Nzoia River Basin is an important water resources development and management unit not only in Kenya but also in the region. The basin drains into Lake Victoria, frequently experiences severe flooding and the catchment area has recently been dominated by unsustainable human activities. The resulting perturbations coupled with a changing climate could have far reaching consequences in the near future. Efforts to understand the influence of the changes is complicated by a dwindling hydro-meteorological network. This study explored the efficacy of satellite data to estimate run-off time series for the basin. NAM model in Mike 11 was set-up, calibrated and validated. A run-off time series was then generated. The Goddard Earth Observing System model version 5 (GEOS-5) satellite data from NASA was then used to derive run-off series when calibrated and when not. The results were compared to identify which approach resulted to better estimates. The optimal runoff model parameters observed were 12.7 for Umax, 136 for Lmax, 0.2 for CQOF, 1100 for CKIF, 61.65 for CK1, 2, 0.248 for TOF, 0.198 for TIF, 0.0495 for TG and 2825 for CKBF. These gave a water balance of about 0.98 and root mean square error of about 460 with R2 of 0.9 and 0.8 for calibration and validation, respectively. Calibrated GEOS-5 data performed reasonably well in runoff estimation for Nzoia basin. While non-calibrated satellite data was poor with an r-squared of 0.6 in relation to observed discharge, calibrated data performed way better with an r-squared of 0.96 for daily values. Satellite derived runoff was found to overestimate the discharge especially the peak discharges. This study showed that satellite data such as NASA's GEOS-5 when adequately calibrated provide suitable estimates for discharges in basins that are sparsely gauged.
Nzoia River Basin is a critical water resources development and management unit but useful decisions cannot be made since the hydro-meteorological network is declining.
Satellite data has been explored to access their efficacy in run-off generation.
Surface-groundwater interaction is the main aspect that influences run-off generation.
Better estimates were derived from calibrated GEOS-5.