasonal wet day amount (or intensity, the conditional dry–day probability (or dry–spell persistence, and the conditional wet-day probability (or wet-spell persistence — were examined using daily rainfall records for ten UK stations for the period 1901–1995. The purpose was first, to determine the extent to which these indices of summer (June–August rainfall were correlated with empirical orthogonal functions (EOFs of summer North Atlantic sea surface temperature (SST anomalies: second, to evaluate the skill of EOFs of preceding winter (December–February SSTs for summer rainfall forecasting and downscaling.Correlation analyses suggest that observed increases in summer dry-spell persistence since the 1970s coincided with positive SST anomalies in the North Atlantic. In contrast, wet-spell persistence and intensities were relatively weakly correlated with the same patterns, implying that the use of SSTs is justifiable for conditioning occurrence but not intensity parameters. Furthermore, the correlation strengths were greater for EOFs of SSTs than those reported for area-average SST anomalies, indicating that the pattern of SST anomalies conveys important information about seasonal rainfall anomalies across the UK. When EOFs of winter SSTs were used to forecast summer rainfall in Cambridge, the skill was once again greater for dry-spells than either wet-spells or intensities. However, even for dry–spells, the correlation with observations — whilst statistically significant — was still rather modest (r Keywords: North Atlantic, ocean temperatures, downscaling, rainfall, forecasting, UK

  2. Nature and Inference of Scaling in Temporal Rainfall

    Veneziano, D.; Lepore, C.


    We pursue three objectives related to the scaling of temporal rainfall: 1. Develop methods for the analysis of scaling within rainstorms, 2. Explain the difference in scaling results when considering the whole record inclusive of storms and inter-storm periods (continuous analysis) or only the storms (within-storm analysis), and 3. Examine whether scaling follows a beta-lognormal model or a more general beta-log-Levy model. Regarding objective 1, there are well-established techniques for continuous scaling analysis but not for the analysis within storms. For the latter, we develop methods based on the partition coefficients and show how to correct for bias and maximize the estimation accuracy. To pursue objective 2 we use historic records, synthetic time series, and toy rainfall models to show that the continuous results reflect mainly the alternation of dry and wet periods and are insensitive to the fluctuations of rainfall intensity inside the storms. Moreover, we find that the rain support is not fractal. From this we conclude that the results from traditional continuous analysis are spurious. By contrast, there is evidence of within-storm scaling. Inside the storms there is higher intermittency (higher intensity fluctuations) and lower lacunarity (more compact rain support) than in the continuous record. These results have important implications on downscaling and the evaluation of rainfall extremes. Concerning objective 3, we note that popular multifractal models for rainfall are of the log-Levy ("universal") type. A key parameter of those models is the stability index 0 < α ≤ 2, with α = 2 corresponding to lognormal models. To account for the alternation of dry and wet periods (also in within-storm analysis), one should add a "beta component" and thus use beta-log-Levy or beta-lognormal models. By using simulations with α = 2, we show that standard estimators of α are negatively biased and the hypothesis of beta-lognormal multifractality inside the

  3. Scaling properties of rainfall time-series in the urban area of Rome

    Volpi, E.; Napolitano, F.; Lombardo, F.


    The rainfall fields exhibits a high space-time variability which generates a large degree of uncertainty in modelling the process, thus causing lack of accuracy in many key hydrological problems, such as the forecasting of floods and the management of water resources. The large amount of literature produced in the last thirty years about this issue deals with the development of stochastic models able to represent the non-linearity and intermittence of rainfall in order to perform the downscaling process, i.e. transferring to finer scales the information on rainfall observed or forecasted at large scales. Traditionally, these models are based upon point processes in both the time (e.g. Waymire and Gupta, 1981) and the space-time domain (e.g. Rodriguez-Iturbe et al., 1986). Although this approach is cluster-based so as to model the physical structure of rainfall, its application may involve an inconvenient mathematical complexity and a large number of parameters, leading to several problems in parameter estimation. Another approach to this problem is based on the empirical detection of some regularity in hydrological observations, such as the scale-invariance properties of rainfall (e.g. Lovejoy and Schertzer, 1985). Models following this approach are based upon the assumption of a power law dependence of all statistical moments on the scale of aggregation. That means scaling properties can provide simple relationships to link the statistical distribution of the rainfall process at different spatial and temporal scales, in the ranges of which the power-low assumption can be verified (Marani, 2003). This work focuses on the analysis of the scaling properties of rainfall time series from a high density rain gauge network covering the Rome's urban area. The network consists of 24 sites, and the gauge record at each site has 10-minute time resolution and about 16-year length (1992-2007). The aim of the study is the identification of temporal scaling regimes, their ranges

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

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


    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

  5. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period

    Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios I.; Zoccatelli, Davide; Creutin, Jean Dominique; Borga, Marco


    Forecasting the occurrence of debris flows is fundamental for issuing hazard warnings, and often focuses on rainfall as a triggering agent and on the use of empirical rainfall thresholds based on rain gauge observations. A recognized component of the uncertainty associated with the use of rainfall thresholds is related to the sampling of strongly varying rainfall variability with sparse rain gauge networks. In this work we examine the spatial distribution of rainfall depth in areas up to 10 km from the debris flow initiation points as a function of return period, and we exploit this information to analyze the errors expected in the estimation of debris flow triggering rainfall when rain gauge data are used. In particular, we investigate the impact of rain gauge density and of the use of different interpolation methods. High-resolution, adjusted radar rainfall estimates, representing the best available spatially-distributed rainfall estimates at the debris flows initiation point and in the surrounding area, are sampled by stochastically generated rain gauge networks characterized by varying densities. Debris flow triggering rainfall is estimated by means of three rainfall interpolation methods: nearest neighbor, inverse distance weighting and ordinary kriging. On average, triggering rainfall shows a local peak corresponding to the debris flow initiation point, with a decay of rainfall with distance which increases with the return period of the triggering rainfall. Interpolation of the stochastically generated rain gauge measurements leads to an underestimation of the triggering rainfall that, irrespective of the interpolation methods, increases with the return period and decreases with the rain gauge density. For small return period events and high rain gauge density, the differences among the methods are minor. With increasing the return period and decreasing the rain gauge density, the nearest neighbor method is less biased, because it makes use only of the

  6. Rainfall variability and seasonality in northern Bangladesh

    Bari, Sheikh Hefzul; Hussain, Md. Manjurul; Husna, Noor-E.-Ashmaul


    This paper aimed at the analysis of rainfall seasonality and variability for the northern part of South-Asian country, Bangladesh. The coefficient of variability was used to determine the variability of rainfall. While rainfall seasonality index (SI ) and mean individual seasonality index ( overline{SI_i} ) were used to identify seasonal contrast. We also applied Mann-Kendall trend test and sequential Mann-Kendall test to determine the trend in seasonality. The lowest variability was found for monsoon among the four seasons whereas winter has the highest variability. Observed variability has a decreasing tendency from the northwest region towards the northeast region. The mean individual seasonality index (0.815378 to 0.977228) indicates that rainfall in Bangladesh is "markedly seasonal with a long dry season." It was found that the length of the dry period is lower at the northeastern part of northern Bangladesh. Trend analysis results show no significant change in the seasonality of rainfall in this region. Regression analysis of overline{SI_i} and SI, and longitude and mean individual seasonality index show a significant linear correlation for this area.

  7. Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response

    D. Zoccatelli


    Full Text Available This paper describes a set of spatial rainfall statistics (termed "spatial moments of catchment rainfall" quantifying the dependence existing between spatial rainfall organisation, basin morphology and runoff response. These statistics describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of catchment-scale storm velocity. The concept of the catchment-scale storm velocity takes into account the role of relative catchment orientation and morphology with respect to storm motion and kinematics. The paper illustrates the derivation of the statistics from an analytical framework recently proposed in literature and explains the conceptual meaning of the statistics by applying them to five extreme flash floods occurred in various European regions in the period 2002–2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km2. The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide useful information on what space-time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space-time aggregation on flood response modeling.

  8. Rainfall intensity-duration conditions for mass movements in Taiwan

    Chen, Chi-Wen; Saito, Hitoshi; Oguchi, Takashi


    Mass movements caused by rainfall events in Taiwan are analyzed during a 7-year period from 2006 to 2012. Data from the Taiwan Soil and Water Conservation Bureau reports were compiled for 263 mass movement events, including 156 landslides, 91 debris flows, and 16 events with both landslides and debris flows. Rainfall totals for each site location were obtained from interpolated rain gauge data. The rainfall intensity-duration ( I-D) relationship was examined to establish a rainfall threshold for mass movements using random sampling: I = 18.10(±2.67) D -0.17(±0.04), where I is mean rainfall intensity (mm/h) and D is the time (h) between the beginning of a rainfall event and the resulting mass movement. Significant differences were found between rainfall intensities and thresholds for landslides and debris flows. For short-duration rainfall events, higher mean rainfall intensities were required to trigger debris flows. In contrast, for long-duration rainfall events, similar mean rainfall intensities triggered both landslides and debris flows. Mean rainfall intensity was rescaled by mean annual precipitation (MAP) to define a new threshold: I MAP = 0.0060(±0.0009) D -0.17(±0.04), where I MAP is rescaled rainfall intensity and MAP is the minimum for mountainous areas in Taiwan (3000 mm). Although the I-D threshold for Taiwan is high, the I MAP -D threshold for Taiwan tends to be low relative to other areas around the world. Our results indicate that Taiwan is highly prone to rainfall-induced mass movements. This study also shows that most mass movements occur in high rainfall-intensity periods, but some events occur before or after the rainfall peak. Both antecedent and peak rainfall play important roles in triggering landslides, whereas debris flow occurrence is more related to peak rainfall than antecedent rainfall.

  9. Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities

    De Paola, Francesco; Giugni, Maurizio; Topa, Maria Elena; Coly, Adrien; Yeshitela, Kumelachew; Kombe, Wilbard; Tonye, Emmanuel; Touré, Hamidou


    The intensity-duration-frequency curves are used in hydrology to express in a synthetic way, the link between the maximum rainfall height h and a generic duration d of a rainfall event, fixed a given return period T. Generally, IDF curves can be characterized by a bi-parameter power law: h(d,T) = a(T)dn where a(T), and n are the parameters that have to be estimated through a probabilistic approach. An intensity-duration-frequency analysis starts by gathering time series record of different durations and extracting annual extremes for each duration. The annual extreme data are then fitted by a probability distribution. The present study, carried out within the FP7-ENV-2010 CLUVA project (CLimate change and Urban Vulnerability in Africa), regards the evaluation of the IDF curves for five case studies: Addis Ababa (Ethiopia), Dar Es Salaam (Tanzania), Douala (Cameroon), Ouagadouogou (Burkina Faso) and Saint Louis (Senegal). The probability distribution chosen to fit the annual extreme data is the classic Gumbel distribution. However, for the case studies, only the maximum annual daily rainfall heights are available. Therefore, to define the IDF curves and the extreme values in a smaller time window (10', 30', 1h, 3h, 6h, 12h), it is required to develop disaggregation techniques of the collected data, in order to generate a synthetic sequence of rainfall, with statistical properties equal to the recorded data. The daily rainfalls were disaggregated using two models: short-time intensity disaggregation model (10', 30', 1h); cascade-based disaggregation model (3h, 6h, 12h). On the basis of disaggegation models and Gumbel distribution , the parameters of the IDF curves for the five test cities were evaluated. In order to estimate the contingent influence of climate change on the IDF curves, the illustrated procedure has been applied to the climate (rainfall) simulations over the time period 2010-2050 provided by the CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici

  10. Intermittent rainfall in dynamic multimedia fate modeling.

    Hertwich, E G


    It has been shown that steady-state multimedia models (level III fugacity models) lead to a substantial underestimate of air concentrations for chemicals with a low Henry's law constant (H multimedia models are used to estimate the spatial range or inhalation exposure. A dynamic model of pollutant fate is developed for conditions of intermittent rainfall to calculate the time profile of pollutant concentrations in different environmental compartments. The model utilizes a new, mathematically efficient approach to dynamic multimedia fate modeling that is based on the convolution of solutions to the initial conditions problem. For the first time, this approach is applied to intermittent conditions. The investigation indicates that the time-averaged pollutant concentrations under intermittent rainfall can be approximated by the appropriately weighted average of steady-state concentrations under conditions with and without rainfall.

  11. Critical Phenomena of Rainfall in Ecuador

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


    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).

  12. Modelling rainfall erosion resulting from climate change

    Kinnell, Peter


    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.

  13. Monitoring Niger River Floods from satellite Rainfall Estimates : overall skill and rainfall uncertainty propagation.

    Gosset, Marielle; Casse, Claire; Peugeot, christophe; boone, aaron; pedinotti, vanessa


    Global measurement of rainfall offers new opportunity for hydrological monitoring, especially for some of the largest Tropical river where the rain gauge network is sparse and radar is not available. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of satellite rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them into the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This paper analyses the potential of satellite rainfall products combined with hydrological modeling to monitor the Niger river floods in the city of Niamey, Niger. A dramatic increase of these floods has been observed in the last decades. The study focuses on the 125000 km2 area in the vicinity of Niamey, where local runoff is responsible for the most extreme floods recorded in recent years. Several rainfall products are tested as forcing to the SURFEX-TRIP hydrological simulations. Differences in terms of rainfall amount, number of rainy days, spatial extension of the rainfall events and frequency distribution of the rain rates are found among the products. Their impacts on the simulated outflow is analyzed. The simulations based on the Real time estimates produce an excess in the discharge. For flood prediction, the problem can be overcome by a prior adjustment of the products - as done here with probability matching - or by analysing the simulated discharge in terms of percentile or anomaly. All tested products exhibit some

  14. Sampling errors in rainfall estimates by multiple satellites

    North, Gerald R.; Shen, Samuel S. P.; Upson, Robert


    This paper examines the sampling characteristics of combining data collected by several low-orbiting satellites attempting to estimate the space-time average of rain rates. The several satellites can have different orbital and swath-width parameters. The satellite overpasses are allowed to make partial coverage snapshots of the grid box with each overpass. Such partial visits are considered in an approximate way, letting each intersection area fraction of the grid box by a particular satellite swath be a random variable with mean and variance parameters computed from exact orbit calculations. The derivation procedure is based upon the spectral minimum mean-square error formalism introduced by North and Nakamoto. By using a simple parametric form for the spacetime spectral density, simple formulas are derived for a large number of examples, including the combination of the Tropical Rainfall Measuring Mission with an operational sun-synchronous orbiter. The approximations and results are discussed and directions for future research are summarized.

  15. Weak linkage between the heaviest rainfall and tallest storms.

    Hamada, Atsushi; Takayabu, Yukari N; Liu, Chuntao; Zipser, Edward J


    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection.

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

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


    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.

  17. Entropy of stable seasonal rainfall distribution in Kelantan

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


    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.

  18. Highway Capacity Loss Induced by Rainfall

    Hashim Mohammed Alhassan


    Full Text Available The effect of rainfall on capacity reduction on highways has been investigated. Traffic data was generated for both wet and dry conditions. The data analysis showed that the highway section studied was operating in free flow region. A 2.7% capacity loss was obtained for the road. It is argued that no traffic instability could arise from this situation if the state of traffic remains in the free flow regime. However, in the event of the coincidence of fixed bottlenecks and rainfall, instabilities arising from that could lead to further capacity loss.

  19. Synoptic Analysis of Heavy Rainfall and Flood Observed in Izmir on 20 May 2015 Using Radar and Satellite Images

    Avsar, Ercument


    In this study, a meteorological analysis is conducted on the sudden and heavy rainfall that occurred in Izmir on May 20, 2015. The barotropic model that is observed in upper carts is shown in detail. We can access the data of and analyze the type, severity and amount of many meteorological parameters using the meteorological radars that form a remote sensing system. The one field that uses the radars most intensively is rainfall. Images from the satellite and radar systems are used in the meteorological analysis of the heavy rainfall that occurred in Izmir on 20 May 2015, and the development of the system that led to this rainfall is shown. In this study, data received from Bornova Automatic Meteorological Observation Station (OMGI), which is under the management of Meteorology General Directorate (MGM), Izmir 2. Regional Directorate; satellite images; Radar PPI (Plan Position Indicator) and Radar MAX (Maximum Display) images are evaluated. In addition, synoptic situation, outputs of numerical estimation models, indices calculated from Skew T Log-P diagram are shown. All these results are mapped and analyzed. At the end of these analyses, it is found that this sudden rainfall had developed according to the frontal system motion. A barotropic model occurred on the day of the rainfall over the Aegean Region. As a result of the rainfall that happened in Izmir at 12.00 UTC (Universal Coordinated Time), the May month rainfall record for the last 64 years is achieved with a rainfall amount of 67.7 mm per meter square. Keywords: Izmir, barotropic model, heavy rainfall, radar, synoptic analysis

  20. A probabilistic approach for assessing landslide-triggering event rainfall in Papua New Guinea, using TRMM satellite precipitation estimates

    Robbins, J. C.


    Large and numerous landslides can result in widespread impacts which are felt particularly strongly in the largely subsistence-orientated communities residing in the most landslide-prone areas of Papua New Guinea (PNG). Understanding the characteristics of rainfall preceding these landslide events is essential for the development of appropriate early warning systems and forecasting models. Relationships between rainfall and landslides are frequently complex and uncertainties tend to be amplified by inconsistent and incomplete landslide catalogues and sparse rainfall data availability. To address some of these uncertainties a modified Bayesian technique has been used, in conjunction with the multiple time frames method, to produce thresholds of landslide probability associated with rainfall events of specific magnitude and duration. Satellite-derived precipitation estimates have been used to derive representative rainfall accumulations and intensities over a range of different rainfall durations (5, 10, 15, 30, 45, 60, 75 and 90 days) for rainfall events which resulted in landslides and those which did not result in landslides. Of the two parameter combinations (accumulation-duration and intensity-duration) analysed, rainfall accumulation and duration provide the best scope for identifying probabilistic thresholds for use in landslide warning and forecasting in PNG. Analysis of historical events and rainfall characteristics indicates that high accumulation (>250 mm), shorter duration (75 days), high accumulation (>1200 mm) rainfall events are more likely to lead to moderate- to high-impact landslides. This analysis has produced the first proxy probability thresholds for landslides in PNG and their application within an early warning framework has been discussed.

  1. Rainfall droplet size distributions (DSD) parameterization: physics and sensibility

    Cecchini, M. A.; Machado, L.


    The CHUVA project (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)) is a Brazillian experiment that aims to understand the several cloud processes that occur in different precipitating regimes. At present, the CHUVA project has conducted 6 field campaigns, the last one being in Manaus jointly with GoAmazon, IARA and ACRIDICON. The main focus of the present study is to bring into perspective the different characteristics of precipitation that reaches the surface in Brazil over several locations. To do so, disdrometer data is analyzed in detail, employing a Gamma fit for each DSD measurement which provides the respective parameters to be studied. Those are disposed in a 3D space, each axis corresponding to one parameter, and the patterns are analyzed. A correlation between the Gamma parameters is defined as a parametric surface that fits the observations with errors smaller than 10% and R2 greater than 0.95. In this way, one parameter can be estimated with respect to the other two, reducing the degrees of freedom of the problem from 3 to 2. As the 3 parameters are defined over this surface, it's possible to obtain a surface representing integral DSD properties such as rainfall intensity (RI). Sensibilities tests are conducted on this estimation and also on other DSD characteristics such as total droplet concentrations and mean mass-weighted diameter. It's shown that the DSD integral properties are generally very sensitive to the Gamma parameters. Nonetheless, the sensibility varies over the surface, being higher in a region where the parameters are not balanced (i.e. a relatively high value in one parameter and low values on the other two). It's suggested that any study proposing parameterization/estimation of DSD properties should be aware of this region of high sensitivity. To further the collaboration with GoAmazon and ACRIDICON, the disdrometer results

  2. Novel SVM-based technique to improve rainfall estimation over the Mediterranean region (north of Algeria) using the multispectral MSG SEVIRI imagery

    Sehad, Mounir; Lazri, Mourad; Ameur, Soltane


    In this work, a new rainfall estimation technique based on the high spatial and temporal resolution of the Spinning Enhanced Visible and Infra Red Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) is presented. This work proposes efficient scheme rainfall estimation based on two multiclass support vector machine (SVM) algorithms: SVM_D for daytime and SVM_N for night time rainfall estimations. Both SVM models are trained using relevant rainfall parameters based on optical, microphysical and textural cloud proprieties. The cloud parameters are derived from the Spectral channels of the SEVIRI MSG radiometer. The 3-hourly and daily accumulated rainfall are derived from the 15 min-rainfall estimation given by the SVM classifiers for each MSG observation image pixel. The SVMs were trained with ground meteorological radar precipitation scenes recorded from November 2006 to March 2007 over the north of Algeria located in the Mediterranean region. Further, the SVM_D and SVM_N models were used to estimate 3-hourly and daily rainfall using data set gathered from November 2010 to March 2011 over north Algeria. The results were validated against collocated rainfall observed by rain gauge network. Indeed, the statistical scores given by correlation coefficient, bias, root mean square error and mean absolute error, showed good accuracy of rainfall estimates by the present technique. Moreover, rainfall estimates of our technique were compared with two high accuracy rainfall estimates methods based on MSG SEVIRI imagery namely: random forests (RF) based approach and an artificial neural network (ANN) based technique. The findings of the present technique indicate higher correlation coefficient (3-hourly: 0.78; daily: 0.94), and lower mean absolute error and root mean square error values. The results show that the new technique assign 3-hourly and daily rainfall with good and better accuracy than ANN technique and (RF) model.

  3. Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

    Blakeley, S. L.; Husak, G. J.


