Risk Assessment of Debris Flow Disasters Triggered by an Outburst of Huokou Lake in Antu County Based on an Information Quantity and Random Forest Approach

Debris flow disasters frequently occur and pose considerable hazards; thus, it is essential to thoroughly evaluate their risks. This study constructs a database comprising 20 assessment indicators, utilizing comprehensive natural disaster risk assessment theory and incorporating the triggering factors of Huokou Lake in the Changbaishan Mountains. This research employs a hybrid ANP-CRITIC methodology to allocate weights to the assessment indicators efficiently. For hazard assessment, this research utilizes both the Information Quantity and Random Forest models for comparative analysis. The ROC curve was employed to validate the outcomes, ultimately favoring the Random Forest model due to its superior accuracy in assessing debris flow hazards. In this study, the risk of debris flow disasters in Antu County is comparatively assessed under scenarios with and without an outburst event. The findings indicate that areas of high and very high risk are predominantly located within the central regions of economically prosperous and densely populated townships. Additionally, the risk in Erdao Baihe Township escalates significantly when considering the outburst of Huokou Lake. The significance of this study lies in its ability to furnish a robust scientific basis for decision-makers aimed at preventing future debris flow disasters. Furthermore, it serves as a crucial reference for advancing sustainable regional development and facilitates the equilibrium between economic growth and environmental protection within disaster management strategies.

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Publication Details

Journal
Sustainability
Published
2024-11-01
DOI
https://doi.org/10.3390/su16219545
Citations
2
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
1.42
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article

Risk Assessment of Debris Flow Disasters Triggered by an Outburst of Huokou Lake in Antu County Based on an Information Quantity and Random Forest Approach

Jintao Huang, Qiuling Lang, Yichen Zhang, Peng Liu et al.
2 citations
Sustainability
Landslides and related hazards
1.42
article

Risk Assessment of Debris Flow Disasters Triggered by an Outburst of Huokou Lake in Antu County Based on an Information Quantity and Random Forest Approach

Jintao Huang, Qiuling Lang, Yichen Zhang, Peng Liu, Jiquan Zhang
article en
2 citations

Abstract

Debris flow disasters frequently occur and pose considerable hazards; thus, it is essential to thoroughly evaluate their risks. This study constructs a database comprising 20 assessment indicators, utilizing comprehensive natural disaster risk assessment theory and incorporating the triggering factors of Huokou Lake in the Changbaishan Mountains. This research employs a hybrid ANP-CRITIC methodology to allocate weights to the assessment indicators efficiently. For hazard assessment, this research utilizes both the Information Quantity and Random Forest models for comparative analysis. The ROC curve was employed to validate the outcomes, ultimately favoring the Random Forest model due to its superior accuracy in assessing debris flow hazards. In this study, the risk of debris flow disasters in Antu County is comparatively assessed under scenarios with and without an outburst event. The findings indicate that areas of high and very high risk are predominantly located within the central regions of economically prosperous and densely populated townships. Additionally, the risk in Erdao Baihe Township escalates significantly when considering the outburst of Huokou Lake. The significance of this study lies in its ability to furnish a robust scientific basis for decision-makers aimed at preventing future debris flow disasters. Furthermore, it serves as a crucial reference for advancing sustainable regional development and facilitates the equilibrium between economic growth and environmental protection within disaster management strategies.

SustainabilityVol. 16(21)
Northeast Normal University (CN), Changchun Institute of Technology (CN)
Climate action
Openalex Percentile: Top 14%
Landslides and related hazards
1.42
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