A space-time rainfall generator for highly convective Mediterranean rainstorms

Directory of Open Access Journals (Sweden)

S. Salsón

2003-01-01

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

Effects of sample size on estimation of rainfall extremes at high temperatures

Science.gov (United States)

Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik

2017-09-01

High precipitation quantiles tend to rise with temperature, following the so-called Clausius-Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

Effects of sample size on estimation of rainfall extremes at high temperatures

Directory of Open Access Journals (Sweden)

B. Boessenkool

2017-09-01

Full Text Available High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

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

DEFF Research Database (Denmark)

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

2014-01-01

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

Variability in rainfall over tropical Australia during summer and relationships with the Bilybara High

Science.gov (United States)

Reason, C. J. C.

2018-04-01

Variability in summer rainfall over tropical Australia, defined here as that part of the continent north of 25° S, and its linkages with regional circulation are examined. In particular, relationships with the mid-level anticyclone (termed the Bilybara High) that exists over the northwestern Australia/Timor Sea region between August and April are considered. This High forms to the southwest of the upper-level anticyclone via a balance between the upper-level divergence over the region of tropical precipitation maximum and planetary vorticity advection and moves south and strengthens during the spring and summer. It is shown that variations in the strength and position of the Bilybara High are related to anomalies in precipitation and temperature over large parts of tropical Australia as well as some areas in the south and southeast of the landmass. Some of the interannual variations in the High are related to ENSO, but there are also a number of neutral years with large anomalies in the High and hence in rainfall. On decadal time scales, a strong relationship exists between the leading mode of tropical Australian rainfall and the Bilybara High. On both interannual and decadal scales, the relationships between the High and the regional rainfall involve changes in the monsoonal northwesterlies blowing towards northern Australia, and further south, in the easterly trade winds over the region.

Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

Science.gov (United States)

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

2009-04-01

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

Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

Science.gov (United States)

Painter, C.; Varble, A.; Zipser, E. J.

2017-12-01

While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

Ecological mechanisms underlying soil bacterial responses to rainfall along a steep natural precipitation gradient.

Science.gov (United States)

Waring, Bonnie; Hawkes, Christine V

2018-02-01

Changes in the structure and function of soil microbial communities can drive substantial ecosystem feedbacks to altered precipitation. However, the ecological mechanisms underlying community responses to environmental change are not well understood. We used an 18-month soil reciprocal transplant experiment along a steep precipitation gradient to quantify how changes in rainfall affected bacterial community structure. We also conducted an enhanced dispersal treatment to ask whether higher immigration rates of taxa from the surrounding environment would accelerate community responses to climate change. Finally, we addressed how the composition of soil bacteria communities was related to the functional response of soil respiration to moisture in these treatments. Bacterial community structure (OTU abundance) and function (respiration rates) changed little in response to manipulation of either rainfall environment or dispersal rates. Although most bacteria were ecological generalists, a subset of specialist taxa, over 40% of which were Actinobacteria, tended to be more abundant in the rainfall environment that matched their original conditions. Bacteria community composition was an important predictor of the respiration response to moisture. Thus, the high compositional resistance of microbial communities dictated respiration responses to altered rainfall in this system.

Long term high resolution rainfall runoff observations for improved water balance uncertainty and database QA-QC in the Walnut Gulch Experimental Watershed.

Science.gov (United States)

Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.

2017-12-01

Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

Science.gov (United States)

Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

2002-01-01

Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

Science.gov (United States)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Impacts of manure application on soil environment, rainfall use efficiency and crop biomass under dryland farming.

Science.gov (United States)

Wang, Xiaojuan; Jia, Zhikuan; Liang, Lianyou; Yang, Baoping; Ding, Ruixia; Nie, Junfeng; Wang, Junpeng

2016-02-12

Because of inadequate nutrient and water supply, soils are often unproductive in Northwest China. We studied the effects of manure application at low (LM 7.5  t ha(-1)), medium (MM 15 t ha(-1)), and high (HM 22.5 t ha(-1)) rates combined with fixed levels of chemical fertilizers on maize growth and rainfall use efficiency compared with chemical fertilizers (CK) under semi-arid conditions over a three-year period. HM and MM treatments could significantly increase soil water storage (0-120 cm) at tasseling stage of maize compared with LM treatment and CK (P < 0.05). Dry matter accumulation and rainfall use efficiency increased as manure application rate increasing (P < 0.05). HM treatment significantly increased rainfall use efficiency by 6.5-12.7% at big trumpeting - tasseling stage compared with LM and MM treatments. HM and MM treatments increased rainfall use efficiency by 8.6-18.1% at tasseling - grain filling stage compared with CK. There was no significant difference on biomass between HM and MM treatments at grain filling and maturity stages of maize in 2009 and 2010.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

Science.gov (United States)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Directory of Open Access Journals (Sweden)

E. Cristiano

2017-07-01

Full Text Available In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Simulation of water-limited growth of the forage shrub saltbush (Atriplex nummularia Lindl.) in a low-rainfall environment of southern Australia

NARCIS (Netherlands)

Descheemaeker, K.K.E.; Smith, A.P.; Robertson, M.J.; Whitbread, A.; Huth, N.I.; Davoren, W.; Emms, J.; Llewellyn, R.

2014-01-01

Old man saltbush (Atriplex nummularia Lindl.) is a useful forage shrub for livestock in the low-rainfall areas of the world, and particularly in Australia. In these semi-arid and arid environments, saltbush is valuable for increasing the production from otherwise marginal areas of the farm and

Polarimetric rainfall retrieval from a C-Band weather radar in a tropical environment (The Philippines)

Science.gov (United States)

Crisologo, I.; Vulpiani, G.; Abon, C. C.; David, C. P. C.; Bronstert, A.; Heistermann, Maik

2014-11-01

We evaluated the potential of polarimetric rainfall retrieval methods for the Tagaytay C-Band weather radar in the Philippines. For this purpose, we combined a method for fuzzy echo classification, an approach to extract and reconstruct the differential propagation phase, Φ DP , and a polarimetric self-consistency approach to calibrate horizontal and differential reflectivity. The reconstructed Φ DP was used to estimate path-integrated attenuation and to retrieve the specific differential phase, K DP . All related algorithms were transparently implemented in the Open Source radar processing software wradlib. Rainfall was then estimated from different variables: from re-calibrated reflectivity, from re-calibrated reflectivity that has been corrected for path-integrated attenuation, from the specific differential phase, and from a combination of reflectivity and specific differential phase. As an additional benchmark, rainfall was estimated by interpolating the rainfall observed by rain gauges. We evaluated the rainfall products for daily and hourly accumulations. For this purpose, we used observations of 16 rain gauges from a five-month period in the 2012 wet season. It turned out that the retrieval of rainfall from K DP substantially improved the rainfall estimation at both daily and hourly time scales. The measurement of reflectivity apparently was impaired by severe miscalibration while K DP was immune to such effects. Daily accumulations of rainfall retrieved from K DP showed a very low estimation bias and small random errors. Random scatter was, though, strongly present in hourly accumulations.

Effect of Rainfall Variability on Water Supply in Ikeduru L.G.A. of Imo ...

African Journals Online (AJOL)

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alternatives, which are that there is a strong relationship between rural water supply in ... Rainfall is a renewable resource, highly variable in space and time and ..... Due to the total dependence on the immediate environment for water supply,.

Assessing Climate Variability using Extreme Rainfall and ...

African Journals Online (AJOL)

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

Comparison of online and offline based merging methods for high resolution rainfall intensities

Science.gov (United States)

Shehu, Bora; Haberlandt, Uwe

2016-04-01

Accurate rainfall intensities with high spatial and temporal resolution are crucial for urban flow prediction. Commonly, raw or bias corrected radar fields are used for forecasting, while different merging products are employed for simulation. The merging products are proven to be adequate for rainfall intensities estimation, however their application in forecasting is limited as they are developed for offline mode. This study aims at adapting and refining the offline merging techniques for the online implementation, and at comparing the performance of these methods for high resolution rainfall data. Radar bias correction based on mean fields and quantile mapping are analyzed individually and also are implemented in conditional merging. Special attention is given to the impact of different spatial and temporal filters on the predictive skill of all methods. Raw radar data and kriging interpolation of station data are considered as a reference to check the benefit of the merged products. The methods are applied for several extreme events in the time period 2006-2012 caused by different meteorological conditions, and their performance is evaluated by split sampling. The study area is located within the 112 km radius of Hannover radar in Lower Saxony, Germany and the data set constitutes of 80 recording stations in 5 min time steps. The results of this study reveal how the performance of the methods is affected by the adjustment of radar data, choice of merging method and selected event. Merging techniques can be used to improve the performance of online rainfall estimation, which gives way to the application of merging products in forecasting.

Spatial Analysis of High-Resolution Radar Rainfall and Citizen-Reported Flash Flood Data in Ultra-Urban New York City

Directory of Open Access Journals (Sweden)

Brianne Smith

2017-09-01

Full Text Available New York City (NYC is an ultra-urban region, with over 50% impervious cover and buried stream channels. Traditional flood studies rely on the presence of stream gages to detect flood stage and discharge, but these methods cannot be used in ultra-urban areas. Here we create a high-resolution radar rainfall dataset for NYC and utilize citizen and expert reports of flooding throughout the city to study flash flooding in NYC. Results indicate that interactions between the urban area and land–sea boundary have an important impact on the spatial variability of both heavy rainfall and flooding, sometimes in contrast to results obtained for other cities. Top days of daily and hourly rainfall exhibit a rainfall maximum over the city center and an extended region of higher rainfall downwind of the city. The mechanism for flooding appears to vary across the city, with high groundwater tables influencing more coastal areas and high rain rates or large rain volumes influencing more inland areas. There is also a strong relationship between sewer type and flood frequency, with fewer floods observed in combined sewer areas. Flooding is driven by maximum one-hour to one-day rainfall, which is often substantially less rain than observed for the city-wide daily maximum.

Use of Aquacrop Model to predict Maize Yields under Varying Rainfall and Temperature in a Semi-Arid Environment in Kenya

International Nuclear Information System (INIS)

Wamari, O. J.; Sijali, V. I; Heng, N. K; Joseph Mutwiri Miriti, M. J; Esilaba, O A

2012-01-01

There has been increasing concern that drier and hotter seasons are becoming more frequent due to climate change especially in semi-arid environments causing adverse effects on agricultural production. Analysis of long-term (1980-2010) trends of rainfall in the first growing season (i.e. March and July) at Katumani, Kenya showed that about 55% of the seasons were below the long-term average, with an all time low occurring in the year 2000. Although the wettest years (1998 and 1985 ) had relatively higher percentages above the long-term average (143.9% and 138.4% ) compared to lower percentages ( 61.7% and 59.7%) of the driest years ( 2000 and 1987), the latter were relatively less in numbers (i.e. 45%). Mean seasonal temperatures however did not show high variation from the long term mean implying that rainfall was the main cause of yield variation in this area. The AquaCrop model (Ver. 3.1) evaluated using three years (i.e. 1999, 2000 and 2001) of experimental results at Katumani, gave reasonable estimates of above ground biomass and grain yield of Katumani composite maize variety. The model was then used to predict Katumani maize yields under 20% depletion of rainfall and 3°C temperature elevation scenarios. Biomass and grain yields simulated respectively ranged between 2.971 to 6.558 and 0.910 to 2.564 T Ha-1 with probabilities of obtaining 3-5 T Ha-1 biomass and 1-2 T Ha-1 grain yields each dropping from 98 to 25%. Adaptation measures are given as management recommendations in line with the changed climatic scenario. (author)

Topographic relationships for design rainfalls over Australia

Science.gov (United States)

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

2016-02-01

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

Drought-avoiding plants with low water use can achieve high rainfall retention without jeopardising survival on green roofs.

Science.gov (United States)

Szota, Christopher; Farrell, Claire; Williams, Nicholas S G; Arndt, Stefan K; Fletcher, Tim D

2017-12-15

Green roofs are increasingly being used among the suite of tools designed to reduce the volume of surface water runoff generated by cities. Plants provide the primary mechanism for restoring the rainfall retention capacity of green roofs, but selecting plants with high water use is likely to increase drought stress. Using empirically-derived plant physiological parameters, we used a water balance model to assess the trade-off between rainfall retention and plant drought stress under a 30-year climate scenario. We compared high and low water users with either drought avoidance or drought tolerance strategies. Green roofs with low water-using, drought-avoiding species achieved high rainfall retention (66-81%) without experiencing significant drought stress. Roofs planted with other strategies showed high retention (72-90%), but they also experienced >50days of drought stress per year. However, not all species with the same strategy behaved similarly, therefore selecting plants based on water use and drought strategy alone does not guarantee survival in shallow substrates where drought stress can develop quickly. Despite this, it is more likely that green roofs will achieve high rainfall retention with minimal supplementary irrigation if planted with low water users with drought avoidance strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Urban rainfall estimation employing commercial microwave links

Science.gov (United States)

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

2015-04-01

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

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

Science.gov (United States)

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

2014-05-01

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

A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

Directory of Open Access Journals (Sweden)

Yinping Long

2016-07-01

Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

Rainfall prediction with backpropagation method

Science.gov (United States)

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

2018-03-01

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

Bias adjustment and advection interpolation of long-term high resolution radar rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.

2014-01-01

It is generally acknowledged that in order to apply radar rainfall data for hydrological proposes adjustment against ground observations are crucial. Traditionally, radar reflectivity is transformed into rainfall rates applying a fixed reflectivity – rainfall rate relationship even though...... this is known to depend on the changing drop size distribution of the specific rain. This creates a transient bias between the radar rainfall and the ground observations due to seasonal changes of the drop size distribution as well as other atmospheric effects and effects related to the radar observational...

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

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

2013-12-01

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

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

Science.gov (United States)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

Science.gov (United States)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

Monsoon Rainfall and Landslides in Nepal

Science.gov (United States)

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

2009-12-01

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

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

Science.gov (United States)

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

2015-12-01

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

Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

Science.gov (United States)

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

2015-04-01

Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error

Rainfall erosivity in Europe.

Science.gov (United States)

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

2015-04-01

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

Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

Science.gov (United States)

Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

2017-02-01

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high

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

Science.gov (United States)

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

2014-05-01

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

Weekend Effect" in Summertime U.S. Rainfall: Evidence for Midweek Intensification of Storms by Pollution

Science.gov (United States)

Bell, Thomas L.; Rosenfeld, Daniel; Kim, Kyu-Myong; Hahnenberger, Maura

2006-01-01

Persistent and strong dependence of rain rate on the day of the week has been found in Tropical Rainfall Measuring Mission (TRMM) satellite estimates of summer afternoon rainfall over the southeast U.S. and the nearby Atlantic from 1998 to 2005. Midweek (Tue-Thu) rain rates and rain area appear to increase over land, and this increase is accompanied by a corresponding diminution of rainfall over nearby waters. Reanalysis data from atmospheric models, suggest that there is a corresponding weekly variation in atmospheric winds consistent with the changes in rainfall. These variations are almost certainly caused by weekly variations in human activity. The most likely cause of the observed changes in rainfall is the well documented weekly variation in atmospheric pollution. Particulate pollution is highest in the middle of the week. Considerable observational and modeling evidence has accumulated concerning the effects of aerosols on precipitation. Most of this evidence relates to the suppression of precipitation by aerosols, but it has been argued that storms in highly unstable moist environments can be invigorated by aerosols, and some modeling studies seem to confirm this. The strong weekly cycle in rainfall observed over the southeast U.S. along with what appears to be dynamical suppression of rainfall over the nearby Atlantic, and the lack of an observable cycle over the southwest U.S., are consistent with this theory.

Rainfall estimation with TFR model using Ensemble Kalman filter

Science.gov (United States)

Asyiqotur Rohmah, Nabila; Apriliani, Erna

2018-03-01

Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models

Science.gov (United States)

Krishnamurthy, Lakshmi; Muñoz, Ángel G.; Vecchi, Gabriel A.; Msadek, Rym; Wittenberg, Andrew T.; Stern, Bill; Gudgel, Rich; Zeng, Fanrong

2018-05-01

The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

Science.gov (United States)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Convective Mode and Mesoscale Heavy Rainfall Forecast Challenges during a High-Impact Weather Period along the Gulf Coast and Florida from 17-20 May 2016

Science.gov (United States)

Bosart, L. F.; Wallace, B. C.

2017-12-01

Two high-impact convective storm forecast challenges occurred between 17-20 May 2016 during NOAA's Hazardous Weather Testbed Spring Forecast Experiment (SFE) at the Storm Prediction Center. The first forecast challenge was 286 mm of unexpected record-breaking rain that fell on Vero Beach (VRB), Florida, between 1500 UTC 17 May and 0600 UTC 18 May, more than doubling the previous May daily rainfall record. The record rains in VRB occurred subsequent to the formation of a massive MCS over the central Gulf of Mexico between 0900-1000 UTC 17 May. This MCS, linked to the earlier convection associated with an anomalously strong subtropical jet (STJ) over the Gulf of Mexico, moved east-northeastward toward Florida. The second forecast challenge was a large MCS that formed over the Mexican mountains near the Texas-Mexican border, moved eastward and grew upscale prior to 1200 UTC 19 May. This MCS further strengthened offshore after 1800 UTC 19 May beneath the STJ. SPC SFE participants expected this MCS to move east-northeastward and bring heavy rain due to training echoes along the Gulf coast as far eastward as the Florida panhandle. Instead, this MCS transitioned into a bowing MCS that resembled a low-end derecho and produced a 4-6 hPa cold pool with widespread surface wind gusts between 35-50 kt. Both MCS events occurred in a large-scale baroclinic environment along the northern Gulf coast. Both MCS events responded to antecedent convection within this favorable large-scale environment. Rainfall amounts with the first heavy rain-producing MCS were severely underestimated by models and forecasters alike. The second MCS produced the greatest forecaster angst because rainfall totals were forecast too high (MCS propagated too fast) and severe wind reports were much more widespread than anticipated (because of cold pool formation). This presentation will attempt to untangle what happened and why it happened.

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

Science.gov (United States)

Leuenberger, D.; Rossa, A.

2007-12-01

Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

Analysis and simulation of mesoscale convective systems accompanying heavy rainfall: The goyang case

Science.gov (United States)

Choi, Hyun-Young; Ha, Ji-Hyun; Lee, Dong-Kyou; Kuo, Ying-Hwa

2011-05-01

We investigated a torrential rainfall case with a daily rainfall amount of 379 mm and a maximum hourly rain rate of 77.5 mm that took place on 12 July 2006 at Goyang in the middlewestern part of the Korean Peninsula. The heavy rainfall was responsible for flash flooding and was highly localized. High-resolution Doppler radar data from 5 radar sites located over central Korea were analyzed. Numerical simulations using the Weather Research and Forecasting (WRF) model were also performed to complement the high-resolution observations and to further investigate the thermodynamic structure and development of the convective system. The grid nudging method using the Global Final (FNL) Analyses data was applied to the coarse model domain (30 km) in order to provide a more realistic and desirable initial and boundary conditions for the nested model domains (10 km, 3.3 km). The mesoscale convective system (MCS) which caused flash flooding was initiated by the strong low level jet (LLJ) at the frontal region of high equivalent potential temperature (θe) near the west coast over the Yellow Sea. The ascending of the warm and moist air was induced dynamically by the LLJ. The convective cells were triggered by small thermal perturbations and abruptly developed by the warm θe inflow. Within the MCS, several convective cells responsible for the rainfall peak at Goyang simultaneously developed with neighboring cells and interacted with each other. Moist absolutely unstable layers (MAULs) were seen at the lower troposphere with the very moist environment adding the instability for the development of the MCS.

Heterogeneity of Dutch rainfall

NARCIS (Netherlands)

Witter, J.V.

