Mapping permafrost distribution and thaw depths in the Inner Tien Shan: A CryoGrid-based modeling approach integrating geophysical data

Abstract. Permafrost degradation poses increasing risks to infrastructure in high-mountain regions, yet quantitative and spatially distributed assessments remain scarce in data-limited areas such as Central Asia. This study focuses on a 1,563 km² area in Inner Tien Shan, Kyrgyzstan, including the Kumtor gold mine and the Arabel plateau. We applied the numerical permafrost model CryoGrid to simulate permafrost thermal conditions and thaw depth across the study area, informed by geophysically derived stratigraphies and assessed against borehole temperatures and ground-based observations. To represent subsurface heterogeneity, surface-type-specific stratigraphies were developed for six landscape classes derived from petrophysical joint inversion of co-located Electrical Resistivity Tomography (ERT) and Refraction Seismic Tomography (RST) data. Legacy borehole measurements from 1986–1992 were incorporated to provide a multi-decadal validation of ground thermal conditions.

The resulting 30 m resolution maps indicate continuous permafrost across the study area, with mean ground temperatures at 5 m depth ranging from −0.1 °C to −6.5 °C and a spatial mean of −2.9 °C. Mean thaw depth at the end of August 2024 is 2.0 m, with surface type exerting a strong control on spatial patterns. Fine-grained and vegetated sediments on the Arabel plateau show comparatively deep thaw, coinciding with thermokarst features and ground subsidence, whereas coarse-blocky debris and rock glaciers exhibit shallow thaw depths. Comparison with ERT-derived thaw depths from 15 profiles shows agreement generally within about 1 m. Simulated ground temperatures show warming trends of 0.20 °C and 0.18 °C per decade at 5 m and 20 m depth since 1975, corresponding to approximately 1 °C warming since the 1980s. These results demonstrate the value of integrating geophysical data and surface-type-specific stratigraphies into modeling studies to represent spatial variability of mountain permafrost in data-scarce regions.