Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa

Abstract. East Africa frequently faces extreme weather events like droughts and floods, underscoring the need for improved hydrological simulations to enhance prediction and mitigate losses. One of the main challenges in achieving this is low-quality of precipitation data and limitations in modelling skills. Due to drought sensitivity, flood proneness and data availability, the upper and middle stream of the Tana River basin was used as a case to address some of the challenge. We performed convection-permitting (CP) simulations using the Weather Research and Forecasting (WRF) model, and utilizing the CPWRF output as a driver we conducted WRF Hydrological modelling (WRF-Hydro) integrated with the lake/reservoir module. The CPWRF precipitation outperforms the ERA5 using IMERG as the benchmark, particularly for the precipitation amount over mountainous regions and light precipitation events (1–15 mm day^-1) in the dry seasons. The improved precipitation especially alleviates the peak false, when comparing the well-calibrated lake-integrated model driven by CRWRF output (LakeCal) to that by ERA5, with an NSE increase of 0.53. Additionally, the lake/reservoir module effectively mitigates the model-data bias, especially for dry-season flow and peak flow, when comparing the lake-integrated model (LakeCal) to the model without the lake (LakeNan), with an NSE increase of 1.67. The lake module makes river discharge more sensitive to spin-up time and affects discharge through lake-related parameters. Adjustments to the lake-integrated model’s runoff infiltration rate, Manning’s roughness coefficient, and the groundwater component have minimal impact on the dry-season flows. Dividing by the total NSE increase, hydrological modelling improvement is 24 % and 76 % from CPWRF simulation and lake module, respectively. Our findings highlight the enhanced hydrological modelling capability with the lake/reservoir module and CPWRF simulations, offering a valuable tool for flood and drought predictability in data-scarce regions such as East Africa.