1984-01-01

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

Rainfall and Development of Zika Virus

African Journals Online (AJOL)

2017-11-01

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

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

Science.gov (United States)

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

2016-08-05

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

Prevention through policy: Urban macroplastic leakages to the marine environment during extreme rainfall events

OpenAIRE

Axelsson, Charles; van Sebille, Erik

2017-01-01

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic leakage is extremely pertinent. Here, we explore why and how coastal cities can reduce macroplastic leakages during extreme rainfall events. Using nine global cities as a basis, we establish that while c...

Sprinkling experiments to simulate high and intense rainfall for process based investigations - a comparison of two methods

Science.gov (United States)

Müller, C.; Seeger, M.; Schneider, R.; Johst, M.; Casper, M.

2009-04-01

Land use and land management changes affect runoff and erosion dynamics. So, measures within this scope are often directed towards the mitigation of natural hazards such as floods and landslides. However, the effects of these changes (e.g. in soil physics after reforestation or a less extensive agriculture) are i) detectable first many years later or ii) hardly observable with conventional methods. Therefore, sprinkling experiments are frequently used for process based investigations of near-surface hydrological response as well as rill and interrill erosion. In this study, two different sprinkling systems have been applied under different land use and at different scales to elucidate and quantify dominant processes of runoff generation, as well as to relate them to the detachment and transport of solids. The studies take place at the micro-scale basin Zemmer and Frankelbach in Germany. At the Zemmer basin the sprinkling experiments were performed on agricultural land while the experiments in Frankelbach were performed at reforested sites. The experiments were carried out i) with a small mobile rainfall simulator of high rainfall intensities (40 mm h-1) and ii) with a larger one covering a slope segment and simulating high rainfall amounts (120 mm in 3 days). Both methods show basically comparable results. On the agricultural sites clear differences could be observed between different soil management types: contrasting to the conventionally tilled soils, deep loosened soils (in combination with conservative tillage) do not produce overland flow, but tend to transfer more water by interflow processes, retaining large amounts in the subsoil. For the forested sites runoff shows a high variability as determined the larger and the smaller rainfall simulations. This variability is rather due to the different forest and soil types than to methodologically different settings of the sprinkling systems. Both rainfall simulation systems characterized the runoff behavior in a

Rainfall Characteristics and Regionalization in Peninsular Malaysia Based on a High Resolution Gridded Data Set

Directory of Open Access Journals (Sweden)

Chee Loong Wong

2016-11-01

Full Text Available Daily gridded rainfall data over Peninsular Malaysia are delineated using an objective clustering algorithm, with the objective of classifying rainfall grids into groups of homogeneous regions based on the similarity of the rainfall annual cycles. It has been demonstrated that Peninsular Malaysia can be statistically delineated into eight distinct rainfall regions. This delineation is closely associated with the topographic and geographic characteristics. The variation of rainfall over the Peninsula is generally characterized by bimodal variations with two peaks, i.e., a primary peak occurring during the autumn transitional period and a secondary peak during the spring transitional period. The east coast zones, however, showed a single peak during the northeast monsoon (NEM. The influence of NEM is stronger compared to the southwest monsoon (SWM. Significantly increasing rainfall trends at 95% confidence level are not observed in all regions during the NEM, with exception of northwest zone (R1 and coastal band of west coast interior region (R3. During SWM, most areas have become drier over the last three decades. The study identifies higher variation of mean monthly rainfall over the east coast regions, but spatially, the rainfall is uniformly distributed. For the southwestern coast and west coast regions, a larger range of coefficients of variation is mostly obtained during the NEM, and to a smaller extent during the SWM. The inland region received least rainfall in February, but showed the largest spatial variation. The relationship between rainfall and the El Niño Southern Oscillation (ENSO was examined based on the Multivariate ENSO Index (MEI. Although the concurrent relationships between rainfall in the different regions and ENSO are generally weak with negative correlations, the rainfall shows stronger positive correlation with preceding ENSO signals with a time lag of four to eight months.

Uganda rainfall variability and prediction

Science.gov (United States)

Jury, Mark R.

2018-05-01

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

Rainfall Erosivity in Europe

DEFF Research Database (Denmark)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Roriz Luciano Machado

2017-12-01

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

Censored rainfall modelling for estimation of fine-scale extremes

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2015-04-01

regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Detecting Climate Variability in Tropical Rainfall

Science.gov (United States)

Berg, W.

2004-05-01

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

Feasibility of High-Resolution Soil Erosion Measurements by Means of Rainfall Simulations and SfM Photogrammetry

Directory of Open Access Journals (Sweden)

Phoebe Hänsel

2016-11-01

Full Text Available The silty soils of the intensively used agricultural landscape of the Saxon loess province, eastern Germany, are very prone to soil erosion, mainly caused by water erosion. Rainfall simulations, and also increasingly structure-from-motion (SfM photogrammetry, are used as methods in soil erosion research not only to assess soil erosion by water, but also to quantify soil loss. This study aims to validate SfM photogrammetry determined soil loss estimations with rainfall simulations measurements. Rainfall simulations were performed at three agricultural sites in central Saxony. Besides the measured data runoff and soil loss by sampling (in mm, terrestrial images were taken from the plots with digital cameras before and after the rainfall simulation. Subsequently, SfM photogrammetry was used to reconstruct soil surface changes due to soil erosion in terms of high resolution digital elevation models (DEMs for the pre- and post-event (resolution 1 × 1 mm. By multi-temporal change detection, the digital elevation model of difference (DoD and an averaged soil loss (in mm is received, which was compared to the soil loss by sampling. Soil loss by DoD was higher than soil loss by sampling. The method of SfM photogrammetry-determined soil loss estimations also include a comparison of three different ground control point (GCP approaches, revealing that the most complex one delivers the most reliable soil loss by DoD. Additionally, soil bulk density changes and splash erosion beyond the plot were measured during the rainfall simulation experiments in order to separate these processes and associated surface changes from the soil loss by DoD. Furthermore, splash was negligibly small, whereas higher soil densities after the rainfall simulations indicated soil compaction. By means of calculated soil surface changes due to soil compaction, the soil loss by DoD achieved approximately the same value as the soil loss by rainfall simulation.

A comprehensive continent-wide regionalisation investigation for daily design rainfall

OpenAIRE

F. Johnson; J. Green

2018-01-01

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

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

Science.gov (United States)

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

2009-04-01

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

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

Directory of Open Access Journals (Sweden)

Assumpta Mukabutera

2016-08-01

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

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

Directory of Open Access Journals (Sweden)

Tingting Shi

2015-09-01

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

Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

Science.gov (United States)

Chen, H.; Chandrasekar, V.; Biswas, S.

2015-12-01

Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

Science.gov (United States)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an

Modifying rainfall patterns in a Mediterranean shrubland: system design, plant responses, and experimental burning.

Science.gov (United States)

Parra, Antonio; Ramírez, David A; Resco, Víctor; Velasco, Ángel; Moreno, José M

2012-11-01

Global warming is projected to increase the frequency and intensity of droughts in the Mediterranean region, as well as the occurrence of large fires. Understanding the interactions between drought, fire and plant responses is therefore important. In this study, we present an experiment in which rainfall patterns were modified to simulate various levels of drought in a Mediterranean shrubland of central Spain dominated by Cistus ladanifer, Erica arborea and Phillyrea angustifolia. A system composed of automatic rainout shelters with an irrigation facility was used. It was designed to be applied in vegetation 2 m tall, treat relatively large areas (36 m2), and be quickly dismantled to perform experimental burning and reassembled back again. Twenty plots were subjected to four rainfall treatments from early spring: natural rainfall, long-term average rainfall (2 months drought), moderate drought (25% reduction from long-term rainfall, 5 months drought) and severe drought (45% reduction, 7 months drought). The plots were burned in late summer, without interfering with rainfall manipulations. Results indicated that rainfall manipulations caused differences in soil moisture among treatments, leading to reduced water availability and growth of C. ladanifer and E. arborea in the drought treatments. However, P. angustifolia was not affected by the manipulations. Rainout shelters had a negligible impact on plot microenvironment. Experimental burns were of high fire intensity, without differences among treatments. Our system provides a tool to study the combined effects of drought and fire on vegetation, which is important to assess the threats posed by climate change in Mediterranean environments.

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

Science.gov (United States)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model

Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...

African Journals Online (AJOL)

ADOWIE PERE

Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.

Sensitivity of point scale surface runoff predictions to rainfall resolution

Directory of Open Access Journals (Sweden)

A. J. Hearman

2007-01-01

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

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

Science.gov (United States)

Liong, Shie-Yui; He, Shan

2010-05-01

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

Rainfall simulation in education

Science.gov (United States)

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

2016-04-01

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

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

Directory of Open Access Journals (Sweden)

A. Cilek

2016-06-01

Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

Rainfall: State of the Science

Science.gov (United States)

Testik, Firat Y.; Gebremichael, Mekonnen

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

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

Science.gov (United States)

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

2015-12-01

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

Extreme rainfall events in karst environments: the case study of September 2014 in the Gargano area (southern Italy)

Science.gov (United States)

Martinotti, Maria Elena; Pisano, Luca; Trabace, Maria; Marchesini, Ivan; Peruccacci, Silvia; Rossi, Mauro; Amoruso, Giuseppe; Loiacono, Pierluigi; Vennari, Carmela; Vessia, Giovanna; Parise, Mario; Brunetti, Maria Teresa

2015-04-01

In the first week of September 2014, the Gargano Promontory (Apulia, SE Italy) was hit by an extreme rainfall event that caused several landslides, floods and sinkholes. As a consequence of the floods, two people lost their lives and severe socio-economic damages were reported. The highest peaks of rainfall were recorded between September 3rd and 6th at the Cagnano Varano and San Marco in Lamis rain gauges with a maximum daily rainfall (over 230 mm) that is about 30% the mean annual rainfall. The Gargano Promontory is characterized by complex orographic conditions, with the highest elevation of about 1000 m a.s.l. The geological setting consists of different types of carbonate deposits affected by intensive development of karst processes. The morphological and climatic settings of the area, associated with frequent extreme rainfall events can cause various types of geohazards (e.g., landslides, floods, sinkholes). A further element enhancing the natural predisposition of the area to the occurrence of landslides, floods and sinkholes is an intense human activity, characterized by an inappropriate land use and management. In order to obtain consistent and reliable data on the effects produced by the storm, a systematic collection of information through field observations, a critical analysis of newspaper articles and web-news, and a co-operation with the Regional Civil Protection and local geologists started immediately after the event. The information collected has been organized in a database including the location, the occurrence time and the type of geohazard documented with photographs. The September 2014 extreme rainfall event in the Gargano Promontory was also analyzed to validate the forecasts issued by the Italian national early-warning system for rainfall-induced landslides (SANF), developed by the Research Institute for Geo-Hydrological Protection (IRPI) for the Italian national Department for Civil Protection (DPC). SANF compares rainfall measurements and

Characterizing rainfall parameters which influence erosivity in southeastern Nigeria

International Nuclear Information System (INIS)

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

1993-12-01

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

Deforestation alters rainfall: a myth or reality

Science.gov (United States)

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

2016-06-01

To cope with the issue of food safety and human shelter, natural landscape has gone through a number of alterations. In the coming future, the expansion of urban land and agricultural farms will likely disrupt the natural environment. Researchers have claimed that land use change may become the most serious issue of the current century. Thus, it is necessary to understand the consequences of land use change on the climatic variables, e.g., rainfall. This study investigated the impact of deforestation on local rainfall. An integrated methodology was adopted to achieve the objectives. Above ground biomass was considered as the indicator of forest areas. Time series data of a Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were obtained for the year of 2000, 2005, and 2010. Rainfall data were collected from the Department of Irrigation and Drainage, Malaysia. The MODIS time series data were classified and four major classes were developed based on the Normalised Difference Vegetation Index (NDVI) ranges. The results of the classification showed that water, and urban and agricultural lands have increased in their area by 2, 3, and 6%, respectively. On the other hand, the area of forest has decreased 10% collectively from 2000 to 2010. The results of NDVI and rainfall data were analysed by using a linear regression analysis. The results showed a significant relationship at a 90% confidence interval between rainfall and deforestation (t = 1.92, p = 0.06). The results of this study may provide information about the consequences of land use on the climate on the local scale.

Agro-Science Journal of Tropical Agriculture, Food, Environment ...

African Journals Online (AJOL)

OLUWOLE AKINNAGBE

2009-09-03

Sep 3, 2009 ... Agro-Science Journal of Tropical Agriculture, Food, Environment and Extension. Volume 8 ... 3 International Institute of Tropical Agriculture, High Rainfall Station,. Onne, Rivers State ...... Biosciences proceedings. 6: 444-454.

Effect of monthly areal rainfall uncertainty on streamflow simulation

Science.gov (United States)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

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

Projections of West African summer monsoon rainfall extremes from two CORDEX models

Science.gov (United States)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

Science.gov (United States)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

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

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

Science.gov (United States)

Li, Yi; Shao, Ming'an

2006-12-01

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

An Atlantic influence on Amazon rainfall

Energy Technology Data Exchange (ETDEWEB)

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

2010-02-15

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

Spatial and temporal variability of rainfall in the Tocantins-Araguaia hydrographic region

Directory of Open Access Journals (Sweden)

Glauber Epifanio Loureiro

2015-01-01

Full Text Available Current paper examines the space-time dynamics of yearly rainfall of the Tocantins-Araguaia Hydrographic Region (TAHR, foregrounded on rainfall volume from isohyet maps and interpolated by Kriging geo-statistical method.  Rainfall space dynamics was undertaken by the analysis of descriptive statistics, Index of Meteorological Irregularity (IMI and Variation Coefficient. Temporal dynamics was analyzed through the distribution of total annual volume precipitation for each TAHR sub-basin by the Standardized Anomaly Index, trend and magnitude test provided by Mann-Kendall and Sen Tests. Results correlated with meteorological anomalies of the Atlantic (Dipole and Pacific (ENOS Oceans show a highly heterogeneous rainfall behavior with temporal variability. Or rather, a decrease of rainfall extensiveness during years of intense meteorological anomaly with a rainfall increase south of the High Tocantins and Araguaia sub-basins and a decrease of rainfall in the Lower Tocantins sub-basin, with El Niño features. Although the Mann-Kendall test does not show statistically a significant trend for rainfall in the TAHR region, Sen’s estimator reveals a decrease in rainfall in the High Tocantins (-1.24 km³ year-1 and Araguaia (-1.13 km³ year-1 sub-basins and a rainfall increase in the Lower Tocantins sub-basin (0.53 km³ year-1 and in the TAHR region (-1.5 km³ year-1.

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

Science.gov (United States)

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

2017-04-01

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

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

Science.gov (United States)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

Darfur: rainfall and conflict

International Nuclear Information System (INIS)

Kevane, Michael; Gray, Leslie

2008-01-01

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

Darfur: rainfall and conflict

Science.gov (United States)

Kevane, Michael; Gray, Leslie

2008-07-01

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

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

CSIR Research Space (South Africa)

Engelbrecht, CJ

2012-09-01

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

Preliminary Investigation on the Behavior of Pore Air Pressure During Rainfall Infiltration

Science.gov (United States)

Ashraf Mohamad Ismail, Mohd; Min, Ng Soon; Hasliza Hamzah, Nur; Hazreek Zainal Abidin, Mohd; Madun, Aziman; Tajudin, Saiful Azhar Ahmad

2018-04-01

This paper focused on the preliminary investigation of pore air pressure behaviour during rainfall infiltration in order to substantiate the mechanism of rainfall induced slope failure. The actual behaviour or pore air pressure during infiltration is yet to be clearly understood as it is regularly assumed as atmospheric. Numerical modelling of one dimensional (1D) soil column was utilized in this study to provide a preliminary insight of this highlighted uncertainty. Parametric study was performed by using rainfall intensities of 1.85 x 10-3m/s and 1.16 x 10-4m/s applied on glass beads to simulate intense and modest rainfall conditions. Analysis results show that the high rainfall intensity causes more development of pore air pressure compared to low rainfall intensity. This is because at high rainfall intensity, the rainwater cannot replace the pore air smoothly thus confining the pore air. Therefore, the effect of pore air pressure has to be taken into consideration particularly during heavy rainfall.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Science.gov (United States)

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

2018-03-01

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

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Hassan Zulkarnain

2018-01-01

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

The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

Science.gov (United States)

Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

2015-04-01

In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national

Stochastic bias-correction of daily rainfall scenarios for hydrological applications

Directory of Open Access Journals (Sweden)

I. Portoghese

2011-09-01

Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.

In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.

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

Science.gov (United States)

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

2017-04-01

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

Regionalization of monthly rainfall erosivity patternsin Switzerland

Science.gov (United States)

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

2016-10-01

the total annual rainfall erosivity is identified within four months only (June-September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

Science.gov (United States)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between

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

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Duangdai, Eakkapong; Likasiri, Chulin

2017-03-01

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

Rainfall effects on rare annual plants

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

2008-01-01

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

Simulation of infiltration and redistribution of intense rainfall using Land Surface Models

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Mueller, Anna; Verhoef, Anne; Cloke, Hannah

2016-04-01

Flooding from intense rainfall (FFIR) can cause widespread damage and disruption. Numerical Weather Prediction (NWP) models provide distributed information about atmospheric conditions, such as precipitation, that can lead to a flooding event. Short duration, high intensity rainfall events are generally poorly predicted by NWP models, because of the high spatiotemporal resolution required and because of the way the convective rainfall is described in the model. The resolution of NWP models is ever increasing. Better understanding of complex hydrological processes and the effect of scale is important in order to improve the prediction of magnitude and duration of such events, in the context of disaster management. Working as part of the NERC SINATRA project, we evaluated how the Land Surface Model (LSM) components of NWP models cope with high intensity rainfall input and subsequent infiltration problems. Both in terms of the amount of water infiltrated in the soil store, as well as the timing and the amount of surface and subsurface runoff generated. The models investigated are SWAP (Soil Water Air Plant, Alterra, the Netherlands, van Dam 1997), JULES (Joint UK Land Environment Simulator a component of Unified Model in UK Met Office, Best et al. 2011) and CHTESSEL (Carbon and Hydrology- Tiled ECMWF Scheme for Surface Exchanges over Land, Balsamo et al. 2009) We analysed the numerical aspects arising from discontinuities (or sharp gradients) in forcing and/or the model solution. These types of infiltration configurations were tested in the laboratory (Vachaud 1971), for some there are semi-analytical solutions (Philip 1957, Parlange 1972, Vanderborght 2005) or reference numerical solutions (Haverkamp 1977, van Dam 2000, Vanderborght 2005). The maximum infiltration by the surface, Imax, is in general dependent on atmospheric conditions, surface type, soil type, soil moisture content θ, and surface orographic factor σ. The models used differ in their approach to

Heavy rainfall equations for Santa Catarina, Brazil

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Álvaro José Back

2011-12-01

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

An Establishment of Rainfall-induced Soil Erosion Index for the Slope Land in Watershed

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Tsai, Kuang-Jung; Chen, Yie-Ruey; Hsieh, Shun-Chieh; Shu, Chia-Chun; Chen, Ying-Hui

2014-05-01

With more and more concentrated extreme rainfall events as a result of climate change, in Taiwan, mass cover soil erosion occurred frequently and led to sediment related disasters in high intensity precipiton region during typhoons or torrential rain storms. These disasters cause a severely lost to the property, public construction and even the casualty of the resident in the affected areas. Therefore, we collected soil losses by using field investigation data from the upstream of watershed where near speific rivers to explore the soil erosion caused by heavy rainfall under different natural environment. Soil losses induced by rainfall and runoff were obtained from the long-term soil depth measurement of erosion plots, which were established in the field, used to estimate the total volume of soil erosion. Furthermore, the soil erosion index was obtained by referring to natural environment of erosion test plots and the Universal Soil Loss Equation (USLE). All data collected from field were used to compare with the one obtained from laboratory test recommended by the Technical Regulation for Soil and Water Conservation in Taiwan. With MATLAB as a modeling platform, evaluation model for soil erodibility factors was obtained by golden section search method, considering factors contributing to the soil erosion; such as degree of slope, soil texture, slope aspect, the distance far away from water system, topography elevation, and normalized difference vegetation index (NDVI). The distribution map of soil erosion index was developed by this project and used to estimate the rainfall-induced soil losses from erosion plots have been established in the study area since 2008. All results indicated that soil erodibility increases with accumulated rainfall amount regardless of soil characteristics measured in the field. Under the same accumulated rainfall amount, the volume of soil erosion also increases with the degree of slope and soil permeability, but decreases with the

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

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

2017-12-01

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

Temporal characteristics of rainfall events under three climate types in Slovenia

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Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

2016-10-01

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

Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

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Ceschia, M.; Micheletti, St.; Carniel, R.