    In West Africa, agriculture is often rain-fed, subjecting agricultural productivity and food availability to climate variability. Agricultural conditions will change as warming temperatures increase evaporative demand, and with a growing population dependent on the food supply, farmers will become more reliant on improved adaptation strategies. Development of such adaptation strategies will need to consider West African rainfall trends to remain relevant in a changing climate. Here, using the CHIRPS rainfall product (provided by the Climate Hazards Group at UC Santa Barbara), I examine trends in West African rainfall variability. My analysis will focus on seasonal rainfall totals, the structure of the rainy season, and the distribution of rainfall. I then use farmer-identified drought years to take an in-depth analysis of intra-seasonal rainfall irregularities. I will also examine other datasets such as potential evapotranspiration (PET) data, other remotely sensed rainfall data, rain gauge data in specific locations, and remotely sensed vegetation data. Farmer bad year data will also be used to isolate "bad" year markers in these additional datasets to provide benchmarks for identification in the future of problematic rainy seasons.

  4. Rainfall extremes: Toward reconciliation after the battle of distributions.

    Serinaldi, Francesco; Kilsby, Chris G


    [1] This study attempts to reconcile the conflicting results reported in the literature concerning the behavior of peak-over-threshold (POT) daily rainfall extremes and their distribution. By using two worldwide data sets, the impact of threshold selection and record length on the upper tail behavior of POT observations is investigated. The rainfall process is studied within the framework of generalized Pareto (GP) exceedances according to the classical extreme value theory (EVT), with particular attention paid to the study of the GP shape parameter, which controls the heaviness of the upper tail of the GP distribution. A twofold effect is recognized. First, as the threshold decreases, and nonextreme values are progressively incorporated in the POT samples, the variance of the GP shape parameter reduces and the mean converges to positive values denoting a tendency to heavy tail behavior. Simultaneously, the EVT asymptotic hypotheses are less and less realistic, and the GP asymptote tends to be replaced by the Weibull penultimate asymptote whose upper tail is exponential but apparently heavy. Second, for a fixed high threshold, the variance of the GP shape parameter reduces as the record length (number of years) increases, and the mean values tend to be positive, thus denoting again the prevalence of heavy tail behavior. In both cases, i.e., threshold selection and record length effect, the heaviness of the tail may be ascribed to mechanisms such as the blend of extreme and nonextreme values, and fluctuations of the parent distributions. It is shown how these results provide a link between previous studies and pave the way for more comprehensive analyses which merge empirical, theoretical, and operational points of view. This study also provides several ancillary results, such as a set of formulae to correct the bias of the GP shape parameter estimates due to short record lengths accounting for uncertainty, thus avoiding systematic underestimation of extremes which

  5. Variation in rainfall interception along a forest succession gradient

    Zimmermann, Beate; Zimmermann, Alexander; van Breugel, Michiel


    Rainfall interception by forest canopies reduces the water influx to the forest floor. When forests are replaced by pasture, the process of canopy interception temporarily stops until a new forest develops on abandoned pasture land. Modern land-cover change typically involves regrowing forests but the relation between forest succession and canopy interception is hardly understood. This lack of knowledge is unfortunate because rainfall interception plays an important role in regional water cycles and needs to be quantified for modeling purposes. To help close the knowledge gap, we designed a chronosequence study of throughfall along a secondary succession gradient in a tropical forest region of Panama. The investigated gradient comprises 20 natural forest patches regrowing for 1 up to about 130 years. We sampled each patch with a minimum of 20 funnel-type throughfall collectors over a continuous two-month period that had nearly 900 mm of rain. At the same time and locations, we acquired forest structure data based on DBH measurements of all trees > 1 cm DBH, identified all tree species, and took hemispherical photographs to calculate canopy openness. We used Bayesian Model Averaging (BMA) to identify those vegetation parameters that have the strongest influence on interception variation. Interception loss increased with forest age from 0 to nearly 200 mm of the total rainfall input (0 - 20 %), with the steepest rise occurring within the first decade of forest succession. Parsimonious models which contain canopy openness and basal area or stem density of stems smaller than 5 cm DBH are favored about more complex models. Leave-one-out cross validation revealed that our BMA approach can be used to predict interception with an RMSE of 5 %. Based on our results we argue that hydrological modeling exercises should account for variation in interception due to succession stage, which is possible e.g. by using a statistical approach to relate interception estimates to forest

  6. Influence of rainfall observation network on model calibration and application

    A. Bárdossy


    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

  7. A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

    Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng


    Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures

  8. Climatic patterns and extreme rainfalls on coastal areas in Central Italy

    Bramati, M. C.; Tarragoni, C.


    In this paper we focus on the extreme values analysis to estimate the rainfall return levels for some Adriatic and Tyrrhenian coastal areas in central Italy. Two approaches are mainly considered: the first one is based on the maximum annual daily rainfall series (1-day, 2-day and 3-day) for which suitable probability distributions are fitted, whereas the second one is based on the series of peaks over annual thresholds (POT) for which the best fitting Generalized Pareto distribution is identified. Spectral analysis and appropriate tests for stationarity and homogeneity are run in order to verify the hypothesis under which the analysis performed is valid. From the density plots and the parameter estimates of the fitted distributions to the various annual maximum rainfall series we can conclude that there is a different pattern in the occurrence of extreme events for the western coast with respect to the eastern coast. Specifically, on the Tyrrhenian side extreme rainfalls are more likely to happen in correspondence of longer time spans (i.e. 3-day series) as the effect of cumulated stable rainfalls over time. On the opposite, for the Adriatic coast extremes are more frequent in shorter time spans (1-day). A vector autoregressive model is then estimated and through a causal ordering the identifying restrictions are set. The impulse response analysis shows a lag in the transmission of rainfall shocks of the central Adriatic coast to the Tyrrhenian one. This paper is prepared as a background paper to the SECOA N1.2 Report: Assessment of frequency-magnitude of extreme rainfall events and flooding. Project SECOA (Solutions for Environmental contrast in Coastal Areas) is funded by the EU Commission within the 7th Framework Programme (2007-2013).

  9. Characterizing rainfall in the Tenerife island

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


    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.

  10. Rainfall erosivity in Brazil: A Review

    In this paper, we review the erosivity studies conducted in Brazil to verify the quality and representativeness of the results generated and to provide a greater understanding of the rainfall erosivity (R-factor) in Brazil. We searched the ISI Web of Science, Scopus, SciELO, and Google Scholar datab...

  11. Determinants of southeast Ethiopia seasonal rainfall

    Jury, Mark R.


    The bi-modal climate of SE Ethiopia shares attributes with East Africa, notably that El Niño enhances rainfall, particularly in Sep-Nov season. In this study SE Ethiopia's continuous and seasonal rainfall relationships to global climate are studied to extend our knowledge of its determinants and predictability. A statistical forecast algorithm for the Sep-Nov short rains accounts for 54% of variance in 1980-2010. The Apr-Jun predictors include South Atlantic sea surface temperature, east Indian Ocean sea level air pressure and China upper zonal wind. Cooling in the South Atlantic coincides with a strengthened sub-tropical anticyclone, and later to changes in low level winds that bring orographic convection to SE Ethiopia. The slower El Niño-Southern Oscillation (ENSO) interacts with the faster Indian Ocean Dipole (IOD), but both signals mature too late for direct use in statistical prediction of Sep-Nov rainfall. Composite differences of the upper divergent circulation exhibit a global wave-2 pattern consistent with satellite-observed convection. One key feature is a zonal gradient in upper velocity potential over the Indian Ocean corresponding with a zonal atmospheric circulation. One outcome of this research is useful forecasts of SE Ethiopia Sep-Nov rainfall that will assist in agricultural planning.

  12. Water Conservation Education with a Rainfall Simulator.

    Kok, Hans; Kessen, Shelly


    Describes a program in which a rainfall simulator was used to promote water conservation by showing water infiltration, water runoff, and soil erosion. The demonstrations provided a good background for the discussion of issues such as water conservation, crop rotation, and conservation tillage practices. The program raised awareness of…

  13. Coping with rainfall variability in northern Tanzania

    Trærup, Sara Lærke Meltofte


    This chapter explores a potential relationship between rainfall data and household self-reported harvest shocks and local (spatial) variability of harvest shocks and coping strategies based on a survey of 2700 rural households in the Kagera region of northern Tanzania. In addition, correlations...

  14. Preliminary study on mechanics-based rainfall kinetic energy

    Yuan Jiuqin Ms.


    Full Text Available A raindrop impact power observation system was employed to observe the real-time raindrop impact power during a rainfall event and to analyze the corresponding rainfall characteristics. The experiments were conducted at different simulated rainfall intensities. As rainfall intensity increased, the observed impact power increased linearly indicating the power observation system would be satisfactory for characterizing rainfall erosivity. Momentum is the product of mass and velocity (Momentum=MV, which is related to the observed impact power value. Since there is no significant difference between momentum and impact power, observed impact power can represent momentum for different rainfall intensities. The relationship between momentum and the observed impact power provides a convenient way to calculate rainfall kinetic energy. The value of rainfall kinetic energy based on the observed impact power was higher than the classic rainfall kinetic energy. The rainfall impact power based kinetic energy and the classic rainfall kinetic energy showed linear correlation, which indicates that the raindrop impact power observation system can characterize rainfall kinetic energy. The article establishes a preliminary way to calculate rainfall kinetic energy by using the real-time observed momentum, providing a foundation for replacing the traditional methods for estimating kinetic energy of rainstorms.

  15. Effects of Spatial Heterogeneity in Rainfall and Vegetation Type on Soil Moisture and Evapotranspiration

    Puma, Michael J; Rodriguez-Iturbe, Ignacio; Nordbotten, Jan M; Guswa, Andrew J; Kavetski, Dmitri


    Nonlinear plant-scale interactions controlling the soil-water balance are generally not valid at larger spatial scales due to spatial heterogeneity in rainfall and vegetation type. The relationships between spatially averaged variables are hysteretic even when unique relationships are imposed at the plant scale. The characteristics of these hysteretic relationships depend on the size of the averaging area and the spatial properties of the soil, vegetation, and rainfall. We upscale the plant-scale relationships to the scale of a regional land-surface model based on simulation data obtained through explicit representation of spatial heterogeneity in rainfall and vegetation type. The proposed upscaled function improves predictions of spatially averaged soil moisture and evapotranspiration relative to the effective-parameter approach for a water-limited Texas shrubland. The degree of improvement is a function of the scales of heterogeneity and the size of the averaging area. We also find that single-valued functi...

  16. Deforestation alters rainfall: a myth or reality

    Hanif, M. F.; Mustafa, M. R.; Hashim, A. M.; Yusof, K. W.


    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.

  17. An Atlantic influence on Amazon rainfall

    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)


    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.)

  18. Assessing dominant factors affecting soil erosion using a portable rainfall simulator



    Investigating the causes of soil erosion is difficult in natural conditions owing to the presence of other factors.Without simplifying the experimental conditions,studying soil behavior with its numerous parameters while considering factors such as vegetation cover,topography,and rainfall is difficult and in most conditions impossible.The application of simulation approaches is therefore necessary to simplify the prototype.In this research,the effects of physical soil factors such as texture and antecedent soil moisture,along with land slope and vegetation cover were evaluated in the Taleghan watershed,lran,using a rainfall simulator and soil erosion plots.For this purpose,a 89 × 120 cm rainfall simulator producing 24.5 and 32 mm/h rainfall intensities of 30 rain duration,as a common condition of the study area,was used at 144 locations over soil erosion plots with dimensions of 95 × 125 cm.Plots had slope classes of 12-20 and 20-30 %,different soil textures,different antecedent soil moistures,and medium to poor vegetation cover conditions.It was found that for 24.5 and 32 mm/h rainfall intensities,the sediment yield had high correlations of-0.771 and -0.796 with vegetation cover and slight correlations of 0.045 and 0.029 with land slope respectively.Regression equations for predicting the sediment yield were also developed for different conditions.

  19. Modelling and Simulation of Seasonal Rainfall Using the Principle of Maximum Entropy

    Jonathan Borwein


    Full Text Available We use the principle of maximum entropy to propose a parsimonious model for the generation of simulated rainfall during the wettest three-month season at a typical location on the east coast of Australia. The model uses a checkerboard copula of maximum entropy to model the joint probability distribution for total seasonal rainfall and a set of two-parameter gamma distributions to model each of the marginal monthly rainfall totals. The model allows us to match the grade correlation coefficients for the checkerboard copula to the observed Spearman rank correlation coefficients for the monthly rainfalls and, hence, provides a model that correctly describes the mean and variance for each of the monthly totals and also for the overall seasonal total. Thus, we avoid the need for a posteriori adjustment of simulated monthly totals in order to correctly simulate the observed seasonal statistics. Detailed results are presented for the modelling and simulation of seasonal rainfall in the town of Kempsey on the mid-north coast of New South Wales. Empirical evidence from extensive simulations is used to validate this application of the model. A similar analysis for Sydney is also described.

  20. Research on stability of the accumulated rock-soil body of reservoir bank under rainfall condition


    The shear strength parameters property of rock-soil aggregates in embankment slope of reservoir,that is,the relationship between cohesion and gravel content,between friction angle and gravel content,and the relationship between cohesion and water content,between friction angle and water content,is studied based on the direct shear test results,the shear strength change law of the rock-soil aggregates is given,and the unsaturated shear strength formulation of rock-soil aggregates that could consider suction and saturation degree influence is put forward in this paper,through which the sliding or failure physical mechanism of this type of slope under the condition of rainfall infiltration is studied. Also the 3D unsteady saturated-unsaturated seepage field and its FEM resolving mode are established based on the analysis of the slope rainfall infiltration process. Case study with this method indicates that the minimum safety factor of the accumulated rock-soil aggregates dose not arrive at the moment of rainfall cessation,but appears several hours after the rainfall cessation,this phenomenon is in accordance with the practical slope engineering’s failure process and could explain appropriately the slope failure caused by rainfall infiltration. Research results in this paper have an important reference value for the research on stability of the accumulated rock-soil aggregates in embankment slope of reservoir,and can enrich the stability analysis method and relevant theory of reservoir embankment slope.

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

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


    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

  2. Satellite-rainfall estimation for identification of rainfall thresholds used for landslide/debris flow prediction

    Maggioni, Viviana; Nikolopoulos, Efthymios I.; Marra, Francesco; Destro, Elisa; Borga, Marco


    Rainfall-induced landslides and debris flows pose a significant and widespread hazard, resulting in a large number of casualties and enormous economic damages worldwide. Rainfall thresholds are often used to identify the local or regional rainfall conditions that, when reached or exceeded, are likely to result in landslides or debris flows. Rain gauge data are the typical source of information for the definition of these rainfall thresholds. However, in-situ observations over mountainous areas, where these hazards mainly occur, are very sparse or inexistent. Therefore identification and use of gauge-based rainfall thresholds is impossible in many landslide prone areas over the globe. The vast advancements in satellite-based precipitation estimation over the last couple of decades have lead to the creation of a number of global precipitation datasets at various spatiotemporal resolutions. Although several investigations have shown that these datasets can be associated with considerable uncertainty, they provide the only source of precipitation information over many areas around the globe. Therefore it is important to assess their performance in the context of landslide/debris flow prediction and investigate how we can potentially benefit from the information they provide. In this work, we evaluate the performance of three widely used quasi-global satellite precipitation products (3B42v7, PERSIANN and CMORPH) for the identification of rainfall threshold for landslide/debris flow triggering. Products are available at 0.25deg/3h resolution. The study region is focused over the Upper Adige river basin, northern Italy where a detailed database of more than 400 identified debris flows (during period 2000-2015) and a raingauge network of 95 stations, is available. Rain-gauge based rainfall thresholds are compared against satellite-based thresholds to evaluate strengths and limitations in using satellite precipitation estimates for defining rainfall thresholds. Analysis of

  3. General Rainfall Patterns in Indonesia and the Potential Impacts of Local Seas on Rainfall Intensity

    Han Soo Lee


    Full Text Available The relationships between observed rainfall, El Niño/Southern Oscillation (ENSO and sea surface temperature (SST variations in the Pacific and Indian Oceans were analyzed using a 1° latitude–longitude grid over Indonesia. The Global Summary of the Day rainfall records provide 26 years of rainfall data (January 1985 to August 2010 for 23 stations throughout the Indonesian islands. The ENSO and SST variations were calculated using the Multivariate ENSO Index (MEI, the Pacific Decadal Oscillation (PDO, NINO1 + 2, NINO3, NINO3.4, NINO4, the Dipole Mode Index (DMI for the Indian Ocean Dipole (IOD, and Indian Ocean Basin-wide (IOBW index. The results show that the rainfall in the southern Sumatra and southern Java Islands, which face the Indian Ocean, was positively correlated with the negative IOD, whereas the rainfall in northwestern Sumatra was positively correlated with the positive IOD. In eastern Indonesia, the rainfall was positively correlated with La Niña. The PDO index was also strongly correlated with the rainfall in this region. In central Indonesia, seasonal variations due to monsoons are predominant, and the rainfall exhibited strong negative and positive correlations with the MEI and NINO.WEST, respectively, indicating that high rainfall occurred during strong La Niña episodes. The highly negative and positive correlations with the MEI and NINO.WEST, respectively, in central Indonesia led us to analyze the impacts of Indonesian seas on the rainfall in the region. Using four synoptic-scale scenarios, we investigated the relative residence time of Indonesian seawater along the pathways associated with the Pacific-Indian hydraulic head difference. The results show that when both the western Pacific and eastern Indian Oceans are warm (positive NINO.WEST and negative DMI, the rainfall intensity over central Indonesia is strongest. This increase is explained by the relationship between the residence time of Indonesian seawater and the

  4. Rainfall events prediction using rule-based fuzzy inference system

    Asklany, Somia A.; Elhelow, Khaled; Youssef, I. K.; Abd El-wahab, M.


    We are interested in rainfall events prediction by applying rule-based reasoning and fuzzy logic. Five parameters: relative humidity, total cloud cover, wind direction, temperature and surface pressure are the input variables for our model, each has three membership functions. The data used is twenty years METAR data for Cairo airport station (HECA) [1972-1992] 30° 3' 29″ N, 31° 13' 44″ E. and five years METAR data for Mersa Matruh station (HEMM) 31° 20' 0″ N, 27° 13' 0″ E. Different models for each station were constructed depending on the available data sets. Among the overall 243 possibilities we have based our models on one hundred eighteen fuzzy IF-THEN rules and fuzzy reasoning. The output variable which has four membership functions, takes values from zero to one hundred corresponding to the percentage for rainfall events given for every hourly data. We used two skill scores to verify our results, the Brier score and the Friction score. The results are in high agreements with the recorded data for the stations with increasing in output values towards the real time rain events. All implementation are done with MATLAB 7.9.

  5. Nonstationarity of daily rainfall annual maxima in Puglia (Southern Italy)

    Totaro, Vincenzo; Gioia, Andrea; Iacobellis, Vito


    Extreme flood events occurring in the last decades, due to climatic conditions in rapid evolution and/or changes in land cover, has lead the scientific community to develop and improve probabilistic techniques in order to take into account these effects, as also requested by the EU Floods Directive 2007/60. In the recent literature are becoming more popular studies that investigate the nonstationarity of the variables usually treated in hydrology through the analysis of their trend behavior. In this context it is also useful to assess the impact that the climate and /or land cover modifications have on the performances of the probabilistic stationary models used to predict hydrological variables such as rainfall and flood peaks. Among several proposed approaches, we use the redefined concept of return period and risk by considering the variability over time of the position parameter of the GEV distribution, with the subsequent discussion about the implications of analytical and technical characters. The analysis was carried out on the time series of annual maximum of daily precipitation available for a broad number of rainfall gauged stations in Puglia (Southern Italy). The investigation, conducted at the regional scale, leads to the identification of areas with different significativity of the statistical tests usually performed in order to assess nonstationarity. The evaluated change of return period leads to considerations useful to redesign methods for regional analysis of flood frequency.

  6. Statistical Inference for Point Process Models of Rainfall

    Smith, James A.; Karr, Alan F.


    In this paper we develop maximum likelihood procedures for parameter estimation and model selection that apply to a large class of point process models that have been used to model rainfall occurrences, including Cox processes, Neyman-Scott processes, and renewal processes. The statistical inference procedures are based on the stochastic intensity λ(t) = lims→0,s>0 (1/s)E[N(t + s) - N(t)|N(u), u process is shown to have a simple expression in terms of the stochastic intensity. The main result of this paper is a recursive procedure for computing stochastic intensities; the procedure is applicable to a broad class of point process models, including renewal Cox process with Markovian intensity processes and an important class of Neyman-Scott processes. The model selection procedure we propose, which is based on likelihood ratios, allows direct comparison of two classes of point processes to determine which provides a better model for a given data set. The estimation and model selection procedures are applied to two data sets of simulated Cox process arrivals and a data set of daily rainfall occurrences in the Potomac River basin.

  7. Sustainability, productivity, and profitability of agroecosystems under variable rainfall

    Vico, G.; Porporato, A. M.


    Agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements. Hence, it is becoming imperative to sustainably manage the available water resources, while simultaneously meeting yield and profitability targets. Simple, widely applicable models of irrigation provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability and are necessary for short- and long-term water resource management. We consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework that includes rainfed agriculture and stress-avoidance irrigation as extreme cases. Mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount are employed to compute water requirements, yields, and net economic gain as a function of climate, crop, and soil parameters. These results provide the necessary starting point to quantify the risks that a certain target yield or profit is not met for given irrigation strategies, with clear implications on food security

  8. Application of the rainfall infiltration breakthrough (RIB) model for ...

    Application of the rainfall infiltration breakthrough (RIB) model for groundwater ... Correlation analysis between rainfall and observed WLF data at daily scale and ... data are more realistic than those for daily data, when using long time series.

  9. Summer monsoon rainfall prediction for India - Some new ideas

    Varkey, M.J.

    Present methods of forecasting of mean Indian rainfall for summer monsoon season are critically examined. Considering the wide variations in mean seasonal rainfalls (more than 5 to less than 400 cm) and crops in various regions of India...

