HYDROLOGICAL MODELING FOR FLOOD FORECASTING IN NIGER RIVER BASIN: BENUE SUB BASIN, NIGERIA

Flood forecasting can help to reduce the socio-economical and ecological effect of flood hazard in Benue Sub Basin, in Nigeria. The objective of this study is to set-up parsimonious flood forecasting model as an input to flood warning in central part of Nigeria. In this study, high resolution (TRMM-3B42) satellite rainfall product was used for model calibration and real time (TRMM-3B42RT) and forecasted (ECMWF) rainfall products were evaluated for flood forecasting. The implications of the TRMM-3B42 and TRMM-3B42RT bias were evaluated. The HEC-HMS rainfall-runoff hydrological model was selected for this study. Performance of the rainfall-runoff model was assessed using Nash- Sutcliffe Efficiency (NSE), Coefficient of determination (R 2 ) and Relative Volume Error (RVE) and percentage error of peak flow (PEPF) performance indices. Real time flow forecast assessment is conducted with respect to three different flood warning threshold levels (Medium, severe and very severe) for 1 to 6 days lead time. The forecast skill was assessed using categorical verification statistical such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). It is found that the model performance was satisfactory in terms of reproducing the observed hydrograph for the Benue basin at Makurdi station though the performance slightly deteriorated for the calibration period. For the study area, the bias of both the operational and real time satellite rainfall product should be corrected to improve forecast skill. When evaluating the graphical forecast skill the bias corrected TRMM- 3B42RT flood forecast was more accurate than the ECMWF flood forecast. Satellite based rainfall product are important for data scarcity area and crucial input for real time flood forecasting model. However, the model performance may be improved further by considering additional rain gauges for the bias correction of satellite products.