Integrated analysis of hydrological components of the Seolma stream watershed by complementing SWAT model and RADAR-based data

This research focused on analyzing the hydrological characteristics of the Seolma stream watershed in Paju, Gyeonggi-do, South Korea. The study employed the SWAT model to evaluate various hydrological components, including precipitation, evapotranspiration, runoff, soil moisture, and groundwater recharge. Seolma stream, a small mountainous stream, was assessed for long-term runoff trends using data spanning from 2004 to 2023, which were then compared with observed records. The study also examined whether substituting rainfall observation data with RADAR-based values could enhance the accuracy of the runoff analysis. To address the absence of flow observation data for the period between June 2022 and April 2023, RADAR data and deep learning techniques were utilized to fill in the gaps.

Acknowledgements Research for this paper was carried out under the 2025 KICT Research Program (Development of IWRM-Korea Technical Convergence Platform Based on Digital New Deal) funded by the Ministry of Science and ICT.