1991-12-01

The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.

Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

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Muhammed, B. U.; Kaduk, J.; Balzter, H.

2012-12-01

In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

Chase the direct impact of rainfall into groundwater in Mt. Fuji from multiple analyses including microbial DNA

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Kato, Kenji; Sugiyama, Ayumi; Nagaosa, Kazuyo; Tsujimura, Maki

2016-04-01

A huge amount of groundwater is stored in subsurface environment of Mt. Fuji, the largest volcanic mountain in Japan. Based on the concept of piston flow transport of groundwater an apparent residence time was estimated to ca. 30 years by 36Cl/Cl ratio (Tosaki et al., 2011). However, this number represents an averaged value of the residence time of groundwater which had been mixed before it flushes out. We chased signatures of direct impact of rainfall into groundwater to elucidate the routes of groundwater, employing three different tracers; stable isotopic analysis (delta 18O), chemical analysis (concentration of silica) and microbial DNA analysis. Though chemical analysis of groundwater shows an averaged value of the examined water which was blended by various water with different sources and routes in subsurface environment, microbial DNA analysis may suggest the place where they originated, which may give information of the source and transport routes of the water examined. Throughout the in situ observation of four rainfall events showed that stable oxygen isotopic ratio of spring water and shallow groundwater obtained from 726m a.s.l. where the average recharge height of rainfall was between 1500 and 1800 m became higher than the values before a torrential rainfall, and the concentration of silica decreased after this event when rainfall exceeded 300 mm in precipitation of an event. In addition, the density of Prokaryotes in spring water apparently increased. Those changes did not appear when rainfall did not exceed 100 mm per event. Thus, findings shown above indicated a direct impact of rainfall into shallow groundwater, which appeared within a few weeks of torrential rainfall in the studied geological setting. In addition, increase in the density of Archaea observed at deep groundwater after the torrential rainfall suggested an enlargement of the strength of piston flow transport through the penetration of rainfall into deep groundwater. This finding was

How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

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Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

2017-04-01

Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in

Predicting of soil erosion with regarding to rainfall erosivity and soil erodibility

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Suif, Zuliziana; Razak, Mohd Amirun Anis Ab; Ahmad, Nordila

2018-02-01

The soil along the hill and slope are wearing away due to erosion and it can take place due to occurrence of weak and heavy rainfall. The aim of this study is to predict the soil erosion degree in Universiti Pertahanan Nasional Malaysia (UPNM) area focused on two major factor which is soil erodibility and rainfall erosivity. Soil erodibility is the possibilities of soil to detach and carried away during rainfall and runoff. The "ROM" scale was used in this study to determine the degree of soil erodibility, namely low, moderate, high, and very high. As for rainfall erosivity, the erosive power caused by rainfall that cause soil loss. A daily rainfall data collected from January to April was analyzed by using ROSE index classification to identify the potential risk of soil erosion. The result shows that the soil erodibilty are moderate at MTD`s hill, high at behind of block Lestari and Landslide MTD hill, and critical at behind the mess cadet. While, the highest rainfall erosivity was recorded in March and April. Overall, this study would benefit the organization greatly in saving cost in landslide protection as relevant authorities can take early measures repairing the most affected area of soil erosion.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

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Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

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Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

OpenAIRE

Pascale, Salvatore; Lucarini, Valerio; Feng, Xue; Porporato, Amilcare; ul Hasson, Shabeh

2016-01-01

In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to qu...

Analysis of Spatiotemporal Statistical Properties of Rainfall in the Phoenix Metropolitan Area

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Mascaro, G.

2016-12-01

The analysis of the rainfall statistical properties at multiple spatiotemporal scales is a necessary preliminary step to support modeling of urban hydrology, including flood prediction and simulation of impacts of land use changes. In this contribution, the rainfall statistical properties are analyzed in the Phoenix Metropolitan area and its surroundings ( 29600 km2) in Arizona using observations from 310 gauges of the Flood Control District of the Maricopa County network. Different techniques are applied to investigate the rainfall properties at temporal scales from 1 min to years and to quantify the associated spatial variability. Results reveal the following. The rainfall regime is characterized by high interannual variability, which is partially explained by teleconnections with El Niño Southern Oscillation, and marked seasonality, with two maxima in the monsoon season from July to September and in winter from November to March. Elevation has a significant control on seasonal rainfall accumulation, strength of thermal convective activity during the monsoon, and peak occurrence of the rainfall diurnal cycle present in summer. The spatial correlation of wintertime rainfall is high even at short aggregation times (cells).

Accuracy of rainfall measurement for scales of hydrological interest

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S. J. Wood

2000-01-01

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

Prediction of Rainfall-Induced Landslides

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Nadim, F.; Sandersen, F.

2009-12-01

Rainfall-induced landslides can be triggered by two main mechanisms: shear failure due to build-up of pore water pressure and erosion by surface water runoff when flow velocity exceeds a critical value. Field measurements indicate that, in the initial phase, the slip surface of a landslide often occurs along the top of a relatively impermeable layer located at some depth within the soil profile, e.g. at the contact with a shallow underlying bedrock or parent rock. The shear strength along this surface and hence the stability of the slope is governed by the pore water pressure. The pore pressure is in turn controlled by water seepage through the slope, either from infiltrated rain, or from groundwater that follows bedrock joints and soil layers with high permeability. When the infiltration rate of the underlying layer is too low for further downward penetration of water or when a wetting front is produced, pore water pressure builds up, reducing the soil shear strength. During high intensity rainfall, surface water runoff will exert shear stresses on the bed material. De-pending on the grain size distribution and specific gravity of the material, erosion might occur when the flow velocity exceeds a critical value. As erosion progresses and sediment concentration increases, the flow regime may become unstable with heavy erosion at high flow velocity locations triggering a debris flow. In many cases, previous landslides along steep gully walls have fed an abundance of loose soil material into the gullies. Landslides along gully walls that obstruct the water transport may also trigger debris flows when the landslide-dam collapses, creating a surge downstream. Both the long-duration (1 or more days) and short-duration precipitation (of the order of 1 hour) are significant in the triggering of shallow landslides, since the critical short-duration rainfall intensity reduces as the antecedent accumulated rainfall increases. Experiences in Norway indicate that the maxi

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

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Birkett, Patricia J; Vanak, Abi T; Muggeo, Vito M R; Ferreira, Salamon M; Slotow, Rob

2012-01-01

The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

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Patricia J Birkett

Full Text Available BACKGROUND: The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana, in relation to local and regional rainfall patterns. METHODOLOGY/PRINCIPAL FINDINGS: We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009. Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. CONCLUSIONS/SIGNIFICANCE: By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or

Hydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin

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Ansoumana Bodian

2016-04-01

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

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

Science.gov (United States)

Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

Science.gov (United States)

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

2017-11-01

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

Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

KAUST Repository

Viswanadhapalli, Yesubabu

2015-08-20

The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

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

Directory of Open Access Journals (Sweden)

Muhammad Suradi

2014-04-01

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

Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria

Science.gov (United States)

O, Sungmin; Foelsche, U.; Kirchengast, G.; Fuchsberger, J.

2018-01-01

Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters - a cluster consists of one national weather station and its four closest WegenerNet stations - allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient (r) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d-1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal (www.wegenernet.org).

Critical Phenomena of Rainfall in Ecuador

Science.gov (United States)

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

2014-02-01

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

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

OpenAIRE

Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

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

Science.gov (United States)

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

2015-10-01

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

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

Science.gov (United States)

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

2013-04-01

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

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

The rainfall plot: its motivation, characteristics and pitfalls.

Science.gov (United States)

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

2017-05-18

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

Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

Science.gov (United States)

Lashkari, A.; Salehnia, N.; Asadi, S.; Paymard, P.; Zare, H.; Bannayan, M.

2018-05-01

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed Information using Artificial Neural Networks), TRMM (Tropical Rainfall Measuring Mission), and AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) precipitation products to apply as input data for CSM-CERES-Wheat crop growth simulation model to predict rainfed wheat yield. Daily precipitation output from various sources for 7 years (2000-2007) was obtained and compared with corresponding ground-observed precipitation data for 16 ground stations across the northeast of Iran. Comparisons of ground-observed daily precipitation with corresponding data recorded by different sources of datasets showed a root mean square error (RMSE) of less than 3.5 for all data. AgMERRA and APHRODITE showed the highest correlation (0.68 and 0.87) and index of agreement (d) values (0.79 and 0.89) with ground-observed data. When daily precipitation data were aggregated over periods of 10 days, the RMSE values, r, and d values increased (30, 0.8, and 0.7) for AgMERRA, APHRODITE, PERSIANN, and TRMM precipitation data sources. The simulations of rainfed wheat leaf area index (LAI) and dry matter using various precipitation data, coupled with solar radiation and temperature data from observed ones, illustrated typical LAI and dry matter shape across all stations. The average values of LAImax were 0.78, 0.77, 0.74, 0.70, and 0.69 using PERSIANN, AgMERRA, ground-observed precipitation data, APHRODITE, and TRMM. Rainfed wheat grain yield simulated by using AgMERRA and APHRODITE daily precipitation data was highly correlated (r 2 ≥ 70) with those simulated using observed precipitation data. Therefore, gridded data have high potential to be used to supply lack of data and

Based on the rainfall system platform raindrops research and analysis of pressure loss

Science.gov (United States)

Cao, Gang; Sun, Jian

2018-01-01

With the rapid development of China’s military career, land, sea and air force all services and equipment of modern equipment need to be in the rain test, and verify its might suffer during transportation, storage or use a different environment temperature lower water or use underwater, the water is derived from the heavy rain, the wind and rain, sprinkler system, splash water, water wheel, a violent shock waves or use underwater, etcTest the product performance and quality, under the condition of rainfall system platform in the process of development, how to control the raindrops pressure loss becomes the key to whether the system can simulate the real rainfall [1], this paper is according to the rainfall intensity, nozzle flow resistance, meet water flow of rain pressure loss calculation and analysis, and system arrangement of the optimal solution of rainfall is obtained [2].

Solar Variability Controls on Rainfall in the Last Millennia: Evidence from a Highly Resolved Stalagmite Record from DeSoto Caverns (USA)

Science.gov (United States)

Aharon, P.; Lambert, W.; Hellstrom, J.

2009-12-01

Moisture transport from the Gulf of Mexico (GOM) inland has a considerable influence on both regional and continental rainfall patterns. Recent episodes of drought in the Southeastern USA exposed the vulnerability of the regional infrastructure to climate changes and gave rise to inter-state “water wars”. In order to better understand the cause of these periodic droughts and their controlling climate factors we have initiated a study of stalagmites from the DeSoto Caverns (Alabama, USA) that intersect the moisture flow from GOM. Combination of unusually high growth rates (up to 2 mm/decade), prominent dark and light seasonal layers, pristine aragonite mineralogy, precise U/Th dates acquired from mg-size samples and tight sampling (n=195) afforded generation of biannual (δ18O and δ13C of exceptional clarity spanning the last 700 yrs. The stalagmite (DSSG1) top yields isotope values (δ18O=-5.5 per-mill VPDB; δ13C=-10.1 per-mill VPDB) that are in good agreement with the predicted equilibrium isotope values. The oxygen and carbon isotope records exhibit a number of alternating negative and positive phase changes of correspond exactly with the Sun quiescence periods known as Dalton, Maunder, Spörer and Wolf Minima, and are corroborated by agreement with the positive shifts in atmospheric radiocarbon levels. Using a forward model we interpret the positive and negative δ18O and δ13C shifts during solar maxima and minima, respectively, as being primarily an expression of rapid shifts in rainfall sourced from GOM moisture and alternating between low and high rainfall intervals. The low and high rainfall intervals discerned in the stalagmite correspond to contemporaneous SST rise and fall in GOM and the Caribbean of about 1 oC amplitude. We suggest that small but measurable SST changes in the Western Hemisphere Warm Pool (WHWP), controlled by solar radiation changes between maxima and minima cycles, have a pronounced effect on the continental rainfall pattern. The

Propagation of radar rainfall uncertainty in urban flood simulations

Science.gov (United States)

Liguori, Sara; Rico-Ramirez, Miguel

2013-04-01

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

Radar rainfall image repair techniques

Directory of Open Access Journals (Sweden)

Stephen M. Wesson

2004-01-01

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

Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

Science.gov (United States)

Chang, P.; Saravanan, R.; Giannini, A.

2003-04-01

The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

Science.gov (United States)

Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

2018-04-01

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set

Rainfall characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

Science.gov (United States)

Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

2018-02-01

The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

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

Science.gov (United States)

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

2017-11-01

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

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

Science.gov (United States)

Zorzetto, E.; Marani, M.

2017-12-01

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

Rainfall erosivity map for Ghana

International Nuclear Information System (INIS)

Oduro Afriyie, K.

1995-10-01

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

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

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

2014-05-01

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

What rainfall events trigger landslides on the West Coast US?

Science.gov (United States)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

2016-04-01

A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

Prevention through policy : Urban macroplastic leakages to the marine environment during extreme rainfall events

NARCIS (Netherlands)

Axelsson, Charles; van Sebille, Erik

2017-01-01

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic

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

Science.gov (United States)

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

2017-04-01

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

Spatial dependence of extreme rainfall

Science.gov (United States)

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

2017-05-01

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

The modification of the typhoon rainfall climatology model in Taiwan

Directory of Open Access Journals (Sweden)

C.-S. Lee

2013-01-01

Full Text Available This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999. Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12 and northward-moving (N-TRCM12 typhoons is superior to that obtained using the original climatological model (TRCM06. Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12 for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

Periods of high intensity rainfall and the safety of the Angra dos Reis nuclear power plant

International Nuclear Information System (INIS)

Nicolli, D.

1993-01-01

The high precipitation rates aggravate the consequences of hypothetical accidental releases of radioactive material from the Angra dos Reis Nuclear Power Plant (NPP), as determined by probabilistic risk assessment. A 30-year rainfall series was analysed, aiming at calculating the probability of occurring a given amount q of precipitation during a certain period of n days. The nine highest precipitation amounts have also been determined. The results show there was a rainier climate in the '50 s and '60 s than in the '70 s and '80 s. The risk of catastrophic landslide has been enhanced as an environmental impact of the construction of the Rio-Santos highway and NPP which have not yet gone through an abnormal rainfall period. It has been suggested that criteria should be established to reduce the nuclear power and shut down the reactor when the precipitation accumulates to a dangerous limit. (author)

RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

Directory of Open Access Journals (Sweden)

Celso A. G. Santos

2016-01-01

Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

Quantifying rainfall-runoff relationships on the Mieso Hypo Calcic ...

African Journals Online (AJOL)

The mean annual rainfall at Mieso is 738 mm. The soil is a Hypo Calcic Vertisol with a high clay and silt content and is very susceptible to crusting. To achieve the objective of the study, rainfall-runoff measurements were made during 2003 and 2004 on 2 m x 2 m plots provided with a runoff measuring system, and replicated ...

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

Science.gov (United States)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Ecosystem and Community Responses to Rainfall Manipulations in Shrublands Depends on Dominant Vegetation Cover

Science.gov (United States)

Esch, E. H.; Lipson, D.; Kim, J. B.; Cleland, E. E.

2014-12-01

Southern California is predicted to face decreasing precipitation with increased interannual variability in the coming century. Native shrublands in this area are increasingly invaded by exotic annual grasses, though invasion dynamics can vary by rainfall scenario, with wet years generally associated with high invasion pressure. Interplay between rainfall and invasion scenarios can influence carbon stocks and community composition. Here we asked how invasion alters ecosystem and community responses in drought versus high rainfall scenarios, as quantified by community identity, biomass production, and the normalized difference vegetation index (NDVI). To do this, we performed a rainfall manipulation experiment with paired plots dominated either by native shrubs or exotic herbaceous species, subjected to treatments of 50%, 100%, or 150% of ambient rainfall. The study site was located in a coastal sage scrub ecosystem, with patches dominated by native shrubs and exotic grasses located in San Diego County, USA. During two growing seasons, we found that native, herbaceous biomass production was significantly affected by rainfall treatment (p<0.05 for both years), though was not affected by dominant community composition. Photosynthetic biomass production of shrub species also varied by treatment (p=0.035). Exotic biomass production showed a significant interaction between dominant community composition and rainfall treatment, and both individual effects (p<0.001 for all). NDVI showed similar results, but also indicated the importance of rainfall timing on overall biomass production between years. Community composition data showed certain species, of both native and exotic identities, segregating by treatment. These results indicate that exotic species are more sensitive to rainfall, and that increased rainfall may promote greater carbon storage in annual dominated communities when compared to shrub dominated communities in high rainfall years, but with drought, this

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Directory of Open Access Journals (Sweden)

Ben Jarihani

2017-07-01

Full Text Available Rainfall is the main driver of hydrological processes in dryland environments and characterising the rainfall variability and processes of runoff generation are critical for understanding ecosystem function of catchments. Using remote sensing and in situ data sets, we assess the spatial and temporal variability of the rainfall, rainfall–runoff response, and effects on runoff coefficients of antecedent soil moisture and ground cover at different spatial scales. This analysis was undertaken in the Upper Burdekin catchment, northeast Australia, which is a major contributor of sediment and nutrients to the Great Barrier Reef. The high temporal and spatial variability of rainfall are found to exert significant controls on runoff generation processes. Rainfall amount and intensity are the primary runoff controls, and runoff coefficients for wet antecedent conditions were higher than for dry conditions. The majority of runoff occurred via surface runoff generation mechanisms, with subsurface runoff likely contributing little runoff due to the intense nature of rainfall events. MODIS monthly ground cover data showed better results in distinguishing effects of ground cover on runoff that Landsat-derived seasonal ground cover data. We conclude that in the range of moderate to large catchments (193–36,260 km2 runoff generation processes are sensitive to both antecedent soil moisture and ground cover. A higher runoff–ground cover correlation in drier months with sparse ground cover highlighted the critical role of cover at the onset of the wet season (driest period and how runoff generation is more sensitive to cover in drier months than in wetter months. The monthly water balance analysis indicates that runoff generation in wetter months (January and February is partially influenced by saturation overland flow, most likely confined to saturated soils in riparian corridors, swales, and areas of shallow soil. By March and continuing through October

Rainfall spatiotemporal variability relation to wetlands hydroperiods

Science.gov (United States)

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

2017-04-01

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

Measuring urban rainfall using microwave links from commercial cellular communication networks

NARCIS (Netherlands)

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

2011-01-01

The estimation of rainfall using commercial microwave links is a new and promising measurement technique. Commercial link networks cover large parts of the land surface of the earth and have a high density, particularly in urban areas. Rainfall attenuates the electromagnetic signals transmitted

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

Science.gov (United States)

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

2017-04-01

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

Mapping monthly rainfall erosivity in Europe.

Science.gov (United States)

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

2017-02-01

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

Persistence Characteristics of Australian Rainfall Anomalies

Science.gov (United States)

Simmonds, Ian; Hope, Pandora

1997-05-01

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

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

Science.gov (United States)

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

2013-04-01

performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)

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

Science.gov (United States)

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

2001-01-01

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

Rainfall Climatology over Asir Region, Saudi Arabia

Science.gov (United States)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Simulation of Tropical Rainfall Variability

Science.gov (United States)

Bader, J.; Latif, M.

