Bin Zhou , Qiang Zou , Hu Jiang , Tao Yang , Wentao Zhou , Siyu Chen , Zihao Zeng
{"title":"喜马拉雅地区多种机制引发的泥石流的概率图","authors":"Bin Zhou , Qiang Zou , Hu Jiang , Tao Yang , Wentao Zhou , Siyu Chen , Zihao Zeng","doi":"10.1016/j.ijdrr.2025.105444","DOIUrl":null,"url":null,"abstract":"<div><div>Debris flows pose a significant hazard in the Himalayas due to the region's diverse climatic conditions and complex topography. However, previous studies have predominantly focused on individual debris flow types, often neglecting the multi-triggering mechanisms that influence their occurrence. This limitation has reduced the accuracy of probability assessments and hindered the development of effective risk management strategies for vulnerable areas. To address this gap, we developed an indicator system that incorporates multi-triggering mechanisms and applied three hybrid machine learning models to comprehensively assess debris flow probability. These models generated probability maps for Rainfall-Triggered Debris Flow (RTDF), Glacier Debris Flow (GDF), Glacial Lake Outburst Debris Flow (GLODF), and multi-type debris flows. The results indicate that high RTDF probability is concentrated in the Yarlung Zangbo River Valley, the Indus River Valley, and the southern slope. High GDF probability is primarily located in the Western Himalayas, while high GLODF probability is predominantly distributed along the Central and Eastern Himalayan ridge. Notably, 52.98 % of catchments are vulnerable to at least one type of debris flow, with 2.04 % at risk from all three types. This study addresses a critical gap in debris flow probability assessment by integrating multi-triggering mechanisms, offering valuable insights to improve risk management and enhance resilience strategies in the Himalayas.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"122 ","pages":"Article 105444"},"PeriodicalIF":4.2000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probability mapping of debris flows triggered by multiple mechanisms in the Himalayas\",\"authors\":\"Bin Zhou , Qiang Zou , Hu Jiang , Tao Yang , Wentao Zhou , Siyu Chen , Zihao Zeng\",\"doi\":\"10.1016/j.ijdrr.2025.105444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Debris flows pose a significant hazard in the Himalayas due to the region's diverse climatic conditions and complex topography. However, previous studies have predominantly focused on individual debris flow types, often neglecting the multi-triggering mechanisms that influence their occurrence. This limitation has reduced the accuracy of probability assessments and hindered the development of effective risk management strategies for vulnerable areas. To address this gap, we developed an indicator system that incorporates multi-triggering mechanisms and applied three hybrid machine learning models to comprehensively assess debris flow probability. These models generated probability maps for Rainfall-Triggered Debris Flow (RTDF), Glacier Debris Flow (GDF), Glacial Lake Outburst Debris Flow (GLODF), and multi-type debris flows. The results indicate that high RTDF probability is concentrated in the Yarlung Zangbo River Valley, the Indus River Valley, and the southern slope. High GDF probability is primarily located in the Western Himalayas, while high GLODF probability is predominantly distributed along the Central and Eastern Himalayan ridge. Notably, 52.98 % of catchments are vulnerable to at least one type of debris flow, with 2.04 % at risk from all three types. This study addresses a critical gap in debris flow probability assessment by integrating multi-triggering mechanisms, offering valuable insights to improve risk management and enhance resilience strategies in the Himalayas.</div></div>\",\"PeriodicalId\":13915,\"journal\":{\"name\":\"International journal of disaster risk reduction\",\"volume\":\"122 \",\"pages\":\"Article 105444\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of disaster risk reduction\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212420925002687\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of disaster risk reduction","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212420925002687","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Probability mapping of debris flows triggered by multiple mechanisms in the Himalayas
Debris flows pose a significant hazard in the Himalayas due to the region's diverse climatic conditions and complex topography. However, previous studies have predominantly focused on individual debris flow types, often neglecting the multi-triggering mechanisms that influence their occurrence. This limitation has reduced the accuracy of probability assessments and hindered the development of effective risk management strategies for vulnerable areas. To address this gap, we developed an indicator system that incorporates multi-triggering mechanisms and applied three hybrid machine learning models to comprehensively assess debris flow probability. These models generated probability maps for Rainfall-Triggered Debris Flow (RTDF), Glacier Debris Flow (GDF), Glacial Lake Outburst Debris Flow (GLODF), and multi-type debris flows. The results indicate that high RTDF probability is concentrated in the Yarlung Zangbo River Valley, the Indus River Valley, and the southern slope. High GDF probability is primarily located in the Western Himalayas, while high GLODF probability is predominantly distributed along the Central and Eastern Himalayan ridge. Notably, 52.98 % of catchments are vulnerable to at least one type of debris flow, with 2.04 % at risk from all three types. This study addresses a critical gap in debris flow probability assessment by integrating multi-triggering mechanisms, offering valuable insights to improve risk management and enhance resilience strategies in the Himalayas.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.