Parameter Sensitivity Analysis of a Korean Debris Flow-Induced Rainfall Threshold Estimation Algorithm

Author:

Choo Kyung-Su1ORCID,Choi Jung-Ryel2ORCID,Lee Byung-Hyun3,Kim Byung-Sik4ORCID

Affiliation:

1. Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University, Samcheok 25913, Republic of Korea

2. Technology Research Division, Korea Slope Safety Association, Sejong-si 30128, Republic of Korea

3. Laboratory of Climate and Smart Disaster Management, Kangwon National University, Samcheok 25913, Republic of Korea

4. Department of Artificial Intelligence and Software, Graduate School of Disaster Prevention, Kangwon National University, Samcheok 25913, Republic of Korea

Abstract

With the increase in both rainfall and intensity due to climate change, the risk of debris flows is also increasing. In Korea, the increasing damage caused by debris flows has become a social issue, and research on debris-flow response is becoming increasingly important. Understanding the rainfall that induces debris flows is crucial for debris-flow response, and methods such as the I-D method have been used to evaluate and predict the risk of debris flows. However, previous studies on debris flow-induced rainfall analysis have been limited by the subjective decision of the researcher to select the impact meteorological stations, which greatly affects reliability. In this paper, in order to establish an objective standard, various maximum allowable distances between debris-flow disaster areas and meteorological stations were adjusted to 1, 3, 5, 7, 9, 11, 13, and 15 km using the CTRL-T automatic calculation algorithm, and the optimal maximum allowable distance suitable for Korean terrain was derived through parameter sensitivity analysis. Based on this, we developed a nomogram for sediment disaster risk prediction and warning in Gangwon-do, and applied it to past disaster cases, and found that, although the prediction time for each stage varies depending on the maximum allowable distance, on average, it is possible to predict the risk of sediment flows 4 to 5 h in advance. It is believed that the results of this study can be used to reduce sediment flow damage in advance.

Funder

Ministry of Interior and Safety of the Korean government

Publisher

MDPI AG

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