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Selin Co, located within permafrost regions surrounded by glaciers, has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau over the last 50 years. Most of the increased lake water volume has been attributed to increased precipitation and the accelerated melting of glacier ice, but these processes are still not sufficient to close the water budget with the expansion of Selin Co. Ground ice meltwater released by thawing permafrost due to continuous climate warming over the past several decades is regarded as another source of lake expansion. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation. We monitored the spatial distribution of surface deformation in the Selin Co basin using the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique and compared the results with the findings of field surveys. Then, the ground ice meltwater volume in the watershed was calculated based on the cumulated settlement. Finally, this volume was compared with the lake volume change during the same period, and the contribution ratio was derived. SBAS-InSAR monitoring during 2017–2020 illustrated widespread and large subsidence in the upstream section of the Zhajiazangbu subbasin, where widespread continuous permafrost is present. The terrain subsidence rate was normally between 5 and 20 mm a -1 , indicating rapid ground ice loss in the region. The ground ice meltwater was released at a rate of ∼57×106 m 3 a -1 , and the rate of increase in lake water storage was ∼485×106 m 3 a -1 during the same period, with ground ice meltwater contributing ∼12 % of the lake volume increase. This study contributes to explaining the rapid expansion of Selin Co and equilibrating the water balance at the watershed scale. More importantly, the proposed method can be extended to other watersheds underlain by permafrost and help in understanding the hydrological changes in these watersheds. [ABSTRACT FROM AUTHOR]

The comprehensive understanding of the occurred changes of permafrost, including the changes of mean annual ground temperature (MAGT) and active layer thickness (ALT), on the Qinghai‐Tibet Plateau (QTP) is critical to project permafrost changes due to climate change. Here, we use statistical and machine learning (ML) modeling approaches to simulate the present and future changes of MAGT and ALT in the permafrost regions of the QTP. The results show that the combination of statistical and ML method is reliable to simulate the MAGT and ALT, with the root‐mean‐square error of 0.53°C and 0.69 m for the MAGT and ALT, respectively. The results show that the present (2000–2015) permafrost area on the QTP is 1.04 × 106 km2 (0.80–1.28 × 106 km2), and the average MAGT and ALT are −1.35 ± 0.42°C and 2.3 ± 0.60 m, respectively. According to the classification system of permafrost stability, 37.3% of the QTP permafrost is suffering from the risk of disappearance. In the future (2061–2080), the near‐surface permafrost area will shrink significantly under different Representative Concentration Pathway scenarios (RCPs). It is predicted that the permafrost area will be reduced to 42% of the present area under RCP8.5. Overall, the future changes of MAGT and ALT are pronounced and region‐specific. As a result, the combined statistical method with ML requires less parameters and input variables for simulation permafrost thermal regimes and could present an efficient way to figure out the response of permafrost to climatic changes on the QTP. Key Points: The combined statistical method with machine learning is efficient to obtain the thermal regime of permafrost on the Qinghai‐Tibet Plateau (QTP)The present permafrost area on the QTP is ∼1.04 × 106 km2, and the average mean annual ground temperature and active layer thickness are −1.35 ± 0.42°C and 2.3 ± 0.60 m, respectivelyThe future changes of permafrost are projected to be pronounced due to climate change, but region‐specific [ABSTRACT FROM AUTHOR]

Using monitored active layer thickness (ALT) and environmental variables of 10 observation fields along the Qinghai-Tibet Highway in permafrost region of the Qinghai-Tibetan Plateau (QTP), a model for ALT estimation was developed. The temporal and spatial characteristics of the ALT were also analyzed. The results showed that in the past 30 years ALT in the study region increased at a rate of 1.33 cm a. Temperatures at the upper limit of permafrost and at 50 cm depth, along with soil cumulative temperature at 5 cm depth also exhibited a rising trend. Soil heat flux increased at a rate of 0.1 W m a. All the above changes demonstrated that the degradation of permafrost happened in the study region on the QTP. The initial thawing date of active layer was advanced, while the initial freezing date was delayed. The number of thawing days increased to a rate of 1.18 d a. The variations of active layer were closely related to the permafrost type, altitude, underlying surface type and soil composition. The variations were more evident in cold permafrost region than in warm permafrost region, in high-altitude region than in low-altitude region, in alpine meadow region than in alpine steppe region; and in fine-grained soil region than in coarse-grained soil region. [ABSTRACT FROM AUTHOR]

