Ground surface boundary condition methods for analysis of climate-driven permafrost thaw: A comparative study and long-term projections for Nunavik, Canada

Infrastructure in northern regions is increasingly threatened by climate change, mainly due to permafrost thaw. Prediction of permafrost stability is essential for assessing the long-term stability of such infrastructure. A key aspect of geotechnical problems subject to climate change is addressing the surface energy balance (SEB). In this study, we evaluated three methodologies for applying surface boundary conditions in long-term thermal geotechnical analyses, including SEB heat flux, n-factors, and machine learning (ML) models by using ERA5-Land climate reanalysis data until 2100. We aimed to determine the most effective approach for accurately predicting ground surface temperatures for climate-resilient design of northern infrastructure. The evaluation results indicated that the ML-based approach outperformed both the SEB heat flux and n-factors methods, demonstrating significantly lower prediction errors. The feasibility of long-term thermal analysis of geotechnical problems using ML-predicted ground surface temperatures was then demonstrated through a permafrost case study in the community of Salluit in northern Canada, for which the thickness of the active layer and talik were calculated under moderate and extreme climate scenarios by the end of the 21st century. Finally, we discussed the application and limitations of surface boundary condition methodologies, such as the limited applicability of the n-factors in long-term analysis and the sensitivity of the SEB heat flux to inputs and thermal imbalance. The findings highlight the importance of selecting suitable boundary condition methodologies in enhancing the reliability of thermal geotechnical analyses in cold regions. • Three surface boundary condition methodologies were evaluated. • Machine learning achieved lowest errors in ground surface temperature predictions. • The proposed approach integrates climate projections for multi-decadal analysis. • Case study reveals active-layer and potential talik formation under climate change. • Site data remain critical for validating permafrost thermal analysis.