  10. Distribution of extreme rainfall events over Ebro River basin

    Saa, Antonio; Tarquis, Ana Maria; Valencia, Jose Luis; Gascó, Jose Maria


    The purpose of this work is to provide a description of the heavy rainfall phenomenon on statistical tools from a Spanish region. We want to quantify the effect of the climate change to verify the rapidity of its evolution across the variation of the probability distributions. Our conclusions have special interest for the agrarian insurances, which may make estimates of costs more realistically. In this work, the analysis mainly focuses on: The distribution of consecutive days without rain for each gauge stations and season. We estimate density Kernel functions and Generalized Pareto Distribution (GPD) for a network of station from the Ebro River basin until a threshold value u. We can establish a relation between distributional parameters and regional characteristics. Moreover we analyze especially the tail of the probability distribution. These tails are governed by law of power means that the number of events n can be expressed as the power of another quantity x : n(x) = x? . ? can be estimated as the slope of log-log plot the number of events and the size. The most convenient way to analyze n(x) is using the empirical probability distribution. Pr(X > x) ∞ x-?. The distribution of rainfall over percentile of order 0.95 from wet days at the seasonal scale and in a yearly scale with the same treatment of tails than in the previous section. The evolution of the distribution in the second XXth century and the impact on the extreme values model. After realized the analyses it does not appreciate difference in the distribution throughout the time which suggests that this region does not appreciate increase of the extreme values both for the number of dry consecutive days and for the value of the rainfall References: Coles, Stuart (2001). An Introduction to Statistical Modeling of Extreme Values,. Springer-Verlag Krishnamoorthy K. (2006), Handbook of Statistical Distributions with Applications, Chapman & Hall/CRC. Bodini A., Cossu A. (2010). Vulnerability assessment

  11. Rainfall mediations in the spreading of epidemic cholera

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


    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

  12. Dual-polarization radar rainfall estimation in Korea according to raindrop shapes obtained by using a 2-D video disdrometer

    Kim, Hae-Lim; Suk, Mi-Kyung; Park, Hye-Sook; Lee, Gyu-Won; Ko, Jeong-Seok


    Polarimetric measurements are sensitive to the sizes, concentrations, orientations, and shapes of raindrops. Thus, rainfall rates calculated from polarimetric radar are influenced by the raindrop shapes and canting. The mean raindrop shape can be obtained from long-term raindrop size distribution (DSD) observations, and the shapes of raindrops can play an important role in polarimetric rainfall algorithms based on differential reflectivity (ZDR) and specific differential phase (KDP). However, the mean raindrop shape is associated with the variation of the DSD, which can change depending on precipitation types and climatic regimes. Furthermore, these relationships have not been studied extensively on the Korean Peninsula. In this study, we present a method to find optimal polarimetric rainfall algorithms for the Korean Peninsula by using data provided by both a two-dimensional video disdrometer (2DVD) and the Bislsan S-band dual-polarization radar. First, a new axis-ratio relation was developed to improve radar rainfall estimations. Second, polarimetric rainfall algorithms were derived by using different axis-ratio relations. The rain gauge data were used to represent the ground truth situation, and the estimated radar-point hourly mean rain rates obtained from the different polarimetric rainfall algorithms were compared with the hourly rain rates measured by a rain gauge. The daily calibration biases of horizontal reflectivity (ZH) and differential reflectivity (ZDR) were calculated by comparing ZH and ZDR radar measurements with the same parameters simulated by the 2DVD. Overall, the derived new axis ratio was similar to the existing axis ratio except for both small particles (≤ 2 mm) and large particles (≥ 5.5 mm). The shapes of raindrops obtained by the new axis-ratio relation carried out with the 2DVD were more oblate than the shapes obtained by the existing relations. The combined polarimetric rainfall relations using ZDR and KDP were more efficient than

  13. Inter-Scale Statistical Analysis of Fine-Resolution Rainfall Datasets over the Japanese Islands

    Gómez García Alvéstegui, Martín; Koike, Toshio


    The continuous improvement of remotely-sensed precipitation estimates has greatly favored the inter-scale statistical study of rainfall fields and its potential applications. One of the expected results of this type of analysis is intended to provide the guidelines to effectively reproduce at finer scales (downscaling) the characteristic geometrical structure. Intermittency (no-rain areas contained within large rainfall fields), slow-varying gradients of intensity, and sudden sharp rises of intensity (high-intensity regions enclosed, or rapidly followed, by lower-intensity fields) are within the structural properties that define the rainfall fields. The concept of intermittency, indicates a positive probability of having no rain at some point, and for that reason the actual magnitude of rainfall intensity is not compatible with some scaling operations. However, the deviations of local means (local fluctuations) proved to be a process with noteworthy inter-scale statistical properties. Previous research revealed that local fluctuations can be well adjusted to stable distributions, in which the characteristic exponent α defines the thickness of the tails. If so, it can be inferred that this parameter should be related to the type of rainfall (rate of variation of intensity). However, the abovementioned research showed that in order to portray a self-similar relationship between scales the fluctuations needed to be divided by their correspondent local mean (standardization). The distribution of these standardized values was observed to be almost Gaussian (α = 2), and even though remarkable, with this operation becomes more challenging to relate the frequency of extreme values with the type of rainfall. In our study the local fluctuations of rainfall were analyzed by fitting the data to a folded stable distribution which is a distribution of absolute values. This approach not only allowed to reveal a somewhat invariance of the characteristic exponent between scales

  14. Towards a comprehensive physically-based rainfall-runoff model

    Z. Liu


    Full Text Available This paper introduces TOPKAPI (TOPographic Kinematic APproximation and Integration, a new physically-based distributed rainfall-runoff model deriving from the integration in space of the kinematic wave model. The TOPKAPI approach transforms the rainfall-runoff and runoff routing processes into three ‘structurally-similar’ non-linear reservoir differential equations describing different hydrological and hydraulic processes. The geometry of the catchment is described by a lattice of cells over which the equations are integrated to lead to a cascade of non-linear reservoirs. The parameter values of the TOPKAPI model are shown to be scale independent and obtainable from digital elevation maps, soil maps and vegetation or land use maps in terms of slope, soil permeability, roughness and topology. It can be shown, under simplifying assumptions, that the non-linear reservoirs aggregate into three reservoir cascades at the basin scale representing the soil, the surface and the drainage network, following the topographic and geomorphologic elements of the catchment, with parameter values which can be estimated directly from the small scale ones. The main advantage of this approach lies in its capability of being applied at increasing spatial scales without losing model and parameter physical interpretation. The model is foreseen to be suitable for land-use and climate change impact assessment; for extreme flood analysis, given the possibility of its extension to ungauged catchments; and last but not least as a promising tool for use with General Circulation Models (GCMs. To demonstrate the quality of the comprehensive distributed/lumped TOPKAPI approach, this paper presents a case study application to the Upper Reno river basin with an area of 1051 km2 based on a DEM grid scale of 200 m. In addition, a real-world case of applying the TOPKAPI model to the Arno river basin, with an area of 8135 km2 and using a DEM grid scale of 1000 m, for the

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

    T. P. Burt


    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.

  16. Rainfall Mechanisms for the Dominant Rainfall Mode over Zimbabwe Relative to ENSO and/or IODZM

    Desmond Manatsa


    Full Text Available Zimbabwe’s homogeneous precipitation regions are investigated by means of principal component analysis (PCA with regard to the underlying processes related to ENSO and/or Indian Ocean Dipole zonal mode (IODZM. Station standardized precipitation index rather than direct rainfall values represent the data matrix used in the PCA. The results indicate that the country’s rainfall is highly homogeneous and is dominantly described by the first principal mode (PC1. This leading PC can be used to represent the major rainfall patterns affecting the country, both spatially and temporarily. The current practice of subdividing the country into the two seasonal rainfall forecast zones becomes irrelevant. Partial correlation analysis shows that PC1 is linked more to the IODZM than to the traditional ENSO which predominantly demonstrates insignificant association with PC1. The pure IODZM composite is linked to the most intense rainfall suppression mechanisms, while the pure El Niño composite is linked to rainfall enhancing mechanisms.

  17. Impacts of Urbanization on Indian Summer Monsoon Rainfall

    Shastri, H. K.; Ghosh, S.; Karmakar, S.


    Rapid urbanisation all around the world is a matter of concern to the scientific community. The fast growing urban areas carries out huge anthropogenic activities that burdens natural environment and its resources like air-water quality and space, thus have different climatology to their rural surroundings. World Urbanization Prospects 2005 annual report described 20th century as witnessing a rapid urbanization of the world's population. Though urbanization is a worldwide phenomenon, it is especially prevalent in India, where urban areas have experienced an unprecedented rate of growth with level of urbanization increased from 17.23 % to 31.16% in year 1951 to 2011and the number of cities with population more than one million has grown from 5 to 53 over the same time. We take up an observational study to understand influence of urbanisation on mesoscale circulations and resulting convection, thus nature of precipitation around urban areas. The spatially distributed analysis of gridded daily precipitation data over the country is carried out to identify nature of trends in selected statistics of Indian summer monsoon precipitation and examine its association with urban land cover to have an impact on precipitation statistics. We evaluate explicit changes around urban land use in context of 40 large Indian urban areas. Further we assess local-urban climatic signals in the point level rainfall observations with model based analysis of two nearby locations under similar climatic conditions but differing largely in terms of urbanisation. The results of gridded data analysis indicate an overall tendency towards decrease in mean precipitation however, rainfall activities are enhanced around urban areas across different climate zones of the country. Though trends observed in selected climatic parameters revealed great degree of spatial inter variability in selected precipitation statistics over the country, they accounts a greater degree of inclination for occurrence under

  18. Investigating changes over time of annual rainfall in Zimbabwe

    D. Mazvimavi


    Full Text Available There is increasing concern in southern Africa about the possible decline of rainfall as a result of global warming. Some studies concluded that average rainfall in Zimbabwe had declined by 10% or 100 mm during the last 100 years. This paper investigates the validity of the assumption that rainfall is declining in Zimbabwe. Time series of annual rainfall, and total rainfall for (a the early part of the rainy season, October-November-December (OND, and (b the mid to end of the rainy season, January-February-March (JFM are analysed for the presence of trends using the Mann-Kendall test, and for the decline or increase during years with either high or low rainfall using quantile regression analysis. The Pettitt test has also been utilized to examine the possible existence of change or break-points in the rainfall time series. The analysis has been done for 40 rainfall stations with records starting during the 1892–1940 period and ending in 2000, and representative of all the rainfall regions.

    The Mann-Kendal test did not identify a significant trend at all the 40 stations, and therefore there is no proof that the average rainfall at each of these stations has changed. Quantile regression analysis revealed a decline in annual rainfall less than the tenth percentile at only one station, and increasing of rainfall greater than the ninetieth percentile at another station. All the other stations had no changes over time in both the low and high rainfall at the annual interval. Climate change effects are therefore not yet statistically significant within time series of total seasonal and annual rainfall in Zimbabwe. The general perception about declining rainfall is likely due to the presence of multidecadal variability characterized by bunching of years with above (e.g. 1951–1958, 1973–1980 and below (e.g. 1959–1972, 1982–1994 average rainfall.

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

    B. Salahi


    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


    Ushiyama, Motoyuki

    "Guerilla heavy rainfall" is a newly-coined word by mass media of Japan. The four major newspaper publishing companies began to use this word frequently from the beginning of August, 2008. The definition of "Guerilla heavy rainfall" is not clear. It was found from the result of newspaper article analysis from 2008 to 2009 that short-time very heavy rainfall events are called "Guerilla heavy rainfall". In this study, the rainfall event of 80mm or more of rainfalls of 1 hour and 149mm or less of rainfalls was defined as "Guerilla heavy rainfall". 104 events of "Guerilla heavy rainfall" were extracted from AMeDAS precipitation data from 1979 to 2008. There were two victims of these heavy rainfall events in total. They killed at basement or underpass. Although inundation above the floor level occurred in 38% of event, the damage of 100 or more buildings was 9%. We may say that "Guerilla heavy rainfall" does not cause large-scale damage. However, it is necessary to keep in mind that damage caused by "Guerilla heavy rainfall" is generated well in high-risk area of flood, such as basement, underpass, low land and river park.

  1. Models are likely to underestimate increase in heavy rainfall in the extratropical regions with high rainfall intensity

    Borodina, Aleksandra; Fischer, Erich M.; Knutti, Reto


    Model projections of regional changes in heavy rainfall are uncertain. On timescales of few decades, internal variability plays an important role and therefore poses a challenge to detect robust model response in heavy rainfall to rising temperatures. We use spatial aggregation to reduce the major role of internal variability and evaluate the heavy rainfall response to warming temperatures with observations. We show that in the regions with high rainfall intensity and for which gridded observations exist, most of the models underestimate the historical scaling of heavy rainfall and the land fraction with significant positive heavy rainfall scalings during the historical period. The historical behavior is correlated with the projected heavy rainfall intensification across models allowing to apply an observational constraint, i.e., to calibrate multimodel ensembles with observations in order to narrow the range of projections. The constraint suggests a substantially stronger intensification of future heavy rainfall than the multimodel mean.

  2. Mapping monthly rainfall erosivity in Europe.

    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


    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

  3. Use of Generalised Linear Models to quantify rainfall input uncertainty to hydrological modelling in the Upper Nile

    Kigobe, M.; McIntyre, N.; Wheater, H. S.


    Interest in the application of climate and hydrological models in the Nile basin has risen in the recent past; however, the first drawback for most efforts has been the estimation of historic precipitation patterns. In this study we have applied stochastic models to infill and extend observed data sets to generate inputs for hydrological modelling. Several stochastic climate models within the Generalised Linear Modelling (GLM) framework have been applied to reproduce spatial and temporal patterns of precipitation in the Kyoga basin. A logistic regression model (describing rainfall occurrence) and a gamma distribution (describing rainfall amounts) are used to model rainfall patterns. The parameters of the models are functions of spatial and temporal covariates, and are fitted to the observed rainfall data using log-likelihood methods. Using the fitted model, multi-site rainfall sequences over the Kyoga basin are generated stochastically as a function of the dominant seasonal, climatic and geographic controls. The rainfall sequences generated are then used to drive a semi distributed hydrological model using the Soil Water and Assessment Tool (SWAT). The sensitivity of runoff to uncertainty associated with missing precipitation records is thus tested. In an application to the Lake Kyoga catchment, the performance of the hydrological model highly depends on the spatial representation of the input precipitation patterns, model parameterisation and the performance of the GLM stochastic models used to generate the input rainfall. The results obtained so far disclose that stochastic models can be developed for several climatic regions within the Kyoga basin; and, given identification of a stochastic rainfall model; input uncertainty due to precipitation can be usefully quantified. The ways forward for rainfall modelling and hydrological simulation in Uganda and the Upper Nile are discussed. Key Words: Precipitation, Generalised Linear Models, Input Uncertainty, Soil Water

  4. Simulation of High Impact Rainfall Events Over Southeastern Hilly Region of Bangladesh Using MM5 Model

    M. N. Ahasan


    Full Text Available Simulation of high impact rainfall events over southeastern hilly region of Bangladesh has been carried out using Fifth-Generation PSU/NCAR Mesoscale Model (MM5 conducting two historical rainfall events, namely, 21 June, 2004 and 11 July, 2004. These extraordinary rainfall events were localized over the Rangamati region and recorded 304 mm and 337 mm rainfall on 21 June, 2004 and 11 July, 2004, respectively, over Rangamati within a span of 24 h. The model performance was evaluated by examining the different predicted and derived parameters. It is found that the seasonal monsoon trough has northerly position compared to normal and pass through Bangladesh extending up to northeast India for both cases. The heat low was found to be intense (996 hPa with strong north-south pressure gradient (12–15 hPa. The analysis of the geopotential height field at 200 hPa shows that the Tibetan high is shifted towards south by 7-8° latitudes with axis along 22–25°N for both cases. The analysis of the wind field shows that the areas of high impact rainfall exhibit strong convergence of low level monsoon circulation (~19–58 knots. The strong southwesterlies were found to exist up to 500 hPa level in both cases. The lower troposphere (925–500 hPa was characterized by the strong vertical wind shear (~9–18 ms−1 and high relative vorticity (~20–40 × 10−5 s−1. The analysis also shows that the areas of high impact rainfall events and neighbourhoods are characterized by strong low level convergence and upper level divergence. The strong southwesterly flow causes transportation of large amount of moisture from the Bay of Bengal towards Bangladesh, especially over the areas of Rangamati and neighbourhoods. The high percentage of relative humidity extends up to the upper troposphere along a narrow vertical column. Model produced details structure of the spatial patterns of rainfall over Bangladesh reasonably well though there are some

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

    S. Raia


    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

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

    S. Raia


    Full Text Available 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

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

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


    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

  8. Capabilities of stochastic rainfall models as data providers for urban hydrology

    Haberlandt, Uwe


    For planning of urban drainage systems using hydrological models, long, continuous precipitation series with high temporal resolution are needed. Since observed time series are often too short or not available everywhere, the use of synthetic precipitation is a common alternative. This contribution compares three precipitation models regarding their suitability to provide 5 minute continuous rainfall time series for a) sizing of drainage networks for urban flood protection and b) dimensioning of combined sewage systems for pollution reduction. The rainfall models are a parametric stochastic model (Haberlandt et al., 2008), a non-parametric probabilistic approach (Bárdossy, 1998) and a stochastic downscaling of dynamically simulated rainfall (Berg et al., 2013); all models are operated both as single site and multi-site generators. The models are applied with regionalised parameters assuming that there is no station at the target location. Rainfall and discharge characteristics are utilised for evaluation of the model performance. The simulation results are compared against results obtained from reference rainfall stations not used for parameter estimation. The rainfall simulations are carried out for the federal states of Baden-Württemberg and Lower Saxony in Germany and the discharge simulations for the drainage networks of the cities of Hamburg, Brunswick and Freiburg. Altogether, the results show comparable simulation performance for the three models, good capabilities for single site simulations but low skills for multi-site simulations. Remarkably, there is no significant difference in simulation performance comparing the tasks flood protection with pollution reduction, so the models are finally able to simulate both the extremes and the long term characteristics of rainfall equally well. Bárdossy, A., 1998. Generating precipitation time series using simulated annealing. Wat. Resour. Res., 34(7): 1737-1744. Berg, P., Wagner, S., Kunstmann, H., Schädler, G

  9. Effect of rainfall as a component of climate change on estuarine fish production in Queensland, Australia

    Meynecke, Jan-Olaf; Lee, Shing Yip; Duke, Norman C.; Warnken, Jan


    The speculation that climate change may impact on sustainable fish production suggests a need to understand how these effects influence fish catch on a broad scale. With a gross annual value of A$ 2.2 billion, the fishing industry is a significant primary industry in Australia. Many commercially important fish species use estuarine habitats such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds and have lifecycles correlated to rainfall and temperature patterns. Correlation of catches of mullet (e.g. Mugil cephalus) and barramundi ( Lates calcarifer) with rainfall suggests that fisheries may be sensitive to effects of climate change. This work reviews key commercial fish and crustacean species and their link to estuaries and climate parameters. A conceptual model demonstrates ecological and biophysical links of estuarine habitats that influences capture fisheries production. The difficulty involved in explaining the effect of climate change on fisheries arising from the lack of ecological knowledge may be overcome by relating climate parameters with long-term fish catch data. Catch per unit effort (CPUE), rainfall, the Southern Oscillation Index (SOI) and catch time series for specific combinations of climate seasons and regions have been explored and surplus production models applied to Queensland's commercial fish catch data with the program CLIMPROD. Results indicate that up to 30% of Queensland's total fish catch and up to 80% of the barramundi catch variation for specific regions can be explained by rainfall often with a lagged response to rainfall events. Our approach allows an evaluation of the economic consequences of climate parameters on estuarine fisheries, thus highlighting the need to develop forecast models and manage estuaries for future climate change impact by adjusting the quota for climate change sensitive species. Different modelling approaches are discussed with respect to their forecast ability.

  10. Borneo vortex and mesoscale convective rainfall

    Koseki, S.; Koh, T.-Y.; Teo, C.-K.


    We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite data sets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the Equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-α cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-β-scale rainfall cells. The intense rainfall in the comma head (comma tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-α cyclone system. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics.

  11. Rainfall Predictions From Global Salinity Anomalies

    Schmitt, R. W.; Li, L.; Liu, T.


    We have discovered that sea surface salinity (SSS) is a better seasonal predictor of terrestrial rainfall than sea surface temperature (SST) or the usual pressure modes of atmospheric variability. In many regions, a 3-6 month lead of SSS over rainfall on land can be seen. While some lead is guaranteed due to the simple conservation of water and salt, the robust seasonal lead for SSS in some places is truly remarkable, often besting traditional SST and pressure predictors by a very significant margin. One mechanism for the lead has been identified in the recycling of water on land through soil moisture in regional ocean to land moisture transfers. However, a global search has yielded surprising long-range SSS-rainfall teleconnections. It is suggested that these teleconnections indicate a marked sensitivity of the atmosphere to where rain falls on the ocean. That is, the latent heat of evaporation is by far the largest energy transfer from ocean to atmosphere and where the atmosphere cashes in this energy in the form of precipitation is well recorded in SSS. SSS also responds to wind driven advection and mixing. Thus, SSS appears to be a robust indicator of atmospheric energetics and moisture transport and the timing and location of rainfall events is suggested to influence the subsequent evolution of the atmospheric circulation. In a sense, if the fall of a rain drop is at least equivalent to the flap of a butterfly's wings, the influence of a billion butterfly rainstorm allows for systematic predictions beyond the chaotic nature of the turbulent atmosphere. SSS is found to be particularly effective in predicting extreme precipitation or droughts, which makes its continued monitoring very important for building societal resilience against natural disasters.

  12. Artificial Neural Network for Monthly Rainfall Rate Prediction

    Purnomo, H. D.; Hartomo, K. D.; Prasetyo, S. Y. J.