2002-12-01

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

Karst Aquifer in Qatar and its bearing on Natural Rainfall Recharge

Science.gov (United States)

Baalousha, Husam; Ackerer, Philippe

2017-04-01

Qatar is an arid country with little rainfall and high evaporation. Surface water is non-existent so aquifer is the only source of natural water. The annual long-term averages of rainfall and evaporation are 80 mm and more than 2000 mm, respectively. Despite the low rainfall and high evaporation, natural recharge from rainfall occurs at an average of approximately 50 million m3 per year. Rainfall recharge in Qatar takes in land depressions that occur all over the country. These depressions are a result of land collapse due to sinkholes and cavity in the limestone formation. In the northern part of the country, karst features occur as a result of dissolution of limestone, which leads to land depressions. Results of this study shows groundwater recharge occurs in land depression areas, especially in the northern part of the country, where surface runoff accumulates in these land depressions and recharges the aquifer. This paper was made possible by NPRP grant # [NPRP 9-030-1-008] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the author[s]."

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

Science.gov (United States)

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

2017-08-01

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

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

Science.gov (United States)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

Conditions for the Occurrence of Slaking and Other Disaggregation Processes under Rainfall

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Frédéric Darboux

2016-07-01

Full Text Available Under rainfall conditions, aggregates may suffer breakdown by different mechanisms. Slaking is a very efficient breakdown mechanism. However, its occurrence under rainfall conditions has not been demonstrated. Therefore, the aim of this study was to evaluate the occurrence of slaking under rain. Two soils with silt loam (SL and clay loam (CL textures were analyzed. Two classes of aggregates were utilized: 1–3 mm and 3–5 mm. The aggregates were submitted to stability tests and to high intensity (90 mm·h−1 and low intensity (28 mm·h−1 rainfalls, and different kinetic energy impacts (large and small raindrops using a rainfall simulator. The fragment size distributions were determined both after the stability tests and rainfall simulations, with the calculation of the mean weighted diameter (MWD. After the stability tests the SL presented smaller MWDs for all stability tests when compared to the CL. In both soils the lowest MWD was obtained using the fast wetting test, showing they were sensitive to slaking. For both soils and the two aggregate classes evaluated, the MWDs were recorded from the early beginning of the rainfall event under the four rainfall conditions. The occurrence of slaking in the evaluated soils was not verified under the simulated rainfall conditions studied. The early disaggregation was strongly related to the cumulative kinetic energy, advocating for the occurrence of mechanical breakdown. Because slaking requires a very high wetting rate on initially dry aggregates, it seems unlikely to occur under field conditions, except perhaps for furrow irrigation.

Parametric study on the effect of rainfall pattern to slope stability

Directory of Open Access Journals (Sweden)

Hakim Sagitaningrum Fathiyah

2017-01-01

Full Text Available Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also observed. The analyses were conducted with SEEP/W for the seepage and SLOPE/W for the slope stability. It is found that the lowest FS for gentle slope is reached under the application of advanced rainfall pattern and the lowest FS for steep slope is reached under the application of delayed rainfall pattern. Reduction of FS is known to be the largest for gentle slope rather than steep slope due to negative pore water pressure reduction and the rising of ground water level. The largest FS reduction caused by rainfall was achieved for gentle slope under advanced rainfall pattern.

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

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Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

A rainfall-based mechanism to regulate the release of water from Ranger uranium mine

International Nuclear Information System (INIS)

Carter, M.W.

1989-01-01

The far north of Australia (the Top End) has a monsoon-like climate. This wet-dry climate presents problems in water management for mining operations. These problems are exacerbated for the Ranger uranium mine at Jabiru due to the need to protect the environment of the surrounding Kakadu National Park, particularly the major wetland system downstream of the Ranger mine. An analysis of rainfall records for the wet-dry tropics of the far north of Australia is presented. A probability curve of the ratio between rainfall at a given date and rainfall at the year end, has been produced from actual data and can be used with a normalized curve to set levels of confidence of predicted rainfall being exceeded. The results of this analysis are used to develop a regulatory mechanism to limit release of waste water from a uranium mine to particularly wet years in accordance with the Australian Government's environmental protection policy. 19 refs., 11 tabs., 17 figs

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh; Chowdary, Jasti S.; Srinivas, G; Gnanaseelan, C; Parekh, Anant; Attada, Raju; Rama Krishna, S S V S

2018-01-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

Science.gov (United States)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh

2018-05-22

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Study of acid mine drainage management with evaluating climate and rainfall in East Pit 3 West Banko coal mine

Science.gov (United States)

Rochyani, Neny

2017-11-01

Acid mine drainage is a major problem for the mining environment. The main factor that formed acid mine drainage is the volume of rainfall. Therefore, it is important to know clearly the main climate pattern of rainfall and season on the management of acid mine drainage. This study focuses on the effects of rainfall on acid mine water management. Based on daily rainfall data, monthly and seasonal patterns by using Gumbel approach is known the amount of rainfall that occurred in East Pit 3 West Banko area. The data also obtained the highest maximum daily rainfall on 165 mm/day and the lowest at 76.4 mm/day, where it is known that the rainfall conditions during the period 2007 - 2016 is from November to April so the use of lime is also slightly, While the low rainfall is from May to October and the use of lime will be more and more. Based on calculation of lime requirement for each return period, it can be seen the total of lime and financial requirement for treatment of each return period.

Predicting watershed acidification under alternate rainfall conditions

International Nuclear Information System (INIS)

Huntington, T.G.

1996-01-01

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

Spatio-temporal trends of rainfall across Indian river basins

Science.gov (United States)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

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

Science.gov (United States)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

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

Landscape sensitivity in a dynamic environment

Science.gov (United States)

Lin, Jiun-Chuan; Jen, Chia-Horn

2010-05-01

Landscape sensitivity at different scales and topics is presented in this study. Methodological approach composed most of this paper. According to the environmental records in the south eastern Asia, the environment change is highly related with five factors, such as scale of influence area, background of environment characters, magnitude and frequency of events, thresholds of occurring hazards and influence by time factor. This paper tries to demonstrate above five points from historical and present data. It is found that landscape sensitivity is highly related to the degree of vulnerability of the land and the processes which put on the ground including human activities. The scale of sensitivity and evaluation of sensitivities is demonstrated in this paper by the data around east Asia. The methods of classification are mainly from the analysis of environmental data and the records of hazards. From the trend of rainfall records, rainfall intensity and change of temperature, the magnitude and frequency of earthquake, dust storm, days of draught, number of hazards, there are many coincidence on these factors with landscape sensitivities. In conclusion, the landscape sensitivities could be classified as four groups: physical stable, physical unstable, unstable, extremely unstable. This paper explain the difference.

Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

Science.gov (United States)

Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

2013-04-01

Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

Comparison and Evolution of Extreme Rainfall-Induced Landslides in Taiwan

Directory of Open Access Journals (Sweden)

Chunhung WU

2017-11-01

Full Text Available This study analyzed the characteristics of, and locations prone to, extreme rainfall-induced landslides in three watersheds in Taiwan, as well as the long-term evolution of landslides in the Laonong River watershed (LRW, based on multiannual landslide inventories during 2003–2014. Extreme rainfall-induced landslides were centralized beside sinuous or meandering reaches, especially those with large sediment deposition. Landslide-prone strata during extreme rainfall events were sandstone and siltstone. Large-scale landslides were likely to occur when the maximum 6-h accumulated rainfall exceeded 420 mm. All of the large-scale landslides induced by short-duration and high-intensity rainfall developed from historical small-scale landslides beside the sinuous or meandering reaches or in the source area of rivers. However, most of the large-scale landslides induced by long-duration and high-intensity rainfall were new but were still located beside sinuous or meandering reaches or near the source. The frequency density of landslides under long-duration and high-intensity rainfall was larger by one order than those under short-duration rainfall, and the β values in the landslide frequency density-area analysis ranged from 1.22 to 1.348. The number of downslope landslides was three times larger than those of midslope and upslope landslides. The extreme rainfall-induced landslides occurred in the erosion gullies upstream of the watersheds, whereas those beside rivers were downstream. Analysis of the long-term evolution of landslides in the LRW showed that the geological setting, sinuousness of reaches, and sediment yield volume determined their location and evolution. Small-scale landslides constituted 71.9–96.2% of the total cases from 2003 to 2014, and were more easily induced after Typhoon Morakot (2009. The frequency density of landslides after Morakot was greater by one order than before, with 61% to 68% of total landslides located in the

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

Science.gov (United States)

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

2015-05-01

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

Rainfall interception by two arboreal species in urban green area

Directory of Open Access Journals (Sweden)

Luzia Ferreira da Silva

2010-12-01

Full Text Available Rainfall interception by the two most usual species in forest urban spaces was analysed by measuring of interception (I or interception losses, through fall (Th, stem flow (St and gross precipitation (Pg. The chosen species were Caesalpinia pluviosa DC. (Fabaceae: Caesalpinoideae or sibipiruna, and Tipuana tipu O. Kuntze (Fabaceae: Faboideae or tipuana. The individuals analysed were more than 50 years old, with three separate individuals and three individuals in each studied group of species at the campus of ”Luiz de Queiroz” College of Agriculture (University of Sao Paulo, Piracicaba. The experiments were carried out from January to February 2007. Water was collected using seven-litre pails, in the edges and in the centre of the canopies. A high correlation of Th with Pg was observed on the centre of the crow of tipuana and by the edges of sibipiruna. St and I had low correlation with Pg for both species. The average of rain interception was greater in the edges of the crow of sibipiruna individuals, 60.6%, and in the centre of tipuana crow, 59.40%. Thus, both species intercepted up to 60% of the water rainfall, which indicates a great potential of both species for arborisation in urban environments.

An assessment of the performance of global rainfall estimates without ground-based observations

Directory of Open Access Journals (Sweden)

C. Massari

2017-09-01

Full Text Available Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS, showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth of the aforementioned products without using a ground benchmark data set. The analysis is carried out during the period 2007–2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern

Parametric study on the effect of rainfall pattern to slope stability

OpenAIRE

Hakim Sagitaningrum Fathiyah; Bahsan Erly

2017-01-01

Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS) of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also obser...

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

Science.gov (United States)

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

2017-04-01

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

Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

Science.gov (United States)

Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

2010-05-01

rainfall amount were analysed for each rainfall sub-region and weather type from 1961-2007 (Ferranti et al., 2010). The conditional analysis showed total rainfall under SW and W weather types to be increasing, with the greatest increases observed in the upland sub-regions. The increase in total SW rainfall is driven by a greater occurrence of SW rain days, and there has been little change to the average wet-day rainfall amount. The increase in total W rainfall is driven in part by an increase in the frequency of wet-days, but more significantly by an increase in the average wet-day rainfall amount. In contrast, total rainfall under C weather types has decreased. Further analysis will investigate how spring, summer and autumn rainfall climatologies have changed for the different weather types and sub-regions. Conditional analysis that combines GIS and synoptic climatology provides greater insights into the processes underlying readily available meteorological data. Dissecting Cumbrian rainfall data under different synoptic and geographic conditions showed the observed changes in winter rainfall are not uniform for the different weather types, nor for the different geographic sub-regions. These intricate details are often lost during coarser resolution analysis, and conditional analysis will provide a detailed synopsis of Cumbrian rainfall processes against which Regional Climate Model (RCM) performance can be tested. Conventionally RCMs try to simulate composite rainfall over many different weather types and sub-regions and by undertaking conditional validation the model performance for individual processes can be tested. This will help to target improvements in model performance, and ultimately lead to better simulation of rainfall in areas of complex topography. BURT, T. P. & FERRANTI, E. J. S. (2010) Changing patterns of heavy rainfall in upland areas: a case study from northern England. Atmospheric Environment, [in review]. FERRANTI, E. J. S., WHYATT, J. D. & TIMMIS, R

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

Directory of Open Access Journals (Sweden)

N. Q. Hung

2009-08-01

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

Entropy of stable seasonal rainfall distribution in Kelantan

Science.gov (United States)

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

2017-05-01

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

Stochastic modelling of daily rainfall sequences

NARCIS (Netherlands)

Buishand, T.A.

1977-01-01

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

Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

Directory of Open Access Journals (Sweden)

Natalie Melissa McLean

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Nana Zhao

2014-09-01

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

Rainfall Stochastic models

Science.gov (United States)

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

2012-04-01

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

Improved rainfall-runoff approach using lumped and conceptual modelling

OpenAIRE

Durán Barroso, Pablo

2016-01-01

Rainfall-runoff quantification is one of the most important tasks in both engineering and watershed management as it allows to identify, forecast and explain watershed response. The division of the rainfall depth between infiltration and runoff has a high level of complexity due to the spatial heterogeneity in real catchments and the temporal precipitation variability, which provide scale effects on the overall runoff volumes. The Natural Resources Conservation Service Curve Number (NRCS CN) ...

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

Science.gov (United States)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

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

Science.gov (United States)

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

2014-05-01

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

ICUD-0471 Weather radar rainfall for design of urban storm water systems

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Wright, D. B.; Nielsen, Jesper Ellerbæk

2017-01-01

Long continuous series of high-resolution radar rainfall series provides valuable information on spatial and temporal variability of rainfall, which can be used in design of urban drainage systems. In design of especially large drainage systems with complex flow patterns (and potentially surface ...

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

Directory of Open Access Journals (Sweden)

Bolívar Erazo

2018-02-01

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

Rainfall: Features and Variations over Saudi Arabia, A Review

Directory of Open Access Journals (Sweden)

Hosny Hasanean

2015-08-01

rainfall will remain the lowest.The climate in the SA is instructed by the El Niño Southern Oscillation (ENSO and other circulations such as centers of high and low pressure, the North Atlantic Oscillation (NAO and SOI. Strength and oscillation of subtropical jet stream play a big role in pulling hot, dry air masses of SA.

Long term variations of extreme rainfall in Denmark and southern Sweden

DEFF Research Database (Denmark)

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

2015-01-01

A high number of studies have detected changes in the observed heavy rainfall in Northern and Central Europe, all adding to the debate on anthropogenic climate change and its potential impact on rainfall extremes. However, it is equally relevant to understand natural variations on which...... the anthropogenic changes are imposed. This study identifies multi-decadal variations in daily rainfall extremes from Denmark and southern Sweden, with a recurrence level relevant for flood hazard analysis. Based on smoothed series it is concluded that the frequency of the extreme events shows both a general...

Conditional probability of intense rainfall producing high ground concentrations from radioactive plumes

International Nuclear Information System (INIS)

Wayland, J.R.

1977-03-01

The overlap of the expanding plume of radioactive material from a hypothetical nuclear accident with rainstorms over dense population areas is considered. The conditional probability of the occurrence of hot spots from intense cellular rainfall is presented

Multisite rainfall downscaling and disaggregation in a tropical urban area

Science.gov (United States)

Lu, Y.; Qin, X. S.

2014-02-01

A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

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

Science.gov (United States)

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

2016-04-01

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

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

Science.gov (United States)

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

2014-05-01

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

Flooding from Intense Rainfall: an overview of project SINATRA

Science.gov (United States)

Cloke, Hannah

2014-05-01

Project SINATRA (Susceptibility of catchments to INTense RAinfall and flooding) is part of the UK NERC's Flooding From Intense Rainfall (FFIR) research programme which aims to reduce the risks of damage and loss of life caused by surface water and flash floods through improved identification, characterisation and prediction of interacting meteorological, hydrological and hydro-morphological processes that contribute to flooding associated with high-intensity rainfall events. Extreme rainfall events may only last for a few hours at most, but can generate terrifying and destructive floods. Their impact can be affected by a wide range factors (or processes) such as the location and intensity of the rainfall, the shape and steepness of the catchment it falls on, how much sediment is moved by the water and the vulnerability of the communities in the flood's path. Furthermore, FFIR are by their nature rapid, making it very difficult for researchers to 'capture' measurements during events. The complexity, speed and lack of field measurements on FFIR make it difficult to create computer models to predict flooding and often we are uncertain as to their accuracy. In addition there is no consensus on how to identify how particular catchments may be vulnerable to FFIR, due to factors such as catchment area, shape, geology and soil type as well as land-use. Additionally, the catchments most susceptible to FFIR are often small and un-gauged. Project SINATRA will: (1) Increase our understanding of what factors cause FFIR and gathering new, high resolution measurements of FFIR by: assembling an archive of past FFIR events in Britain and their impacts, as a prerequisite for improving our ability to predict future occurrences of FFIR; making real time observations of flooding during flood events as well as post-event surveys and historical event reconstruction, using fieldwork and crowd-sourcing methods; and characterizing the physical drivers for UK summer flooding events by

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

Science.gov (United States)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

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

Science.gov (United States)

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

2017-12-01

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

Variability of rainfall over small areas

Science.gov (United States)

Runnels, R. C.

1983-01-01

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

Analysis of rainfall infiltration law in unsaturated soil slope.

Science.gov (United States)

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

2014-01-01

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

Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Sørup, Hjalte Jomo Danielsen; Madsen, Henrik

2013-01-01

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type...... in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated...... from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases...

Probabilistic clustering of rainfall condition for landslide triggering

Science.gov (United States)

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

2013-04-01

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

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

NARCIS (Netherlands)

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

2006-01-01

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

Hydrology in a mediterranean mountain environment. The Vallcebre research catchment (north eastern Spain) II. Rainfall-runoff relationships and runoff processes

International Nuclear Information System (INIS)

Latron, J.; Solar, M.; Nord, G.; Llorens, P.; Gallart, F.

2009-01-01

Hydrological response and runoff processes have been studied in the Vallcebre research basins (North Eastern Spain) for almost 20 years. Results obtained allowed to build a more complete perceptual model of the hydrological functioning of Mediterranean mountains basins. On a seasonal and monthly scale, there was no simple relationship between rainfall and runoff depths. Monthly rainfall and runoff values revealed the existence of a threshold in the relationship between rainfall and runoff depths. At the event scale, the storm-flow coefficient had a clear seasonal pattern. The effect of the water table position on how rainfall and runoff volumes relate was observed. Examination of soil water potential and water table dynamics during representative floods helped to identify 3 types of characteristic hydrological behaviour during the year. Under dry conditions, runoff was generated essentially as infiltration excess runoff in low permeable areas, whereas saturation excess runoff dominated during wetting-up and wet conditions. During wetting-up transition, saturated areas resulted from the development of scattered perched water tables, whereas in wet conditions they were linked to the rise of the shallow water table. (Author) 8 refs.

Rainfall variability and floods occurrence in the city of Bamenda (Northwest of Cameroon

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Frederic Saha

2017-06-01

Full Text Available This study is based on analysis of rainfall data from 1951-2010 collected at the climatic station of Bamenda. We also use the results of a questionnaire survey applied to 172 households in at-risk neighborhoods. The inventory of some cases of flooding that occurred in the city of Bamenda was done through focus groups. The appreciation of the socio-economic and demographic environment is based on surveys among Cameroonian Households by the National Institute of Statistics (NIS and General Census of Population and Housing. Statistical examination revealed that annual rainfall in the city of Bamenda experienced a break in 1958. This break buckled the wettest decade of the series. After three decades of worsening, rainfall is experiencing rising since early 1990. The average profile of the annual distribution of rainfall shows a concentration of over 53% in 03 months (July, August and September. During these three months, the rivers of the city know their flood flows and populations in the valleys are affected. The analysis of the annual number of rainy days shows a downward trend and an increase of extreme rainfall event frequency (≥50mm in 24h. It is also apparent that more and more years are experiencing erratic distribution of their precipitation. Then, the perception of people is significantly reduced. Subsistence activities are also affected and development is facing new subtleties. In conclusion, the rainfall experienced strong variability in the city of Bamenda. This situation reinforces the risk of flooding by increasing flood water and increasing the vulnerability of populations.

