Predicting and evaluating slope stability in permafrost regions of the central Qinghai‒Tibetan Plateau
Thermokarst landslides have frequently occurred in the central Qinghai‒Tibetan Plateau (QTP), endangering infrastructure and the environment. However, there have been no adequate methods to predict thermokarst landslides until now. Therefore, establishing a reliable slope stability evaluation method...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-04-01
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| Series: | Advances in Climate Change Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674927825000784 |
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| Summary: | Thermokarst landslides have frequently occurred in the central Qinghai‒Tibetan Plateau (QTP), endangering infrastructure and the environment. However, there have been no adequate methods to predict thermokarst landslides until now. Therefore, establishing a reliable slope stability evaluation method is paramount for hazard forewarning and prevention. In this study, we analyzed the distribution characteristics of thermokarst landslides based on historical landslide data from the central QTP. By applying threshold values for these distribution characteristics, non-thermokarst landslide areas were identified and masked. We then assessed and predicted the slope stability of permafrost regions using a permafrost slope stability calculation model combined with GIS software. The stability assessment results indicate that most of the masked study area is unstable. Compared to the initial state, the areas of unstable regions increased by 7.7%, 19.0%, and 29.5% for SSP126; 6.3%, 23.5%, and 37.3% for SSP245; and 14.1%, 32.6%, and 51.2% for SSP585 during the periods 2020–2040, 2040–2060, and 2060–2080, respectively. This increasing trend in unstable areas becomes even more pronounced when temperature and rainfall changes are considered. Under the SSP585 precipitation scenario, the areas of unstable regions from 2060 to 2080 increased by 52.9%, 52.5%, and 51.9% compared to only considering temperature variation scenarios. Additionally, we cross-validated the slope stability results from 2000 to 2020 with the thermokarst landslide susceptibility results. The overall distribution trends of unstable areas from both methods were broadly consistent, with a difference of only 7% in unstable area size. The correlation between the slope stability and landslide susceptibility evaluation results reached 0.76 (p < 0.05). These cross-validation findings support the reliability of this paper's regional slope stability evaluation method. |
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| ISSN: | 1674-9278 |