A Proposed Method for Calculating the Rainfall Threshold Based on the Multi-Method to Provide Heavy Rain Disaster Impact Information.

Recently, Korea has been affected by various disasters caused by climate change and the resulting changes in weather, which have been taking an increasing toll on the country. A review of weather phenomena and their socioeconomic impact identified weather disasters as one of the most damaging categories of disasters. As such, this study suggests a method for calculating the rainfall threshold to predict the impact of heavy rain. In order to calculate the rainfall threshold based on the multi-method, the entire territory of South Korea was divided into 1 km by 1 km grids, and a method for calculating the rainfall threshold was proposed by grouping them into four categories: standard watershed, urban areas, rivers, and inundation traces. This study attempted to verify the results of the rainfall threshold in standard watersheds and urban areas. The results were verified using the data from events during the heavy rain in Seoul in 2022 and 2018, the heavy rain in Busan in 2020, and Typhoon Mitag in October 2019. As a result of the verification and calculation, a rainfall threshold was found on the grid where the actual flooding damage occurred in Busan, where heavy rain caused a large amount of urban flooding in July 2020. The application of the rainfall threshold on the grid caused enough damage to flood vehicles. After this application, it was found that flooding of more than 0.2 m affected vehicles. During early September in the Gangneung grid, flooding damage was caused by Typhoon Haishen, which affected traffic. In this damaged grid, it was also found that flooding of more than 0.2 m occurred according to the rainfall impact limit. In this study, since there were no quantitative data, verification was performed using qualitative data such as news and SNS. Therefore, quantitative verification methods using flooding sensors and CCTVs need to be carried out in the future. After verification using qualitative data, we found that the time when the actual flooding damage occurred and the flooding patterns were well ascertained. The rainfall threshold calculation method and the rainfall prediction information developed in this study are expected to be applicable to impact forecasting, which can provide people affected by heavy rainfall with information on how the rainfall will affect them, as well as simple rainfall forecasts. [ABSTRACT FROM AUTHOR]