A MULTI-COMPONENT MODEL FOR LONG-TERM RIVER FLOW FORECASTING

Abstract

The principle of seasonal forecast is to predict a range of most likely occurred values during the next season extending, probably, up to a year ahead. Seasonal flow forecast information could help in the decision-making process for water resources management. A response-based hydrologic model was developed by this research for long-term rainfall-runoff simulations over the river basins. The model overcomes the typical difficulties in estimating infiltration and evapotranspiration parameters using a modified version of the Soil Conservation Service curve number SCS-CN method. In addition, the model simulates the surface and groundwater hydrograph components using the response unit-hydrograph approach instead of using a linear reservoir routing approach for routing surface and groundwater to the basin outlet. The model is less sensitive to groundwater infiltration parameters since groundwater is actually controlled by the surface component and not the opposite. For that reason, the model is called the SCHydro model (Surface Controlled Hydrologic model). The Model was calibrated and validated over the upper Blue Nile basin using observed flow data at Diem station for the period (1990-2009) and (2010-2017) respectively. Three statistical criteria were used; Nash-Sutcliffe Efficiency (NSE), Percent Bias (Bias%) and Root Mean Squared Error to observation Standard Deviation Ratio (RSR), for the comparison. The results show that the developed model can simulate the long-term behavior of the upper Blue Nile basin due to its very good performance according to the values