Preprints
https://doi.org/10.5194/essd-2021-439
https://doi.org/10.5194/essd-2021-439

  14 Jan 2022

14 Jan 2022

Review status: this preprint is currently under review for the journal ESSD.

Retrogressive thaw slumps along the Qinghai-Tibet Engineering Corridor: a comprehensive inventory and their distribution characteristics

Zhuoxuan Xia1, Lingcao Huang1,4, Chengyan Fan2, Shichao Jia2, Zhanjun Lin3, Lin Liu1, Jing Luo3, Fujun Niu3, and Tingjun Zhang2 Zhuoxuan Xia et al.
  • 1Earth System Science Programme, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
  • 2Key Laboratory of West China's Environments (DOE), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
  • 3Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
  • 4Earth Science and Observation Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA

Abstract. The important Qinghai Tibet Engineering Corridor (QTEC) covers the part of the Highway and Railway underlain by permafrost. The permafrost on the QTEC is sensitive to climate warming and human disturbance and suffers accelerating degradation. Retrogressive thaw slumps (RTSs) are slope failures due to the thawing of ice-rich permafrost. They typically retreat and expand at high rates, damaging infrastructure, and releasing carbon preserved in frozen ground. Along the critical and essential corridor, RTSs are commonly distributed but remain poorly investigated. To compile the first comprehensive inventory of RTSs, this study uses an iteratively semi-automatic method built on deep learning to delineate thaw slumps in the 2019 PlanetScope CubeSat images over a ~54,000 km2 corridor area. The method effectively assesses every image pixel using DeepLabv3+ with limited training samples and manually inspects the deep-learning-identified thaw slumps based on their geomorphic features and temporal changes. The inventory includes 875 RTSs, of which 474 are clustered in the Beiluhe region, and 38 are near roads or railway lines. The dataset is available at https://doi.org/10.1594/PANGAEA.933957 (Xia et al., 2021), with the Chinese version at https://data.tpdc.ac.cn/zh-hans/disallow/50de2d4f-75e1-4bad-b316-6fb91d915a1a/. These RTSs tend to be located on north-facing slopes with gradients of 1.2°–18.1° and distributed at medium elevations ranging from 4511 to 5212 m. a.s.l. They prefer to develop on land receiving relatively low annual solar radiation (from 2900 to 3200 kWh m−2), alpine meadow covered, and silt loam underlay. The results provide a significant and fundamental benchmark dataset for quantifying thaw slump changes in this vulnerable region undergoing strong climatic warming and extensive human activities.

Zhuoxuan Xia et al.

Status: open (until 11 Mar 2022)

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Data sets

An Inventory of Retrogressive Thaw Slumps Along the Vulnerable Qinghai-Tibet Engineering Corridor Xia, Zhuoxuan; Huang, Lingcao; Liu, Lin https://doi.org/10.1594/PANGAEA.933957

An inventory of retrogressive thaw slumps along the vulnerable Qinghai-Tibet engineering corridor (2019) Xia, Zhuoxuan; Huang, Lingcao; Liu, Lin https://data.tpdc.ac.cn/zh-hans/disallow/50de2d4f-75e1-4bad-b316-6fb91d915a1a/

Zhuoxuan Xia et al.

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Short summary
Retrogressive thaw slumps are slope failures resulting from abrupt permafrost thaw, widely distributed along the Qinghai-Tibet Engineering Corridor. Due to the potential damage to infrastructure and the carbon emission of thaw slumps, we use a semi-automatic method and obtain a comprehensive inventory with 875 RTSs. The inventory fills the knowledge gap of thaw slump locations and provides key benchmarks for analyzing the distribution features and quantifying spatio-temporal changes.