Run off modelling of the Mara River using Satellite Observed Soil Moisture and Rainfall

Hydrological models are essential in water resources management. However modeling in poorly gauged catchments is a big challenge. Recent research has shown that satellite based hydrological and meteorological data has the potential of being part of the solution towards overcoming this challenge. In this research, we modify the conceptual lumped rainfall-runoff model by Meier et al. (2011) to simulate the runoff of the Mara River basin. The model is developed based on the relationships found between satellite observed soil moisture and rainfall and the measured runoff. It uses the satellite observed rainfall as the prime forcing, and the soil moisture to separate the fast surface runoff and slow base flow contributions. The soil moisture and rainfall products used in this research are Advanced Scatterometer Soil Water Index (ASCAT SWI) and Tropical Rainfall Measurement Mission (TRMM) 3B42 v7 respectively. The performance of the model is evaluated for three sub-catchments defined by the Mara mines, Nyangores and Amala gauging stations along the Mara River. The Pearson correlation (r) for Mara mines Nyangores and Amala during calibration and (validation) were 0.54 (0.77), 0.67 (0.74), 0.125 (0.48) respectively. The model showed great potential in simulating dry season runoff, but needs further improvement to be able to reliably simulate wet season runoff. Nevertheless, this study demonstrates the potential role operational satellite based soil moisture and rainfall products can play in quantifying the available water resources particularly in the many un-gauged river basins across Africa.