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DC FieldValueLanguage
dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.contributor.advisorDing, Xiao-li (LSGI)en_US
dc.creatorLi, Jierui-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/13697-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleStudy on responsive relationship between climate dry-wet cycle and regional debris flow susceptibilityen_US
dcterms.abstractDebris flow is a type of gravity flow involving significant solid material movement, commonly occurring in mountainous areas. However, due to the threat debris flows pose to lives, properties, and infrastructures, preventing unexpected events is crucial. Challenges in quantitatively characterizing the formation and initiation mechanism of debris flows often lead to inaccurate warnings, either missing alarms or causing false ones. The frequency and scale of debris flows have increased due to recent extreme weather events. Though current warning techniques have considered extreme weather influences by extreme rainstorms or tropical cyclones, the impacts of extreme droughts and climate dry-wet cycles have been overlooked. Thus, preventing and mitigating debris flows regionally under extreme dry-wet events is a new scientific challenge. Urgent research is needed to explain the formation and initiation mechanisms of debris flows related to extreme weather.en_US
dcterms.abstractThis study focuses on the typical rainfall-induced debris flows in subtropical monsoon climates. Sichuan Province and the Hong Kong Special Administrative Region, both in mountainous areas of China, are selected as study areas. Historical debris flow inventories and geo-environmental databases, including geological, terrain, meteorological, soil, and land use, are compiled. Dry-wet cycle characteristics are derived from long-term historical dry-wet indices based on the geo-environmental databases using autocorrelation function, wavelet analysis, and multifractal spectrum analysis, while debris flow average recurrence intervals are estimated using historical debris flow inventories. Statistically based on dry-wet indices, in the two study areas of this study, debris flows occur when suffering extreme wet, while extreme drought generally exists 6-8 years before debris flow occurrences. The responsive relationship between climatic dry-wet cycles and debris flow susceptibility is explored by analyzing the debris flow average recurrence intervals and the dry-wet cycle characteristics in the study areas. Stronger correlations have been observed between debris flow recurrence interval and dry-wet cycles compared to that between debris flow recurrence interval and maximum rainfall, which is one of the most used factors for debris flow early warning. Soil sampling and testing in typical debris flow gullies help explain the mechanism behind the correlation between debris flow recurrence interval and dry-wet cycles. The dry-wet cycle characteristics are utilized to construct regional debris flow susceptibility assessment models. The responsive relationship between the climatic dry-wet cycles and debris flow susceptibility is further validated by promoting the machine learning model performance by 1-4%. The importance of dry-wet cycle characteristics in debris flow susceptibility assessment is quantitatively explained. Relative influence and partial dependence based on model structure further disclose the main drivers and their impacts on debris flow susceptibility. Factors affecting the performance of dry-wet cycle characteristics in debris flow susceptibility assessment models have been disclosed by comparing the model performance from different study regions.en_US
dcterms.abstractThis study reveals the responsive relationship and explains the mechanisms between extreme weather events and regional debris flow susceptibility. A method is proposed to assess the debris flow susceptibility by considering dry-wet cycle characteristics. The contributions of various factors to debris flow susceptibility are quantified, enabling targeted disaster prevention and mitigation plans.en_US
dcterms.extentxviii, 219 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2025en_US
dcterms.educationalLevelPh.D.en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHMudflowsen_US
dcterms.LCSHLandslide hazard analysisen_US
dcterms.LCSHClimatic extremesen_US
dcterms.LCSHRain and rainfallen_US
dcterms.LCSHSoil mechanicsen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsopen accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/13697