Prediction of early summer rainfall over South China by a physical-empirical model

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2014-10-01

In early summer (May-June, MJ) the strongest rainfall belt of the northern hemisphere occurs over the East Asian (EA) subtropical front. During this period the South China (SC) rainfall reaches its annual peak and represents the maximum rainfall variability over EA. Hence we establish an SC rainfall index, which is the MJ mean precipitation averaged over 72 stations over SC (south of 28°N and east of 110°E) and represents superbly the leading empirical orthogonal function mode of MJ precipitation variability over EA. In order to predict SC rainfall, we established a physical-empirical model. Analysis of 34-year observations (1979-2012) reveals three physically consequential predictors. A plentiful SC rainfall is preceded in the previous winter by (a) a dipole sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (b) a tripolar SST tendency in North Atlantic Ocean, and (c) a warming tendency in northern Asia. These precursors foreshadow enhanced Philippine Sea subtropical High and Okhotsk High in early summer, which are controlling factors for enhanced subtropical frontal rainfall. The physical empirical model built on these predictors achieves a cross-validated forecast correlation skill of 0.75 for 1979-2012. Surprisingly, this skill is substantially higher than four-dynamical models' ensemble prediction for 1979-2010 period (0.15). The results here suggest that the low prediction skill of current dynamical models is largely due to models' deficiency and the dynamical prediction has large room to improve.

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

NARCIS (Netherlands)

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

2015-01-01

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

Extreme value analysis of rainfall data for Kalpakkam

International Nuclear Information System (INIS)

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

2016-01-01

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

Error threshold inference from Global Precipitation Measurement (GPM) satellite rainfall data and interpolated ground-based rainfall measurements in Metro Manila

Science.gov (United States)

Ampil, L. J. Y.; Yao, J. G.; Lagrosas, N.; Lorenzo, G. R. H.; Simpas, J.

2017-12-01

IMERG performs well for moderate to high intensity rainfall and that the interpolation remains effective only when rainfall exceeds a certain threshold value. Over Metro Manila, an F-RMSE threshold of 0.5 mm indicated better correspondence between ground measured and satellite measured rainfall.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

Directory of Open Access Journals (Sweden)

Haris Akram Bhatti

2016-06-01

Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

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K C Gouda

2017-10-01

Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

Science.gov (United States)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

Science.gov (United States)

Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

2016-09-01

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rain rate. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e., RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance but also for use in hydrological modeling. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.

Satellite-based estimation of rainfall erosivity for Africa

NARCIS (Netherlands)

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

2010-01-01

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

Temporal and spatial variability of rainfall distribution and ...

African Journals Online (AJOL)

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

Remote sensing entropy to assess the sustainability of rainfall in tropical catchment

Science.gov (United States)

Mahmud, M. R.; Reba, M. N. M.; Wei, J. S.; Razak, N. H. Abdul

2018-02-01

This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments. There were two major issues need to be anticipated in monitoring the tropical catchments; first is the frequent monitoring of the rainfall and second is the appropriate indicator that sensitive to rainfall pattern changes or disorder. For the first issue, the use of satellite remote sensing precipitation data is suggested. Meanwhile for the second issue, the utilization of entropy concept in interpreting the disorder of temporal rainfall can be used to assess the sustain ability had been successfully adopted in some studies. Therefore, we hypothesized that the use of satellite precipitation as main data to compute entropy can be a novel tool in anticipating the above-mentioned conflict earlier. The remote sensing entropy results and in-situ river level showed good agreement indicating its reliability. 72% of the catchment has moderate to good rainfall supply during normal or non-drought condition. However, our result showed that the catchments were highly sensitive to drought especially in the west coast and southern part of the Peninsular Malaysia. High resiliency was identified in the east coast. We summarized that the proposed entropy-quantity scheme was a useful tool for cost-effective, quick, and operational sustainability assessment This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments.

Tropical intraseasonal rainfall variability in the CFSR

Energy Technology Data Exchange (ETDEWEB)

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

2012-06-15

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

Assessing the water balance in the Sahel : Impact of small scale rainfall variability on runoff. Part 2 : Idealized modeling of runoff sensitivity

OpenAIRE

Vischel, Théo; Lebel, Thierry

2007-01-01

As in many other semi-arid regions in the world, the Sahelian hydrological environment is characterized by a mosaic of small endoreic catchments with dry soil surface conditions producing mostly Hortonian runoff. Using an SCS-type event based rainfall-runoff model, an idealized modeling experiment of a Sahelian environment is set up to study the sensitivity of runoff to small scale rainfall variability. A set of 548 observed rain events is used to force the hydrological model to study the sen...

Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

Directory of Open Access Journals (Sweden)

Basile Pauthier

2016-01-01

Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

Characteristics of Rainfall-Discharge and Water Quality at Limboto Lake, Gorontalo, Indonesia

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Luki Subehi

2016-08-01

Full Text Available Problems of high turbidity, sedimentation, water pollution and siltation occur at Limboto Lake, Gorontalo, Indonesia. The objective of this study was to analyze the rainfall-discharge relationship and its implications for water quality conditions. Secchi disk (water transparency, chlorophyll-a (chl-a, and total organic matter (TOM were measured in May 2012, September 2012 and March 2013 at three sites of the lake (L-1, L-2 and L-3 to observe the impacts on the surrounding catchment. Based on representative stations for rainfall data from 2004 to 2013, monthly averages of rainfall in March-May (166.7 mm and September (76.4 mm were used to represent the wet and dry period, respectively. Moreover, sediment traps at these three sites were installed in September 2012. Based on the analysis it is suggested that rainfall magnitude and land use change at the Alopohu River catchment influenced the amount of materials flowing into the lake, degrading the water quality. Specifically, the higher average rainfall in May (184.5 mm gave a higher average total sediment load (4.41 g/L/day. In addition, water transparency decreased with increasing chl-a. This indicates that the concentrations of sediment and nutrients, reflected by the high amount of chl-a, influenced the water quality conditions.

Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea

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Sara Pensieri

2015-01-01

Full Text Available Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.

THE VARIABILITY OF RAINFALL REGIME, INDUCED BY CLIMATE CHANGES, IN DOLJ COUNTY AND IT IMPACT ON THE ENVIRONMENT

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MIREA ADRIAN

2016-03-01

Full Text Available Climate change is now widely recognized as an actual fact: temperatures are rising, rainfall patterns are changing, glaciers and snow melts, and average global sea level rises. We expect these changes to continue and extreme weather conditions that lead to risks like floods and droughts to become more frequent and increase their intensity. Drought and phenomena associated with it, namely aridization (lowering excessive groundwater level and desertification (reduced area of ground covered by vegetation and a considerable depletion and soil erosion represents, after pollution, the second largest problem facing humanity, currently affecting all regions of the globe. In Dolj County, the area between Calafat-Poiana Mare-Sadova-Bechet- Dăbuleni and the Danube, covering about 104 600 hectares, represents the most typical aspect of semi-arid zone with accents of aridity and even desertification in Romania, the phenomenon being favored by the presence of sandy soils. In Dolj County, there may be seen an important manifestation of climate change on the rainfall regime: increasing linear trend especially in the northern part of the county compared to the extreme south of the country, where atmospheric circulation interaction with local relief conditions,often causes diminishing rainfall.

Evolution of rainfall in the Sahel

International Nuclear Information System (INIS)

Diallo, M.A.

1995-09-01

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

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

Science.gov (United States)

Lucero, Omar A.; Rozas, Daniel

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

Improving the extreme rainfall forecast of Typhoon Morakot (2009) by assimilating radar data from Taiwan Island and mainland China

Science.gov (United States)

Bao, Xuwei; Wu, Dan; Lei, Xiaotu; Ma, Leiming; Wang, Dongliang; Zhao, Kun; Jou, Ben Jong-Dao

2017-08-01

This study examined the impact of an improved initial field through assimilating ground-based radar data from mainland China and Taiwan Island to simulate the long-lasting and extreme rainfall caused by Morakot (2009). The vortex location and the subsequent track analyzed through the radial velocity data assimilation (VDA) are generally consistent with the best track. The initial humidity within the radar detecting region and Morakot's northward translation speed can be significantly improved by the radar reflectivity data assimilation (ZDA). As a result, the heavy rainfall on both sides of Taiwan Strait can be reproduced with the joint application of VDA and ZDA. Based on sensitivity experiments, it was found that, without ZDA, the simulated storm underwent an unrealistic inward contraction after 12-h integration, due to underestimation of humidity in the global reanalysis, leading to underestimation of rainfall amount and coverage. Without the vortex relocation via VDA, the moister (drier) initial field with (without) ZDA will produce a more southward (northward) track, so that the rainfall location on both sides of Taiwan Strait will be affected. It was further found that the improvement in the humidity field of Morakot is mainly due to assimilation of high-value reflectivity (strong convection) observed by the radars in Taiwan Island, especially at Kenting station. By analysis of parcel trajectories and calculation of water vapor flux divergence, it was also found that the improved typhoon circulation through assimilating radar data can draw more water vapor from the environment during the subsequent simulation, eventually contributing to the extreme rainfall on both sides of Taiwan Strait.

Determining rainfall thresholds that trigger landslides in Colombia

International Nuclear Information System (INIS)

Mayorga Marquez, Ruth

2003-01-01

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

The development rainfall forecasting using kalman filter

Science.gov (United States)

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

2018-04-01

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

Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

Science.gov (United States)

Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

2016-04-01

Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance

Analysis of rainfall-induced shallow landslides and debris flows in the Eastern Pyrenees

Science.gov (United States)

Portilla Gamboa, M.; Hürlimann, M.; Corominas, J.

2009-09-01

The inventory of rainfall-induced mass movements, rainfall data, and slope characteristics are considered the basis of the analysis determining appropriate rainfall thresholds for mass movements in a specific region. The rainfall-induced landslide thresholds established in the literature for the Catalan Pyrenees have been formulated referring to the rainfall events of November 1982, September 1992, December 1997, and others occurred after 1999. It has been shown that a rainfall intensity greater than 190 mm in 24 hours without antecedent rainfall would be necessary to produce mass movements (Corominas and Moya, 1999; Corominas et al, 2002) or 51mm in 24h with 61 mm of accumulated rainfall (Marco, 2007). Short duration-high intensity rainfalls have brought about several mass movements in some Catalonian regions throughout the course of twenty-first century (Berga, Bonaigua, Saldes, Montserrat, Port-Ainé, Riu Runer, and Sant Nicolau). Preliminary analysis of these events shows that it is necessary to review the thresholds defined so far and redo the existing inventory of mass movements for the Catalan Pyrenees. The present work shows the usefulness of aerial photographs in the reconstruction of the inventory of historic mass movements (Molló-Queralbs, 1940; Arties-Vielha, 1963; Barruera-Senet, 1940 and 1963, and Berga-Cercs, 1982, 1997 and 2008). Also, it highlights the treatment given to scarce and scattered rainfall data available inside these Catalonia’s regions, and the application of Geographic Information Systems (ArcGIS) in the management of the gathered information. The results acquired until now show that the historic rainfall events occurred in the Eastern Pyrenees have yielded many more mass movements than those reported in the literature. Besides, it can be said that the thresholds formulated for the Pyrenees are valid for longstanding regional rainfalls, and not for local downpours. In the latter cases it should be necessary to take into account the

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

Science.gov (United States)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Soil degradation level under particular annual rainfall at Jenawi District– Karanganyar, Indonesia

Science.gov (United States)

Herawati, A.; Suntoro; Widijanto, H.; Pusponegoro, I.; Sutopo, N. R.; Mujiyo

2018-03-01

The study of the climatic elements such as rainfall is vital for the sustainable development of agriculture at a region. The aims of the study were to evaluate the soil degradation based on the annual rainfall and to determine the key factors which responsible for the soil degradation at in Jenawi Sub-District. The mapping of soil degradation potency is an identification of initial soil condition to discover the potential of the land degradation. The mapping was done by overlaying the map of soil, slope, rainfall and land use with the standard procedures to obtain the value and status of Soil Degradation Potency (SDP). The result showed that SDP in Jenawi District categorized in very low (SDP I) 0.00 ha (0.00%); low (SDP II) 109.01 ha (2.57%); moderate (SDP III) 1,935.92 ha (45.63%); high (SDP IV) 1,959.54 ha (46.19%) and very high (SDP V) 238.08 ha (5.61%). The rainfall is the factor which has the strong correlation with the SDP (r = 0.65, P local soil-land characteristics.

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

Directory of Open Access Journals (Sweden)

U. Haberlandt

2008-12-01

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

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

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

Science.gov (United States)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Combined Forecasting of Rainfall Based on Fuzzy Clustering and Cross Entropy

Directory of Open Access Journals (Sweden)

Baohui Men

2017-12-01

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

Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

Science.gov (United States)

Meena, Hari Mohan; Machiwal, Deepesh; Santra, Priyabrata; Moharana, Pratap Chandra; Singh, D. V.

2018-05-01

Knowledge of rainfall variability is important for regional-scale planning and management of water resources in agriculture. This study explores spatio-temporal variations, trends, and homogeneity in monthly, seasonal, and annual rainfall series of 62 stations located in arid region of Rajasthan, India using 55 year (1957-2011) data. Box-whisker plots indicate presence of outliers and extremes in annual rainfall, which made the distribution of annual rainfall right-skewed. Mean and coefficient of variation (CV) of rainfall reveals a high inter-annual variability (CV > 200%) in the western portion where the mean annual rainfall is very low. A general gradient of the mean monthly, seasonal, and annual rainfall is visible from northwest to southeast direction, which is orthogonal to the gradient of CV. The Sen's innovative trend test is found over-sensitive in evaluating statistical significance of the rainfall trends, while the Mann-Kendall test identifies significantly increasing rainfall trends in June and September. Rainfall in July shows prominently decreasing trends although none of them are found statistically significant. Monsoon and annual rainfall show significantly increasing trends at only four stations. The magnitude of trends indicates that the rainfall is increasing at a mean rate of 1.11, 2.85, and 2.89 mm year-1 in August, monsoon season, and annual series. The rainfall is found homogeneous over most of the area except for few stations situated in the eastern and northwest portions where significantly increasing trends are observed. Findings of this study indicate that there are few increasing trends in rainfall of this Indian arid region.

Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

Directory of Open Access Journals (Sweden)

Panos Panagos

2016-03-01

Full Text Available As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices as well as natural hazard protection (landslides and flood prediction. We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland or former data density was not satisfactory (Austria, France, and Spain. The different time resolutions (from 5 to 60 min of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54 than in summer (August: 2.13, applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France, the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France show the largest from February to April. The average monthly erosivity density is very large in August (1.67 and July (1.63, while very small in January and February (0.37. This study addresses

Location-Based Rainfall Nowcasting Service for Public

Science.gov (United States)

Woo, Wang-chun

2013-04-01

-configurable manner. Verification indicates that the service achieves a detection rate of 76% and a false alarm rate of 26% in the first 30 minute forecast. The skill decreases as the forecast range extends, with the detection rate lowered to 40% and false alarm rate increased to 63% for the two hour forecast. A number of factors affect the accuracy of the forecast, notably the anomalous propagation, the sensitivity and vertical coverage of the radar, as well as the growth and decay of the rain echoes. The service has been gaining popularity rapidly since launch, and has already registered over 12,000 users who have opted for notifications. The successful launch of the location-based rainfall nowcast service in Hong Kong and favourable verification results reveal the high practicality of such services.

Derivation of critical rainfall thresholds for landslide in Sicily

Science.gov (United States)

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

2015-04-01

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

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

OpenAIRE

E. Cristiano; M.-C. ten Veldhuis; N. van de Giesen

2017-01-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological res...

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

OpenAIRE

Gairola, R. M.; Prakash, Satya; Pal, P. K.

2015-01-01

In this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates and rain gauge data, using a successive correction method in order to further refine the operational IMSRA rainfall estimates. The successive correction method benefits from high spatial and temporal resolutions of the Kalpana-1 satellite and accurate rainfall estima...

The wildgeographer avatar shows how to measure soil erosion rates by means of a rainfall simulator

Science.gov (United States)

Cerdà, Artemi; González Pelayo, Óscar; Pereira, Paulo; Novara, Agata; Iserloh, Thomas; Prosdocimi, Massimo

2015-04-01

. 1998a. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Cerdà, A. 1998b. The influence of aspect and vegetation on seasonal changes in erosion under rainfall simulation on a clay soil in Spain. Canadian Journal of Soil Science, 78, 321-330. Cerdà, A., Jurgensen, M. F. 2011. Ant mounds as a source of sediment on citrus orchard plantations in eastern Spain. A three-scale rainfall simulation approach. Catena, 85(3), 231-236. Dunkerley, D. 2012. Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Hydrological Processes, 26(15), 2211-2224. Iserloh, T., Ries, J.B., Arnaez, J., Boix Fayos, C., Butzen, V., Cerdà, A., Echeverría, M.T., Fernández-Gálvez, J., Fister, W., Geißler, C., Gómez, J.A., Gómez-Macpherson, H., Kuhn, N.J., Lázaro, R., León, F.J., Martínez-Mena, M., Martínez-Murillo, J.F., Marzen, M., Mingorance, M.D., Ortigosa, L., Peters, P., Regüés, D., Ruiz-Sinoga, J.D., Scholten, T., Seeger, M., Solé-Benet, A., Wengel, R., Wirtz, S. 2013. European small portable rainfall simulators: a comparison of rainfall characteristics. Catena, 110, 100-112. Doi: 10.1016/j.catena.2013.05.013 Iserloh, T., Ries, J.B., Cerdà, A., Echeverría, M.T., Fister, W., Geißler, C., Kuhn, N.J., León, F.J., Peters, P., Schindewolf, M., Schmidt, J., Scholten, T., Seeger, M. (2012): Comparative measurements with seven rainfall simulators on uniform bare fallow land. Zeitschrift für Geomorphologie, 57, 193-201. DOI: 10.1127/0372- 8854/2012/S-00118. Ziadat, F. M., Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

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

Directory of Open Access Journals (Sweden)

T. P. Burt

2014-09-01

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

Analysis of rainfall distribution in Kelantan river basin, Malaysia

Science.gov (United States)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

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

Understanding extreme rainfall events in Australia through historical data

Science.gov (United States)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

Extreme Rainfall In A City

Science.gov (United States)

Nkemdirim, Lawrence

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

Constraining continuous rainfall simulations for derived design flood estimation

Science.gov (United States)

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

2016-11-01

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

Simulation of daily rainfall through markov chain modeling

International Nuclear Information System (INIS)

Sadiq, N.

2015-01-01

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

Weather radar rainfall data in urban hydrology

DEFF Research Database (Denmark)

Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

2017-01-01

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

The regional geological hazard forecast based on rainfall and WebGIS in Hubei, China

Science.gov (United States)

Zheng, Guizhou; Chao, Yi; Xu, Hongwen

2008-10-01

Various disasters have been a serious threat to human and are increasing over time. The reduction and prevention of hazard is the largest problem faced by local governments. The study of disasters has drawn more and more attention mainly due to increasing awareness of the socio-economic impact of disasters. Hubei province, one of the highest economic developing provinces in China, suffered big economic losses from geo-hazards in recent years due to frequent geo-hazard events with the estimated damage of approximately 3000 million RMB. It is therefore important to establish an efficient way to mitigate potential damage and reduce losses of property and life derived from disasters. This paper presents the procedure of setting up a regional geological hazard forecast and information releasing system of Hubei province with the combination of advanced techniques such as World Wide Web (WWW), database online and ASP based on WEBGIS platform (MAPGIS-IMS) and rainfall information. A Web-based interface was developed using a three-tiered architecture based on client-server technology in this system. The study focused on the upload of the rainfall data, the definition of rainfall threshold values, the creation of geological disaster warning map and the forecast of geohazard relating to the rainfall. Its purposes are to contribute to the management of mass individual and regional geological disaster spatial data, help to forecast the conditional probabilities of occurrence of various disasters that might be posed by the rainfall, and release forecasting information of Hubei province timely via the internet throughout all levels of government, the private and nonprofit sectors, and the academic community. This system has worked efficiently and stably in the internet environment which is strongly connected with meteorological observatory. Environment Station of Hubei Province are making increased use of our Web-tool to assist in the decision-making process to analyze geo

Synergistic effects of seasonal rainfall, parasites and demography on fluctuations in springbok body condition

Science.gov (United States)

Turner, Wendy C.; Versfeld, Wilferd D.; Kilian, J. Werner; Getz, Wayne M.