Soil thermal diffusivity is a crucial physical parameter that affects soil temperature. By applying sinusoidal boundary conditions, an analytical solution using separated variables for the heat conduction-convection equation was developed. The thermal diffusivity and liquid water flux density were calculated with data collected at field observation sites in permafrost regions of Qinghai-Xizang (Tibet) Plateau (QXP). By taking the soil layer at the depth of 5 cm as the upper boundary, the soil temperature at a depth of 10 cm was modeled by the thermal conduction-convection method, amplitude method and phase method. The statistical analysis of the standard error of the estimate (SEE), the normalized standard error (NSEE) and the root mean square error (RMSE) demonstrated that the thermal conduction-convection method provided the most accurate prediction of soil temperature, with average SEE, NSEE, and RMSE of 0.72 °C, 9.26% and 0.72 °C, respectively. The thermal conduction-convection method provides a useful tool for calculating soil thermal parameters, simulating soil temperature and land surface processes parameterization for permafrost changes modelling under global warming. [ABSTRACT FROM AUTHOR]

Active-layer thickness's distribution is a key parameter for permafrost area studies. In the past, the factors of vegetation, soil water content usually were employed to forecast the spatial distribution of active-layer thickness. But in coarse material distribution area, the above method is often unsatisfactory due to the failure in accurate acquisition of biomass and soil water content. In this paper, a simple method was recommended to be used for calculating of active layer thickness distribution, which is suitable for all kinds of soil texture. Our study analyzed the relationship between ground surface layer permittivity and the thawing depth of the active layer in a permafrost area that was undisturbed by subsurface water flow or local melting. Ground surface layer permittivity is confirmed as having a strong correlation with soil moisture content and biomass of the vegetation cover. We used the direct ground wave velocities from GPR detecting results to compute the dielectric permittivity. Our conclusion is that in our specific study area, a power function relationship existed between the ground surface layer permittivity and the thawing depth of the active layer. [ABSTRACT FROM AUTHOR]

Abstract: Data observed at monitoring stations in the Tanggula Pass (TGLMS) and in the Xidatan region (XDTMS) were used to calculate the surface energy fluxes, that is, net radiation, ground surface heat flux, sensible heat flux, and latent heat flux. The energy closure statuses obtained by the daily accumulated energy fluxes at the TGLMS and XDTMS sites were good and the turbulent fluxes were slightly higher than the available energy, but this was influenced by differing time-scales. From an energy perspective, the phenomenon of turbulent fluxes being greater than the available energy is advantageous to the development of permafrost, and snow cover is advantageous to storing cold energy in soil. The sensible heat flux and the latent heat flux exhibited a seasonal alternation characteristic, that is, the sensible heat flux was higher than the latent heat flux in winter and spring, but was lower than the latent heat flux in summer and autumn. This is mainly related to the precipitation influenced by the monsoon and the freezing-thawing processes of the active layer. Analysis of diurnal flux variations included the daily freezing-thawing processes. Variations of the Bowen ratios at the two sites were greater than 1.0 from June to September, and less than 1.0 in the other months. Negative Bowen ratios appeared when the snow cover reached a certain thickness (in this case, 10 cm). [Copyright &y& Elsevier]

Abstract: The sensible and latent heat fluxes in the Tanggula region were calculated using turbulent flux monitoring data from June 2004 to December 2005. The monitoring site was located on a gentle slope covered by meadow vegetation (91°56′E, 33°04′N; elevation 5100 m). The turbulent flux monitoring was conducted using the eddy covariance system and a meteorological gradient tower. The results indicated that the average surface energy closure ratio (CR) was 1.07 for the period from June to December of 2004, and 1.03 for the year 2005. The surface energy balance was greatly influenced by rainfalls, snowfalls and snow cover. The sensible heat flux was higher in spring and had a heat sink in summer due to the heat consumed in thawing of the active layer. The latent heat flux was much higher in summer because the soil moisture content was higher, resulting from the thawing of the active layer and more precipitation during the summer monsoon season. It also was found that the amplitudes of the energy fluxes on cloudy days were lower than that on clear days. The evapotranspiration was well related to the surface soil moisture content. The freezing and thawing cycles played a significant role in the land surface processes. [Copyright &y& Elsevier]