    Rainfall rate forecasting plays an important role in various human activities. Rainfall forecasting is a challenging task due to the uncertainty of natural phenomena. In this paper, two neural network models are proposed for monthly rainfall rate forecasting. The performance of the proposed model is assesses based on monthly rainfall rate in Ampel, Boyolali, from 2001-2013. The experiment results show that the accuracy of the first model is much better than the accuracy of the second model. Its average accuracy is just above 98%, while the accuracy of the second model is approximately 75%. In additional, both models tend to perform better when the fluctuation of rainfall is low.

  13. Rainfall-enhanced blooming in typhoon wakes

    Lin, Y.-C.; Oey, L.-Y.


    Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

  14. Rainfall regimes of the Green Sahara.

    Tierney, Jessica E; Pausata, Francesco S R; deMenocal, Peter B


    During the "Green Sahara" period (11,000 to 5000 years before the present), the Sahara desert received high amounts of rainfall, supporting diverse vegetation, permanent lakes, and human populations. Our knowledge of rainfall rates and the spatiotemporal extent of wet conditions has suffered from a lack of continuous sedimentary records. We present a quantitative reconstruction of western Saharan precipitation derived from leaf wax isotopes in marine sediments. Our data indicate that the Green Sahara extended to 31°N and likely ended abruptly. We find evidence for a prolonged "pause" in Green Sahara conditions 8000 years ago, coincident with a temporary abandonment of occupational sites by Neolithic humans. The rainfall rates inferred from our data are best explained by strong vegetation and dust feedbacks; without these mechanisms, climate models systematically fail to reproduce the Green Sahara. This study suggests that accurate simulations of future climate change in the Sahara and Sahel will require improvements in our ability to simulate vegetation and dust feedbacks.

  15. Statistical distribution of rainfall in Uttarakhand, India

    Kumar, Vikram; Shanu; Jahangeer


    Understanding of rainfall is an important issue for Uttarakhand, India which having varied topography and due to that extreme rainfall causes quick runoff which warns structural and functional safety of large structures and other natural resources. In this study, an attempt has been made to determine the best-fit distribution of the annual series of rainfall data for the period of 1991-2002 of 13 districts of Uttarakhand. A best-fit distribution such as Chi-squared, Chi-squared (2P), exponential, exponential (2P), gamma, gamma (3P), gen. extreme value (GEV), log-Pearson 3, Weibull, Weibull (3P) distributions was applied. Comparisons of best distributions were based on the use of goodness-of-fit tests such as Kolmogorov-Smirnov, Anderson-Darling, and Chi squared. Results showed that the Weibull distribution performed the best with 46% of the total district, while the second best distribution was Chi squared (2P) and log-Pearson. The results of this study would be useful to the water resource engineers, policy makers and planners for the agricultural development and conservation of natural resources of Uttarakhand.

  16. Cyclical components of local rainfall data

    Mentz, R. P.; D'Urso, M. A.; Jarma, N. M.; Mentz, G. B.


    This paper reports on the use of a comparatively simple statistical methodology to study local short time series rainfall data. The objective is to help in agricultural planning, by diminishing the risks associated with some uncertainties affecting this business activity.The analysis starts by assuming a model of unobservable components, trend, cycle, seasonal and irregular, that is well known in many areas of application. When series are in the realm of business and economics, the statistical methods popularized by the US Census Bureau US National Bureau of Economic Research are used for seasonal and cyclical estimation, respectively. The flexibility of these methods makes them good candidates to be applied in the meteorological context, and this is done in this paper for a selection of monthly rainfall time series.Use of the results to help in analysing and forecasting cyclical components is emphasized. The results are interesting. An agricultural entrepreneur, or a group of them located in a single geographical region, will profit by systematically collecting information (monthly in our work) about rainfall, and adopting the scheme of analysis described in this paper.

  17. Tropical stratospheric circulation and monsoon rainfall

    Sikder, A. B.; Patwardhan, S. K.; Bhalme, H. N.


    Interannual variability of both SW monsoon (June September) and NE monsoon (October December) rainfall over subdivisions of Coastal Andhra Pradesh, Rayalaseema and Tamil Nadu have been examined in relation to monthly zonal wind anomaly for 10 hPa, 30 hPa and 50 hPa at Balboa (9°N, 80°W) for the 29 year period (1958 1986). Correlations of zonal wind anomalies to SW monsoon rainfall ( r=0.57, significant at 1% level) is highest with the longer lead time (August of the previous year) at 10 hPa level suggesting some predictive value for Coastal Andhra Pradesh. The probabilities estimated from the contingency table reveal non-occurrence of flood during easterly wind anomalies and near non-occurrence of drought during westerly anomalies for August of the previous year at 10 hPa which provides information for forecasting of performance of SW monsoon over Coastal Andhra Pradesh. However, NE monsoon has a weak relationship with zonal wind anomalies of 10 hPa, 30 hPa and 50 hPa for Coastal Andhra Pradesh, Rayalaseema and Tamil Nadu. Tracks of the SW monsoon storms and depressions in association with the stratospheric wind were also examined to couple with the fluctuations in SW monsoon rainfall. It is noted that easterly / westerly wind at 10 hPa, in some manner, suppresses / enhances monsoon storms and depressions activity affecting their tracks.

  18. Rainfall regimes of the Green Sahara

    Tierney, Jessica E.; Pausata, Francesco S. R.; deMenocal, Peter B.


    During the “Green Sahara” period (11,000 to 5000 years before the present), the Sahara desert received high amounts of rainfall, supporting diverse vegetation, permanent lakes, and human populations. Our knowledge of rainfall rates and the spatiotemporal extent of wet conditions has suffered from a lack of continuous sedimentary records. We present a quantitative reconstruction of western Saharan precipitation derived from leaf wax isotopes in marine sediments. Our data indicate that the Green Sahara extended to 31°N and likely ended abruptly. We find evidence for a prolonged “pause” in Green Sahara conditions 8000 years ago, coincident with a temporary abandonment of occupational sites by Neolithic humans. The rainfall rates inferred from our data are best explained by strong vegetation and dust feedbacks; without these mechanisms, climate models systematically fail to reproduce the Green Sahara. This study suggests that accurate simulations of future climate change in the Sahara and Sahel will require improvements in our ability to simulate vegetation and dust feedbacks. PMID:28116352

  19. Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

    Singh, A.; Mohanty, U. C.; Ghosh, K.


    Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall

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

    Svoboda Vojtěch


    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.

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

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


    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

  2. Observed daily large-scale rainfall patterns during BOBMEX-1999

    A K Mitra; M Das Gupta; R K Paliwal; S V Singh


    A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.

  3. Prediction of daily rainfall by a hybrid wavelet-season-neuro technique

    Altunkaynak, Abdusselam; Nigussie, Tewodros Assefa


    Accurate daily rainfall prediction is required for accurate streamflow prediction, flooding risk analysis, constructing a reliable flood control and early warning system. However, because of its nonlinearity, prediction of daily rainfall with high accuracy and long prediction lead time is difficult. There are many daily rainfall prediction methods in the literature, but they are known to yield inaccurate predictions with short lead time, require many physical parameters and involve complicated mathematical equations with huge computational burden. Recently, artificial neural network has been used for predicting rainfall with the objective of addressing the above mentioned problems. But still, the accuracy has not been satisfactory and predictions are with short lead time. In this study, two methods called combined season-multilayer perceptron (SAS-MP) and hybrid wavelet-season-multilayer perceptron (W-SAS-MP) were developed to enhance prediction accuracy and extend prediction lead time of daily rainfall up to 5 days by using data from two stations in Turkey. These two models were compared with the stand-alone multilayer perceptron and another most commonly used method called combined wavelet-multilayer perceptron (W-MP). The performances of the models were evaluated by using coefficient of determination, coefficient of efficiency and root mean squared error. The SAS-MP model was found to be better than W-MP in most cases, except lead time day 1, where W-MP performed better. Throughout all the lead times, however, the hybrid W-SAS-MP model performed best with CE values of 0.911 and 0.909, respectively, for prediction lead time of 1 day and 0.588 and 0.570, respectively, for prediction lead time of 5 days at Stations 17836 and 17837, respectively, at the model testing (validation) phase. Therefore, W-SAS-MP can be an appropriate tool for enhancing daily rainfall prediction accuracy and extend prediction lead time.

  4. Rainfall-Runoff Modelling using Modified NRCS-CN,RS and GIS -A Case Study

    P.Sundara Kumar


    Full Text Available Study of rainfall and runoff for any area and modeling it, is one of the important aspects for planning and development of water resources. The development of water resources and its effective management plays a vital role in development of any country more particularly in India, which is an agricultural based economy. Hence it is intended to develop a model of Rainfall and runoff to a river basin and also apply the methodology to Sarada River Basin which has drainage area of 1252.99 The basin is situated in Vishakhapatnam district of Andhra Pradesh, India. The rainfall and runoff data has been collected from the gauging stations of the basin apart from rainfall data from nearby stations. MNRCS-CN method has been adopted to calculate runoff. Various hydrological parameters like soil information, rainfall, land use and land cover (LU/LC were considered to use in MNRCS-CN method. The depth of runoff has been computed for different land use patterns using, IRS-P4- LISS IV data for the study area. Based on the analysis, land use/land cover pattern of Sarada River Basin has been prepared. The land use/land cover patterns were also visually interpreted and digitized using ERDAS IMAGINE software. The raster data was processed in ERDAS and geo-referenced and various maps viz. LU/LC maps, drainage map, contour map, DEM (Digital elevation model have been generated apart from rainfall potential map using GIS tool. The estimated runoff using MNRCS-CN model has been simulated and compared with that of actual runoff. The performance of the model is found to be good for the data considered. The coefficient of determination R2 value for the observed runoff and that of the computed runoff is found to be more than 0.72 for the selected watershed basin

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

    Worku, L. Y.


    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.

  6. What are the best covariates for developing non-stationary rainfall Intensity-Duration-Frequency relationship?

    Agilan, V.; Umamahesh, N. V.


    Present infrastructure design is primarily based on rainfall Intensity-Duration-Frequency (IDF) curves with so-called stationary assumption. However, in recent years, the extreme precipitation events are increasing due to global climate change and creating non-stationarity in the series. Based on recent theoretical developments in the Extreme Value Theory (EVT), recent studies proposed a methodology for developing non-stationary rainfall IDF curve by incorporating trend in the parameters of the Generalized Extreme Value (GEV) distribution using Time covariate. But, the covariate Time may not be the best covariate and it is important to analyze all possible covariates and find the best covariate to model non-stationarity. In this study, five physical processes, namely, urbanization, local temperature changes, global warming, El Niño-Southern Oscillation (ENSO) cycle and Indian Ocean Dipole (IOD) are used as covariates. Based on these five covariates and their possible combinations, sixty-two non-stationary GEV models are constructed. In addition, two non-stationary GEV models based on Time covariate and one stationary GEV model are also constructed. The best model for each duration rainfall series is chosen based on the corrected Akaike Information Criterion (AICc). From the findings of this study, it is observed that the local processes (i.e., Urbanization, local temperature changes) are the best covariate for short duration rainfall and global processes (i.e., Global warming, ENSO cycle and IOD) are the best covariate for the long duration rainfall of the Hyderabad city, India. Furthermore, the covariate Time is never qualified as the best covariate. In addition, the identified best covariates are further used to develop non-stationary rainfall IDF curves of the Hyderabad city. The proposed methodology can be applied to other situations to develop the non-stationary IDF curves based on the best covariate.

  7. Development of Hierarchical Bayesian Model Based on Regional Frequency Analysis and Its Application to Estimate Areal Rainfall in South Korea

    Kim, J.; Kwon, H. H.


    The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, This study aims to develop a hierarchical Bayesian model based regional frequency analysis in that spatial patterns of the design rainfall with geographical information are explicitly incorporated. This study assumes that the parameters of Gumbel distribution are a function of geographical characteristics (e.g. altitude, latitude and longitude) within a general linear regression framework. Posterior distributions of the regression parameters are estimated by Bayesian Markov Chain Monte Calro (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the Gumbel distribution by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Acknowledgement: This research was supported by a grant (14AWMP-B079364-01) from Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  8. Value of bias-corrected satellite rainfall products in SWAT simulations and comparison with other models in the Mara basin

    Serrat-Capdevila, A.; Abitew, T. A.; Roy, T.; van Griensven, A.; Valdes, J. B.; Bauwens, W.


    Hydrometeorological monitoring networks are often limited for basins located in the developing world such as the transboundary Mara Basin. The advent of earth observing systems have brought satellite rainfall and evapotranspiration products, which can be used to force hydrological models in data scarce basins. The objective of this study is to develop improved hydrologic simulations using distributed satellite rainfall products (CMORPH and TMPA) with a bias-correction, and compare the performance with different input data and models. The bias correction approach for the satellite-products (CMORPH and TMPA) involves the use of a distributed reference dataset (CHIRPS) and historical ground gauge records. We have applied the bias-corrected satellite products to force the Soil and Water Assessment Tool (SWAT) model for the Mara Basin. Firstly, we calibrate the SWAT parameters related to ET simulation using ET from remote sensing. Then, the SWAT parameters that control surface processes are calibrated using the available limited flow. From the analysis, we noted that not only the bias-corrected satellite rainfall but also augmenting limited flow data with monthly remote sensing ET improves the model simulation skill and reduces the parameter uncertainty to some extent. We have planned to compare these results from a lumped model forced by the same input satellite rainfall. This will shed light on the potential of satellite rainfall and remote sensing ET along with in situ data for hydrological processes modeling and the inherent uncertainty in a data scarce basin.

  9. Passive microwave rainfall retrieval: A mathematical approach via sparse learning

    Ebtehaj, M.; Lerman, G.; Foufoula-Georgiou, E.


    Detection and estimation of surface rainfall from spaceborne radiometric imaging is a challenging problem. The main challenges arise due to the nonlinear relationship of surface rainfall with its microwave multispectral signatures, the presence of noise, insufficient spatial resolution in observations, and the mixture of the earth surface and atmospheric radiations. A mathematical approach is presented for the detection and retrieval of surface rainfall from radiometric observations via supervised learning. In other words, we use a priori known libraries of high-resolution rainfall observations (e.g., obtained by an active radar) and their coincident spectral signatures (i.e., obtained by a radiometer) to design a mathematical model for rainfall retrieval. This model views the rainfall retrieval as a nonlinear inverse problem and relies on sparsity-promoting Bayesian inversion techniques. In this approach, we assume that small neighborhoods of the rainfall fields and their spectral signatures live on manifolds with similar local geometry and encode those neighborhoods in two joint libraries, the so-called rainfall and spectral dictionaries. We model rainfall passive microwave images by sparse linear combinations of the atoms of the spectral dictionary and then use the same representation coefficients to retrieve surface rain rates from the corresponding rainfall dictionary. The proposed methodology is examined by the use of spectral and rainfall dictionaries provided by the microwave imager (TMI) and precipitation radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Pros and cons of the presented approach are studied by extensive comparisons with the current operational rainfall algorithm of the TRMM satellite. Future extensions are also highlighted for potential application in the era of the Global Precipitation Measurement (GPM) mission. Comparing the retrieved rain rates for Hurricane Danielle 08/29/2010 (UTC 09:48:00). (Top panel) PR-2A

  10. Uncertainty of Areal Rainfall Estimation Using Point Measurements

    McCarthy, D.; Dotto, C. B. S.; Sun, S.; Bertrand-Krajewski, J. L.; Deletic, A.


    The spatial variability of precipitation has a great influence on the quantity and quality of runoff water generated from hydrological processes. In practice, point rainfall measurements (e.g., rain gauges) are often used to represent areal rainfall in catchments. The spatial rainfall variability is difficult to be precisely captured even with many rain gauges. Thus the rainfall uncertainty due to spatial variability should be taken into account in order to provide reliable rainfall-driven process modelling results. This study investigates the uncertainty of areal rainfall estimation due to rainfall spatial variability if point measurements are applied. The areal rainfall is usually estimated as a weighted sum of data from available point measurements. The expected error of areal rainfall estimates is 0 if the estimation is an unbiased one. The variance of the error between the real and estimated areal rainfall is evaluated to indicate the uncertainty of areal rainfall estimates. This error variance can be expressed as a function of variograms, which was originally applied in geostatistics to characterize a spatial variable. The variogram can be evaluated using measurements from a dense rain gauge network. The areal rainfall errors are evaluated in two areas with distinct climate regimes and rainfall patterns: Greater Lyon area in France and Melbourne area in Australia. The variograms of the two areas are derived based on 6-minute rainfall time series data from 2010 to 2013 and are then used to estimate uncertainties of areal rainfall represented by different numbers of point measurements in synthetic catchments of various sizes. The error variance of areal rainfall using one point measurement in the centre of a 1-km2 catchment is 0.22 (mm/h)2 in Lyon. When the point measurement is placed at one corner of the same-size catchment, the error variance becomes 0.82 (mm/h)2 also in Lyon. Results for Melbourne were similar but presented larger uncertainty. Results

  11. A Modeling Study of Surface Rainfall Processes Associated with a Torrential Rainfall Event over Hubei, China, during July 2007

    ZHOU Yushu; CUI Chunguang


    The surface rainfall processes associated with the torrential rainfall event over Hubei,China,during July 2007 were investigated using a two-dimensional cloud-resolving model.The model integrated the large-scale vertical velocity and zonal wind data from National Centers for Environmental Prediction (NCEP)/Global Data Assimilation System (GDAS) for 5 days.The time and model domain mean surface rain rate was used to identify the onset,mature,and decay periods of rainfall.During the onset period,the descending motion data imposed in the lower troposphere led to a large contribution of stratiform rainfall to the model domain mean surface rainfall.The local atmospheric drying and transport of rain from convective regions mainly contributes to the stratiform rainfall.During the mature periods,the ascending motion data integrated into the model was so strong that water vapor convergence was the dominant process for both convective and stratiform rainfall.Both convective and stratiform rainfalls made important contributions to the model domain mean surface rainfall. During the decay period,descending motion data input into the model prevailed,making stratiform rainfall dominant.Stratiform rainfall was mainly caused by the water vapor convergence over raining stratiform regions.

  12. Simulation of radar rainfall errors and their propagation into rainfall-runoff processes

    Aghakouchak, A.; Habib, E.


    Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolution. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in Z-R relationship, vertical profile of reflectivity, spatial and temporal sampling, etc. Characterization of such uncertainties in radar data and their effects on hydrologic simulations (e.g., streamflow estimation) is a challenging issue. This study aims to analyze radar rainfall error characteristics empirically to gain information on prosperities of random error representativeness and its temporal and spatial dependency. To empirically analyze error characteristics, high resolution and accurate rain gauge measurements are required. The Goodwin Creek watershed located in the north part of Mississippi is selected for this study due to availability of a dense rain gauge network. A total of 30 rain gauge measurement stations within Goodwin Creak watershed and the NWS Level II radar reflectivity data obtained from the WSR-88dD Memphis radar station with temporal resolution of 5min and spatial resolution of 1 km2 are used in this study. Radar data and rain gauge measurements comparisons are used to estimate overall bias, and statistical characteristics and spatio-temporal dependency of radar rainfall error fields. This information is then used to simulate realizations of radar error patterns with multiple correlated variables using Monte Calro method and the Cholesky decomposition. The generated error fields are then imposed on radar rainfall fields to obtain statistical realizations of input rainfall fields. Each simulated realization is then fed as input to a distributed physically based hydrological model resulting in an ensemble of predicted runoff hydrographs. The study analyzes the propagation of radar errors on the simulation of different rainfall-runoff processes such as streamflow, soil moisture, infiltration, and over-land flooding.

  13. Quantifying uncertainty in observational rainfall datasets

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen


    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  14. Integration of Volterra model with artificial neural networks for rainfall-runoff simulation in forested catchment of northern Iran

    Kashani, Mahsa H.; Ghorbani, Mohammad Ali; Dinpashoh, Yagob; Shahmorad, Sedaghat


    Rainfall-runoff simulation is an important task in water resources management. In this study, an integrated Volterra model with artificial neural networks (IVANN) was presented to simulate the rainfall-runoff process. The proposed integrated model includes the semi-distributed forms of the Volterra and ANN models which can explore spatial variation in rainfall-runoff process without requiring physical characteristic parameters of the catchments, while taking advantage of the potential of Volterra and ANNs models in nonlinear mapping. The IVANN model was developed using hourly rainfall and runoff data pertaining to thirteen storms to study short-term responses of a forest catchment in northern Iran; and its performance was compared with that of semi-distributed integrated ANN (IANN) model and lumped Volterra model. The Volterra model was applied as a nonlinear model (second-order Volterra (SOV) model) and solved using the ordinary least square (OLS) method. The models performance were evaluated and compared using five performance criteria namely coefficient of efficiency, root mean square error, error of total volume, relative error of peak discharge and error of time for peak to arrive. Results showed that the IVANN model performs well than the other semi-distributed and lumped models to simulate the rainfall-runoff process. Comparing to the integrated models, the lumped SOV model has lower precision to simulate the rainfall-runoff process.

  15. Random cascade driven rainfall disaggregation for urban hydrology: An evaluation of six models and a new generator

    Licznar, Paweł; Łomotowski, Janusz; Rupp, David E.


    Six variations of multiplicative random cascade models for generating fine-resolution (i.e., 5-minute interval) rainfall time series were evaluated for rainfall in Wroclaw, Poland. Of these variations, one included a new beta-normal generator for a microcanonical cascade. This newly proposed model successfully reproduces the statistical behavior of local 5-minute rainfalls, in terms of intermittency as well as variability. In contrast, both the canonical cascade models with either constant or time-scaled parameters and a microcanonical cascade model with a beta generator substantially underestimate 5-minute maximum rainfall intensities. The canonical models also fail to properly reproduce the intermittency of the rainfall process across a range of timescales. New observations are also made concerning the histograms of the breakdown coefficients (BDC). The tendency of the BDC histograms to have values exactly equal to 0.5 is identified and explained by the quality of pluviograph records. Moreover, the hierarchical evolution of BDC histograms from beta-like for long time steps to beta-normal histograms for short time steps is observed for the first time. The potential advantage is shown of synthetic high resolution rainfall time series generated by the revised microcanonical model for use in hydrology, especially hydrodynamic modelling of urban drainage networks.