2011-01-01

Summary 1. Seasonality of rainfall can exert a strong influence on animal condition and on host-parasite interactions. The body condition of ruminants fluctuates seasonally in response to changes in energy requirements, foraging patterns and resource availability, and seasonal variation in parasite infections may further alter ruminant body condition. 2. This study disentangles effects of rainfall and gastrointestinal parasite infections on springbok (Antidorcas marsupialis) body condition and determines how these factors vary among demographic groups. 3. Using data from four years and three study areas, we investigated i) the influence of rainfall variation, demographic factors and parasite interactions on parasite prevalence or infection intensity, ii) whether parasitism or rainfall is a more important predictor of springbok body condition and iii) how parasitism and condition vary among study areas along a rainfall gradient. 4. We found that increased parasite intensity is associated with reduced body condition only for adult females. For all other demographic groups, body condition was significantly related to prior rainfall and not to parasitism. Rainfall lagged by two months had a positive effect on body condition. 5. Adult females showed evidence of a “periparturient rise” in parasite intensity, and had higher parasite intensity and lower body condition than adult males after parturition and during early lactation. After juveniles were weaned, adult females had lower parasite intensity than adult males. Sex differences in parasitism and condition may be due to differences between adult females and males in the seasonal timing of reproductive effort and its effects on host immunity, as well as documented sex differences in vulnerability to predation. 6. Our results highlight that parasites and the environment can synergistically affect host populations, but that these interactions might be masked by their interwoven relationships, their differential

Spillway design implications resulting from changes in rainfall extremes

International Nuclear Information System (INIS)

Muzik, I.

1999-01-01

A study was conducted in order to determine how serious implications regarding spillway design of small dams would result from changes in flood frequencies and magnitudes, because of changes in rainfall regime in turn brought on by climate change due to carbon dioxide accumulation in the atmosphere. The region selected for study was the central Alberta foothills and adjacent prairie environment. A study watershed, representative of the region, was chosen to assess the present and possible future flood frequency-magnitude relationships. A Monte Carlo simulation method was used in conjunction with rainfall-runoff modelling of the study watershed to generate data for flood frequency analysis of maximum annual flood series corresponding to the present and future climate scenarios. The impact of resulting differences in design floods for small dams on spillway design was investigated using the Prairie Farm Rehabilitation Administration small dam design method. Changes in the mean and standard deviation of rainfall depth of design storms in a region will result in new probability distributions of the maximum annual flood flows. A 25% increase in the mean and standard deviation of design rainfall depth resulted in greater increases of 1:2 and 1:100 flood flows than a 50% increase in the standard deviation alone did. Under scenario 1, the 1:2 flood flows increased more than did the 1:100 flows. Scenario 2 produced opposite results, whereby the 1:100 flows increased more than did the 1:2 flows. It seems that a climate change of the type of scenario 1 would result in a more severe increase in flood flows than scenario 2 would. Retrofitting existing spillways of small dams would in most cases require increasing flow capacities of both operating and auxilliary spillways. 23 refs

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

Science.gov (United States)

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

2017-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-01-01

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

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

Science.gov (United States)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

Science.gov (United States)

Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

2018-05-01

Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

Contribution of tropical cyclones to global rainfall

Science.gov (United States)

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

2016-04-01

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

TRMM Applications for Rainfall-Induced Landslide Early Warning

Science.gov (United States)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

(snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

Monthly Rainfall Erosivity Assessment for Switzerland

Science.gov (United States)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

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

Quantifying Rainfall Interception Loss of a Subtropical Broadleaved Forest in Central Taiwan

Directory of Open Access Journals (Sweden)

Yi-Ying Chen

2016-01-01

Full Text Available The factors controlling seasonal rainfall interception loss are investigated by using a double-mass curve analysis, based on direct measurements of high-temporal resolution gross rainfall, throughfall and stemflow from 43 rainfall events that occurred in central Taiwan from April 2008 to April 2009. The canopy water storage capacity for the wet season was estimated to be 1.86 mm, about twice that for the dry season (0.91 mm, likely due to the large reduction in the leaf area index (LAI from 4.63 to 2.23 (m2·m−2. Changes in seasonal canopy structure and micro-meteorological conditions resulted in temporal variations in the amount of interception components, and rainfall partitioning into stemflow and throughfall. Wet canopy evaporation after rainfall contributed 41.8% of the wet season interception loss, but only 17.1% of the dry season interception loss. Wet canopy evaporation during rainfall accounted for 82.9% of the dry season interception loss, but only 58.2% of the wet season interception loss. Throughfall accounted for over 79.7% of the dry season precipitation and 76.1% of the wet season precipitation, possibly due to the change in gap fraction from 64.2% in the dry season to 50.0% in the wet season. The reduced canopy cover in the dry season also produced less stemflow than that of the wet season. The rainfall stemflow ratio ( P s f / P g was reduced from 12.6% to 8.9%. Despite relatively large changes in canopy structure, seasonal variation of the ratio of rainfall partitioned to interception was quite small. Rainfall interception loss accounted for nearly 12% of gross precipitation for both dry and wet seasons.

Commercial application of rainfall simulation

Science.gov (United States)

Loch, Rob J.

2010-05-01

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

Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

OpenAIRE

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

2014-01-01

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

Rainfall thresholds for the triggering of landslides in Slovenia

Science.gov (United States)

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

2017-04-01

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

The impact of Amazonian deforestation on Amazon basin rainfall

Science.gov (United States)

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

2015-11-01

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

Stability of termite mound populations in a variable environment ...

African Journals Online (AJOL)

Of all the climatic variables in the environment of termites in southern Kenya, only rainfall shows marked seasonality and unpredictability. But despite the great variability in rainfall patterns, the populations of termite mounds of various species in three well-separated study areas remained remarkably constant over a period ...

On the determination of trends in rainfall

African Journals Online (AJOL)

2008-02-19

Feb 19, 2008 ... it was decided to start from the inherent distribution of rainfall and develop a method for determining temporal .... first log-transformed to stabilise the variance of the time series ... the Kolmogorov-Zurbenko filter had a very high probability of ... seasonality, the SKT test and a t-test adjusted for seasonality.

Rainfall interception from a lowland tropical rainforest in Brunei

Science.gov (United States)

Dykes, A. P.

1997-12-01

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

Linking Vital Rates of Landbirds on a Tropical Island to Rainfall and Vegetation Greenness.

Directory of Open Access Journals (Sweden)

James F Saracco

Full Text Available Remote tropical oceanic islands are of high conservation priority, and they are exemplified by range-restricted species with small global populations. Spatial and temporal patterns in rainfall and plant productivity may be important in driving dynamics of these species. Yet, little is known about environmental influences on population dynamics for most islands and species. Here we leveraged avian capture-recapture, rainfall, and remote-sensed habitat data (enhanced vegetation index [EVI] to assess relationships between rainfall, vegetation greenness, and demographic rates (productivity, adult apparent survival of three native bird species on Saipan, Northern Mariana Islands: rufous fantail (Rhipidura rufifrons, bridled white-eye (Zosterops conspicillatus, and golden white-eye (Cleptornis marchei. Rainfall was positively related to vegetation greenness at all but the highest rainfall levels. Temporal variation in greenness affected the productivity of each bird species in unique ways. Predicted productivity of rufous fantail was highest when dry and wet season greenness values were high relative to site-specific 5-year seasonal mean values (i.e., relative greenness; while the white-eye species had highest predicted productivity when relative greenness contrasted between wet and dry seasons. Survival of rufous fantail and bridled white eye was positively related to relative dry-season greenness and negatively related to relative wet-season greenness. Bridled white-eye survival also showed evidence of a positive response to overall greenness. Our results highlight the potentially important role of rainfall regimes in affecting population dynamics of species on oceanic tropical islands. Understanding linkages between rainfall, vegetation, and animal population dynamics will be critical for developing effective conservation strategies in this and other regions where the seasonal timing, extent, and variability of rainfall is expected to change in the

Heavy daily-rainfall characteristics over the Gauteng Province

African Journals Online (AJOL)

2009-02-09

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

Convective Cloud and Rainfall Processes Over the Maritime Continent: Simulation and Analysis of the Diurnal Cycle

Science.gov (United States)

Gianotti, Rebecca L.

The Maritime Continent experiences strong moist convection, which produces significant rainfall and drives large fluxes of heat and moisture to the upper troposphere. Despite the importance of these processes to global circulations, current predictions of climate change over this region are still highly uncertain, largely due to inadequate representation of the diurnally-varying processes related to convection. In this work, a coupled numerical model of the land-atmosphere system (RegCM3-IBIS) is used to investigate how more physically-realistic representations of these processes can be incorporated into large-scale climate models. In particular, this work improves simulations of convective-radiative feedbacks and the role of cumulus clouds in mediating the diurnal cycle of rainfall. Three key contributions are made to the development of RegCM3-IBIS. Two pieces of work relate directly to the formation and dissipation of convective clouds: a new representation of convective cloud cover, and a new parameterization of convective rainfall production. These formulations only contain parameters that can be directly quantified from observational data, are independent of model user choices such as domain size or resolution, and explicitly account for subgrid variability in cloud water content and nonlinearities in rainfall production. The third key piece of work introduces a new method for representation of cloud formation within the boundary layer. A comprehensive evaluation of the improved model was undertaken using a range of satellite-derived and ground-based datasets, including a new dataset from Singapore's Changi airport that documents diurnal variation of the local boundary layer height. The performance of RegCM3-IBIS with the new formulations is greatly improved across all evaluation metrics, including cloud cover, cloud liquid water, radiative fluxes and rainfall, indicating consistent improvement in physical realism throughout the simulation. This work

Hydrological Effects of Historic Rainfall on the Waccamaw River

Science.gov (United States)

Jolly, J.; Bao, S.

2017-12-01

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

Utilizing Mobile-Phone-Link Data to Improve Rainfall Monitoring over Cyprus

Science.gov (United States)

Lange, Manfred; Alpert, Pinhas; David, Noam

2013-04-01

There is a need for spatially denser and temporally more detailed observations of precipitation in most countries, including Cyprus. Traditionally, rainfall is measured with rain gauges that are either read manually once a day or automatically at higher temporal frequencies. However, these are point measurements with poor spatial representativeness due to the small sampling area. In Cyprus rain gauges are typically installed close to populated communities and built-up areas, leaving substantial parts of the country only sparsely covered. On the other hand, wireless communication networks are widely spread across the terrain, at heights of only a few tens of meters off the surface. The microwave links, used in these networks, are deployed by cellular providers for backhaul communication between base stations. Since these links operate at frequencies of tens of GHz, atmospheric conditions and particularly rainfall affect the electromagnetic channel causing attenuations to the microwave signals between the radio masts. Cellular networks infrastructures can therefore be regarded as relatively high-precision atmospheric observation system offering fairly dense spatial coverage and high temporal resolution. The principal feasibility of rainfall delineation by microwave attenuation between commercial radio links has been shown by Messer et al. (2006). In the meantime, the group of P. Alpert and H. Messer at Tel Aviv University, and additional groups around the world (e.g. Leijnse et al 2010; Chwala et al., 2012; Wang et al., 2012 ) have further developed the methodology. The objectives of the current project, which is still being implemented, can be summarized as follows: i. to carry out a feasibility study on the utilization of mobile-phone-link-data for rainfall observations in Cyprus; ii. to evaluate, adapt and implement the analysis methodology/software developed and used at TAU at the Energy, Environment and Water Research Center of The Cyprus Institute; iii. to

Implications of rainfall for agricultural and urban development of Eldoret, Kenya

Directory of Open Access Journals (Sweden)

E. Ofori- Sarpong

2013-07-01

Full Text Available This paper examines the role of rainfall in the urban development of Kenya. The rainfall characteristics have been analysed and their influence on agricultural and urban development assessed. It is noted that since Eldoret is one of the rapidly expanding towns in Kenya located in highly potential agricultural region, variability of rainfall and drought can seriously affect urban development as farmers in the hinterland will abandon their farms and migrate to the town thus creating food shortage. Secondly, in times of drought, the water supply problems in the town will be exacerbated as it depends on surface water source. The tempo of rural-urban migration will be speeded up and this will create more socio-economic problems.

Analysis of convection-permitting simulations for capturing heavy rainfall events over Myanmar Region

Science.gov (United States)

Acierto, R. A. E.; Kawasaki, A.

2017-12-01

Perennial flooding due to heavy rainfall events causes strong impacts on the society and economy. With increasing pressures of rapid development and potential for climate change impacts, Myanmar experiences a rapid increase in disaster risk. Heavy rainfall hazard assessment is key on quantifying such disaster risk in both current and future conditions. Downscaling using Regional Climate Models (RCM) such as Weather Research and Forecast model have been used extensively for assessing such heavy rainfall events. However, usage of convective parameterizations can introduce large errors in simulating rainfall. Convective-permitting simulations have been used to deal with this problem by increasing the resolution of RCMs to 4km. This study focuses on the heavy rainfall events during the six-year (2010-2015) wet period season from May to September in Myanmar. The investigation primarily utilizes rain gauge observation for comparing downscaled heavy rainfall events in 4km resolution using ERA-Interim as boundary conditions using 12km-4km one-way nesting method. The study aims to provide basis for production of high-resolution climate projections over Myanmar in order to contribute for flood hazard and risk assessment.

Temporal rainfall estimation using input data reduction and model inversion

Science.gov (United States)

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

2016-12-01

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

Relationship of Rainfall Distribution and Water Level on Major Flood 2014 in Pahang River Basin, Malaysia

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Nur Hishaam Sulaiman

2017-01-01

Full Text Available Climate change gives impact on extreme hydrological events especially in extreme rainfall. This article discusses about the relationship of rainfall distribution and water level on major flood 2014 in Pahang River Basin, Malaysia in helping decision makers to flood management system. Based on DID Malaysia rainfall station, 56 stations have being use as point in this research and it is including Pahang, Terengganu, Kelantan and Perak. Data set for this study were analysed with GIS analysis using interpolation method to develop Isohyet map and XLstat statistical software for PCA and SPC analyses. The results that were obtained from the Isohyet Map for three months was mid-November, rainfall started to increase about in range of 800mm-1200mm and the intensity keep increased to 2200mm at mid-December 2014. The high rainfall intensity sense at highland that is upstream of Pahang River. The PCA and SPC analysis also indicates the high relationship between rainfall and water level of few places at Pahang River. The Sg. Yap station and Kg. Serambi station obtained the high relationship of rainfall and water level with factor loading value at 0.9330 and 0.9051 for each station. Hydrological pattern and trend are extremely affected by climate such as north east monsoon season that occurred in South China Sea and affected Pahang during November to March. The findings of this study are important to local authorities by providing basic data as guidelines to the integrated river management at Pahang River Basin.

Rainfall interception of three trees in Oakland, California

Science.gov (United States)

Qingfu Xiao; E. Gregory McPherson

2011-01-01

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

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

KAUST Repository

Srinivas, C. V.

2015-09-11

This study examines the ability of the Advanced Research WRF (ARW) regional model to simulate Indian summer monsoon (ISM) rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP) global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department) rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid) of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast) with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative) and above-normal onset (June positive) phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over northeast, east and

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

Directory of Open Access Journals (Sweden)

C. V. Srinivas

2015-09-01

Full Text Available This study examines the ability of the Advanced Research WRF (ARW regional model to simulate Indian summer monsoon (ISM rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative and above-normal onset (June positive phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

OpenAIRE

Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

2016-01-01

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts...

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

Science.gov (United States)

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

2017-11-01

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

Nitrate Accumulation and Leaching in Surface and Ground Water Based on Simulated Rainfall Experiments

Science.gov (United States)

Wang, Hong; Gao, Jian-en; Li, Xing-hua; Zhang, Shao-long; Wang, Hong-jie

2015-01-01

To evaluate the process of nitrate accumulation and leaching in surface and ground water, we conducted simulated rainfall experiments. The experiments were performed in areas of 5.3 m2 with bare slopes of 3° that were treated with two nitrogen fertilizer inputs, high (22.5 g/m2 NH4NO3) and control (no fertilizer), and subjected to 2 hours of rainfall, with. From the 1st to the 7th experiments, the same content of fertilizer mixed with soil was uniformly applied to the soil surface at 10 minutes before rainfall, and no fertilizer was applied for the 8th through 12th experiments. Initially, the time-series nitrate concentration in the surface flow quickly increased, and then it rapidly decreased and gradually stabilized at a low level during the fertilizer experiments. The nitrogen loss in the surface flow primarily occurred during the first 18.6 minutes of rainfall. For the continuous fertilizer experiments, the mean nitrate concentrations in the groundwater flow remained at less than 10 mg/L before the 5th experiment, and after the 7th experiment, these nitrate concentrations were greater than 10 mg/L throughout the process. The time-series process of the changing concentration in the groundwater flow exhibited the same parabolic trend for each fertilizer experiment. However, the time at which the nitrate concentration began to change lagged behind the start time of groundwater flow by approximately 0.94 hours on average. The experiments were also performed with no fertilizer. In these experiments, the mean nitrate concentration of groundwater initially increased continuously, and then, the process exhibited the same parabolic trend as the results of the fertilization experiments. The nitrate concentration decreased in the subsequent experiments. Eight days after the 12 rainfall experiments, 50.53% of the total nitrate applied remained in the experimental soil. Nitrate residues mainly existed at the surface and in the bottom soil layers, which represents a

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

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Carlos Salinas-Rodriguez

2018-03-01

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

Satellite and gauge rainfall merging using geographically weighted regression

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Q. Hu

2015-05-01

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

Abrupt state change of river water quality (turbidity): Effect of extreme rainfalls and typhoons.

Science.gov (United States)

Lee, Chih-Sheng; Lee, Yi-Chao; Chiang, Hui-Min

2016-07-01

River turbidity is of dynamic nature, and its stable state is significantly changed during the period of heavy rainfall events. The frequent occurrence of typhoons in Taiwan has caused serious problems in drinking water treatment due to extremely high turbidity. The aim of the present study is to evaluate impact of typhoons on river turbidity. The statistical methods used included analyses of paired annual mean and standard deviation, frequency distribution, and moving standard deviation, skewness, and autocorrelation; all clearly indicating significant state changes of river turbidity. Typhoon Morakot of 2009 (recorded high rainfall over 2000mm in three days, responsible for significant disaster in southern Taiwan) is assumed as a major initiated event leading to critical state change. In addition, increasing rate of turbidity in rainfall events is highly and positively correlated with rainfall intensity both for pre- and post-Morakot periods. Daily turbidity is also well correlated with daily flow rate for all the eleven events evaluated. That implies potential prediction of river turbidity by river flow rate during rainfall and typhoon events. Based on analysis of stable state changes, more effective regulations for better basin management including soil-water conservation in watershed are necessary. Furthermore, municipal and industrial water treatment plants need to prepare and ensure the adequate operation of water treatment with high raw water turbidity (e.g., >2000NTU). Finally, methodology used in the present of this study can be applied to other environmental problems with abrupt state changes. Copyright © 2016 Elsevier B.V. All rights reserved.

The effects of simulated rainfall on immature population dynamics of Aedes albopictus and female oviposition

Science.gov (United States)

Dieng, Hamady; Rahman, G. M. Saifur; Abu Hassan, A.; Che Salmah, M. R.; Satho, Tomomitsu; Miake, Fumio; Boots, Michael; Sazaly, Abubakar

2012-01-01

Larvae of Aedes albopictus Skuse typically inhabit natural and artificial containers. Since these larval habitats are replenished by rainfall, Ae. albopictus may experience increased loss of immature stages in areas with high levels of rainfall. In this study, we investigated the effects of rainfall and container water level on population density, and oviposition activity of Ae. albopictus. In field and laboratory experiments, we found that rainfall resulted in the flushing of breeding habitats. Excess rain negatively impacted larval and pupal retention, especially in small habitats. When filled with water to overflowing, container habitats were significantly repellent to ovipositing females. Taken together, these data suggest that rainfall triggers population loss of Ae. albopictus and related species through a direct detrimental effect (flushing out) and an indirect effect (ovipositional repellency).

