Sensitivity analysis and calibration of a semi-distributed HBV model in the data-limited and regulated Nile River Basin

The Nile River Basin Developing hydrologic models for large transboundary basins characterized by significant spatial variability, complexity, and limited data is a particularly challenging task. This study conducts a parameter sensitivity analysis and multi-site calibration of the Nile River Basin (NRB) semi-distributed HBV hydrologic model emulated by the Raven framework. The sensitivity analysis included 40 hydrologic and routing parameters to identify the most significant parameters at nine subbasins using the Normalized Sensitivity Coefficient (NSC) method. We then investigated five different calibration approaches, which are based on subbasin types (natural or regulated), calibration procedure, and dam operation rules’ simulation method, at fifteen subbasin outlets. The results revealed 21 significant parameters to be tuned in the model calibration and therefore indicate the most relevant data to be collected in the study area. Soil parameters, including hygroscopic minimum saturation, field capacity saturation, and topsoil thickness, were top-ranked in most subbasins, except the Lake Tana subbasin, where the lake control parameter was most significant. Model calibration and validation showed good performances at natural subbasins and Blue Nile’s regulated subbasins, where dam operation rules were available with adequate details. However, performance varied at other regulated subbasins where data limitation is more severe. The calibration approach, which involves separately tuning natural subbasin parameters and simulating the annual cycle of monthly streamflow, achieved the overall best performance. This study’s findings help guide future hydrologic modelling studies in the NRB and similar basins. • Performed sensitivity analysis for 40 parameters in the Nile Basin hydrologic model. • Identified 21 significant parameters, with soil and lake parameters top-ranked. • Investigated five approaches to multi-site calibration of the Nile hydrologic model. • Separately tuning natural subbasin parameters achieved the best overall performance. • Future research should refine the calibration approaches for other regions/models.