Performance assessment of a daily time-step HYMOD conceptual rainfall-runoff model for the Upper Benue River, Cameroon

Abstract

<p><span>Conceptual rainfall-runoff models are commonly used in many hydrological applications in support of water resources management practices. They provide an advantage in data scarce areas due to their ability to use limited data and generate sufficiently reliable information. The main challenge with this type of hydrological models remains the ability to establish an optimal model parameter space due to a number of sources of uncertainties. This study is conducted in the Upper Benue River Basin (UBRB) in Cameroon with the aim to establish a rainfall-runoff model that is fit in the context of hydro-climate characteristics of the basin. The UBRB is the second-largest river in Cameroon and one of the most important water resources in northern Cameroon from both a water supply and hydropower generation perspective. A Monte Carlo procedure was implemented to calibrate the HYMOD conceptual rainfall-runoff model using five statistical performance measures: the Absolute percent bias (PBIAS), the ratio between root mean square error (RMSE) and standard deviation of observed data (STDEVobs) (RSR), the Pearson correlation coefficient (r), the Nash–Sutcliffe efficiency (NSE) and the Kling–Gupta efficiency (KGE). The results reveal that the model performance varies from good to very good with NSE greater than 0.78 and RSR less than 0.46 during the calibration and validation periods. Therefore, this model can be used to support various water resources management initiatives in the basin.</span></p>