Automated reconstruction of rainfall events responsible for shallow landslides

Science.gov (United States)

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

2014-04-01

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

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

Science.gov (United States)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting

Science.gov (United States)

Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.

2018-04-01

Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.

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

Science.gov (United States)

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

2016-05-17

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

Measurements of effective non-rainfall in soil with the use of time-domain reflectometry technique

Science.gov (United States)

Nakonieczna, Anna; Kafarski, Marcin; Wilczek, Andrzej; Szypłowska, Agnieszka; Skierucha, Wojciech

2014-05-01

The non-rainfall vectors are fog, dew, hoarfrost and vapour adsorption directly from the atmosphere. The measurements of the amount of water supplied to the soil due to their temporary existence are essential, because in dry areas such water uptake can exceed that of rainfall. Although several devices and methods were proposed for estimating the effective non-rainfall input into the soil, the measurement standard has not yet been established. This is mainly due to obstacles in measuring small water additions to the medium, problems with taking readings in actual soil samples and atmospheric disturbances during their course in natural environment. There still exists the need for automated devices capable of measuring water deposition on real-world soil surfaces, whose resolution is high enough to measure the non-rainfall intensity and increase rate, which are usually very low. In order to achieve the desirable resolution and accuracy of the effective non-rainfall measurements the time-domain reflectometry (TDR) technique was employed. The TDR sensor designed and made especially for the purpose was an untypical waveguide. It consisted of a base made of laminate covered with copper, which served as a bottom of a cuboidal open container in which the examined materials were placed, and a copper signal wire placed on the top of the container. The wire adhered along its entire length to the tested material in order to eliminate the formation of air gaps between the two, what enhanced the accuracy of the measurements. The tested porous materials were glass beads, rinsed sand and three soil samples, which were collected in south-eastern Poland. The diameter ranges of their constituent particles were measured with the use of the laser diffraction technique. The sensor filled with the wetted material was placed on a scale and connected to the TDR meter. The automated readings of mass and TDR time were collected simultaneously every minute. The TDR time was correlated with the

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

Directory of Open Access Journals (Sweden)

Dongkyun Kim

2014-01-01

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

Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

Science.gov (United States)

Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

2017-12-01

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product

Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

Science.gov (United States)

Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

2017-07-01

The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

Predicting extreme rainfall over eastern Asia by using complex networks

International Nuclear Information System (INIS)

He Su-Hong; Gong Yan-Chun; Huang Yan-Hua; Wu Cheng-Guo; Feng Tai-Chen; Gong Zhi-Qiang

2014-01-01

A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971–2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ≤ n ≤ 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ≤ n ≤ 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. (geophysics, astronomy, and astrophysics)

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

Science.gov (United States)

Costa, Veber; Fernandes, Wilson

2017-11-01

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

Rainfall erosivity factor estimation in Republic of Moldova

Science.gov (United States)

Castraveš, Tudor; Kuhn, Nikolaus

2017-04-01

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

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

African Journals Online (AJOL)

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

Projected changes of rainfall event characteristics for the Czech Republic

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Svoboda Vojtěch

2016-12-01

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

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

Science.gov (United States)

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

2014-05-01

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

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

Science.gov (United States)

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

2018-01-01

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

The development of a capability for aerodynamic testing of large-scale wing sections in a simulated natural rain environment

Science.gov (United States)

Bezos, Gaudy M.; Cambell, Bryan A.; Melson, W. Edward

1989-01-01

A research technique to obtain large-scale aerodynamic data in a simulated natural rain environment has been developed. A 10-ft chord NACA 64-210 wing section wing section equipped with leading-edge and trailing-edge high-lift devices was tested as part of a program to determine the effect of highly-concentrated, short-duration rainfall on airplane performance. Preliminary dry aerodynamic data are presented for the high-lift configuration at a velocity of 100 knots and an angle of attack of 18 deg. Also, data are presented on rainfield uniformity and rainfall concentration intensity levels obtained during the calibration of the rain simulation system.

Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

Science.gov (United States)

Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2016-04-01

high-resolution atmospheric reanalysis over France with the SAFRAN-gauge-based analysis system (Vidal et al., 2010). We have then built samples of maximal rainfalls for each cell location (the "point" rainfalls) and for different areas centered on each cell location (the areal rainfalls) of these gridded data. To compute rainfall quantiles, we have fitted a Gumbel law, with the L-moment method, on each of these samples. Our daily and hourly ARF have then shown four main trends: i) a sensitivity to the return period, with ARF values decreasing when the return period increases; ii) a sensitivity to the rainfall duration, with ARF values decreasing when the rainfall duration decreases; iii) a sensitivity to the season, with ARF values smaller for the summer period than for the winter period; iv) a sensitivity to the geographical location, with low ARF values in the French Mediterranean area and ARF values close to 1 for the climatic zones of Northern and Western France (oceanic to semi-continental climate). The results of this data-intensive study led for the first time on the whole French territory are in agreement with studies led abroad (e.g. Allen and DeGaetano 2005, Overeem et al. 2010) and confirm and widen the results of previous studies that were carried out in France on smaller areas and with fewer rainfall durations (e.g. Ramos et al., 2006, Neppel et al., 2003). References Allen R. J. and DeGaetano A. T. (2005). Areal reduction factors for two eastern United States regions with high rain-gauge density. Journal of Hydrologic Engineering 10(4): 327-335. Arnaud P., Fine J.-A. and Lavabre J. (2007). An hourly rainfall generation model applicable to all types of climate. Atmospheric Research 85(2): 230-242. Cantet, P. and Arnaud, P. (2014). Extreme rainfall analysis by a stochastic model: impact of the copula choice on the sub-daily rainfall generation, Stochastic Environmental Research and Risk Assessment, Springer Berlin Heidelberg, 28(6), 1479-1492. Neppel L

Monitoring and Warning of Landslides Based On Rainfall

Science.gov (United States)

Yudhbir, Y.

Management issues of landslide hazards assume much greater significance in poorest segments of society living in landslide risk prone hilly areas in developing countries. Analysis of the temporal recurrence of landslides shows that disastrous events occur with a frequency higher than the social and economic capacity of these societies to recover from previous events. In the context of landslide hazard management in In- dian Himalayan states this problem assumes much greater significance. Majority of the population lives on hill slopes which experience repeated landsliding activity es- pecially during the summer monsoon rains. Considering the high cost of structural control measures and the lack of necessary spatial database in respect of Quaternary geology, detailed topography and geohydrology etc., there is an acute need to develop a monitoring and warning system which is economical, easy to operate and does not require high technological inputs. Since most of the landslides in these areas are triggered by high incidence of rain, it appears attractive to explore development of a monitoring and warning network based on critical rainfall intensity thresholds. Such an option for management of landslide hazards would also provide useful meteorological data required for assessment of wa- ter resources, soil loss due to erosion, agricultural practices and flood incidence. In this paper, available approaches to the prediction and warning of landslide based on rainfall data will be critically reviewed. Various criteria recommended in litera- ture for threshold rainfall values in rain induced ground movements/failures would be compared and these relationships will be contrasted with the limited data available for the Indian Himalayan landslides. A plan for a network of automatic rain gauges and a suitable warning system will be discussed.

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

Science.gov (United States)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

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

Directory of Open Access Journals (Sweden)

R. Giannecchini

2006-01-01

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

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

Indian Academy of Sciences (India)

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

Infrastructure mitigates the sensitivity of child growth to local agriculture and rainfall in Nepal and Uganda.

Science.gov (United States)

Shively, Gerald E

2017-01-31

This paper investigates linear growth and weight gain among 11,946 children below the age of 5 y in Nepal and Uganda, testing the hypothesis that child growth is sensitive to precipitation during key periods in a child's early life. The paper also tests the importance of the economic and physical environments in which children reside. Outcomes are not completely explained by agricultural performance or the observed characteristics of children or their households. Associations between height-for-age z-score (HAZ) and weight-for-height z-score (WHZ) and rainfall are generally positive, but patterns are heterogeneous. At the mean, an increase of 1 SD in agricultural season rainfall is associated with a 0.05- to 0.25-point higher z-score, which translates into increases of roughly 4-13% for HAZ and 1-7% for WHZ. Nutrition sensitivity to rainfall is greater in Nepal, where rainfall is lower on average and wider ranging, than in Uganda. Health and transport infrastructure help to buffer children from the deleterious nutritional effects of precipitation shortfalls, underscoring the role of broadly based economic development in promoting child nutrition.

Regional rainfall thresholds for landslide occurrence using a centenary database

Science.gov (United States)

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

2018-04-01

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

Extreme Rainfall Mechanisms Exhibited by Typhoon Morakot (2009

Directory of Open Access Journals (Sweden)

Ching-Yuang Huang

2011-01-01

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

Radar Rainfall Bias Correction based on Deep Learning Approach

Science.gov (United States)

Song, Yang; Han, Dawei; Rico-Ramirez, Miguel A.

2017-04-01

Radar rainfall measurement errors can be considerably attributed to various sources including intricate synoptic regimes. Temperature, humidity and wind are typically acknowledged as critical meteorological factors in inducing the precipitation discrepancies aloft and on the ground. The conventional practices mainly use the radar-gauge or geostatistical techniques by direct weighted interpolation algorithms as bias correction schemes whereas rarely consider the atmospheric effects. This study aims to comprehensively quantify those meteorological elements' impacts on radar-gauge rainfall bias correction based on a deep learning approach. The deep learning approach employs deep convolutional neural networks to automatically extract three-dimensional meteorological features for target recognition based on high range resolution profiles. The complex nonlinear relationships between input and target variables can be implicitly detected by such a scheme, which is validated on the test dataset. The proposed bias correction scheme is expected to be a promising improvement in systematically minimizing the synthesized atmospheric effects on rainfall discrepancies between radar and rain gauges, which can be useful in many meteorological and hydrological applications (e.g., real-time flood forecasting) especially for regions with complex atmospheric conditions.

Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods

Directory of Open Access Journals (Sweden)

Hao Wu

2017-12-01

Full Text Available This study aims to reveal rainfall anomalies and changes over the Yellow River Basin due to the fragile ecosystem and rainfall-related disasters. Common trend analyses relate to overall trends in mean values. Therefore, we used two graphical methods: the quantile perturbation method (QPM was used to investigate anomalies over time in extreme rainfall, and the partial trend method (PTM was used to analyze rainfall changes at different intensities. A nonparametric bootstrap procedure is proposed in order to identify significant PTM indices. The QPM indicated prevailing positive anomalies in extreme daily rainfall 50 years ago and in the middle reaches during the 1970s and 1980s. The PTM detected significant decreases in annual rainfall mainly in the latter half of the middle reaches, two-thirds of which occurred in high and heavy rainfall. Most stations in the middle and lower reaches showed significant decreases in rainy days. Daily rainfall intensity had a significant increase at 13 stations, where rainy days were generally decreasing. The combined effect of these opposing changes explains the prevailing absence of change in annual rainfall, and the observed decreases in annual rainfall can be attributed to the decreasing number of rainy days. The changes in rainy days and rainfall intensity were dominated by the wet season and dry season, respectively.

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

Science.gov (United States)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

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

CSIR Research Space (South Africa)

Engelbrecht, CJ

2014-10-01

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

prediction of rainfall in the southern highlands of tanzania

African Journals Online (AJOL)

User

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

Climate change impact assessment on urban rainfall extremes and urban drainage: Methods and shortcomings

DEFF Research Database (Denmark)

Willems, P.; Arnbjerg-Nielsen, Karsten; Olsson, J.

2012-01-01

Cities are becoming increasingly vulnerable to flooding because of rapid urbanization, installation of complex infrastructure, and changes in the precipitation patterns caused by anthropogenic climate change. The present paper provides a critical review of the current state-of-the-art methods...... for assessing the impacts of climate change on precipitation at the urban catchment scale. Downscaling of results from global circulation models or regional climate models to urban catchment scales are needed because these models are not able to describe accurately the rainfall process at suitable high temporal...... and spatial resolution for urban drainage studies. The downscaled rainfall results are however highly uncertain, depending on the models and downscaling methods considered. This uncertainty becomes more challenging for rainfall extremes since the properties of these extremes do not automatically reflect those...

The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates

Science.gov (United States)

Seyyedi, H.; Anagnostou, E. N.

2011-12-01

This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.

20-50-day oscillation of summer Yangtze rainfall in response to intraseasonal variations in the subtropical high over the western North Pacific and South China Sea

Energy Technology Data Exchange (ETDEWEB)

Mao, Jiangyu; Wu, Guoxiong [Institute of Atmospheric Physics, Chinese Academy of Sciences, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), P.O. Box 9804, Beijing (China); Sun, Zhang [Institute of Atmospheric Physics, Chinese Academy of Sciences, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), P.O. Box 9804, Beijing (China); Zhejiang Meteorological Observatory, Hangzhou (China)

2010-04-15

The spatio-temporal variability in summer rainfall within eastern China is identified based on empirical orthogonal function (EOF) analysis of daily rain-gauge precipitation data for the period 1979-2003. Spatial coherence of rainfall is found in the Yangtze Basin, and a wavelet transform is applied to the corresponding principal component to capture the intraseasonal oscillation (ISO) of Yangtze rainfall. The ensemble mean wavelet spectrum, representing statistically significant intraseasonal variability, shows a predominant oscillation in summer Yangtze rainfall with a period of 20-50 days; a 10-20-day oscillation is pronounced during June and July. This finding suggests that the 20-50-day oscillation is a major agent in regulating summer Yangtze rainfall. Composite analyses reveal that the 20-50-day oscillation of summer Yangtze rainfall arises in response to intraseasonal variations in the western North Pacific subtropical high (WNPSH), which in turn is modulated by a Rossby wave-like coupled circulation-convection system that propagates northward and northwestward from the equatorial western Pacific. When an anomalous cyclone associated with this Rossby wave-like system reaches the South China Sea (SCS) and Philippine Sea, the WNPSH retreats northeastward due to a reduction in local pressure. Under these conditions, strong monsoonal southwesterlies blow mainly toward the SCS-Philippine Sea, while dry conditions form in the Yangtze Basin, with a pronounced divergent flow pattern. In contrast, the movement of an anomalous anticyclone over the SCS-Philippine Sea results in the southwestward extension of the WNPSH; consequently, the tropical monsoonal southwesterlies veer to the northeast over the SCS and then converge toward the Yangtze Basin, producing wet conditions. Therefore, the 20-50-day oscillation of Yangtze rainfall is also manifest as a seesaw pattern in convective anomalies between the Yangtze Basin and the SCS-Philippine Sea. A considerable zonal

Characteristic and Behavior of Rainfall Induced Landslides in Java Island, Indonesia : an Overview

Science.gov (United States)

Christanto, N.; Hadmoko, D. S.; Westen, C. J.; Lavigne, F.; Sartohadi, J.; Setiawan, M. A.

2009-04-01

Landslides are important natural hazards occurring on mountainous area situated in the wet tropical climate like in Java, Indonesia. As a central of economic and government activity, Java become the most populated island in Indonesia and is increasing every year. This condition create population more vulnerable to hazard. Java is populated by 120 million inhabitants or equivalent with 60% of Indonesian population in only 6,9% of the total surface of Indonesia. Due to its geological setting, its topographical characteristics, and its climatic characteristics, Java is the most exposed regions to landslide hazard and closely related to several factors: (1) located on a subduction zone, 60% of Java is mountainous, with volcano-tectonic mountain chains and 36 active volcanoes out of the 129 in Indonesia, and these volcanic materials are intensively weathered (2) Java is under a humid tropical climate associated with heavy rainfall during the rainy season from October to April. On top of these "natural" conditions, the human activity is an additional factor of landslide occurrence, driven by a high demographic density The purpose of this paper was to collect and analyze spatial and temporal data concerning landslide hazard for the period 1981-2007 and to evaluate and analyze the characteristic and the behavior of landslide in Java. The results provides a new insight into our understanding of landslide hazard and characteristic in the humid tropics, and a basis for predicting future landslides and assessing related hazards at a regional scale. An overview of characteristic and behavior of landslides in Java is given. The result of this work would be valuable for decision makers and communities in the frame of future landslide risk reduction programs. Landslide inventory data was collected from internal database at the different institutions. The result is then georefenced. The temporal changes of landslide activities was done by examining the changes in number and

The relation of vegetation over the Tibetan Plateau to rainfall in China during the boreal summer

Energy Technology Data Exchange (ETDEWEB)

Zuo, Zhiyan; Zhang, Renhe [Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather, Beijing (China); Zhao, Ping [National Meteorological Information Centre, Beijing (China)

2011-03-15

The relationship between vegetation on the Tibetan Plateau (TP) and summer (June-August) rainfall in China is investigated using the normalized difference vegetation index (NDVI) from the Earth Resources Observation System and observed rainfall data from surface 616 stations in China for the period 1982-2001. The leading mode of empirical orthogonal functions analysis for summer rainfall variability in China shows a negative anomaly in the area from the Yangtze River valley to the Yellow River valley (YYR) and most of western China, and positive anomalies in southern China and North China. This mode is significantly correlated with summer NDVI around the southern TP. This finding indicates that vegetation around the southern TP has a positive correlation with summer rainfall in southern China and North China, but a negative correlation with summer rainfall in YYR and western China. We investigate the physical process by which vegetation change affects summer rainfall in China. Increased vegetation around the southern TP is associated with a descending motion anomaly on the TP and the neighboring area to the east, resulting in reduced surface heating and a lower Bowen ratio, accompanied by weaker divergence in the upper troposphere and convergence in the lower troposphere on the TP. In turn, these changes result in the weakening of and a westward shift in the southern Asian High in the upper troposphere and thereby the weakening of and an eastward withdrawal in the western Pacific subtropical high. These features result in weak circulation in the East Asian summer monsoon. Consequently, enhanced summer rainfall occurs in southern China and North China, but reduced rainfall in YYR. (orig.)

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

Directory of Open Access Journals (Sweden)

Álvaro José Back

2012-06-01

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

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

Science.gov (United States)

Larsen, Matthew C.; Simon, Andrew

1993-01-01

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

Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

Science.gov (United States)

Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

2015-12-01

The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean

Statistical Analysis of 30 Years Rainfall Data: A Case Study

Science.gov (United States)

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

2017-07-01

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

Imaging rainfall infiltration processes with the time-lapse electrical resistivity imaging method

Science.gov (United States)

Jia, Zhengyuan; Jiang, Guoming; Zhang, Guibin; Zhang, Gang

2017-04-01

Electrical Resistivity Imaging (ERI) was carried out continuously for ten days to map the subsurface resistivity distribution along a potentially hazardous hillslope at the Jieshou Junior High School in Taoyuan, Taiwan. The inversions confirm the viability of ERI in tracking the movement of groundwater flow and rainfall infiltration by recording the variation of subsurface resistivity distribution. Meanwhile, relative-water-saturation (RWS) maps can be obtained from ERI images via Archie's Law, which provide a more intuitive reflection of the variation of subsurface rainfall infiltration and a more capable means of estimating the stability of a landslide body. What is more, we then found that the averaged RWS is significantly correlated with daily precipitation. Our observations indicate that real-time ERI is effective in monitoring subterraneous rainfall infiltration, and thereby in estimating the stability of a potential landslide body. When the agglomerate rainfall in the landslide slippage surface was infiltrated quickly without sustaining hydraulic pressure along the landslide slippage surface, the probability of landslides occurring was very low. On the contrary, the probability of landslides occurring could be increased due to the overpressure of pore fluids. Keywords Electrical Resistivity Imaging; Depth-of-Investigation; Archie's Law; Landslide Monitoring; Rainfall Infiltration; Preferential Path

Non-parametric characterization of long-term rainfall time series

Science.gov (United States)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

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

A High-Resolution ENSO-Driven Rainfall Record Derived From an Exceptionally Fast Growing Stalagmite From Niue Island (South Pacific)

Science.gov (United States)

Troy, S.; Aharon, P.; Lambert, W. J.