  16. Spatial Modeling of Rainfall Patterns over the Ebro River Basin Using Multifractality and Non-Parametric Statistical Techniques

    José L. Valencia


    Full Text Available Rainfall, one of the most important climate variables, is commonly studied due to its great heterogeneity, which occasionally causes negative economic, social, and environmental consequences. Modeling the spatial distributions of rainfall patterns over watersheds has become a major challenge for water resources management. Multifractal analysis can be used to reproduce the scale invariance and intermittency of rainfall processes. To identify which factors are the most influential on the variability of multifractal parameters and, consequently, on the spatial distribution of rainfall patterns for different time scales in this study, universal multifractal (UM analysis—C1, α, and γs UM parameters—was combined with non-parametric statistical techniques that allow spatial-temporal comparisons of distributions by gradients. The proposed combined approach was applied to a daily rainfall dataset of 132 time-series from 1931 to 2009, homogeneously spatially-distributed across a 25 km × 25 km grid covering the Ebro River Basin. A homogeneous increase in C1 over the watershed and a decrease in α mainly in the western regions, were detected, suggesting an increase in the frequency of dry periods at different scales and an increase in the occurrence of rainfall process variability over the last decades.

  17. Rainfall thresholds for possible landslide occurrence in Italy

    Peruccacci, Silvia; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Melillo, Massimo; Rossi, Mauro; Guzzetti, Fausto


    The large physiographic variability and the abundance of landslide and rainfall data make Italy an ideal site to investigate variations in the rainfall conditions that can result in rainfall-induced landslides. We used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with - mostly shallow - landslides in Italy between January 1996 and February 2014. For each rainfall event with landslides, we reconstructed the rainfall history that presumably caused the slope failure, and we determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm). Adopting a power law threshold model, we determined cumulated event rainfall-rainfall duration (ED) thresholds, at 5% exceedance probability, and their uncertainty. We defined a new national threshold for Italy, and 26 regional thresholds for environmental subdivisions based on topography, lithology, land-use, land cover, climate, and meteorology, and we used the thresholds to study the variations of the rainfall conditions that can result in landslides in different environments, in Italy. We found that the national and the environmental thresholds cover a small part of the possible DE domain. The finding supports the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining thresholds for small geographical areas. We observed differences between some of the thresholds. With increasing mean annual precipitation (MAP), the thresholds become higher and steeper, indicating that more rainfall is needed to trigger landslides where the MAP is high than where it is low. This suggests that the landscape adjusts to the regional meteorological conditions. We also observed that the thresholds are higher for stronger rocks, and that forested areas require more rainfall than agricultural areas to initiate landslides. Finally, we

  18. Assessing soil surface roughness decay during simulated rainfall by multifractal analysis

    E. Vidal Vázquez


    Full Text Available Understanding and describing the spatial characteristics of soil surface microrelief are required for modelling overland flow and erosion. We employed the multifractal approach to characterize topographical point elevation data sets acquired by high resolution laser scanning for assessing the effect of simulated rainfall on microrelief decay. Three soil surfaces with different initial states or composition and rather smooth were prepared on microplots and subjected to successive events of simulated rainfall. Soil roughness was measured on a 2×2 mm2 grid, initially, i.e. before rain, and after each simulated storm, yielding a total of thirteen data sets for three rainfall sequences. The vertical microrelief component as described by the statistical index random roughness (RR exhibited minor changes under rainfall in two out of three study cases, which was due to the imposed wet initial state constraining aggregate breakdown. The effect of cumulative rainfall on microrelief decay was also assessed by multifractal analysis performed with the box-count algorithm. Generalized dimension, Dq, spectra allowed characterization of the spatial variation of soil surface microrelief measured at the microplot scale. These Dq spectra were also sensitive to temporal changes in soil surface microrelief, so that in all the three study rain sequences, the initial soil surface and the surfaces disturbed by successive storms displayed great differences in their degree of multifractality. Therefore, Multifractal parameters best discriminate between successive soil stages under a given rain sequence. Decline of RR and multifractal parameters showed little or no association.

  19. Assessing Climate change Impacts to Rainfall Intensity-Duration-Frequency Curves over the Florida Panhandle &Peninsula

    Ghosh, D. K.; Wang, D.; Obeysekera, J.; Hagen, S. C.


    The type, amount, intensity and frequency of rainfall are being directly influenced and altered due to potential climate changes. Consideration should be given to a revision of the rainfall intensity-duration-frequency (IDF) curve, developed based on the historical rainfall data, for storm water drainage design and flood control facilities. Proper adaptation by quantifying the potential effects of climate changes is one of the major ways to reduce vulnerability. As a result, updating IDF curves based on the future climate condition is very important for managing the hydraulic structures. In this study, the climate change impact to rainfall IDF curves over the Florida panhandle and peninsula are assessed using the COAPS Regional Downscaling data from the Florida Climate Institute. The COAPS Land-Atmosphere Regional Ensemble Climate Change Experiment for the Southeast United States at 10-km resolution consists of three regional climate models (RCM) by downscaling the general circulation models: the Community Climate System Model (CCSM), the Hadley Centre Coupled Model version 3 (HadCM3), and the Geophysical Fluid Dynamics Laboratory GCM (GFDL). The RCMs have been performed for the historical simulations (1969-1999) and the future projections (2038-2070) under the AR4 A2 emissions scenario. In this study, more than 30-years of hourly precipitation data are gathered from 57 weather stations in Florida. The performance of the RCMs is evaluated by comparing historical simulations with observations. The parameters of generalized extreme value (GEV) distributions including location, scale, and shape parameters are mapped for the period of 1969-1999 and 2038-2070. The spatial distribution map of rainfall intensity under various durations and return periods will be presented. The response on the Florida panhandle will be compared and contrasted with that of the larger peninsula. These maps will provide insight that can lead to a useful engineering tool for designing the

  20. A study of non-linearity in rainfall-runoff response using 120 UK catchments

    Mathias, Simon A.; McIntyre, Neil; Oughton, Rachel H.


    This study presents a catchment characteristic sensitivity analysis concerning the non-linearity of rainfall-runoff response in 120 UK catchments. Two approaches were adopted. The first approach involved, for each catchment, regression of a power-law to flow rate gradient data for recession events only. This approach was referred to as the recession analysis (RA). The second approach involved calibrating a rainfall-runoff model to the full data set (both recession and non-recession events). The rainfall-runoff model was developed by combining a power-law streamflow routing function with a one parameter probability distributed model (PDM) for soil moisture accounting. This approach was referred to as the rainfall-runoff model (RM). Step-wise linear regression was used to derive regionalization equations for the three parameters. An advantage of the RM approach is that it utilizes much more of the observed data. Results from the RM approach suggest that catchments with high base-flow and low annual precipitation tend to exhibit greater non-linearity in rainfall-runoff response. In contrast, the results from the RA approach suggest that non-linearity is linked to low evaporative demand. The difference in results is attributed to the aggregation of storm-flow and base-flow into a single system giving rise to a seemingly more non-linear response when applying the RM approach to catchments that exhibit a strongly dual storm-flow base-flow response. The study also highlights the value and limitations in a regionlization context of aggregating storm-flow and base-flow pathways into a single non-linear routing function.

  1. Investigation of summer monsoon rainfall variability in Pakistan

    Hussain, Mian Sabir; Lee, Seungho


    This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

  2. Accuracy of rainfall measurement for scales of hydrological interest

    S. J. Wood


    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

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

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


    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.

  4. Variations of characteristics of consecutive rainfall days over northern Thailand

    Klongvessa, P.; Lu, M.; Chotpantarat, S.


    The Chao Phraya basin, Thailand, is frequently inundated by flooding during the southwest monsoon period. Most floods coincide with consecutive rainfall days. This study investigated consecutive rainfall days during the southwest monsoon period at 11 stations over northern Thailand, the upstream area of this basin. The Markov chain probability model was used to study the consecutiveness of days with at least 0.1, 10.1, and 35.1 mm of rainfall. The consecutive length of rainfall days from the model showed good agreement with the observed value. A chi-square test of independence was applied to assess the significance of the consecutiveness, and it was found that days with at least 10.1 mm of rainfall tend to be consecutive over the entire area. Moreover, days with at least 35.1 mm of rainfall were found to be consecutive over the joint area where the mountainous region meets the plain area. However, the consecutiveness of days with less than 10.1 mm of rainfall was not obvious. The rainfall amount on days with at least 10.1 mm of rainfall was also calculated and it showed lower values over the mountainous region than over the plain. Hence, this study established the characteristics of consecutive rainfall days over the plain, mountainous region, and joint area.


    Numan Shehadeh


    Full Text Available Climatic models that project the impact of climate change upon rainfall in the Eastern Mediterranean region predict that the negative impact will be more pronounced upon winter rainfall rather than Fall or Spring rainfall where instability conditions become more pronounced. Those models, also, predict that, due to the great geographical diversity, projected rainfall trends in the above region will show great spatial variability. Therefore, this study aims to analyze the possible impact of climate change upon winter rainfall (December, January and February in Jordan. Data from six meteorological stations that represent well the spatial variation of rainfall in the country is used. Various statistical techniques are applied in this study including, linear regression, t- test, moving averages and CUSUM charts. Results of the analysis reveal a decreasing rainfall trend in all the sample stations. However, the decreasing trends are significant at the 0.05 level in three stations only (Salt, Amman and Irbid. The negative impact of climate change upon winter rainfall totals in the northern and central parts of Jordan, where most of winter rainfall is associated with Mediterranean depressions, is statistically significant at the 0.05 level. However, such impact is not significant in the southern and eastern parts of the country, where a greater portion of winter rainfall is associated with khamasini depressions and instability conditions. Further research analyzing the impact of climate change upon other climatic elements such as temperature, relative humidity and dust storms is needed.

  6. Constraining continuous rainfall simulations for derived design flood estimation

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


    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.

  7. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko


    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify

  8. Validating NEXRAD MPE and Stage III precipitation products for uniform rainfall on the Upper Guadalupe River Basin of the Texas Hill Country

    Wang, Xianwei; Xie, Hongjie; Sharif, Hatim; Zeitler, Jon


    SummaryThis study examines the performance of the Next Generation Weather Radar (NEXRAD) Multisensor Precipitation Estimator (MPE) and Stage III precipitation products, using a high-density rain gauge network located on the Upper Guadalupe River Basin of the Texas Hill Country. As point-area representativeness error of gauge rainfall is a major concern in assessment of radar rainfall estimation, this study develops a new method to automatically select uniform rainfall events based on coefficient of variation criterion of 3 by 3 radar cells. Only gauge observations of those uniform rainfall events are used as ground truth to evaluate radar rainfall estimation. This study proposes a new parameter probability of rain detection (POD) instead of the conditional probability of rain detection (CPOD) commonly used in previous studies to assess the capability that a radar or gauge detects rainfall. Results suggest that: (1) gauge observations of uniform rainfall better represent ground truth of a 4 × 4 km 2 radar cell than non-uniform rainfall; (2) the MPE has higher capability of rain detection than either gauge-only or Stage III; (3) the MPE has much higher linear correlation and lower mean relative difference with gauge measurements than the Stage III does; (4) the Stage III tends to overestimate precipitation (20%), but the MPE tends to underestimate (7%).

  9. Universal Inverse Power Law Distribution of Rainfall in the Indian Region

    Selvam, A M


    Space-time fluctuations of meteorological parameters exhibit selfsimilar fractal fluctuations. A general systems theory developed by the author predicts universal inverse power law form incorporating the golden mean for the fractal fluctuations. The monthly total rainfall for the Indian region for the period 1871 to 2011 (141 years) was analysed. The model predicted distribution is in close agreement with observed fractal fluctuations of all size scales. The results of the study are presented.

  10. Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

    F. Yusof; Kane, I. L.; Yusop, Z.


    A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long ...

  11. Short memory or long memory: an empirical survey of daily rainfall data

    F. Yusof; Kane, I. L.


    A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semi parametric contexts proposed by Geweke and Porter-Hudak to analyze nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit lon...

  12. Hic Sunt Leones: Anomalous Scaling In Rainfall

    Ferraris, L.; Gabellani, S.; Provenzale, A.; Rebora, N.

    In recent years the spatio-temporal intermittency of precipitation fields has often been quantified in terms of scaling and/or multifractal behaviour. In this work we anal- yse the spatial scaling properties of precipitation intensity fields measured during the GATE radar experiment, and compare the results with those obtained from surrogate data generated by nonlinearly filtered, linear stochastic processes and from random shuffling of the original data. The results of the study suggest a spurious nature of the spatial multifractal behaviour of the GATE fields and indicate that claims of multifrac- tality and anomalous scaling in rainfall may have to be reconsidered.

  13. Rainfall as proxy for evapotranspiration predictions

    Collischonn, Bruno; Collischonn, Walter


    In this work, we evaluated the relationship between evapotranspiration and precipitation, based on the data recently made available by the Brazilian Meteorological Institute. ETP tend to be lower in rainy periods and vice-versa. This relationship was assessed both in physical and statistical ways, identifying the contribution of each explaining variable of ETP. We derived regression equations between monthly rainfall and ETP, which can be useful in studies where ETP time series are not available, such as reservoir design, irrigation management and flow forecast.

  14. Properties of Extreme Point Rainfall I

    Harremoës, Poul; Mikkelsen, Peter Steen


    Extreme rainfall has been recorded by the larger municipalities in Denmark since 1933. National intensity-duration-frequency curves were produced on this basis for engineering application in the whole of Denmark. In 1979, on the initiative of The Danish Water Pollution Control Committee under...... The Society of Danish Engineers, the old municipal rain gauges for measuring extreme rain were exchanged with a modern system of gauges tabbed electronically from a central computer at The Danish Meteorological Institute. The data have revealed a geographical variability that calls for revision...

  15. Multidecadal oscillations in rainfall and hydrological extremes

    Willems, Patrick


    Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water

  16. Rainfall effects on rare annual plants

    Levine, J.M.; McEachern, A.K.; Cowan, C.


    Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood.We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future.Species showed 9 to 100-fold between-year variation in plant density over the 5–12 years of censusing, including a severe drought and a wet El Niño year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants.Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect.Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life table response

  17. Coping with rainfall variability in northern Tanzania

    Trærup, Sara Lærke Meltofte


    This chapter explores a potential relationship between rainfall data and household self-reported harvest shocks and local (spatial) variability of harvest shocks and coping strategies based on a survey of 2700 rural households in the Kagera region of northern Tanzania. In addition, correlations...... of household reported harvest shocks differs significantly between districts and correspond to the observed variability in local climate patterns. Coping strategies are focused on spreading risks and include reduced consumption, casual employment, new crops, external support and the selling of assets...

  18. Properties of Extreme Poin Rainfall II

    Mikkelsen, Peter Steen; Harremoës, Poul; Rosbjerg, Dan


    As an alternative to the traditional non-parametric method the partial duration series approach with exponentially distributed exceedances is used to model extreme values of depth and maximum 10 min intensity per rainfall event, measured at gauges placed at different locations in Denmark....... A statistically significant regional variation is documented and shown to be of importance to engineering application. The apparent variability is divided into sampling uncertainty and uncertainty caused by true regional variability. Further, a method for assessing the total inherent design uncertainty, taking...

  19. Space-time organization of debris flows-triggering rainfall: effects on the identification of the rainfall threshold relationships

    Borga, Marco; Nikolopoulos, Efthymios; Creutin, Jean Dominique; Marra, Francesco


    Debris flow occurrence is generally forecasted by means of empirical rainfall depth-duration thresholds which are often derived based on rain gauge observations (Guzzetti et al., 2008). Rainfall sampling errors, related to the sparse nature of raingauge data, lead to underestimation of the intensity-duration thresholds (Nikolopoulos et al., 2014, Nikolopoulos et al., 2015). This underestimation may be large when debris flows are triggered by convective rainfall events, characterized by limited spatial extent, turning into less efficient forecasts of debris flow occurrence. This work investigates the spatial and temporal structure of rainfall patterns and its effects on the derived rainfall threshold relationships using high-resolution, carefully corrected radar data for 82 debris flows events occurred in the eastern Italian Alps. We analyze the spatial organization of rainfall depths relative to the rainfall occurred over the debris flows initiation point using the distance from it as the main coordinate observing that, on average, debris flows initiation points are characterized by a maximum in the rainfall depth field. We investigate the relationship between spatial organization and duration of rainfall pointing out that the rainfall underestimation is larger for the shorter durations and increases regularly as the distance between rainfall measurement location and debris flow initiation point increases. We introduce an analytical framework that explains how the combination of the mean rainfall depth spatial pattern and its relationship with rainfall duration causes the bias observed in the raingauge-based thresholds. The consistency of this analytical framework is proved by using a Monte Carlo sampling of radar rainfall fields. References Guzzetti, F., Peruccacci, S., Rossi, M., Stark, C.P., 2008. The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides 5, 3-17, 10.1007/s10346-625 007-0112-1 Nikolopoulos, E.I., S

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

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


    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

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

    Lee, Ju Young, E-mail: [Natural Products Center, KIST(Korea Institute of Science and Technology)-Gangneung Institute, Gangnueng 210-340 (Korea, Republic of); Kim, Hyoungjun, E-mail: [Department of Civil and Environmental Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-744 (Korea, Republic of); Kim, Youngjin, E-mail: [Department of Agricultural Engineering, National Institute of Agricultural Science, Gwonseon-Gu, Suwon 442-701 (Korea, Republic of); Han, Moo Young, E-mail: [Department of Civil and Environmental Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-744 (Korea, Republic of)


    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{sub cr}, TSS, TPHs, TKN, NO{sub 3}, TP, PO{sub 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{sup 3}/event and decreasing EMC after 70-80 m{sup 3}/event. - This study investigate the characterization of the EMC of runoff during rainfall event on highway.

  2. Contrasting tropical cyclone and non-tropical cyclone related rainfall drop size distribution at Darwin, Australia

    Deo, Anil; Walsh, Kevin J. E.


    In this study the rainfall drop size distribution (DSD) during the passage of seven tropical cyclones (TCs) over Darwin is compared and contrasted with that associated with non-tropical cyclone (non-TC) events, using the impact disdrometer data at the Darwin Atmospheric Radiation and Measurement (ARM) site. The disparity of the DSD with respect to rainfall types (between TC and non-TC conditions) and distance from TC centre is also examined. It is shown that TC DSDs are statistically different from the non-TC DSDs, the former encompassing a larger concentration of small to moderate drop sizes. The TC mass-weighted mean diameter (Dm) is lower than the non-TC values at all rain rates and also for the different precipitation types (convective, transition and stratiform). The TC DSD varies with distance from the TC centre, as rainfall near the TC centre (< 60 km) comprises of relatively smaller drops which are strongly evident at small to moderate rain rates (< 30 mm h- 1). Such variations in the DSD have implications for the parameters used in the algorithm that converts radar reflectivity to rainfall rate in TCs, as well as for the analytical expressions used in describing the observed DSD employed in cloud modelling parameterizations.

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

    P. K. Patra


    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.

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

    Patra, P. K.; Behera, S. K.; Herman, J. R.; Maksyutov, S.; Akimoto, H.; Yamagata, Y.


    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.

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

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


    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.

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

    Banasik Kazimierz


    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. Regional simulation of aerosol radiative effects and their influence on rainfall over India using WRFChem model

    Kedia, Sumita; Cherian, Ribu; Islam, Sahidul; Das, Subrata Kumar; Kaginalkar, Akshara


    A regional climate model, WRFChem has been utilized to simulate aerosol and rainfall distribution over India during July 2010 which was a normal monsoon year. Two identical simulations, one includes aerosol feedback via their direct and indirect effects and other one without any aerosol effect, are structured to understand the impact of aerosol net (direct + indirect) effect on rainfall pattern over India. Model results are accompanied by satellite and ground based observations to examine the robustness of the model simulations. It is shown that the model can reproduce the spatial and temporal characteristics of meteorological parameters, rainfall distribution, aerosol optical depth and single scattering albedo reasonably well. Model simulated spatial distribution and magnitude of aerosol optical depth over India are realistic, particularly over northwest India, where mineral dust is a major contributor to the total aerosol loading and over Indo-Gangetic Plain region (IGP) where AOD remains high throughout the year. Net (shortwave + longwave) atmospheric heating rate is the highest (> 0.27 K day - 1) over east IGP due to abundant dust and anthropogenic aerosols while it is the lowest over peninsular India and over the Thar desert (< 0.03 K day - 1) which can be attributed to less aerosol concentration and longwave cooling, respectively. It is shown that, inclusion of aerosol direct and indirect effects have strong influence ( ± 20%) on rainfall magnitude and its distribution over Indian subcontinent during monsoon.

  8. Application of radar data to estimate distributed return periods of extreme rainfall events over Trondheim

    Abdella, Yisak Sultan


    The return period of a given rainfall intensity is an important parameter for the Trondheim municipality since the drainage systems in Trondheim have been and are still being designed on the basis of a selected return period. Since rainfall is a spatially distributed phenomenon, a single event passing over a city can yield different return periods at different locations in the same city. In order to account for this spatial variability, a tool has been developed in this project for determining distributed return periods for rainfall events over Trondheim using the measurements from Rissa radar. The tool includes a method for adjusting radar rainfall using rain gauge measurements and an accumulation technique which accounts for storm movement and temporal variation in intensity. The tool has been tested on two extreme events which occurred on July 29 2007 and August 13 2007. The application on the two events has demonstrated a fully-automated estimation of distributed return periods using readily available data. For the particular rain gauge network in Trondheim, it has also been shown how areas of maximum intensity observed by the radar can be missed by all the gauges. (author)




    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.

