Developing a lumped rainfall-runoff model in daily timestep for the Central European regions: A case study of the Czech Republic

Abstract

The negative impact of climate change mainly affects the delicate balance of the water cycle between precipitation, evaporation, discharge, and other interactions between the atmosphere and the surface of the earth. Thus, the adaptation of the environment to these changing hydrological conditions is crucial. One of the crucial tasks for the assessment of the environment adaptation is hydrological modeling. Hence, we propose a conceptual lumped water balance hydrological model which was developed for the Central European moderate climatic conditions. Based on previous works that aimed for a monthly timestep, this model's concept has been innovated to a daily timestep. The model was tested by modeling six catchments with a wide range of surface areas in the Czech Republic and using performance ranking system. Additionally, a comprehensive multi-model comparison was conducted across these catchments, further validating the robustness and superior performance of the proposed model.The negative impact of climate change mainly affects the delicate balance of the water cycle between precipitation, evaporation, discharge, and other interactions between the atmosphere and the surface of the earth. Thus, the adaptation of the environment to these changing hydrological conditions is crucial. One of the crucial tasks for the assessment of the environment adaptation is hydrological modeling. Hence, we propose a conceptual lumped water balance hydrological model which was developed for the Central European moderate climatic conditions. Based on previous works that aimed for a monthly timestep, this model's concept has been innovated to a daily timestep. The model was tested by modeling six catchments with a wide range of surface areas in the Czech Republic and using performance ranking system. Additionally, a comprehensive multi-model comparison was conducted across these catchments, further validating the robustness and superior performance of the proposed model.