2012-12-01

El Niño-Southern Oscillation's (ENSO) dominant control over the present global climate and its unpredictable response to a global warming makes the study of paleo-ENSO important. So far corals, spanning the Tropical Pacific Ocean, are the most commonly used geological archives of paleo-ENSO. This is because corals typically exhibit high growth rates (>1 cm/yr), and reproduce reliably surface water temperatures at sub-annual resolution. However there are limitations to coral archives because their time span is relatively brief (in the order of centuries), thus far making a long and continuous ENSO record difficult to achieve. On the other hand stalagmites from island settings can offer long and continuous records of ENSO-driven rainfall. Niue Island caves offer an unusual opportunity to investigate ENSO-driven paleo-rainfall because the island is isolated from other large land masses, making it untainted by continental climate artifacts, and its geographical location is within the Tropical Pacific "rain pool" (South Pacific Convergence Zone; SPCZ) that makes the rainfall variability particularly sensitive to the ENSO phase switches. We present here a δ18O and δ13C time series from a stalagmite sampled on Niue Island (19°00' S, 169°50' W) that exhibits exceptionally high growth rates (~1.2 mm/yr) thus affording a resolution comparable to corals but for much longer time spans. A precise chronology, dating back to several millennia, was achieved by U/Th dating of the stalagmite. The stalagmite was sampled using a Computer Automated Mill (CAM) at 300 μm increments in order to receive sub-annual resolution (every 3 months) and calcite powders of 50-100 μg weight were analyzed for δ18O and δ13C using a Continuous Flow Isotope Ratio Mass Spectrometer (CF-IRMS). The isotope time series contains variable shifts at seasonal, inter-annual, and inter-decadal periodicities. The δ13C and δ18O yield ranges of -3.0 to -13.0 (‰ VPDB) and -3.2 to -6.2 (‰ VPDB

Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

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Kumar, Brijesh; Patra, Kanhu Charan; Lakshmi, Venkat

2016-07-01

Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June-September or JJAS) from 2005-2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall. The detection of precipitation amount is strongly dependent on the topography. In the plains areas, TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimates the amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capture the high-intensity rain events but does well with low-intensity rain events in both hilly regions as well as the plain region. The continuous variable verification method shows better agreement of TRMM rainfall products with rain gauge data. TRMM fares better in the prediction of probability of occurrence of high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies that TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography.

EVALUATION OF RAINFALL-RUNOFF EROSIVITY FACTOR FOR CAMERON HIGHLAND, PAHANG, MALAYSIA

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Abdulkadir Taofeeq Sholagberu

2016-07-01

Full Text Available Rainfall-runoff is the active agent of soil erosion which often resulted in land degradation and water quality deterioration. Its aggressiveness to induce erosion is usually termed as rainfall erosivity index or factor (R. R-factor is one of the factors to be parameterized in the evaluation of soil loss using the Universal Soil Loss Equation and its reversed versions (USLE/RUSLE. The computation of accurate R-factor for a particular watershed requires high temporal resolution rainfall (pluviograph data with less than 30-minutes intensities for at least 20 yrs, which is available only in a few regions of the world. As a result, various simplified models have been proposed by researchers to evaluate R-factor using readily available daily, monthly or annual precipitation data. This study is thus aimed at estimating R-factor and to establish an approximate relationship between R-factor and rainfall for subsequent usage in the estimation of soil loss in Cameron highlands watershed. The results of the analysis showed that the least and peak (critical R-factors occurred in the months of January and April with 660.82 and 2399.18 MJ mm ha-1 h-1year-1 respectively. Also, it was observed that erosivity power starts to increase from the month of January through April before started falling in the month of July. The monthly and annual peaks (critical periods may be attributed to increased rainfall amount due to climate change which in turn resulted to increased aggressiveness of rains to cause erosion in the study area. The correlation coefficient of 0.985 showed that there was a strong relationship rainfall and R-factor.

Regional rainfall thresholds for landslide occurrence using a centenary database

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

2017-04-01

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

Temperature and rainfall interact to control carbon cycling in tropical forests.

Science.gov (United States)

Taylor, Philip G; Cleveland, Cory C; Wieder, William R; Sullivan, Benjamin W; Doughty, Christopher E; Dobrowski, Solomon Z; Townsend, Alan R

2017-06-01

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short-term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer-term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate - C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate - C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth. © 2017 John Wiley & Sons Ltd/CNRS.

The Impact of Climate Change in Rainfall Erosivity Index on Humid Mudstone Area

Science.gov (United States)

Yang, Ci-Jian; Lin, Jiun-Chuan

2017-04-01

It has been quite often pointed out in many relevant studies that climate change may result in negative impacts on soil erosion. Then, humid mudstone area is highly susceptible to climate change. Taiwan has extreme erosion in badland area, with annual precipitation over 2000 mm/y which is a considerably 3 times higher than other badland areas around the world, and with around 9-13 cm/y in denudation rate. This is the reason why the Erren River, a badland dominated basin has the highest mean sediment yield in the world, over 105 t km2 y. This study aims to know how the climate change would affect soil erosion from the source in the Erren River catchment. Firstly, the data of hourly precipitation from 1992 to 2016 are used to establish the regression between rainfall erosivity index (R, one of component for USLE) and precipitation. Secondly, using the 10 climate change models (provide form IPCC AR5) simulates the changes of monthly precipitation in different scenario from 2017 to 2216, and then over 200 years prediction R values can be use to describe the tendency of soil erosion in the future. The results show that (1) the relationship between rainfall erosion index and precipitation has high correction (>0.85) during 1992-2016. (2) From 2017 to 2216, 7 scenarios show that annual rainfall erosion index will increase over 2-18%. In contrast, the others will decrease over 7-14%. Overall, the variations of annual rainfall erosion index fall in the range of -14 to 18%, but it is important to pay attention to the variation of annual rainfall erosion index in extreme years. These fall in the range of -34 to 239%. This explains the extremity of soil erosion will occur easily in the future. Keywords: Climate Change, Mudstone, Rainfall Erosivity Index, IPCC AR5

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

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Renato Fontes Guimarães

2017-10-01

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

Apply data mining to analyze the rainfall of landslide

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Lee Chou-Yuan

2018-01-01

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

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

Science.gov (United States)

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

2013-04-01

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

The response of ungulates to rainfall along the riverbeds of the Southern Kalahari

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M. G. L Mills

1984-12-01

Full Text Available The responses of springbok Antidorcas marsupialis, gemsbok Oryx gazella, blue wildebeest Connochaetes taurinus and red hartebeest Alcelaphus buselaphus to rainfall along the riverbeds of the southern Kalahari are analysed. Springbok reacted most rapidly to rainfall along the riverbeds and, by browsing in dry times, maintained a fairly stable presence throughout the year, although the actual number present in any one year was dependent on annual rainfall. Gemsbok responded more slowly to rainfall and reached their highest numbers in years of high rainfall when the grasses were tall and mature, after which they rapidly departed from the riverbeds. Red hartebeest also reached their highest numbers during the rainy season, but departed slightly more slowly than gemsbok. In dry years, they too, failed to come into the riverbeds. Blue wildebeest in the vicinity of the riverbeds tended to be more sedentary than the other species. The presence of potable artificial water appeared to be more important for wildebeest than for the other species and, although rainfall was undoubtedly an important factor in regulating their numbers along the riverbeds, they depended to a greater extent on breeding success and mortality factors, than on emigration and immigration. The overall seasonal pattern of ungulate abundance along the riverbeds in the southern Kalahari was one of wet season concentrations and dry season dispersion.

Sediment yield during typhoon events in relation to landslides, rainfall, and catchment areas in Taiwan

Science.gov (United States)

Chen, Chi-Wen; Oguchi, Takashi; Hayakawa, Yuichi S.; Saito, Hitoshi; Chen, Hongey; Lin, Guan-Wei; Wei, Lun-Wei; Chao, Yi-Chiung

2018-02-01

Debris sourced from landslides will result in environmental problems such as increased sediment discharge in rivers. This study analyzed the sediment discharge of 17 main rivers in Taiwan during 14 typhoon events, selected from the catchment area and river length, that caused landslides according to government reports. The measured suspended sediment and water discharge, collected from hydrometric stations of the Water Resources Agency of Taiwan, were used to establish rating-curve relationships, a power-law relation between them. Then sediment discharge during typhoon events was estimated using the rating-curve method and the measured data of daily water discharge. Positive correlations between sediment discharge and rainfall conditions for each river indicate that sediment discharge increases when a greater amount of rainfall or a higher intensity of rainfall falls during a typhoon event. In addition, the amount of sediment discharge during a typhoon event is mainly controlled by the total amount of rainfall, not by peak rainfall. Differences in correlation equations among the rivers suggest that catchments with larger areas produce more sediment. Catchments with relatively low sediment discharge show more distinct increases in sediment discharge in response to increases in rainfall, owing to the little opportunity for deposition in small catchments with high connectivity to rivers and the transportation of the majority of landslide debris to rivers during typhoon events. Also, differences in geomorphic and geologic conditions among catchments around Taiwan lead to a variety of suspended sediment dynamics and the sediment budget. Positive correlation between average sediment discharge and average area of landslides during typhoon events indicates that when larger landslides are caused by heavier rainfall during a typhoon event, more loose materials from the most recent landslide debris are flushed into rivers, resulting in higher sediment discharge. The high

Distributional changes in rainfall and river flow in Sarawak, Malaysia

Science.gov (United States)

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

2017-11-01

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

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

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

2018-01-01

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

Regions Subject to Rainfall Oscillation in the 5–10 Year Band

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Jean-Louis Pinault

2018-01-01

Full Text Available The decadal oscillation of rainfall in Europe that has been observed since the end of the 20th century is a phenomenon well known to climatologists. Consequences are considerable because the succession of wet or dry years produces floods or, inversely, droughts. Moreover, much research has tried to answer the question about the possible link between the frequency and the intensity of extra-tropical cyclones, which are particularly devastating, and global warming. This work aims at providing an exhaustive description of the rainfall oscillation in the 5–10 year band during one century on a planetary scale. It is shown that the rainfall oscillation results from baroclinic instabilities over the oceans. For that, a joint analysis of the amplitude and the phase of sea surface temperature anomalies and rainfall anomalies is performed, which discloses the mechanisms leading to the alternation of high and low atmospheric pressure systems. For a prospective purpose, some milestones are suggested on a possible link with very long-period Rossby waves in the oceans.

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

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Ali, H.; Mishra, V.

2017-12-01

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

EFFECT OF RAINFALL INTENSITY AND ENERGY ON GULLY ...

African Journals Online (AJOL)

Also the galling impact of soil erosion on the study locations which were observed to have biophysical and socio-economic ramifications were looked at. Farming is the dominant land use of the area intensifies in two orders of magnitude annually. Also, the high rainfall belts of the study area, frail soil type, undulating ...

Mathematical and physical modeling of rainfall in centrifuge

OpenAIRE

CAICEDO, Bernardo; THOREL, Luc; TRISTANCHO, Julian

2015-01-01

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

Impact of Rainfall on Multilane Roundabout Flowrate Contraction

Science.gov (United States)

PARKSHIR, Amir; BEN-EDIGBE, Johnnie

2017-08-01

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

Estimation of return levels against different return periods of extreme annual rainfall over Baluchistan

International Nuclear Information System (INIS)

Ali, M.; Jan, B.; Iqbal, J.

2012-01-01

Unprecedented heavy monsoon rainfall began in the last week of July 2010 in the Northern part of our country, causes floods in Baluchistan and Sindh. As the high frequency rainfall events are a significant cause of current severe flooding in Pakistan and any fluctuation in the level of such events may cause huge economic losses as well as social problem, urban structures (i.e. dams, urban drainage systems and flood). Statistical distributions are used to identify extremes of annual rainfall of different cities of Baluchistan (Quetta, Sibbi, Khuzdar, Lasbella, Dalbandin and Pasni) with their return periods. Analysis predicts that Gumbel Max. (GM) Distribution is the best fitted distribution for Sibbi and Lasbella while the GEV distribution is the best fitted for Quetta, Khuzdar, Dalbandin and Pasni. The analysis also suggests that different cities of Baluchistan have 30-years return period for getting more than 90 mm average daily rainfall while they have 100-years return period for receiving more than 118 mm daily rainfall. This suggests for suitable flood forecasting and improving the river structure in Baluchistan, Pakistan. (author)

[Responses of sap flow to natural rainfall and continuous drought of tree species growing on bedrock outcrops].

Science.gov (United States)

Zhang, Hui Ling; Ding, Ya Li; Chen, Hong Song; Wang, Ke Lin; Nie, Yun Peng

2018-04-01

This study focused on bedrock outcrops, a very common habitat in karst region of southwest China. To reveal the responses of plant transpiration to natural rainfall and continuous drought, two tree species typical to this habitat, Radermachera sinica and Triadica rotundifolia, were selected as test materials. A rainout shelter was used to simulate continuous drought. The sap flow dynamics were monitored using the method of Granier's thermal dissipation probe (TDP). Our results showed that sap flow density increased to different degrees after rain in different stages of the growing season. Sap flow density of the deciduous species T. rotundifolia was always higher than that of the semi-deciduous species R. sinica. After two months without rainfall input, both species exhibited no obvious decrease in sap flow density, indicating that rainfall was not the dominant source for their water uptake, at least in the short-term. Based on the regression relationships between sap flow density and meteorological factors before and after rainfall, as well as at different stages of continuous drought, we found that the dynamics of meteorological factors contributed little to plant transpiration. The basic transpiration characteristics of both species were not changed in the circumstance of natural rainfall and short-term continuous drought, which would be closely related to the special water storage environments of bedrock outcrops and the reliance on deep water sources by tree species.

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

Energy Technology Data Exchange (ETDEWEB)

Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

2010-03-15

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

Science.gov (United States)

Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

2017-10-01

Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method

Reducing Production Basis Risk through Rainfall Intensity Frequency (RIF) Indexes: Global Sensitivity Analysis' Implication on Policy Design

Science.gov (United States)

Muneepeerakul, Chitsomanus; Huffaker, Ray; Munoz-Carpena, Rafael

2016-04-01

The weather index insurance promises financial resilience to farmers struck by harsh weather conditions with swift compensation at affordable premium thanks to its minimal adverse selection and moral hazard. Despite these advantages, the very nature of indexing causes the presence of "production basis risk" that the selected weather indexes and their thresholds do not correspond to actual damages. To reduce basis risk without additional data collection cost, we propose the use of rain intensity and frequency as indexes as it could offer better protection at the lower premium by avoiding basis risk-strike trade-off inherent in the total rainfall index. We present empirical evidences and modeling results that even under the similar cumulative rainfall and temperature environment, yield can significantly differ especially for drought sensitive crops. We further show that deriving the trigger level and payoff function from regression between historical yield and total rainfall data may pose significant basis risk owing to their non-unique relationship in the insured range of rainfall. Lastly, we discuss the design of index insurance in terms of contract specifications based on the results from global sensitivity analysis.

Computation of rainfall erosivity from daily precipitation amounts.

Science.gov (United States)

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

2018-10-01

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

Rainfall simulation for environmental application

Energy Technology Data Exchange (ETDEWEB)

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

1977-08-01

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

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

Science.gov (United States)

Rahimi, A.; Zhang, L.

2012-12-01

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

Characterizing rainfall in the Tenerife island

Science.gov (United States)

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

2017-04-01

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

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2018-05-01

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

A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

Directory of Open Access Journals (Sweden)

Velautham Daksiya

2017-01-01

Full Text Available The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

Rainfall Characteristic on the Slopes of Mount Merapi Region (Empirical Formula, Duration, Distribution, And Critical Line Woro River

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Pudak Juni Laksana

2015-05-01

Full Text Available Debris flow on the slopes of Mount Merapi area became a serious natural disasters because it has great destructive force and velocity. Rainfall with a certain intensity and duration is one component triggering debris flow. Rainfall has variability of the temporal and spatial characteristics influenced by various factors, such as topography and climate. Dharma (2012 suggested to define the characteristics of the intensity of rainfall using rainfall data with a shorter duration with statistical tests to establish the best empirical IDF formula.  This research was using of 30 minutes rainfall data for short duration (<3 hours and a spreadsheet software representing duration and distribution of the rainfall. The most appropriate rainfall intensity formula was done by the empirical IDF formula, i.e. Sherman, Kimijima, Hasper and Mononobe. Rainfall intensity analysis applied Frequency Analysis Software (based on Microsoft Excel. Debris flow occurrence was analyzed using MLIT for method A to establish standard rainfall index.  Sherman formula performed the best fit to the IDF characteristics of rainfall in the region of the slopes of Mount Merapi. Rainfall distribution pattern showed high intensity rainfall in the first hour and then decreased in the next hour which means distribution for the duration of 3 hours, 12%, 28%, 25%, 16%, 12%, and 7%, respectively with an interval of 30 minutes. Based on critical line, 5 mm of standard rainfall index was gained in the case of warning (R1 and 28 mm in the case of evacuation (R2.

Soil erosion under multiple time-varying rainfall events

Science.gov (United States)

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

2010-05-01

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

FREQUENCY ANALYSIS OF RAINFALL FOR FLOOD CONTROL IN ...

African Journals Online (AJOL)

The Niger Delta Region of Nigeria is within the mangrove forest region and is crisscrossed by series of streams and creeks. As a result of the high rainfall volume within this region there is a tendency for severe flooding to occur. These flood events have severe consequences on lives and properties. It is therefore necessary ...

Rainfall changes affect the algae dominance in tank bromeliad ecosystems

Science.gov (United States)

Pires, Aliny Patricia Flauzino; Leal, Juliana da Silva; Peeters, Edwin T. H. M.

2017-01-01

Climate change and biodiversity loss have been reported as major disturbances in the biosphere which can trigger changes in the structure and functioning of natural ecosystems. Nonetheless, empirical studies demonstrating how both factors interact to affect shifts in aquatic ecosystems are still unexplored. Here, we experimentally test how changes in rainfall distribution and litter diversity affect the occurrence of the algae-dominated condition in tank bromeliad ecosystems. Tank bromeliads are miniature aquatic ecosystems shaped by the rainwater and allochthonous detritus accumulated in the bases of their leaves. Here, we demonstrated that changes in the rainfall distribution were able to reduce the chlorophyll-a concentration in the water of bromeliad tanks affecting significantly the occurrence of algae-dominated conditions. On the other hand, litter diversity did not affect the algae dominance irrespective to the rainfall scenario. We suggest that rainfall changes may compromise important self-reinforcing mechanisms responsible for maintaining high levels of algae on tank bromeliads ecosystems. We summarized these results into a theoretical model which suggests that tank bromeliads may show two different regimes, determined by the bromeliad ability in taking up nutrients from the water and by the total amount of light entering the tank. We concluded that predicted climate changes might promote regime shifts in tropical aquatic ecosystems by shaping their structure and the relative importance of other regulating factors. PMID:28422988

Relationship between rainfall and microbiological contamination of ...

African Journals Online (AJOL)

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

Developing empirical relationship between interrill erosion, rainfall ...

African Journals Online (AJOL)

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

Statistical Modelling of Extreme Rainfall in Taiwan

NARCIS (Netherlands)

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

2012-01-01

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

Statistical Modelling of Extreme Rainfall in Taiwan

NARCIS (Netherlands)

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

2013-01-01

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

Rainfall thresholds for the possible occurrence of landslides in Italy

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M. T. Brunetti

2010-03-01

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