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Evaluation and application of alternative rainfall data sources for forcing hydrologic models in the Mara Basin
Author(s) -
Tadesse Alemayehu,
Fidelis Kilonzo,
Ann van Griensven,
Willy Bauwens
Publication year - 2017
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 1996-9694
pISSN - 0029-1277
DOI - 10.2166/nh.2017.081
Subject(s) - streamflow , environmental science , soil and water assessment tool , climatology , forcing (mathematics) , climate forecast system , structural basin , surface runoff , hydrological modelling , rain gauge , scale (ratio) , hydrology (agriculture) , swat model , water resources , climate change , drainage basin , meteorology , precipitation , geography , geology , ecology , paleontology , oceanography , cartography , geotechnical engineering , biology
Accurate and spatially distributed rainfall data are crucial for a realistic simulation of the hydrological processes in a watershed. However, limited availability of observed hydro-meteorological data often challenges the rainfall–runoff modelling efforts. The main goal of this study is to evaluate the Climate Forecast System Reanalysis (CFSR) and Water and Global Change (WATCH) rainfall by comparing them with gauge observations for different rainfall regimes in the Mara Basin (Kenya/Tanzania). Additionally, the skill of these rainfall datasets to simulate the observed streamflow is assessed using the Soil and Water Assessment Tool (SWAT). The daily CFSR and WATCH rainfall show a poor performance (up to 52% bias and less than 0.3 correlation) when compared with gauge rainfall at grid and basin scale, regardless of the rainfall regime. However, the correlations for both CFSR and WATCH substantially improve at monthly scale. The 95% prediction uncertainty (95PPU) of the simulated daily streamflow, as forced by CFSR and WATCH rainfall, bracketed more than 60% of the observed streamflows. We however note high uncertainty for the high flow regime. Yet, the monthly and annual aggregated CFSR and WATCH rainfall can be a useful surrogate for gauge rainfall data for hydrologic application in the study area.

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