격자기반 분포형 수문모형 Cell2Flood를 활용한 농업용 저수지 유역의 강우-유출 모의

Abstract

Recent climate change has increased the frequency and severity of flooding events, including super typhoons, localized heavy rainstorms, and torrentialdownpours. According to the Disaster Yearbook published by the Ministry of the Interior and Safety (MOIS), flood-related disasters, including heavyrain and typhoons, have accounted for 90% of total natural disaster damages over the past decade. The continuous and systematic collection ofmeteorological data (e.g., rainfall, water level, and flow rate) is crucial for hydrological analysis and forecasting to predict and prepare for floods. Floodcontrol centers have established measurement systems to facilitate forecasting. These centers monitor hydrological data every 10 minutes at rainfall andwater level observation stations and calculate runoff from rainfall to predict flood potential. Additionally, flood forecasts are issued when river waterlevels are anticipated to exceed flood warning or alert thresholds. However, compared to the flood forecasting systems currently in operation, predictivecapabilities for runoff and flood volume in agricultural reservoirs are lacking. Improved flood forecasting for agricultural reservoirs and catchments isneeded, utilizing meteorological forecasts and low water level measurement data. This study aims to apply a grid-based, distributed short-termhydrological model using weather forecast data, field-measured water level data, land cover data, Digital Elevation Model (DEM) data, and soil data. We will calibrate and validate a spatiotemporal rainfall-runoff analysis model for agricultural reservoirs.