Integrating Satellite Rainfall Estimates with Hydrological Water Balance Model: Rainfall-Runoff Modeling in Awash River Basin, Ethiopia

Hydrologic models play an indispensable role in managing the scarce water resources of a region, and developing countries, availability distribution data are challenging. This research aimed to integrate compare satellite rainfall products, namely, Tropical Rainfall Measuring Mission (TRMM 3B43v7) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), with GR2M hydrological balance model over diversified terrain Awash River Basin Ethiopia. Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient determination (R2), root mean square error (RMSE) Pearson correlation (PCC) were used evaluate products hydrologic performances basin. The estimations both showed higher PCC (above 0.86) areal observed Uplands, Western highlands, Lower sub-basins. However, it was weakly associated Upper valley Eastern catchments basin ranging 0.45 0.65. findings assimilated exhibited that 80% calibrated 60% validated watersheds had lower magnitude PBIAS (<±10), which resulted better accuracy flow simulation. poor performance (≥±25) only Melka Kuntire 3B43v7 PERSIANN-CDR), Mojo Metehara (in all sets), Kessem watersheds. Therefore, integrating these data, particularly data-scarce basin, generally appeared be useful. validation ground is required for effective planning management Furthermore, recommended make corrections poorlyww performing before assimilating model.