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University of Khartoum (2017)

Rainfall - Runoff Modelling for Flood Forecasting For Tekzee-Settet- Atbara River

Ahmed, Samar Mohamed Khalafalla

Titre : Rainfall - Runoff Modelling for Flood Forecasting For Tekzee-Settet- Atbara River

Auteur : Ahmed, Samar Mohamed Khalafalla

Université de soutenance : University of Khartoum

Grade : Master of Science (MS) 2017

Résumé
This study aimed to develop a rainfall-runoff model based on Hydrologic Engineering Center’s-Hydrologic Modeling System (HEC-HMS), for flood forecasting in the Tekzee Settet Atbara Basin (TSA) in Eastern Sudan. The objective is to contribute to the early warning system for the Nile. The TSA is a transboundary basin shared between Ethiopia, Eritrea and Sudan. The study uses Satellite Based Rainfall Datasets (SBRD) derived from FEWS as well as runoff data for a period of six years (2008-2013) at two stations, namely Kubor (Rumella) at the out let of Upper Atbara River, and Wadelheliew (Bardana) at the out let of Settet River. Four years (2008-2011) were used for model calibration and the remaining two years (2012-2013) were used for model verification. The catchment boundaries and physical characteristics were derived using GIS for the two main basins Upper Atbara and Settet. Each basin consists of three subbasins (semi-distributed model). Simulations was conducted with HEC-HMS model using combinations of Initial and Constant loss, Clarck unit hydrograph transformation , Monthly constant base flow and Muskingum Routing with Losses /Gain. Meteorological data were considered using appropriate weights gages. Model calibration was conducted manually till the best fit between the observed and estimated peaks was obtained. Simulations results were evaluated based on three model performance measures, namely, Root Mean Square (RMSE), Nash and Sutcliffe Model Efficiency (NSE) and Correlation Coefficient (R). For results on daily basis, the model performance generally tended to overestimate the peaks for Upper Atbara and slightly underestimate them for Settet basin. For Rumella station, low values of NSE (<50%) were obtained for both calibration and verification when calculated on a whole years basis. However, the performance didn’t improve when NSE was estimated during wet season, only R was found to be larger than 60%, while RMSE was found to be 336.514 m3/which was close to the mean of Q observed of 393.529m3/s, indicating that the model results was poor. Bardana station had better performance of NSE >50%, R >70% and RMSE 188.95 m3/s, compared to standard deviation for observed flow of 274.5 m3/s. The study concluded that the statistical values have improved when the flows were aggregated to monthly and ten-day scales. At monthly scale, values of R were larger than 80%,NSE >50% and RMSE was found to be 123.20m3/s and 273.8 m3/s which was close to the half of standard deviation, indicating that the model results was good for both basins. On a ten-day basis, Settet`s R was 89%, NSE was equal to72% and RMSE 140.56 m3/s. For Upper Atbara’s R was 84% while NSE was equal to 41% and RMSE was found 258.12 m3/s. The overall results showed that a good correspondence for Settet`s basin peaks in years 2008, 2009 and 2011, while 2010 gave poor results. For Upper Atbara basin a good correspondence was obtained in 2008 and 2009 but poor in 2010 and 2011. TSA has limitations of adequate quality meteorological data, which imposes difficulty in reliable forecasting and prediction of flood occurrence and water availability in the basin. Therefore, the study recommended that more SBRD (TRMM, CMORPH and ECMWF) available for basin could be used to enhance model efficiency .Also, it is important to improve data exchange between transboundary countries. In addition, it recommended to use modelling tools that can simulate reservoirs

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Page publiée le 17 novembre 2018