High-resolution assessment of retrogressive thaw slump susceptibility in the Qinghai-Tibet Engineering Corridor  

作　　者：GuoAn Yin Jing Luo FuJun Niu MingHao Liu ZeYong Gao TianChun Dong WeiHeng Ni 

机构地区：[1]Soil Engineering,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou,Gansu 730000,China [2]China Railway Qinghai-Tibet Group Co.,Ltd,Xining,Qinghai 810000,China [3]School of Engineering and Science,University of Chinese Academy of Sciences,Beijing 100049,China

出　　处：《Research in Cold and Arid Regions》2023年第6期288-294,共7页寒旱区科学（英文版）

基　　金：funded by the National Natural Science Foundation of China(42372334);the Science and Technology Research and Development Program of the Qinghai-Tibet Group Corporation(Grant No.QZ2022-G05)。

摘　　要：Under the rapidly warming climate in the Arctic and high mountain areas,permafrost is thawing,leading to various hazards at a global scale.One common permafrost hazard termed retrogressive thaw slump(RTS)occurs extensively in ice-rich permafrost areas.Understanding the spatial and temporal distributive features of RTSs in a changing climate is crucial to assessing the damage to infrastructure and decision-making.To this end,we used a machine learning-based model to investigate the environmental factors that could lead to RTS occurrence and create a susceptibility map for RTS along the Qinghai-Tibet Engineering Corridor(QTEC)at a local scale.The results indicate that extreme summer climate events(e.g.,maximum air temperature and rainfall)contributes the most to the RTS occurrence over the flat areas with fine-grained soils.The model predicts that 13%(ca.22,948 km^(2))of the QTEC falls into high to very high susceptibility categories under the current climate over the permafrost areas with mean annual ground temperature at 10 m depth ranging from-3 to-1℃.This study provides insights into the impacts of permafrost thaw on the stability of landscape,carbon stock,and infrastructure,and the results are of value for engineering planning and maintenance.

关 键 词：Retrogressive thaw slumps THERMOKARST Permafrost degradation Machine learning 

分 类 号：TU445[建筑科学—岩土工程] P642.14[建筑科学—土工工程]