Permafrost Degradation Risk Evaluation in the Qinghai-Tibet Plateau Under Climate Change Based on Machine Learning Models

被引:3
|
作者
Zhang, Mingyi [1 ,2 ]
Li, Renwei [1 ,2 ]
Pei, Wansheng [1 ,2 ]
Zhou, Yanqiao [1 ,2 ]
Li, Guanji [1 ,2 ]
Yang, Sheng [1 ,2 ]
机构
[1] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Frozen Soil Engn, Lanzhou, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
climate warming; permafrost degradation; mean annual ground temperature; active layer thickness; Qinghai-Tibet Plateau; THERMAL STATE; ACTIVE LAYER; AREA;
D O I
10.1029/2023JD039611
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Permafrost in the Qinghai-Tibet Plateau (QTP) is sensitive to climate warming, but the associated degradation risk still lacks accurate evaluation. To address this issue, machine learning (ML) models are established to simulate the mean annual ground temperature (MAGT) and active layer thickness (ALT), and climate data from shared socioeconomic pathways (SSPs) are prepared for evaluation in the future period. Based on the projections, permafrost is expected to remain relatively stable under the SSP1-2.6 scenario, and large-scale permafrost degradation will occur after the 2050s, resulting in area losses of 30.15% (SSP2-4.5), 58.96% (SSP3-7.0), and 65.97% (SSP5-8.5) in the 2090s relative to the modeling period (2006-2018). The average permafrost MAGT (ALT) is predicted to increase by 0.50 degrees C (59 cm), 0.67 degrees C (89 cm), and 0.79 degrees C (97 cm) in the 2090s with respect to the modeling period under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Permafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradation. In the future period, permafrost on the sunny slopes is more prone to degradation and the sunny-shade slope effect of permafrost distribution will be further enhanced under climate warming. The lower limit of permafrost distribution is expected to rise by about 100 m in the 2050s under the SSP2-4.5 scenario. These findings can provide valuable insights about future permafrost changes in the QTP. In the past decades, the Qinghai-Tibet Plateau (QTP) warmed at more than twice the global average, and permafrost degradation within this process has become widely acknowledged. To project the possible changes, a combination of climate data from global climate model, machine learning model, and permafrost field observation data were used, based on a comprehensive review of previous studies. The findings indicate that permafrost in the QTP is not expected to undergo significant degradation under the SSP1-2.6 scenario. However, noticeable permafrost degradation is projected to occur after the 2050s under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, particularly in the Qilian Mountains and Three Rivers Source region. It is predicted that permafrost on sunny slopes is more susceptible to degradation under climate warming, and the permafrost area difference between the sunny and shade slopes will be further expanded. The mean annual air temperature of the QTP will rise by about 1.5 degrees C in the 2050s under the SSP2-4.5 scenario relative to the average between 2006 and 2018, which may lead to a 100 m rise on the low limit of permafrost distribution. Permafrost area of the Qinghai-Tibet Plateau (QTP) is expected to lose by 30.15% (SSP2-4.5) to 65.97% (SSP5-8.5) in the 2090sPermafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradationThe lower limit of permafrost distribution in the QTP is forecasted to rise by about 100 m in the 2050s under the SSP2-4.5 scenario
引用
收藏
页数:18
相关论文
共 50 条
  • [41] Multisite evaluation of physics-informed deep learning for permafrost prediction in the Qinghai-Tibet Plateau
    Liu, Yibo
    Ran, Youhua
    Li, Xin
    Che, Tao
    Wu, Tonghua
    COLD REGIONS SCIENCE AND TECHNOLOGY, 2023, 216
  • [42] Delineating the hydrological processes and hydraulic connectivities under permafrost degradation on Northeastern Qinghai-Tibet Plateau, China
    Yang, Yuzhong
    Wu, Qingbai
    Jin, Huijun
    Wang, Qingfeng
    Huang, Yadong
    Luo, Dongliang
    Gao, Shuhui
    Jin, Xiaoying
    JOURNAL OF HYDROLOGY, 2019, 569 : 359 - 372
  • [43] Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau
    Qing Lu
    Dongsheng Zhao
    Shaohong Wu
    Scientific Reports, 7
  • [44] Study on permafrost distribution in Qinghai-Tibet Plateau based on MODIS data
    Wang Kun
    Jiang Qigang
    PROCEEDINGS OF THE 2013 THE INTERNATIONAL CONFERENCE ON REMOTE SENSING, ENVIRONMENT AND TRANSPORTATION ENGINEERING (RSETE 2013), 2013, 31 : 448 - 451
  • [45] Carbon Balance of Grasslands on the Qinghai-Tibet Plateau under Future Climate Change: A Review
    Leng, Rong
    Yuan, Quanzhi
    Wang, Yushuang
    Kuang, Qian
    Ren, Ping
    SUSTAINABILITY, 2020, 12 (02)
  • [46] Spatiotemporal vegetation cover variations in the Qinghai-Tibet Plateau under global climate change
    Xu XingKui
    Chen Hong
    Levy, Jason K.
    CHINESE SCIENCE BULLETIN, 2008, 53 (06): : 915 - 922
  • [47] Performance comparison of permafrost models in Wudaoliang Basin, Qinghai-Tibet Plateau, China
    Guo-an Yin
    Fu-jun Niu
    Zhan-ju Lin
    Jing Luo
    Ming-hao Liu
    Journal of Mountain Science, 2016, 13 : 1162 - 1173
  • [48] Performance comparison of permafrost models in Wudaoliang Basin, Qinghai-Tibet Plateau, China
    Yin Guo-an
    Niu Fu-jun
    Lin Zhan-ju
    Luo Jing
    Liu Ming-hao
    JOURNAL OF MOUNTAIN SCIENCE, 2016, 13 (07) : 1162 - 1173
  • [49] Spatiotemporal vegetation cover variations in the Qinghai-Tibet Plateau under global climate change
    Jason K LEVY
    ChineseScienceBulletin, 2008, (06) : 915 - 922
  • [50] Active layer thickness variations on the Qinghai-Tibet Plateau under the scenarios of climate change
    Pang, Qiangqiang
    Zhao, Lin
    Li, Shuxun
    Ding, Yongjian
    ENVIRONMENTAL EARTH SCIENCES, 2012, 66 (03) : 849 - 857