Performance assessment of daily GR conceptual rainfall-runoff models in the Upper Benue River (Cameroon) using airGR packages

Abstract

Many hydrological applications employ conceptual-lumped rainfall-runoff models to support water resource management techniques. Because of their ability to exploit minimal data and provide enough credible information, they provide an edge in data-scarce domains. The purpose of this research is to evaluate the feasibility of using multiple rainfall-runoff hydrologic models Génie Rural à 4, 5, 6 paramètres Journalier (GR4J, GR5J, and GR6J) in the Upper Benue River (UBR) in Northern Cameroon. The models were calibrated using Michel's calibration algorithm implemented in airGR packages, while considering different objective functions (NSE, KGE, composite criterion). The objective here was to find the optimum objective function that takes into account the various components of the hydrographs in this watershed and to assess the impact of the chosen objective function on parameter optimization. The results reveal that the model performance as well as the optimized parameters of the different GR models vary according to the selected objective function. According to the study, adopting the composite criterion as an objective function during model calibration improves model accuracy. The model's performance reveals that two of the three models (GR5J and GR6J) reproduced the discharge well in the considered catchment, with NSE and KGE greater than 0.62 during the model validation. This highlights how these two GR models can be applied to various water management concerns in the UBR.