• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1B
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• pp.41-51
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• 2010

In this study, runoff simulation was carried out in the area of Bisan 7-dong, Seo-gu, Daegu as drainage basin and the effects of the installation of underground storage facilities were analyzed during heavy rainfall. SWMM model was used for the runoff and pipe network analysis on Typhoon Maemi, 2003. 2-D inundation analysis model based on diffusion wave was employed for inundation analysis and to verify computed inundation areas with observed inundation trace map. The simulation results agree with observed in terms of inundation area and depth. Also, the effects of flood damage mitigation were analyzed through the overflow discharge and 2-D inundation analysis, depending upon whether the underground storage facility is installed or not. When the underground storage facility ($W:120m{\times}L:180m{\times}H:1.7m$) is installed, volume of overflow could be reduced by 72% and flooding area could be reduced by 40.1%. When the underground storage facility ($W:120m{\times}L:180 m{\times}H:2.0m$) is installed, volume of overflow could be reduced by 84.8% and flooding area could be reduced by 50.6%. When the underground storage facility ($W:120m{\times}L:180m{\times}H:2.2m$) is installed, volume of overflow could be reduced by 94% and flooding area could be reduced by 91.2%. There is no overflow of manhole, when the height of storage facility is 2.5 m. It is expected that the study results presented through quantitative analysis on the effects of underground facilities can be used as base data for socially and economically effective installation of underground facilities to prevent flood damage.