Influenced by a warm and humid climate, the permafrost on the Qinghai-Tibet Plateau is undergoing significant degradation, leading to the occurrence of extensive thermokarst landforms. Among the most typical landforms in permafrost areas is thaw slump. This study, based on three periods of data from keyhole images of 1968-1970, the fractional images of 2006-2009 and the Gaofen (GF) images of 2018-2019, combined with field surveys for validation, investigates the distribution characteristics and spatiotemporal variation trends of thaw slumps in the Hoh Xil area and evaluates the susceptibility to thaw slumping in this area. The results from 1968 to 2019 indicate a threefold increase in the number and a twofold increase in total area of thaw slumps. Approximately 70% of the thaw slumps had areas less than 2 x 104 m2. When divided into a grid of 3 km x 3 km, about 1.3% (128 grids) of the Hoh Xil region experienced thaw slumping from 1968 to 1970, while 4.4% (420 grids) showed such occurrences from 2018 to 2019. According to the simulation results obtained using the informativeness method, the area classified as very highly susceptible to thaw slumping covers approximately 26% of the Hoh Xil area, while the highly susceptible area covers about 36%. In the Hoh Xil, 61% of the thaw slump areas had an annual warming rate ranging from 0.18 to 0.25 degrees C/10a, with 70% of the thaw slump areas experiencing a precipitation increase rate exceeding 12 mm/10a. Future assessments of thaw slump development suggest a possible minimum of 41 and a maximum of 405 thaw slumps occurrences annually in the Hoh Xil region. Under rapidly changing climatic conditions, apart from environmental risks, there also exist substantial potential risks associated with thaw slumping, such as the triggering of large-scale landslides and debris flows. Therefore, it is imperative to conduct simulated assessments of thaw slumping throughout the entire plateau to address regional risks in the future.

The current spatial atmospheric forcing data cannot accurately depict the actual conditions of the Qinghai-Tibet Plateau (QTP), where monitoring stations are scarce and unevenly distributed. This deficiency in atmospheric data hinders accurate simulation of plateau permafrost changes on the plateau. In this study, we develop a new approach to evaluate regional permafrost changes, which does not rely on spatially distributed meteorological data but instead uses the regional climate change processes or temperature change rates. Centred on a transient heat conduction permafrost model, this approach was applied to the Qinghai Hoh Xil National Nature Reserve (referred to as Hoh Xil) within the QTP from 1960 to 2015, using the rate of air temperature change provided by the Wudaoliang Meteorological Station, the only national station in Hoh Xil. Simulation results showed that the difference between the simulated and observed change rates of mean annual ground temperature (MAGT) was less than 0.04 degrees C per decade from 2001 to 2015 at five long-term monitoring sites. The simulated ground temperature profiles in four boreholes from various permafrost zones revealed an error of less than 0.7 degrees C below 5 m in depth. Model validation demonstrates the reliability of this approach for predicting long-term permafrost changes. Future regional permafrost changes were further simulated based on the latest warming scenarios (BCC-CSM2-MR) from the Coupled Model Intercomparison Project Phase 6. Predictions revealed significant differences in the regional permafrost degradation rate under different climate warming scenarios. Under the most severe warming scenario (SSP58.5), permafrost in the study area is projected to still cover 72.2% of the total area by 2100, with most of the Hoh Xil's permafrost becoming warm (MAGT > 1 degrees C) permafrost. This approach not only facilitates the simulation of frozen ground changes in areas with few meteorological monitoring stations but also provides a new perspective for using coarse-resolution palaeoclimate data to investigate permafrost formation and evolution over long time scales.