The permafrost degradation can cause long‐term ground surface subsidence, and the surface undergoes frost heave and thaw settlement due to the ice‐water phase change in the active layer. The multi‐year surveys by leveling observations and Interferometric Synthetic Aperture Radar monitoring (InSAR) are helpful to understand the characteristics of seasonal deformation and to model the permafrost terrain surface deformation. In this paper, we studied the characteristics of seasonal deformation over permafrost terrain in Xidatan, obtained by leveling measurements from 2010 to 2018, Sentinel‐1 data from 2014 to 2020, and hydrothermal‐data‐based simulation. The results consistently showed a four‐stage pattern of seasonal deformation characteristics: Summer thaw subsiding, warm‐season stable‐standing, winter freeze heaving and stable‐standing. The leveling measurements proved that spatial heterogeneity also exists on a small spatial scale (400 m²). The deformation amplitude obtained by leveling data is the largest, and the InSAR data is the smallest.

Ground-penetrating radar (GPR) is a convenient geophysical technique for active-layer soil moisture detection in permafrost regions, which is theoretically based on the petrophysical relationship between soil moisture (θ) and the soil dielectric constant (ε). The θ–ε relationship varies with soil type and thus must be calibrated for a specific region or soil type. At present, there is lack of such a relationship for active-layer soil moisture estimation for the Qinghai–Tibet plateau permafrost regions. In this paper, we utilize the Complex Refractive Index Model to establish such a calibration equation that is suitable for active-layer soil moisture estimation with GPR velocity. Based on the relationship between liquid water, temperature, and salinity, the soil water dielectric constant was determined, which varied from 84 to 88, with an average value of 86 within the active layer for our research regions. Based on the calculated soil-water dielectric constant variation range, and the exponent value range within the Complex Refractive Index Model, the exponent value was determined as 0.26 with our field-investigated active-layer soil moisture and dielectric data set. By neglecting the influence of the soil matrix dielectric constant and soil porosity variations on soil moisture estimation at the regional scale, a simple active-layer soil moisture calibration curve, named CRIM, which is suitable for the Qinghai–Tibet plateau permafrost regions, was established. The main shortage of the CRIM calibration equation is that its calculated soil-moisture error will gradually increase with a decreasing GPR velocity and an increasing GPR velocity interpretation error. To avoid this shortage, a direct linear fitting calibration equation, named as υ-fitting, was acquired based on the statistical relationship between the active-layer soil moisture and GPR velocity with our field-investigated data set. When the GPR velocity interpretation error is within ±0.004 m/ns, the maximum moisture error calculated by CRIM is within 0.08 m³/m³. While when the GPR velocity interpretation error is larger than ±0.004 m/ns, a piecewise formula calculation method, combined with the υ-fitting equation when the GPR velocity is lower than 0.07 m/ns and the CRIM equation when the GPR velocity is larger than 0.07 m/ns, was recommended for the active-layer moisture estimation with GPR detection in the Qinghai–Tibet plateau permafrost regions.

Permafrost has been warming and thawing globally, with subsequent effects on the climate, hydrology, and the ecosystem. However, the permafrost thermal state variation in the northern lower limit of the permafrost zone (Xidatan) on the Qinghai–Tibet Plateau (QTP) is unclear. This study attempts to explore the changes and variability in this permafrost using historical (1970–2019) and future projection datasets from remote-sensing-based land surface temperature product (LST) and climate projections from Earth system model (ESM) outputs of the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5, CMIP6). Our model considers phase-change processes of soil pore water, thermal-property differences between frozen and unfrozen soil, geothermal flux flow, and the ground ice effect. Our model can consistently reproduce the vertical ground temperature profiles and active layer thickness (ALT), recognizing permafrost boundaries, and capture the evolution of the permafrost thermal regime. The spatial distribution of permafrost and its thermal conditions over the study area were controlled by elevation with a strong influence of slope orientation. From 1970 to 2019, the mean annual ground temperature (MAGT) in the region warmed by 0.49 ^∘C in the continuous permafrost zone and 0.40 ^∘C in the discontinuous permafrost zone. The lowest elevation of the permafrost boundary (on the north-facing slopes) rose approximately 47 m, and the northern boundary of discontinuous permafrost retreated southwards by approximately 1–2 km, while the lowest elevation of the permafrost boundary remained unchanged for the continuous permafrost zone. The warming rate in MAGT is projected to be more pronounced under shared socioeconomic pathways (SSPs) than under representative concentration pathways (RCPs), but there are no distinct discrepancies in the areal extent of the continuous and discontinuous permafrost and seasonally frozen ground among SSP and RCP scenarios. This study highlights the slow delaying process of the response of permafrost in the QTP to a warming climate, especially in terms of the areal extent of permafrost distribution.