Review of research on testing and models of the trigger mechanism of slope debris flows
Slope debris flow (SDF) is a common geological disaster with complex formation processes and strong destructive forces causing significant casualties and economic losses in mountainous areas worldwide. Experimental research and models of the trigger mechanism of SDF are the key scientific issues as...
Published in: | NATURAL HAZARDS |
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Main Authors: | , , , , |
Format: | Article; Early Access |
Language: | English |
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SPRINGER
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001177377200001 |
author |
Zhao Yuandi; Saadon Azlinda; Abdullah Jazuri; Amini Pishro Ahad |
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Zhao Yuandi; Saadon Azlinda; Abdullah Jazuri; Amini Pishro Ahad Review of research on testing and models of the trigger mechanism of slope debris flows Geology; Meteorology & Atmospheric Sciences; Water Resources |
author_facet |
Zhao Yuandi; Saadon Azlinda; Abdullah Jazuri; Amini Pishro Ahad |
author_sort |
Zhao |
spelling |
Zhao, Yuandi; Saadon, Azlinda; Abdullah, Jazuri; Amini Pishro, Ahad Review of research on testing and models of the trigger mechanism of slope debris flows NATURAL HAZARDS English Article; Early Access Slope debris flow (SDF) is a common geological disaster with complex formation processes and strong destructive forces causing significant casualties and economic losses in mountainous areas worldwide. Experimental research and models of the trigger mechanism of SDF are the key scientific issues as they provide the basis for studying technologies for the prevention, mitigation, prediction, and forecasting of these disasters. This paper summarizes the methods of data collection, analysis, and status of recent experimental research on the trigger mechanism and models of SDF under the action of artificial rainfall. The main progress and theoretical achievements related to the SDF are discussed in terms of the experimental parameter settings, the mechanism of water-soil coupling action, and the start-up model of SDF. On this basis, the suggestions for experimental research on the mechanism and models of triggers for debris flows are proposed. First, future experiments on debris flow triggering should increase the similarities between rainfall patterns and loose soil characteristics. Second, the mechanism research of SDF is needed on the changes in the physical and mechanical characteristics of soil and the response to debris flow triggers under enhanced rainfall. Third, the parameters of the debris flow trigger model should be simplified, and the model's applicability should be improved with artificial intelligence. Through these efforts, the debris flow trigger test under artificial rainfall should be developed and refined, and the microscopic and multi-factor correlations of water-soil coupling should be applied to reveal the debris flow trigger mechanism in greater detail and establish a more applicable model of debris flow triggering. SPRINGER 0921-030X 1573-0840 2024 10.1007/s11069-024-06478-4 Geology; Meteorology & Atmospheric Sciences; Water Resources WOS:001177377200001 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001177377200001 |
title |
Review of research on testing and models of the trigger mechanism of slope debris flows |
title_short |
Review of research on testing and models of the trigger mechanism of slope debris flows |
title_full |
Review of research on testing and models of the trigger mechanism of slope debris flows |
title_fullStr |
Review of research on testing and models of the trigger mechanism of slope debris flows |
title_full_unstemmed |
Review of research on testing and models of the trigger mechanism of slope debris flows |
title_sort |
Review of research on testing and models of the trigger mechanism of slope debris flows |
container_title |
NATURAL HAZARDS |
language |
English |
format |
Article; Early Access |
description |
Slope debris flow (SDF) is a common geological disaster with complex formation processes and strong destructive forces causing significant casualties and economic losses in mountainous areas worldwide. Experimental research and models of the trigger mechanism of SDF are the key scientific issues as they provide the basis for studying technologies for the prevention, mitigation, prediction, and forecasting of these disasters. This paper summarizes the methods of data collection, analysis, and status of recent experimental research on the trigger mechanism and models of SDF under the action of artificial rainfall. The main progress and theoretical achievements related to the SDF are discussed in terms of the experimental parameter settings, the mechanism of water-soil coupling action, and the start-up model of SDF. On this basis, the suggestions for experimental research on the mechanism and models of triggers for debris flows are proposed. First, future experiments on debris flow triggering should increase the similarities between rainfall patterns and loose soil characteristics. Second, the mechanism research of SDF is needed on the changes in the physical and mechanical characteristics of soil and the response to debris flow triggers under enhanced rainfall. Third, the parameters of the debris flow trigger model should be simplified, and the model's applicability should be improved with artificial intelligence. Through these efforts, the debris flow trigger test under artificial rainfall should be developed and refined, and the microscopic and multi-factor correlations of water-soil coupling should be applied to reveal the debris flow trigger mechanism in greater detail and establish a more applicable model of debris flow triggering. |
publisher |
SPRINGER |
issn |
0921-030X 1573-0840 |
publishDate |
2024 |
container_volume |
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container_issue |
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doi_str_mv |
10.1007/s11069-024-06478-4 |
topic |
Geology; Meteorology & Atmospheric Sciences; Water Resources |
topic_facet |
Geology; Meteorology & Atmospheric Sciences; Water Resources |
accesstype |
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id |
WOS:001177377200001 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001177377200001 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1809678795151507456 |