Different strategies of the catchment division in the process of multi-objective calibrating the conceptual rainfall-runoff model

While the familiar path of experimenting with multi-objective calibrating a conceptual rainfall-runoff model involves the whole catchment area, this study examines and compares various spatial divisions of the catchment during the calibration process. The input data that is used includes runoff values (Q), precipitation (P), air temperature (T), and potential evapotranspiration (PET). Additionally, values of soil moisture obtained by the sensors of the remote sensing source (advanced scatterometer (ASCAT) remote sensing product-ASCAT SWI) were also incorporated into the analysis within a selected catchment in Slovakia. This study provides insights into the best practices for integrating satellite soil moisture data into multi-objective calibration. Moreover, including satellite soil moisture data is particularly significant, offering a novel perspective on moisture dynamics within the catchment. One of the objectives of this research is to identify the optimal spatial division of the catchment, explicitly evaluating the effectiveness of elevation-based division versus land cover-based division. These different catchment subdivisions should point to the impact on the accuracy and reliability of the rainfall-runoff model. The calibration strategy chosen for this study is divided into the period from 2007 to 2014 for the calibration run and for the validation run chosen period from 2015 to 2019. First results show improvement of soil moisture correlation results in land cover-based division contrary to elevation zone subdivision, in the whole period of calibration (2007-2014), as well as in only summer months period (June, July, August and September). Different established calibration strategies should offer a robust framework for calibrating the rainfall-runoff model in future. Acknowledgement This study was supportedby the VEGA Grant Agency No. VEGA 1/0577/23.