  10. Country-wide rainfall maps from cellular communication networks

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko


    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both


    Vahid Nourani


    Full Text Available Increasing importance of watershed management during last decades highlighted the need for sufficient data and accurate estimation of rainfall and runoff within watersheds. Therefore, various conceptual models have been developed with parameters based on observed data. Since further investigations depend on these parameters, it is important to accurately estimate them. This study by utilizing various methods, tries to estimate Nash rainfall-runoff model parameters and then evaluate the reliability of parameter estimation methods; moment, least square error, maximum likelihood, maximum entropy and genetic algorithm. Results based on a case study on the data from Ammameh watershed in Central Iran, indicate that the genetic algorithm method, which has been developed based on artificial intelligence, more accurately estimates Nash’s model parameters.

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

    Emad Habib


    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.

  13. Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides

    Bezak, Nejc; Šraj, Mojca; Mikoš, Matjaž


    Floods, landslides and debris flows are natural events that occur all over the world and are often induced by extreme rainfall conditions. Several extreme events occurred in Slovenia (Europe) in the last 25 years that caused 18 casualties and approximately 500 million Euros of economic loss. The intensity-duration-frequency (IDF) relationship was constructed using the Frank copula function for several rainfall stations using high-resolution rainfall data with an average subsample length of 34 years. The empirical rainfall threshold curves were also evaluated for selected extreme events. Post-event analyses showed that rainfall characteristics triggering flash floods and landslides are different. The sensitivity analysis results indicate that the inter-event time definition (IETD) and subsample definition methodology can have a significant influence on the position of rainfall events in the intensity-duration space, the constructed IDF curves and on the relationship between the empirical rainfall threshold curves and the IDF curves constructed using the copula approach. Furthermore, a combination of several empirical rainfall thresholds with an appropriate high-density rainfall measurement network can be used as part of the early warning system of the initiation of landslides and debris flows. However, different rainfall threshold curves should be used for lowland and mountainous areas in Slovenia.

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

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


    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.

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

    Serinaldi, F.


    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 that the dependence of MC and BLS

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

    F. Serinaldi


    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

  17. Assessing the performance of the independence method in modeling spatial extreme rainfall

    Zheng, Feifei; Thibaud, Emeric; Leonard, Michael; Westra, Seth


    Spatial statistical methods are often employed to improve precision when estimating marginal distributions of extreme rainfall. Methods such as max-stable and copula models parameterize the spatial dependence and provide a continuous spatial representation. Alternatively, the independence method can be used to estimate marginal parameters without the need for parameterizing the spatial dependence, and this method has been under-utilized in hydrologic applications. This paper investigates the effectiveness of the independence method for marginal parameter estimation of spatially dependent extremes. Its performance is compared with three spatial dependence models (max-stable Brown-Resnick, max-stable Schlather, and Gaussian copula) by means of a simulation study. The independence method is statistically robust in estimating parameters and their associated confidence intervals for spatial extremes with various underlying dependence structures. The spatial dependence models perform comparably with the independence method when the spatial dependence structure is correctly specified; otherwise they exhibit considerably worse performance. We conclude that the independence method is more appealing for modeling the marginal distributions of spatial extremes (e.g., regional estimation of trends in rainfall extremes) due to its greater robustness and simplicity. The four statistical methods are illustrated using a spatial data set comprising 69 subdaily rainfall series from the Greater Sydney region, Australia.

  18. Main diurnal cycle pattern of rainfall in East Java

    Rais, Achmad Fahruddin; Yunita, Rezky


    The diurnal cycle pattern of rainfall was indicated as an intense feature in East Java. The research of diurnal cycle generally was only based on satellite estimation which had limitations in accuracy and temporal resolution. The hourly rainfall data of Climate Prediction Center Morphing Technique (CMORPH) and gauge were blended using the best correction method between transformation distribution (DT) and quantile mapping (QM) to increase the accuracy. We used spatiotemporal composite to analyse the concentration patterns of maximum rainfall and principal component analysis (PCA) to identify the spatial and temporal dominant patterns of diurnal rainfall. QM was corrected CMORPH data since it was best method. The eastern region of East Java had a rainfall peak at 14 local time (LT) and the western region had a rainfall peak at 16 LT.

  19. Adequacy of satellite derived rainfall data for stream flow modeling

    Artan, G.; Gadain, Hussein; Smith, Jody L.; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.


    Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

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

    Natalie Melissa McLean


    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.

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

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


    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.

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

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


    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

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

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


    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

  4. Research of optical rainfall sensor based on CCD linear array

    YANG; Bifeng; LIU; Yuyan; LU; Ying; WU; Shangqian


    Rainfall monitoring is one of the most important meteorological observation elements for the disaster weather. The maintenance of current tipping bucket rain gauge and weighing type rain gauge is a critical issue. The optical rainfall sensor based on CCD linear array is mainly studied in this paper. Because of the maintenance-free time and good adaptability,it can be widely used in the automatic rainfall monitoring in severe environment and have a good perspective in using.

  5. Effects of rainfall acidification on plant pathogens

    Shriner, D. S.; Cowling, E. B.


    Wind-blown rain, rain splash, and films of free moisture play important roles in the epidemiology of many plant diseases. The chemical nature of the aqueous microenvironment at the infection court is a potentially significant factor in the successful dissemination, establishment, and survival of plant pathogenic microorganisms. Acidic rainfall has a potential for influencing not only the pathogen, but also the host organism, and the host-pathogen complex. Although host-pathogen interactions add a degree of complexity to the study of abiotic environmental stress of plants, it is our hope, through the use of a combination of general concepts, theoretical postulations, and experimental data, to describe the potential role that rainfall acidity may play in the often subtle balance between populations of plants and populations of plant pathogens. The direct effects of acidic precipitation on vegetation are becoming increasingly better understood. The indirect consequences of both acute and chronic exposure of vegetation to acidic precipitation are very complex, however. Their effect is variable in time, and involves a variety of potential interactions which are only partially understood.

  6. Calibrating max-stable models of rainfall extremes at multiple timescales

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


    Understanding the probabilistic behaviour of extreme rainfall events is critical for estimating the risk of flooding, leading to better design of infrastructure and management of flood events. The majority of engineering design is based on estimates of the probability of extreme rainfall known as the Intensity-Frequency-Duration relationship (IDF). IDF curves are estimated at each rain gauge and are subsequently interpolated for application to ungauged locations. The pointwise nature of IDF estimates leads to difficulties, especially at sub-daily timescales, due to the sparseness of sub-daily extreme rainfall data. As a result there is greater uncertainty and potential for bias when estimating sub-daily extreme rainfall. By using a model that incorporates dependence between spatial extremes as well as across multiple timescales, there is considerable potential to improve estimates of extreme rainfall. The aim of this research is to develop max-stable models of extreme rainfall that have both spatial dependence as well as dependence across timescales. Max-stable processes are a direct extension of the univariate generalized extreme value (GEV) model into the spatial domain. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, Koutsoyiannis et al. (1998) proposed a mathematical framework which expresses the parameters as a function of timescale. This parameterization is important because it allows data to be incorporated from daily rainfall stations to improve estimates at sub-daily timescales. The approach therefore addresses the issue of sparseness for sub-daily stations by exploiting the denser network of daily stations. A case study in the Hawkesbury-Nepean catchment near Sydney is used, having 82 daily gauges (>50 years) and 13 sub-daily gauges (>24 years) over a region of 300 km x 300 km area. The max

  7. Rainfall-runoff simulation and flood forecasting for Huaihe Basin

    Li Zhijia; Wang Lili; Bao Hongjun; Song Yu; Yu Zhongbo


    The main purpose of this study was to forecast the inflow to Hongze Lake using the Xin'anjiang rainfall-runoff model. The upper area of Hongze Lake in the Huaihc Basin was divided into 23 sub-basins, including the surface of Hongze Lake. The influence of reservoirs and gates on flood forecasting was considered in a practical and simple way. With a one-day time step, the linear and non-linear Muskingum method was used for channel flood routing, and the least-square regression model was used for real-time correction in flood forecasting. Representative historical data were collected tor the model calibration. The hydrological model parameters for each sub-basin were calibrated individually, so the parameters of the Xin'anjiang model were different for different sub-basins. This flood forecasting system was used in the real-time simulation of the large flood in 2005 and the results are satisfactory when compared with measured data from the flood.

  8. Impacts of Two-Type ENSO on Rainfall over Taiwan

    Chen-Chih Lin; Yi-Jiun Liou; Shih-Jen Huang


    Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different...

  9. Impacts of Two-Type ENSO on Rainfall over Taiwan

    Chen-Chih Lin; Yi-Jiun Liou; Shih-Jen Huang


    Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different...

  10. Temporal correlation between malaria and rainfall in Sri Lanka

    Galappaththy Gawrie NL


    Full Text Available Abstract Background Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex. Methods The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression. Results For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre-whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one or weak negative (at lags two to six correlations were found in pre-whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography. Conclusion Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.

  11. Changing Rainfall and its Impact on Landslides in Sri Lanka

    Uditha Ratnayake; Srikantha Herath


    During the recent past the rainfall pattern in Sri Lanka has shown a noticeable change. This paper describes the effect of this change on the occurrence of landslides and their impacts to eco systems. This study shows that most of the landslides occurring in Sri Lanka during northeast monsoons,southwest monsoons and second inter-monsoon were located in three distinctively separated areas. Analysis of rainfall time series shows a trend of increased lengths of dry periods along with an increasing trend of rainfall intensity, especially after the late seventies.A strong relation is obtained between the location of landslides and the spatial distribution of areas where rainfall intensity is increased.

  12. A rainfall simulation model for agricultural development in Bangladesh

    M. Sayedur Rahman


    Full Text Available A rainfall simulation model based on a first-order Markov chain has been developed to simulate the annual variation in rainfall amount that is observed in Bangladesh. The model has been tested in the Barind Tract of Bangladesh. Few significant differences were found between the actual and simulated seasonal, annual and average monthly. The distribution of number of success is asymptotic normal distribution. When actual and simulated daily rainfall data were used to drive a crop simulation model, there was no significant difference of rice yield response. The results suggest that the rainfall simulation model perform adequately for many applications.

  13. Pattern-oriented memory interpolation of sparse historical rainfall records

    Matos, J. P.; Cohen Liechti, T.; Portela, M. M.; Schleiss, A. J.


    The pattern-oriented memory (POM) is a novel historical rainfall interpolation method that explicitly takes into account the time dimension in order to interpolate areal rainfall maps. The method is based on the idea that rainfall patterns exist and can be identified over a certain area by means of non-linear regressions. Having been previously benchmarked with a vast array of interpolation methods using proxy satellite data under different time and space availabilities, in the scope of the present contribution POM is applied to rain gauge data in order to produce areal rainfall maps. Tested over the Zambezi River Basin for the period from 1979 to 1997 (accurate satellite rainfall estimates based on spaceborne instruments are not available for dates prior to 1998), the novel pattern-oriented memory historical interpolation method has revealed itself as a better alternative than Kriging or Inverse Distance Weighing in the light of a Monte Carlo cross-validation procedure. Superior in most metrics to the other tested interpolation methods, in terms of the Pearson correlation coefficient and bias the accuracy of POM's historical interpolation results are even comparable with that of recent satellite rainfall products. The new method holds the possibility of calculating detailed and performing daily areal rainfall estimates, even in the case of sparse rain gauging grids. Besides their performance, the similarity to satellite rainfall estimates inherent to POM interpolations can contribute to substantially extend the length of the rainfall series used in hydrological models and water availability studies in remote areas.

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

    Sun, X


    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...

  15. Tropical rainfall regimes and their evolution on hourly to daily timescales

    Elsaesser, Gregory Scott


    Data from multiple satellite and in situ sources are used to investigate the dominant raining cloud populations in the tropics, with the purpose of documenting how diverse the raining cloud populations are at any given time over a scale similar in size to the grid-box (˜100 -- 200 km) of a present-day global climate model (GCM). For all locations in the tropics, three similar rainfall clusters (defined according to their ensemble of clouds) are found. Differences in mean-state rainfall (e.g. East versus West Pacific Ocean) are largely the result of similar rainfall clusters occurring at ocean basin-dependent relative frequencies of occurrence. Area-average rainfall rates are substantially different for each cluster. While each rainfall cluster is observed in all tropical basins, differing relative frequencies of occurrence imply that rainfall lifecycles (i.e. the time duration for transition from light to deep rainfall) vary as a function of basin. Among the processes influencing this transition, both mesoscale cold pools (inferred from QuikSCAT surface wind field retrievals) and convective inhibition (CIN, derived from radiosonde-observations) emerge as important parameters driving the transition from light rainfall to deep convection at the spatial scale of 100 -- 200 km. Associated with significant increases in rainfall are substantial decreases (40%) in convective available potential energy (CAPE). The temporal evolution of rainfall clusters is derived for different lifecycle stages of a composite Madden-Julian Oscillation (MJO) event. It is found that the rainfall cluster consisting of shallow (<3 km) and congestus raining clouds exhibits little temporal variation for all stages of the composite event, while non-raining scenes and deeper clouds are modulated as a function of time for all stages. Instead of a "transition" from shallow to deep convection, the results suggest an "addition" of deep convection at the expense of non-raining scenes. Unique to the

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

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


    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 precipitatio...

  17. Uncertainty Analysis in the Evaluation of Extreme Rainfall Trends and Its Implications on Urban Drainage System Design

    Vincenza Notaro


    Full Text Available Future projections provided by climate models suggest that the occurrence of extreme rainfall events will increase and this is evidence that the climate is changing. Because the design of urban drainage systems is based on the statistical analysis of past events, variations in the intensity and frequency of extreme rainfall represent a critical issue for the estimation of rainfall. For this reason, the design criteria of drainage systems should take into account the trends in the past and the future climate changes projections. To this end, a Bayesian procedure was proposed to update the parameters of depth–duration–frequency (DDF curves to assess the uncertainty related to the estimation of these values, once the evidence of annual maximum rainfall trends was verified. Namely, in the present study, the historical extreme rainfall series with durations of 1, 3, 6, 12 and 24 h for the period of 1950–2008, recorded by the rain gauges located near the Paceco urban area (southern Italy, were analyzed to detect statistically significant trends using the non‐parametric Mann‐Kendall test. Based on the rainfall trends, the parameters of the DDF curves for a five‐year return period were updated to define some climate scenarios. Finally, the implications of the uncertainty related to the DDF parameters estimation on the design of a real urban drainage system was assessed to provide an evaluation of its performance under the assumption of climate change. Results showed that the future increase of annual maximum precipitation in the area of study would affect the analyzed drainage system, which could face more frequent episodes of surcharge.

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

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


    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

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

    R. Giannecchini


    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

  20. Choice of rainfall inputs for event-based rainfall-runoff modeling in a catchment with multiple rainfall stations using data-driven techniques

    Chang, Tak Kwin; Talei, Amin; Alaghmand, Sina; Ooi, Melanie Po-Leen


    Input selection for data-driven rainfall-runoff models is an important task as these models find the relationship between rainfall and runoff by direct mapping of inputs to output. In this study, two different input selection methods were used: cross-correlation analysis (CCA), and a combination of mutual information and cross-correlation analyses (MICCA). Selected inputs were used to develop adaptive network-based fuzzy inference system (ANFIS) in Sungai Kayu Ara basin, Selangor, Malaysia. The study catchment has 10 rainfall stations and one discharge station located at the outlet of the catchment. A total of 24 rainfall-runoff events (10-min interval) from 1996 to 2004 were selected from which 18 events were used for training and the remaining 6 were reserved for validating (testing) the models. The results of ANFIS models then were compared against the ones obtained by conceptual model HEC-HMS. The CCA and MICCA methods selected the rainfall inputs only from 2 (stations 1 and 5) and 3 (stations 1, 3, and 5) rainfall stations, respectively. ANFIS model developed based on MICCA inputs (ANFIS-MICCA) performed slightly better than the one developed based on CCA inputs (ANFIS-CCA). ANFIS-CCA and ANFIS-MICCA were able to perform comparably to HEC-HMS model where rainfall data of all 10 stations had been used; however, in peak estimation, ANFIS-MICCA was the best model. The sensitivity analysis on HEC-HMS was conducted by recalibrating the model by using the same selected rainfall stations for ANFIS. It was concluded that HEC-HMS model performance deteriorates if the number of rainfall stations reduces. In general, ANFIS was found to be a reliable alternative for HEC-HMS in cases whereby not all rainfall stations are functioning. This study showed that the selected stations have received the highest total rain and rainfall intensity (stations 3 and 5). Moreover, the contributing rainfall stations selected by CCA and MICCA were found to be located near the outlet of

  1. Inverse hydrological modelling of spatio-temporal rainfall patterns

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András


    Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment

  2. Countrywide rainfall maps from a commercial cellular telecommunication network

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.


    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data

  3. Observed and projected urban extreme rainfall events in India

    Ali, Haider; Mishra, Vimal; Pai, D. S.


    We examine changes in extreme rainfall indices over 57 major urban areas in India under the observed (1901-2010) and projected future climate (2010-2060). Between 1901 and 2010, only four out of the total 57 urban areas showed a significant (p-value urban areas experienced significant increases in the extreme rainfall indices for the different periods. Moreover, rainfall maxima for 1-10 day durations and at 100 year return period did not change significantly over the majority of urban areas in the post-1955 period. Results do not indicate any significant change (p > 0.05) in the pooled mean and distribution of the extreme rainfall indices for the pre- and post-1983 periods revealing an insignificant role of urbanization on rainfall extremes in the major urban areas in India. We find that at the majority of urban areas changes in the extreme rainfall indices are driven by large scale climate variability. Regional Climate Models (RCMs) that participated in the CORDEX-South Asia program showed a significant bias in the monsoon maximum rainfall and rainfall maxima at 100 year return period for the majority of urban areas. For instance, most of the models fail to simulate rainfall maxima within ±10% bias, which can be considered appropriate for a storm water design at many urban areas. Rainfall maxima at 1-3 day durations and 100 year return period is projected to increase significantly under the projected future climate at the majority of urban areas in India. The number of urban areas with significant increases in rainfall maxima under the projected future climate is far larger than the number of areas that experienced significant changes in the historic climate (1901-2010), which warrants a careful attention for urban storm water infrastructure planning and management.

  4. Rainfall thresholds for shallow landslides occurrence in Calabria, southern Italy

    C. Vennari


    Full Text Available In many areas, rainfall is the primary trigger of landslides. Determining the rainfall conditions responsible for landslide occurrence is important, and may contribute to save lives and properties. In a long-term national project for the definition of rainfall thresholds for possible landslide occurrence in Italy, and for the implementation of a national landslide warning system, we compiled a catalogue of 186 rainfall events that have resulted in 251 shallow landslides in Calabria, southern Italy, from January 1996 to September 2011. Landslides were located geographically using Google Earth®, and were given a mapping and a temporal accuracy. We used the landslide information, and sub-hourly rainfall measurements obtained from two complementary networks of rain gauges, to determine cumulated event vs. rainfall duration (ED thresholds for Calabria. For the purpose, we adopted an existing method used to prepare rainfall thresholds and to estimate their associated uncertainties in central Italy. The regional thresholds for Calabria were found nearly identical to previous ED thresholds for Calabria obtained using a reduced set of landslide information, and slightly higher than the ED thresholds obtained for central Italy. We segmented the regional catalogue of rainfall events with landslides on lithology, soil regions, rainfall zones, and seasonal periods. The number of events in each subdivision was insufficient to determine reliable thresholds, but allowed for preliminary conclusions on the role of the environmental factors on the rainfall conditions responsible for shallow landslides in Calabria. We further segmented the regional catalogue based on administrative subdivisions used for hydro-meteorological monitoring and operational flood forecasting, and we determined separate ED thresholds for the Tyrrhenian and the Ionian coasts of Calabria. We expect the ED rainfall thresholds for Calabria to be used in regional and national landslide warning

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

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


    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 (; 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

  6. Prediction of Rainfall-Induced Landslides in Tegucigalpa, Honduras, Using a Hydro-Geotechnical Model

    Garcia Urquia, Elias; Axelsson, K.


    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.

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

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


    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.

