Water resources assessment in poorly gauged and ungauged basins demand supportive rainfall-runoff estimation, while resolving practical water resource management and planning issues. In this study, the research method...Water resources assessment in poorly gauged and ungauged basins demand supportive rainfall-runoff estimation, while resolving practical water resource management and planning issues. In this study, the research method employed involves rainfall-runoff modeling and simulation with proper efficiency criteria evaluation using the MODMENS modeling platform, a numerical rainfall-runoff semi-distributed GR2M conceptual lumped model. The rainfall-runoff simulation was carried-out in three selected sub-basins of Lower River Niger Basin based on observable discharge dataset. Related error estimation was carried-out to estimate the runoff simulation uncertainty while model optimization approach entails use of Rosenbrock-Simplex method and model reliability evaluation entails the use of Nash and Sutcliffe efficiency criteria methods. Result shows a satisfactory model performance at Baro and Makurdi gauging stations （savannah ecological zone） while under-estimation characterizes simulated flow at Onitsha gauging station（Forest ecological region）. Seasonally, the model best fit the dry season flow but underestimate during the high flow periods （rainy seasons and wetter years）.展开更多
文摘Water resources assessment in poorly gauged and ungauged basins demand supportive rainfall-runoff estimation, while resolving practical water resource management and planning issues. In this study, the research method employed involves rainfall-runoff modeling and simulation with proper efficiency criteria evaluation using the MODMENS modeling platform, a numerical rainfall-runoff semi-distributed GR2M conceptual lumped model. The rainfall-runoff simulation was carried-out in three selected sub-basins of Lower River Niger Basin based on observable discharge dataset. Related error estimation was carried-out to estimate the runoff simulation uncertainty while model optimization approach entails use of Rosenbrock-Simplex method and model reliability evaluation entails the use of Nash and Sutcliffe efficiency criteria methods. Result shows a satisfactory model performance at Baro and Makurdi gauging stations （savannah ecological zone） while under-estimation characterizes simulated flow at Onitsha gauging station（Forest ecological region）. Seasonally, the model best fit the dry season flow but underestimate during the high flow periods （rainy seasons and wetter years）.
