%0 Journal Article
%T Spatial distribution and zonation characteristics of permafrost ground ice on the Qinghai‒Xizang Engineering Corridor, China
%A Fan, Xing-Wen
%A Gao, Ze-Yong
%A Luo, Jing
%A Niu, Fu-Jun
%A Li, Wen-Jiao
%A Wu, Xu-Yang
%A Lin, Zhan-Ju
%J Advances in Climate Change Research
%D 2026
%@ 1674-9278
%F FAN2026
%X Permafrost ground ice represents a critical solid water resource and engineering medium, with high ice-content permafrost in the Qinghai‒Xizang Engineering Corridor (QTEC) exhibiting heightened sensitivity to degradation, which in turn limiting our ability to accurately simulate permafrost degradation in climate models and to develop effective hazard mitigation strategies for engineering infrastructure in vulnerable cryospheric regions. Using 1158 subsurface borehole datasets, we employed Random Forest and Decision Tree modeling to simulate spatial ice-content distributions across the QTEC. Our results show that along a 560-km transect from Xidatan to Amdo, geological drilling data reveal 220 km of high ice-content permafrost and 180 km of seasonal frozen soil or ice-poor permafrost. High ice-content layers predominantly occur at the permafrost table (3–6 m depth). Vertical zonation analysis indicates that high ice-content permafrost forms continuous bands with increasing altitude. 200-m resolution simulations indicate 50% of the QTEC comprises high ice-content permafrost, with mean annual air temperature, ground temperature, active layer thickness, elevation, and precipitation as primary controlling factors. This study provides critical baselines for quantifying complex ground ice reserves and informs ecological conservation and engineering design in permafrost regions.
%K Permafrost ground ice, Qinghai‒Xizang Engineering Corridor (QTEC), Machine learning simulation, Ice-content zonation
%R https://doi.org/10.1016/j.accre.2026.02.005
%U https://www.sciencedirect.com/science/article/pii/S1674927826000389
%U https://doi.org/https://doi.org/10.1016/j.accre.2026.02.005