Lakes on the Qinghai-Tibet Plateau (QTP) have notably expanded over the past 20 years. Due to lake water level rise and lake area expansion, the permafrost surrounding these lakes is increasingly becoming submerged by lake water. However, the change process of submerged permafrost remains unclear, which is not conducive to further analyzing the environmental effects of permafrost change. Yanhu Lake, a tectonic lake on the QTP, has experienced significant expansion and water level rise. Field measurement results indicate that the water level of Yanhu Lake increased by 2.87 m per year on average from 2016 to 2019. Cold permafrost, developed in the lake basin, was partially submerged by lake water at the end of 2017. Based on the water level change and permafrost thermal regime, a numerical heat conduction permafrost model was employed to predict future changes in permafrost beneath the lake bottom. The simulated results indicate that the submerged permafrost would continuously degrade because of the significant thermal impact of lake water. By 2100, the maximum talik thicknesses could reach approximately 7, 12, 16, and 19 m under lake-bottom temperatures of +2.0, +4.0, +6.0, and +8.0 degrees C, respectively. Approximately 291 years would be required to completely melt 47 m of submerged permafrost under the lake-bottom temperature of +4 degrees C. Note that the permafrost table begins to melt earlier than does the permafrost base, and the decline in the permafrost table occurs relatively fast at first, but then the process is attenuated, after which the permafrost table again rapidly declines. Compared to climate warming, the degradation of the submerged permafrost beneath the lake bottom occurred more rapidly and notably.

Most lakes on the Qinghai-Tibet Plateau have expanded in recent years. Zonag lake, a critical habitat for Tibetan antelopes in the continuous permafrost zone, burst and overflowed after several years of expansion, resulting in a reduction of approximately 100 km(2) in the lake area. Observations have revealed new permafrost is forming on the exposed bottom, accompanied by various periglacial landscapes. The permafrost aggradation on the exposed bottom is rapid, and the permafrost base reached 4.9 m, 5.4 m, and 5.7 m in the first three years, respectively. In this study, the future changes and influencing factors of recently formed permafrost are simulated using a one-dimensional finite element model of heat flow. The simulated results indicate that the permafrost on the exposed bottom is likely to continue to develop, appearing first quick back slow trend. Besides the surface temperature, the annual amplitude is also an important factor in affecting the aggradation of permafrost. The unidirectional permafrost aggradation in the study area is different from the bidirectional permafrost aggradation on the closed taliks around the Arctic. Additionally, snow cover and vegetation are two important factors influencing the future development of permafrost on the exposed lake bottom.

Air and soil temperatures are important factors that contribute to hydro-thermal processes and ecosystem dynamics in permafrost regions. However, there is little research regarding soil thermal dynamics during freeze thaw processes in permafrost regions with thermal orbits on the Tibetan Plateau. Thermal orbits can provide simplified illustrations of the relationships between air and ground temperatures. This paper presents a new quantitative analysis for thermal orbits by combining the characteristics of ellipse and linear regression theories. A sensibility analysis of thermal orbits was conducted with different air and ground temperatures and vegetation types on the Tibetan Plateau. Results indicated that the thermal orbit regression slopes and intercepts had variations in characteristics between air and ground temperatures at different depths. More specifically, both air and ground temperatures showed homologous variation with increasing depth. This type of analysis is important for a better understanding of permafrost thermal properties as they relate to soil moisture, climate change, and vegetation effects in permafrost regions on the Tibetan Plateau.

We developed a simple model to estimate ice ablation under a debris cover. The ablation process is modelled using energy and mass conservation equations for debris and ice and heat conduction, driven by input of either i) debris surface temperature or ii) radiation fluxes, and solved through a finite difference scheme computing the conductive heat flux within the supra-glacial debris layer. For model calibration, input and validation, we used approximately bi-weekly surveys of ice ablation rate, debris cover temperature, air temperature and solar incoming and upwelling radiation during for Summer 2007. We calibrated the model for debris thermal conductivity using a subset of ablation data and then we validated using another subset. Comparisons between calculated and measured values showed a good agreement (RMSE = 0.04 m w.e., r = 0.79), thus suggesting a good performance of the model in predicting ice ablation. Thermal conductivity was found to be the most critical parameter in the proposed model, and it was estimated by debris temperature and thickness, with value changing along the investigated ablation season. The proposed model may be used to quantify buried ice ablation given a reasonable assessment of thermal conductivity.