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Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas

Journal of Mountain Science 2024年第10期21卷 3396-3412页

作者： UWIZEYIMANA David LIU Weiming HUANG Yu habumugisha jules maurice ZHOU Yanlian YANG Zewen State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of Sciences(CAS)Chengdu 610299China China–Pakistan Joint Research Center on Earth Sciences CAS-HECIslamabad 45320Pakistan University of Chinese Academy of Sciences Beijing 100049China

Climate warming is constantly causing hydro-meteorological perturbations,especially in high-altitude mountainous regions,which lead to the occurrences of *** impact of climatic variables(i.e.,precipitation and temperature)on the distribution of landslides in the eastern regions of the Himalayas is poorly *** address this,the current study analyzes the relationship between the spatial distribution of landslide characteristics and climatic variables from 2013 to *** Earth Engine(GEE)was employed to make landslide inventories using satellite *** results show that 2163,6927,and 9601 landslides were heterogeneously distributed across the study area in 2013,2017,and 2021,*** maximum annual temperature was positively correlated with the distribution of landslides,whereas precipitation was found to have a non-significant impact on the landslide ***,most of the landslides occurred in areas with maximum annual precipitation ranging from 800 to 1600 mm and maximum annual temperature above 15℃.However,in certain regions,earthquake disruptions marginally affected the occurrence of *** were highly distributed in areas with elevations ranging between 3000 and 5000 m above sea level,and many landslides occurred near the lower permafrost limit and close to *** latter indicates that temperature change-induced freeze-thaw action influences landslides in the *** changes have shown a positive correlation with the number of landslides within elevations,indicating that temperature affects their spatial *** climate projections suggest that the region will experience further warming,which will increase the likelihood of landslides in the ***,it is crucial to enhance ground observation capabilities and climate datasets to effectively monitor and mitigate landslide risks.

关键词： Landslide inventory Climate variables Normalized difference vegetation index Cryosphere Eastern Himalaya

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Flooding and its relationship with land cover change, population growth, and road density

引用

Geoscience Frontiers 2021年第6期12卷 16-35页

作者： Mahfuzur Rahman Chen Ningsheng Golam Iftekhar Mahmud Md Monirul Islam Hamid Reza Pourghasemi Hilal Ahmad jules maurice habumugisha Rana Muhammad Ali Washakh Mehtab Alam Enlong Liu Zheng Han Huayong Ni Tian Shufeng Ashraf Dewan Key Laboratory for Mountain Hazards and Earth Surface Process Institute of Mountain Hazards and Environment(IMHE)Chinese Academy of Sciences(CAS)Chengdu 610041China University of Chinese Academy of Sciences(UCAS) Beijing 100049China Department of Civil Engineering International University of Business Agriculture and Technology(IUBAT)Dhaka 1230Bangladesh Academy of Plateau Science and Sustainability Xining 810016China Development Research Initiative Dhaka 1216Bangladesh Department of Natural Resources and Environmental Engineering College of AgricultureShiraz UniversityShiraz 71454Iran School of Architecture Neijiang Normal UniversityNeijiang 641100China Institute of Tibetan Plateau Research Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Hydraulics and Mountain River Engineering College of Water Resource and HydropowerSichuan UniversityChengdu 610065China School of Civil Engineering Central South UniversityChangsha 410075China Chengdu Institute of Geology and Mineral Resources China Geological SurveyChina School of Earth and Planetary Sciences Curtin UniversityKent StBentleyWA 6102Australia

Bangladesh experiences frequent hydro-climatic disasters such as *** disasters are believed to be associated with land use changes and climate ***,identifying the factors that lead to flooding is *** study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve—receiver operating characteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC>90%)standalone and other ensemble models for the three time periods ***,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the period between 2000 and *** results showed that areas with very high susceptibility to flooding increased by 19.72%between 2000 and 2017,while the PG rate increased by 51.68%over the same *** Pearson correlation coefficient for RCF and RD was calculated to be *** findings highlight the significant association between floods and causative *** study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.

关键词： Hydro-climatic disasters Machine learning algorithms Statistical model Ensemble model Relative change in flooding areas

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