  8. A rainfall simulator based on multifractal generator

    Akrour, Nawal; mallet, Cecile; barthes, Laurent; chazottes, Aymeric


    The Precipitations are due to complex meteorological phenomenon's and unlike other geophysical constituents such as water vapour concentration they present a relaxation behaviour leading to an alternation of dry and wet periods. Thus, precipitations can be described as intermittent process. The spatial and temporal variability of this phenomenon is significant and covers large scales. This high variability can cause extreme events which are difficult to observe properly because of their suddenness and their localized character. For all these reasons, the precipitations are therefore difficult to model. This study aims to adapt a one-dimensional time series model previously developed by the authors [Akrour et al., 2013, 2014] to a two-dimensional rainfall generator. The original time series model can be divided into 3 major steps : rain support generation, intra event rain rates generation using multifractal and finally calibration process. We use the same kind of methodology in the present study. Based on dataset obtained from meteorological radar of Météo France with a spatial resolution of 1 km x 1 km we present the used approach : Firstly, the extraction of rain support (rain/no rain area) allowing the retrieval of the rain support structure function (variogram) and fractal properties. This leads us to use either the rain support modelisation proposed by ScleissXXX [ref] or directly real rain support extracted from radar rain maps. Then, the generation (over rain areas) of rain rates is made thanks to a 2D multifractal Fractionnally Integrated Flux (FIF) model [ref]. This second stage is followed by a calibration/forcing step (forcing average rain rate per events) added in order to provide rain rate coherent with observed rain-rate distribution. The forcing process is based on a relation identified from the average rain rate of observed events and their surfaces. The presentation will first explain the different steps presented above, then some results

  9. Improvements of Satellite Derived Cyclonic Rainfall Over The North Atlantic and Implications Upon The Air-sea Interaction

    Klepp, C.; Bakan, S.; Grassl, H.

    out why the con vective cluster rainfall is systematically absent in the NWP models. These mesoscale storm clusters contribute up to 25% to the total amount of rainfall in North Atlantic cyclones. Systematically neglecting these rainfall equiva lents of 1 Sv of freshwater flux into the North Atlantic account for large errors in the water cycle. Further analysis of VOS and HOAPS (Hamburg Ocean and Atmosphere Parameters and Fluxes from Satellite 1 Data) data points out the climatological importance of the cyclones for the water- and energy cycle over the North Atlantic. 2

  10. Measuring rainfall with low-cost cameras

    Allamano, Paola; Cavagnero, Paolo; Croci, Alberto; Laio, Francesco


    In Allamano et al. (2015), we propose to retrieve quantitative measures of rainfall intensity by relying on the acquisition and analysis of images captured from professional cameras (SmartRAIN technique in the following). SmartRAIN is based on the fundamentals of camera optics and exploits the intensity changes due to drop passages in a picture. The main steps of the method include: i) drop detection, ii) blur effect removal, iii) estimation of drop velocities, iv) drop positioning in the control volume, and v) rain rate estimation. The method has been applied to real rain events with errors of the order of ±20%. This work aims to bridge the gap between the need of acquiring images via professional cameras and the possibility of exporting the technique to low-cost webcams. We apply the image processing algorithm to frames registered with low-cost cameras both in the lab (i.e., controlled rain intensity) and field conditions. The resulting images are characterized by lower resolutions and significant distortions with respect to professional camera pictures, and are acquired with fixed aperture and a rolling shutter. All these hardware limitations indeed exert relevant effects on the readability of the resulting images, and may affect the quality of the rainfall estimate. We demonstrate that a proper knowledge of the image acquisition hardware allows one to fully explain the artefacts and distortions due to the hardware. We demonstrate that, by correcting these effects before applying the image processing algorithm, quantitative rain intensity measures are obtainable with a good accuracy also with low-cost modules.

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

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


    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.

  12. Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

    Elena Tarnavsky


    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.

  13. Urban Run-off Volumes Dependency on Rainfall Measurement Method

    Pedersen, L.; Jensen, N. E.; Rasmussen, Michael R.;


    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 area...... resolutions and single gauge rainfall was fed to a MOUSE run-off model. The flow and total volume over the event is evaluated.......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...... suggests that rainfall needs to be measured with a much higher spatial resolution (Jensen and Pedersen, 2004). This paper evaluates the impact of using high-resolution rainfall information from weather radar compared to the conventional single gauge approach. The radar rainfall in three different...

  14. Association between Australian rainfall and the Southern Annular Mode

    Meneghini, Belinda; Simmonds, Ian; Smith, Ian N.


    In this study, we explore the relationships between seasonal Australian rainfall and the Southern Annular Mode (SAM). We produce two seasonal indices of the SAM: the Antarctic Oscillation Index (AOI), and an Australian regional version (AOIR) using ERA-40 mean sea-level pressure (MSLP) reanalysis data. The seasonal rainfall data are based on gridded monthly rainfall provided by the Australian Bureau of Meteorology.For the period 1958-2002 a significant inverse relationship is found between the SAM and rainfall in southern Australia, while a significant in-phase relationship is found between the SAM and rainfall in northern Australia. Furthermore, widespread significant inverse relationships in southern Australia are only observed in winter, and only with the AOIR. The AOIR accounts for more of the winter rainfall variability in southwest Western Australia, southern South Australia, western and southern Victoria, and western Tasmania than the Southern Oscillation Index. Overall, our results suggest that changes in the SAM may be partly responsible for the current decline in winter rainfall in southern South Australia, Victoria, and Tasmania, but not the long-term decline in southwest Western Australian winter rainfall.

  15. Impacts of Two-Type ENSO on Rainfall over Taiwan

    Chen-Chih Lin


    Full Text Available Impacts of two-type ENSO (El Niño/Southern Oscillation, canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI. The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different depending on the effects of two-type ENSO. In canonical El Niño episode, the rainfall increases in winter and spring while it reduces in summer and autumn. On the contrary, the rainfall increases in summer and autumn but reduces in winter and spring in El Niño Modoki episode. Nevertheless, two types of La Niña cause similar effects on the rainfall over Taiwan. It increases in autumn only. The rainfall variations in different types of ENSO are mainly caused by the monsoon and topography.

  16. Users guide for distributed routing rainfall-runoff model

    Dawdy, D.R.; Schaake, John C.; Alley, William M.


    A computer program of a watershed model for routing urban flood discharges through a branched system of pipes or natural channels using rainfall as input has been developed and documented. The model combines soil-moisture-accounting and rainfall-excess components developed by Dawdy and others (1972) with the kinematic-wave routing method presented by Leclerc and Schaake (1973). (Woodard-USGS)

  17. East coast lows, atmospheric blocking and rainfall: A Tasmanian perspective

    Pook, Michael; Risbey, James; McIntosh, Peter, E-mail: Mike.Pook@csiro.a [Centre for Australian Weather and Climate Research (A partnership between CSIRO and Bureau of Meteorology), Castray Esplanade, Hobart, Tasmania 7000 (Australia)


    Although the term 'east coast low' is normally associated with intense cyclones near the east coast of mainland Australia, cutoff lows of similar type also affect Tasmania. This paper demonstrates that the cutoff low is a major source of rainfall for the agricultural districts and water catchments of eastern Tasmania. In particular, an analysis of synoptic systems and daily rainfall reveals that cutoff lows are responsible for almost 50% of April to October rainfall in parts of the northeast and a slightly lower proportion in the southeast. The other large contribution to rainfall is from frontal systems but the relative effects of the various synoptic types vary widely across the state as a result of the complex topography. Cutoff lows commonly form the cyclonic portion of a blocking dipole which can have opposing influences on Tasmanian rainfall. The high latitude anticyclone suppresses rainfall in western and southwestern Tasmania, while the cutting off of a relatively small cyclonic component equatorwards of the high frequently results in enhanced rainfall over eastern Tasmania. Results from two climate models indicate that the accurate simulation of blocking and cutoff lows remains difficult to achieve and this has implications for projections of Tasmanian rainfall on seasonal and longer time scales.

  18. Simulating diverse native C4 perennial grasses with varying rainfall

    Rainfall is recognized as a major factor affecting the rate of plant growth development. The impact of changes in amount and variability of rainfall on growth and production of different forage grasses needs to be quantified to determine how climate change can impact rangelands. Growth and product...

  19. Curve number estimation from Brazilian Cerrado rainfall and runoff data

    The Curve Number (CN) method has been widely used to estimate runoff from rainfall events in Brazil, however, CN values for use in the Brazilian savanna (Cerrado) are poorly documented. In this study we used experimental plots to measure natural rainfall-driven rates of runoff under undisturbed Cerr...

  20. Uncertainty evaluation of design rainfall for urban flood risk analysis.

    Fontanazza, C M; Freni, G; La Loggia, G; Notaro, V


    A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity-duration-frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.

  1. Rainfall measurement using radio links from cellular communication networks

    Leijnse, H.; Uijlenhoet, R.; Stricker, J.N.M.


    We investigate the potential of radio links such as employed by commercial cellular communication companies to monitor path-averaged rainfall. We present an analysis of data collected using two 38-GHz links during eight rainfall events over a 2-month period (October¿November 2003) during mostly stra

  2. Madagascar corals reveal Pacific multidecadal modulation of rainfall since 1708

    C. A. Grove


    Full Text Available The Pacific Ocean modulates Australian and North American rainfall variability on multidecadal timescales, in concert with the Pacific Decadal Oscillation (PDO. It has been suggested that Pacific decadal variability may also influence Indian Ocean surface temperature and rainfall in a far-field response, similar to the El Niño Southern Oscillation (ENSO on interannual timescales. However, instrumental records of rainfall are too short and too sparse to confidently assess such multidecadal climatic teleconnections. Here, we present four climate archives spanning the past 300 yr from giant Madagascar corals. We decouple 20th century human deforestation effects from rainfall induced soil erosion using spectral luminescence scanning and geochemistry. The corals provide the first evidence for Pacific decadal modulation of rainfall over the Western Indian Ocean. We find that positive PDO phases are associated with increased Indian Ocean temperatures and rainfall in Eastern Madagascar, while precipitation in Southern Africa and Eastern Australia declines. Consequently, the negative PDO phase that started in 1998 should lead to reduced rainfall over Eastern Madagascar and increased precipitation in Southern Africa and Eastern Australia. We conclude that the PDO has important implications for future multidecadal variability of African rainfall, where water resource management is increasingly important under the warming climate.

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

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


    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

  4. Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria

    Fethi Ouallouche


    Full Text Available Rain areas delineation proposed in this paper is based on the image fusion from geostationary Meteosat Second Generation (MSG satellite, with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM satellite. The fusion technique described in this work used an artificial neural network (ANN. It's has been developed to detect instantaneous rainfall by using information from the IR images of MSG satellite and from TRMM Microwave Imager (TMI. The study is carried out over north of Algeria. Seven spectral parameters are used as input data of ANN to identify raining or non - raining pixels. Corresponding data of raining /non-raining pixels are taken from a PR (precipitation radar issued from TRMM. Results from the developed scheme are compared with the results of SI method (Scattering Index taken as reference method. The results show that the developed model performs very well and overcomes the deficiencies of use a single satellite.

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

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


    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, NO₃, TP, PO₄ 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.

  6. Assessing spatio-temporal variability of rainfall using a simple physically based statistical model

    Hutchinson, M. F.; Xu, T.; Kesteven, J.


    Reliable assessment of spatio-temporal variability of observed rainfall is difficult in the current climate because of the complex spatial variability displayed by daily and shorter time scale rainfall data. As demonstrated in a recent analysis of Canadian daily precipitation data by Hutchinson et al. (2009), direct interpolation of short time scale precipitation data is a poor way to address spatial patterns of rainfall extremes. Addressing the behaviour of projected future precipitation extremes is made even more difficult by the limited temporal and spatial resolution of precipitation as simulated by global climate models. The “uniform drizzle” that tends to be produced by these models makes the assessment of even straightforward statistics, such as daily rainfall occurrence, problematic. Putting aside significant inter-model variability, the more reliable outputs of global models include mean fluxes, such as monthly rainfall amounts, and associated insight into the nature of the modelled precipitation in relation to forcing synoptic systems. The truncated power of normal distribution, as described by Hutchinson (1995), offers a relatively simple way to make progress. Two of the three model parameters are simply calibrated in terms of monthly mean fluxes and the model is able to accurately describe precipitation extremes. These model parameters can also be robustly determined from serially incomplete data. It can be argued that the model has a broad physical process basis by modelling rainfall as an event that occurs as an appropriate threshold is exceeded. This analysis extends the approach of Stidd (1954, 1973) who suggested the cube root as a universal normalising power. We show that the power parameter, once robustly calibrated, displays a broadly spatially varying distribution of around 0.5. This corresponds well with the two dimensional synoptic convergence that is required to produce precipitation. The power parameter appears to be related to the

  7. Positive response of Indian summer rainfall to Middle East dust

    Jin, Qinjian


    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.

  8. Tree ring reconstructed rainfall over the southern Amazon Basin

    Lopez, Lidio; Stahle, David; Villalba, Ricardo; Torbenson, Max; Feng, Song; Cook, Edward


    Moisture sensitive tree ring chronologies of Centrolobium microchaete have been developed from seasonally dry forests in the southern Amazon Basin and used to reconstruct wet season rainfall totals from 1799 to 2012, adding over 150 years of rainfall estimates to the short instrumental record for the region. The reconstruction is correlated with the same atmospheric variables that influence the instrumental measurements of wet season rainfall. Anticyclonic circulation over midlatitude South America promotes equatorward surges of cold and relatively dry extratropical air that converge with warm moist air to form deep convection and heavy rainfall over this sector of the southern Amazon Basin. Interesting droughts and pluvials are reconstructed during the preinstrumental nineteenth and early twentieth centuries, but the tree ring reconstruction suggests that the strong multidecadal variability in instrumental and reconstructed wet season rainfall after 1950 may have been unmatched since 1799.

  9. The Interdependence between Rainfall and Temperature: Copula Analyses

    Cong, Ronggang; Brady, Mark


    Rainfall and temperature are important climatic inputs for agricultural production, especially in the context of climate change. However, accurate analysis and simulation of the joint distribution of rainfall and temperature are difficult due to possible interdependence between them. As one...... 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...... 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...

  10. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp. plant

    Y.-M. Cabidoche


    Full Text Available Rainfall partitioning by vegetation modifies the intensity of rainwater reaching the ground, which affects runoff generation. Incident rainfall is intercepted by the plant canopy and then redistributed into throughfall and stemflow. Rainfall intensities at the soil surface are therefore not spatially uniform, generating local variations of runoff production that are disregarded in runoff models. The aim of this paper was to model runoff at the plot scale, accounting for rainfall partitioning by vegetation in the case of plants concentrating rainwater at the plant foot and promoting stemflow. We developed a lumped modelling approach, including a stemflow function that divided the plot into two compartments: one compartment including stemflow and the relative water pathways and one compartment for the rest of the plot. This stemflow function was coupled with a production function and a transfer function to simulate a flood hydrograph using the MHYDAS model. Calibrated parameters were a "stemflow coefficient", which compartmented the plot; the saturated hydraulic conductivity (Ks, which controls infiltration and runoff; and the two parameters of the diffusive wave equation. We tested our model on a banana plot of 3000 m2 on permeable Andosol (mean Ks=75 mm h−1 under tropical rainfalls, in Guadeloupe (FWI. Runoff simulations without and with the stemflow function were performed and compared to 18 flood events from 10 to 130 mm rainfall depth. Modelling results showed that the stemflow function improved the calibration of hydrographs according to the error criteria on volume and on peakflow and to the Nash and Sutcliffe coefficient. This was particularly the case for low flows observed during residual rainfall, for which the stemflow function allowed runoff to be simulated for rainfall intensities lower than the Ks measured at the soil surface. This approach also allowed us to take into account the experimental data, without needing to calibrate

  11. Applicability of open rainfall data to event-scale urban rainfall-runoff modelling

    Niemi, Tero J.; Warsta, Lassi; Taka, Maija; Hickman, Brandon; Pulkkinen, Seppo; Krebs, Gerald; Moisseev, Dmitri N.; Koivusalo, Harri; Kokkonen, Teemu


    Rainfall-runoff simulations in urban environments require meteorological input data with high temporal and spatial resolutions. The availability of precipitation data is constantly increasing due to the shift towards more open data sharing. However, the applicability of such data for urban runoff assessments is often unknown. Here, the feasibility of Finnish Meteorological Institute's open rain gauge and open weather radar data as input sources was studied by conducting Storm Water Management Model simulations at a very small (33.5 ha) urban catchment in Helsinki, Finland. In addition to the open data sources, data were also available from two research gauges, one of them located on-site, and from a research radar. The results confirmed the importance of local precipitation measurements for urban rainfall-runoff simulations, implying the suitability of open gauge data to be largely dictated by the gauge's distance from the catchment. Performance of open radar data with 5 min and 1 km2 resolution was acceptable in terms of runoff reproduction, albeit peak flows were constantly and flow volumes often underestimated. Gauge adjustment and advection interpolation were found to improve the quality of the radar data, and at least gauge adjustment should be performed when open radar data are used. Finally, utilizing dual-polarization capabilities of radars has a potential to improve rainfall estimates for high intensity storms although more research is still needed.

  12. The contribution of tropical cyclones to rainfall in Mexico

    Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

    Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

  13. Evaluating rainfall kinetic energy - intensity relationships with observed disdrometric data

    Angulo-Martinez, Marta; Begueria, Santiago; Latorre, Borja


    Rainfall kinetic energy is required for determining erosivity, the ability of rainfall to detach soil particles and initiate erosion. Its determination relay on the use of disdrometers, i.e. devices capable of measuring the drop size distribution and velocity of falling raindrops. In the absence of such devices, rainfall kinetic energy is usually estimated with empirical expressions relating rainfall energy and intensity. We evaluated the performance of 14 rainfall energy equations in estimating one-minute rainfall energy and event total energy, in comparison with observed data from 821 rainfall episodes (more than 100 thousand one-minute observations) by means of an optical disdrometer. In addition, two sources of bias when using such relationships were evaluated: i) the influence of using theoretical terminal raindrop fall velocities instead of measured values; and ii) the influence of time aggregation (rainfall intensity data every 5-, 10-, 15-, 30-, and 60-minutes). Empirical relationships did a relatively good job when complete events were considered (R2 > 0.82), but offered poorer results for within-event (one-minute resolution) variation. Also, systematic biases where large for many equations. When raindrop size distribution was known, estimating the terminal fall velocities by empirical laws produced good results even at fine time resolution. The influence of time aggregation was very high in the estimated kinetic energy, although linear scaling may allow empirical correction. This results stress the importance of considering all these effects when rainfall energy needs to be estimated from more standard precipitation records. , and recommends the use of disdrometer data to locally determine rainfall kinetic energy.

  14. Rainfall estimation using moving cars as rain gauges - laboratory experiments

    Rabiei, E.; Haberlandt, U.; Sester, M.; Fitzner, D.


    The spatial assessment of short time-step precipitation is a challenging task. Low density of observation networks, as well as the bias in radar rainfall estimation motivated the new idea of exploiting cars as moving rain gauges with windshield wipers or optical sensors as measurement devices. In a preliminary study, this idea has been tested with computer experiments (Haberlandt and Sester, 2010). The results have shown that a high number of possibly inaccurate measurement devices (moving cars) provide more reliable areal rainfall estimations than a lower number of precise measurement devices (stationary gauges). Instead of assuming a relationship between wiper frequency (W) and rainfall intensity (R) with an arbitrary error, the main objective of this study is to derive valid W-R relationships between sensor readings and rainfall intensity by laboratory experiments. Sensor readings involve the wiper speed, as well as optical sensors which can be placed on cars and are usually made for automating wiper activities. A rain simulator with the capability of producing a wide range of rainfall intensities is designed and constructed. The wiper speed and two optical sensors are used in the laboratory to measure rainfall intensities, and compare it with tipping bucket readings as reference. Furthermore, the effect of the car speed on the estimation of rainfall using a car speed simulator device is investigated. The results show that the sensor readings, which are observed from manual wiper speed adjustment according to the front visibility, can be considered as a strong indicator for rainfall intensity, while the automatic wiper adjustment show weaker performance. Also the sensor readings from optical sensors showed promising results toward measuring rainfall rate. It is observed that the car speed has a significant effect on the rainfall measurement. This effect is highly dependent on the rain type as well as the windshield angle.

  15. Physically based modelling of sediment generation and transport under a large rainfall simulator

    Adams, Russell; Elliott, Sandy


    A series of large rainfall simulator experiments was conducted in 2002 and 2003 on a small plot located in an experimental catchment in the North Island of New Zealand. These experiments measured both runoff and sediment transport under carefully controlled conditions. A physically based hydrological modelling system (SHETRAN) was then applied to reproduce the observed hydrographs and sedigraphs. SHETRAN uses physically based equations to represent flow and sediment transport, and two erodibility coefficients to model detachment of soil particles by raindrop erosion and overland flow erosion. The rate of raindrop erosion also depended on the amount of bare ground under the simulator; this was estimated before each experiment. These erodibility coefficients were calibrated systematically for summer and winter experiments separately, and lower values were obtained for the summer experiments. Earlier studies using small rainfall simulators in the vicinity of the plot also found the soil to be less erodible in summer and autumn. Limited validation of model parameters was carried out using results from a series of autumn experiments. The modelled suspended sediment load was also sensitive to parameters controlling the generation of runoff from the rainfall simulator plot; therefore, we found that accurate runoff predictions were important for the sediment predictions, especially from the experiments where the pasture cover was good and overland flow erosion was the dominant mechanism. The rainfall simulator experiments showed that the mass of suspended sediment increased post-grazing, and according to the model this was due to raindrop detachment. The results indicated that grazing cattle or sheep on steeply sloping hill-country paddocks should be carefully managed, especially in winter, to limit the transport of suspended sediment into watercourses.

  16. Prediction of Experimental Rainfall-Eroded Soil Area Based on S-Shaped Growth Curve Model Framework

    Wen Nie


    Full Text Available Rainfall-induced soil erosion of a mountain area plays a significant role in supplying sediment and shaping the landscape. The related area of soil erosion, as an index of the changed landscape, is easier to calculate visually using some popular imaging tools. By image analysis, our work shows that the changing of the soil erosion area admits the structure of an S-growth curve. Therefore, we propose to establish an S-curve model, based on incremental learning, to predict the soil erosion area. In the process of incremental learning, we dynamically update the accumulative rainfall and rainfall intensity to train the parameters of our S-curve model. In order to verify our prediction model, the index of area is utilized to express the output of eroded soil in a series of experiments. The results show that the proposed S-growth curve model can be used to estimate the growth of the soil erosion area (average relative error 3%–9.7% according to variable soil material and rainfall intensity. The original S-growth curve model can calculate the erosion areas of just one soil material and one rainfall condition whose average relative error is 7.5%–12.2%; compared to the simple time series analysis-moving average method (average relative error 5.7%–12.1%, our proposed S-growth curve model can reveal the physical mechanism and evolution of the research object.

  17. Rainfall and runoff regime in the Golema reka watershed on the territory of the hunting ground Valnište

    Kostadinov Stanimir


    Full Text Available Fenced hunting ground "Valnište" covers 410 ha on the slopes of the mountain Čemernik, in the Municipality Crna Trava. The hunting ground is situated in the Golema Reka watershed. Rainfall and runoff regime in the Golema Reka watershed were researched in order to create a hydrological base with the data on rainfall, available water resources and maximal discharges. Average annual rainfall design value for the watershed is 860. 14 mm. The highest monthly rainfall occurs in June and May, and the lowest in September and October. As there are no measured data, runoff regime was determined based on the method of parameter hydrology. The following calculation results are adopted for the maximal discharge: Q1000=19,0 m3·s-1 i Q100=10,90 m3·s-1. The adopted value of mean annual specific discharge (runoff module is MQ=16,0 l·s-1·km-2.The study results of rainfall and runoff regime in the Golema Reka watershed show that hydrological conditions are favorable for the development of hunting and hunting tourism.

