Performance assessment and uncertainty prediction of a daily time-step HBV-Light rainfall-runoff model for the Upper Benue River Basin, Northern Cameroon

• DOI: 10.1016/j.ejrh.2021.100849
• Publication Date: 2021-06-15T15:44:24Z
• Authors: Rodric M. Nonki; André Lenouo; Raphael M. Tshimanga; Francine C. Donfack; Clément Tchawoua
• Keywords: Identifiability

The Upper Benue River Basin (UBRB), the second-largest river in Cameroon and one of most important water resources northern from both a supply hydro-power generation perspective. aim study is to establish rainfall-runoff model that fitted context hydro-climate characteristics basin. applies One-factor-At-Time (OAT) method for sensitivity analysis (SA) Monte-Carlo calibration parameter identifiability identify influential, well-identified optimal parameters, predict uncertainties conceptual-lumped -the daily HBV-Light model, basin using five performance measures. Based on individual SA, parameters were reduced nine parameters. This can reduce interaction between time-consuming therefore limiting prediction uncertainty. Despite arising calibrated sets themselves, results reveal varies good very good, while uncertainty behavioural reveals best simulation with regard measured streamflow lies within narrow 95 % band. Therefore, this be used support various management initiatives