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Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea
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Hazard Assessment Based on the Combination of DAN3D and Machine Learning Method for Planning Closed-Type Barriers against Debris-Flow

Department of Civil and Environmental Engineering, KAIST, Daejeon 34141, Korea
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Water 2020, 12(1), 170; https://doi.org/10.3390/w12010170 (registering DOI)
Received: 31 October 2019 / Revised: 16 December 2019 / Accepted: 3 January 2020 / Published: 7 January 2020
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
If a slope located near a densely populated region is susceptible to debris-flow hazards, barriers are used as a mitigation method by placing them in flow channels; i.e., flowpaths. Selecting the location and the design of a barrier requires hazard assessment to determine the width, volume, and impact pressure of debris-flow at the moment of collision. DAN3D (Three-Dimensional Dynamic Analysis), a 3D numerical model for simulating debris-flow, has been widely used to perform hazard assessment; however, solely using DAN3D would be both insufficient and inefficient in finding the optimal barrier location. Therefore, the present study developed a framework that interprets the results from DAN3D simulation without considering any barriers. Then, the framework generates hazard assessment maps showing the impact parameters of debris-flow along the flowpath by various algorithms and machine learning methods, such as the k-means clustering algorithm, and also computes the width of the debris-flow, which is not explicitly calculated in DAN3D. A case study of the debris-flow at Umyeon mountain, Korea, in 2011, was used to generate hazard assessment maps. The maps were demonstrated to be a tool to quickly compute the impact parameters for conceptual barrier design with the aim of finding potential barrier locations. View Full-Text
Keywords: debris flow; DAN3D; barrier; hazard assessment; machine learning; Umyeon mountain 2011 debris flow; DAN3D; barrier; hazard assessment; machine learning; Umyeon mountain 2011
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Cheon, E.; Lee, S.-R.; Lee, D.-H. Hazard Assessment Based on the Combination of DAN3D and Machine Learning Method for Planning Closed-Type Barriers against Debris-Flow. Water 2020, 12, 170.

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