  18. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

    Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki


    Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs.

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

    Engelbrecht, CJ


    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 hPa...

  20. Parameter Estimation


    of optimisation techniques coupled with dynamic solution of the underlying model. Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set......In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....

  1. Are extreme rainfall intensities more frequent? Analysis of trends in rainfall patterns relevant to urban drainage systems.

    De Toffol, S; Laghari, A N; Rauch, W


    The fact that climate change is affecting the intensity and frequency of rainfall is well accepted in the scientific community. This is backed by a multitude of reports on the basis of daily rainfall series analysis; however, little research is available for short duration intensities. Due to its significant influence on the behaviour of urban drainage, it is critical to investigate the changes in short duration rainfall intensities. In this study different intensities relevant for the urban drainage and the total rainfall per rain event are analysed. The trend is investigated using the Mann-Kendall test. The rainfall series analysed are from the alpine region Tyrol. The results present differences depending on the duration of the intensity and the series considered, however an increase in the number of extreme events is detectable for short durations for the most series.

  2. Can SAPHIR Instrument Onboard MEGHATROPIQUES Retrieve Hydrometeors and Rainfall Characteristics ?

    Goyal, J. M.; Srinivasan, J.; Satheesh, S. K.


    MEGHATROPIQUES (MT) is an Indo-French satellite launched in 2011 with the main intention of understanding the water cycle in the tropical region and is a part of GPM constellation. MADRAS was the primary instrument on-board MT to estimate rainfall characteristics, but unfortunately it's scanning mechanism failed obscuring the primary goal of the mission.So an attempt has been made to retrieve rainfall and different hydrometeors using other instrument SAPHIR onboard MT. The most important advantage of using MT is its orbitography which is specifically designed for tropical regions and can reach up to 6 passes per day more than any other satellite currently in orbit. Although SAPHIR is an humidity sounder with six channels centred around 183 GHz channel, it still operates in the microwave region which directly interacts with rainfall, especially wing channels and thus can pick up rainfall signatures. Initial analysis using radiative transfer models also establish this fact .To get more conclusive results using observations, SAPHIR level 1 brightness temperature (BT) data was compared with different rainfall products utilizing the benefits of each product. SAPHIR BT comparison with TRMM 3B42 for one pass clearly showed that channel 5 and 6 have a considerable sensitivity towards rainfall. Following this a huge database of more than 300000 raining pixels of spatially and temporally collocated 3B42 rainfall and corresponding SAPHIR BT for an entire month was created to include all kinds of rainfall events, to attain higher temporal resolution collocated database was also created for SAPHIR BT and rainfall from infrared sensor on geostationary satellite Kalpana 1.These databases were used to understand response of various channels of SAPHIR to different rainfall regimes . TRMM 2A12 rainfall product was also used to identify capabilities of SAPHIR to retrieve cloud and ice water path which also gave significant correlation. Conclusively,we have shown that SAPHIR has

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

    M. T. Brunetti


    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

  4. Rainfall deficit and excess rainfall during vegetation of early potatoes varieties in central-eastern Poland (1971-2005

    Elżbieta Radzka


    Full Text Available The study was based on data collected from nine stations of the Institute of Meteoro­logy and Water Management in central-eastern Poland (1971-2005 concerning monthly precipitation total and mean monthly air temperature during the vegetation period of early potatoes (April-July. Optimal precipitation for early potato was calculated according to the Klatt indexes for medium cohesive and light soils in the successive months of the vegetation period. Rainfall deficit and excess rainfall were determined based on differences between monthly precipitation totals recorded in the years of the study and values considered to be optimal. It was found that the frequency of rainfall deficit during vegetation of early potato in each analysed location both for medium cohesive soil and for light soil exceeded the frequency of its excess. The greatest mean monthly rainfall deficit from the multiannual period in the vegetation season of early potato in all the analysed locations and for both soil types was recorded in June, while excess rainfall was observed in July. Lower values of standard deviation for rainfall deficit were calculated in the case of light soil than medium cohesive soil, while an opposite dependence was recorded for excess rainfall. The risk for early potato plantations on light soil was connected with frequent extreme deficits. They were observed most often in the south-eastern part of the study area, while they were rarest in the belt from Pułtusk towards Szepietowo. Values of the slope of the trend lines were low for all the weather stations and most of them were statistically non-significant. However, all values concerning rainfall deficit were negative, which indicates its slight increase from year to year. A significant trend for changes in rainfall deficit was observed only in Włodawa and Siedlce, while for excess rainfall it was found in Szepietowo and Białowieża.

  5. Relationships between atmospheric circulation indices and rainfall in Northern Algeria and comparison of observed and RCM-generated rainfall

    Taibi, S.; Meddi, M.; Mahé, G.; Assani, A.


    This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1-5, 5-10, 10-20, 20-50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10-20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.

  6. Characteristics of rainfall triggering of debris flows in the Chenyulan watershed, Taiwan

    Chen, J. C.; C. D. Jan; Huang, W. S.


    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 analy...

  7. 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

    Weiping Liu


    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.

  8. A rainfall-based warning model for shallow landslides

    Zeng, Yi-Chao; Wang, Ji-Shang; Jan, Chyan-Deng; Yin, Hsiao-Yuan; Lo, Wen-Chun


    According to the statistical data of past rainfall events, the climate has changed in recent decades. Rainfall patterns have presented a more concentrated, high-intensity and long-duration trend in Taiwan. The most representative event is Typhoon Morakot which induced a total of 67 enormous landslides by the extreme amount of rain during August 7 to 10 in 2009 and resulted in the heaviest casualties in southern Taiwan. In addition, the nature of vulnerability such as steep mountains and rushing rivers, fragile geology and loose surface soil results in more severe sediment-relative disasters, in which shallow landslides are widespread hazards in mountainous regions. This research aims to develop and evaluate a model for predicting shallow landslides triggered by rainfall in mountainous area. Considering the feasibility of large-scale application and practical operation, the statistical techniques is adopted to form the landslide model based on abundant historical rainfall data and landslide events. The 16 landslide inventory maps and 15 variation results by comparing satellite images taken before and after the rainfall event were interpreted and delineated since 2004 to 2011. Logit model is utilized for interpreting the relationship between rainfall characteristics and landslide events delineated from satellite. Based on the analysis results of logistic regression, the rainfall factors that are highly related to shallow landslide occurrence are selected which are 3 hours rainfall intensity I3 (mm/hr) and the effective cumulative precipitation Rt (mm) including accumulated rainfall at time t and antecedent rainfall. A landslide rainfall triggering index (LRTI) proposed for assessing the occurrence potential of shallow landslides is defined as the product of I3 and Rt. A form of probability of shallow landslide triggered threshold is proposed to offer a measure of the likelihood of landslide occurrence. Two major critical lines which represent the lower and upper

  9. Influence of Northwest Cloudbands on Southwest Australian Rainfall

    Nicola Telcik


    Full Text Available Northwest cloudbands are tropical-extratropical feature that crosses the Australian continent originating from Australia’s northwest coast and develops in a NW-SE orientation. In paper, atmospheric and oceanic reanalysis data (NCEP and Reynolds reconstructed sea surface temperature data were used to examine northwest cloudband activity across the Australian mainland. An index that reflected the monthly, seasonal, and interannual activity of northwest cloudbands between 1950 and 1999 was then created. Outgoing longwave radiation, total cloud cover, and latent heat flux data were used to determine the number of days when a mature northwest cloudband covered part of the Australian continent between April and October. Regional indices were created for site-specific investigations, especially of cloudband-related rainfall. High and low cloudband activity can affect the distribution of cloudbands and their related rainfall. In low cloudband activity seasons, cloudbands were mostly limited to the south and west Australian coasts. In high cloudband activity seasons, cloudbands penetrated farther inland, which increased the inland rainfall. A case study of the southwest Australian region demonstrated that, in a below average rainfall year, cloudband-related rainfall was limited to the coast. In an above average rainfall year, cloudband-related rainfall occurred further inland.

  10. Interannual variability of rainfall characteristics over southwestern Madagascar

    Randriamahefasoa, T. S. M.; Reason, C. J. C.


    The interannual variability of daily frequency of rainfall [>1 mm/day] and heavy rainfall [>30 mm/day] is studied for the southwestern region of Madagascar, which is relatively arid compared to the rest of the island. Attention is focused on the summer rainy season from December to March at four stations (Morondava, Ranohira, Toliara and Taolagnaro), whose daily rainfall data covering the period 1970-2000 were obtained from the Madagascar Meteorological Service. El Niño Southern Oscillation (ENSO) was found to have a relatively strong correlation with wet day frequency at each station and, particularly, for Toliara in the extreme southwest. In terms of seasonal rainfall totals, most El Niño (La Niña) summers receive below (above) average amounts. An ENSO connection with heavy rainfall events was less clear. However, for heavy rainfall events, the associated atmospheric circulation displays a Southern Annular Mode-like pattern throughout the hemisphere. For ENSO years and the neutral seasons 1979/80, 1981/82 which had large anomalies in wet day frequency, regional atmospheric circulation patterns consisted of strong anomalies in low-level moisture convergence and uplift over and near southwestern Madagascar that made conditions correspondingly more or less favourable for rainfall. Dry (wet) summers in southern Madagascar were also associated with an equatorward (poleward) displacement of the ITCZ in the region.

  11. Interannual variability in rainfall and wet spell frequency during the New South Wales sugarcane harvest season

    Everingham, Yvette L; Reason, C. J. C


    .... Farmer groups acknowledge that, whilst information about seasonal rainfall totals can assist forward planning activities impacted by harvest rainfall, knowledge about the number of wet spells during...

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

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


    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.

  13. Rainfall monitoring with microwave link networks -state of the art

    de Vos, Lotte; Overeem, Aart; Ríos Gaona, Manuel; van Leth, Tommy; Uijlenhoet, Remko


    For the purpose of hydrological applications, meteorology, climate monitoring and agriculture, accurate high resolution rainfall monitoring is highly desirable. Often used techniques to measure rainfall include rain gauge networks and radar. However, accurate rainfall information is lacking in large areas in the world, and the number of rain gauges is even severely declining in Europe, South-America and Africa. The investments required for the installation and maintenance of dense sensor networks can form a large obstacle. Over the past decade, various investigations have shown that microwave links from cellular communication networks may be used for rainfall monitoring. These commercial networks are installed for the purpose of cellular communication. These consist of antennas that transmit microwave link signals through the atmosphere over a path of typically several kilometers. Microwave signals are sensitive to rainfall at the frequencies that are typically used. The loss of signal (attenuation) over the link-path, which is logged in real-time by cellular communication companies for quality monitoring, can therefore be interpreted as a rainfall measurement. In recent years, various techniques have been developed to quantitatively determine rainfall from these microwave link attenuations. An overview of error sources in this process, quantitative rainfall determination techniques, as well as the results of various validation studies are provided. These studies show that there is considerable potential in using commercial microwave link networks for rainfall monitoring. This is a promising development, as these networks cover 20% of the land surface of the earth and have high density, especially in urban areas where there is generally a lack of in situ ground measurements.

  14. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  15. Rainfall variation by geostatistical interpolation method

    Glauber Epifanio Loureiro


    Full Text Available This article analyses the variation of rainfall in the Tocantins-Araguaia hydrographic region in the last two decades, based upon the rain gauge stations of the ANA (Brazilian National Water Agency HidroWeb database for the years 1983, 1993 and 2003. The information was systemized and treated with Hydrologic methods such as method of contour and interpolation for ordinary kriging. The treatment considered the consistency of the data, the density of the space distribution of the stations and the periods of study. The results demonstrated that the total volume of water precipitated annually did not change significantly in the 20 years analyzed. However, a significant variation occurred in its spatial distribution. By analyzing the isohyet it was shown that there is a displacement of the precipitation at Tocantins Baixo (TOB of approximately 10% of the total precipitated volume. This displacement can be caused by global change, by anthropogenic activities or by regional natural phenomena. However, this paper does not explore possible causes of the displacement.

  16. Linking landscape structure and rainfall runoff behaviour in a thermodynamic optimality context

    Zehe, Erwin; Ehret, Uwe; Blume, Theresa; Kleidon, Axel; Scherer, Ulrike; Westhoff, Martijn


    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.

  17. A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

    Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis


    This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of

  18. Stochastic modeling of hourly rainfall times series in Campania (Italy)

    Giorgio, M.; Greco, R.


    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

  19. The influence of seasonal rainfall upon Sahel vegetation

    Proud, Simon Richard; Rasmussen, Laura Vang


    include changes in total yearly rainfall, land-use change and migration. But these factors are not fully explanatory. This study addresses other possible factors for variation in vegetation patterns through the analysis of the Normalized Difference Vegetation Index (NDVI) produced by satellite sensors. We...... focus on precipitation, but instead of looking at the total yearly amount of rainfall, the intra-annual variation is examined. Here we show that plant growth is strongly correlated with the number and frequency of days within the rainy season upon which there is no rainfall. Furthermore, we find...

  20. Fluvial signatures of modern and paleo orographic rainfall gradients

    Schildgen, Taylor; Strecker, Manfred


    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

  1. Productivity responses of desert vegetation to precipitation patterns across a rainfall gradient.

    Li, Fang; Zhao, Wenzhi; Liu, Hu


    The influences of previous-year precipitation and episodic rainfall events on dryland plants and communities are poorly quantified in the temperate desert region of Northwest China. To evaluate the thresholds and lags in the response of aboveground net primary productivity (ANPP) to variability in rainfall pulses and seasonal precipitation along the precipitation-productivity gradient in three desert ecosystems with different precipitation regimes, we collected precipitation data from 2000 to 2012 in Shandan (SD), Linze (LZ) and Jiuquan (JQ) in northwestern China. Further, we extracted the corresponding MODIS Normalized Difference Vegetation Index (NDVI, a proxy for ANPP) datasets at 250 m spatial resolution. We then evaluated different desert ecosystems responses using statistical analysis, and a threshold-delay model (TDM). TDM is an integrative framework for analysis of plant growth, precipitation thresholds, and plant functional type strategies that capture the nonlinear nature of plant responses to rainfall pulses. Our results showed that: (1) the growing season NDVIINT (INT stands for time-integrated) was largely correlated with the warm season (spring/summer) at our mildly-arid desert ecosystem (SD). The arid ecosystem (LZ) exhibited a different response, and the growing season NDVIINT depended highly on the previous year's fall/winter precipitation and ANPP. At the extremely arid site (JQ), the variability of growing season NDVIINT was equally correlated with the cool- and warm-season precipitation; (2) some parameters of threshold-delay differed among the three sites: while the response of NDVI to rainfall pulses began at about 5 mm for all the sites, the maximum thresholds in SD, LZ, and JQ were about 55, 35 and 30 mm respectively, increasing with an increase in mean annual precipitation. By and large, more previous year's fall/winter precipitation, and large rainfall events, significantly enhanced the growth of desert vegetation, and desert ecosystems

  2. Analysis of a temperature- and rainfall-dependent model for malaria transmission dynamics.

    Okuneye, Kamaldeen; Gumel, Abba B


    A new non-autonomous model is designed and used to assess the impact of variability in temperature and rainfall on the transmission dynamics of malaria in a population. In addition to adding age-structure in the host population and the dynamics of immature malaria mosquitoes, a notable feature of the new model is that recovered individuals do not revert to wholly-susceptible class (that is, recovered individuals enjoy reduced susceptibility to new malaria infection). In the absence of disease-induced mortality, the disease-free solution of the model is shown to be globally-asymptotically stable when the associated reproduction ratio is less than unity. The model has at least one positive periodic solution when the reproduction ratio exceeds unity (and the disease persists in the community in this case). Detailed uncertainty and sensitivity analysis, using mean monthly temperature and rainfall data from KwaZulu-Natal province of South Africa, shows that the top three parameters of the model that have the most influence on the disease transmission dynamics are the mosquito carrying capacity, transmission probability per contact for susceptible mosquitoes and human recovery rate. Numerical simulations of the model show that, for the KwaZulu-Natal province, malaria burden increases with increasing mean monthly temperature and rainfall in the ranges ([17-25]°C and [32-110] mm), respectively (and decreases with decreasing mean monthly temperature and rainfall values). In particular, transmission is maximized for mean monthly temperature and rainfall in the ranges [21-25]°C and [95-125] mm. This occurs for a six-month period in KwaZulu-Natal (hence, this study suggests that anti-malaria control efforts should be intensified during this period). It is shown, for the fixed mean monthly temperature of KwaZulu-Natal, that malaria burden decreases whenever the amount of rainfall exceeds a certain threshold value. It is further shown (through sensitivity analysis and

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

    Yaokui Cui


    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.

  4. Forty years experience in developing and using rainfall simulators under tropical and Mediterranean conditions

    Pla-Sentís, Ildefonso; Nacci, Silvana


    Rainfall simulation has been used as a practical tool for evaluating the interaction of falling water drops on the soil surface, to measure both stability of soil aggregates to drop impact and water infiltration rates. In both cases it is tried to simulate the effects of natural rainfall, which usually occurs at very different, variable and erratic rates and intensities. One of the main arguments against the use of rainfall simulators is the difficulty to reproduce the size, final velocity and kinetic energy of the drops in natural rainfall. Since the early 70´s we have been developing and using different kinds of rainfall simulators, both at laboratory and field levels, and under tropical and Mediterranean soil and climate conditions, in flat and sloping lands. They have been mainly used to evaluate the relative effects of different land use and management, including different cropping systems, tillage practices, surface soil conditioning, surface covers, etc. on soil water infiltration, on runoff and on erosion. Our experience is that in any case it is impossible to reproduce the variable size distribution and terminal velocity of raindrops, and the variable changes in intensity of natural storms, under a particular climate condition. In spite of this, with the use of rainfall simulators it is possible to obtain very good information, which if it is properly interpreted in relation to each particular condition (land and crop management, rainfall characteristics, measurement conditions, etc.) may be used as one of the parameters for deducing and modelling soil water balance and soil moisture regime under different land use and management and variable climate conditions. Due to the possibility for a better control of the intensity of simulated rainfall and of the size of water drops, and the possibility to make more repeated measurements under very variable soil and land conditions, both in the laboratory and specially in the field, the better results have been

  5. Consideration notes on the critical rainfall threshold to predict the triggering of pyroclastic flows

    Scotto di Santolo, A.


    Atmospheric air pressure; • Homogenous soil; • Absence of evapotranspiration. The Richard's Equation, which regulates the process, has been solved using both the FEM HYDRUS 1D code (Symunek et al, 2005) and a code prepared by the current authors. The characteristic curve and the saturated permeability have been experimentally calculated at the DIGA. The different initial suction conditions are the result of the numerous in situ measurements made by the authors (Scotto di Santolo et al., 2005). The results obtained show that the criticality of a pluviometric event, besides depending on the intensity of rainfall and the average duration, also depends on numerous factors such as the following: • Water retention curve and permeability; • Initial suction conditions • Forms of temporal development of the rainfall, that is the law i(t) between intensity and time t (the analyses were carried out on the basis of average hours of rainfall). With reference to this latter aspect, assuming rainfall with a random distribution with a constant total average and height, it is possible to calculate the probability of the event being triggered, for each temporal evolution of the meteoric event. All these considerations suggest that there is no single model of "critical rainfall" but that each one is valid only on the basis of local conditions. Moreover, it is demonstrated that their use is extremely uncertain and requires the definition of rainfall through two mean parameters such as intensity and duration, regardless of the evolution of the pluviometric event.

  6. Torrential Rainfall Responses to Ice Microphysical Processes during Pre-Summer Heavy Rainfall over Southern China

    SHEN Xinyong; LIU Jia; Xiaofan LI


    In this study,the effects of key ice microphysical processes on the pre-summer heavy rainfall over southern China during 3-8 June 2008 were investigated.A series of two-dimensional sensitivity cloud-resolving model simulations were forced with zonally uniform vertical velocity,zonal wind,horizontal temperature,and water vapor advection data from the National Centers for Environmental Prediction (NCEP)/Global Data Assimilation System (GDAS).The effects of key ice microphysical processes on the responses of rainfall to large-scale forcing were analyzed by comparing two sensitivity experiments with a control experiment.In one sensitivity experiment,ice crystal radius,associated with depositional growth of snow from cloud ice,was reduced from 100 μm in the control experiment to 50 μm,and in the other sensitivity experiment the efficiency of the growth of graupel from the accretion of snow was reduced to 50% from 100% in the control experiment.The results show that the domain-mean rainfall responses to these ice microphysical processes are stronger during the decay phase than during the onset and mature phases.During the decay phase,the increased mean rain rate resulting from the decrease in ice crystal radius is associated with the enhanced mean local atmospheric drying,the increased mean local hydrometeor loss,and the suppressed mean water vapor divergence.The increased mean rain rate caused by the reduction in accretion efficiency is related to the reduced mean water vapor divergence and the enhanced mean local hydrometeor loss.

  7. Along the Rainfall-Runoff Chain: From Scaling of Greatest Point Rainfall to Global Change Attribution

    Fraedrich, K.


    Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.

  8. Estimation of Real-Time Flood Risk on Roads Based on Rainfall Calculated by the Revised Method of Missing Rainfall

    Eunmi Kim


    Full Text Available Recently, flood damage by frequent localized downpours in cities is on the increase on account of abnormal climate phenomena and the growth of impermeable areas due to urbanization. This study suggests a method to estimate real-time flood risk on roads for drivers based on the accumulated rainfall. The amount of rainfall of a road link, which is an intensive type, is calculated by using the revised method of missing rainfall in meteorology, because the rainfall is not measured on roads directly. To proce