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To develop a comprehensive computational framework for optimizing high-dimensional parameters in permafrost modeling.

An integrated computational framework for high-dimensional parameter optimization in coupled hydro-thermal permafrost modelling

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To develop a comprehensive computational framework for optimizing high-dimensional parameters in permafrost modeling.
Integrated the GEOtop 3.0 model with MATLAB for automated modeling.
Applied Particle Swarm Optimization to calibrate 101 parameters across three boreholes.
Conducted Global Sensitivity Analysis using the Morris method to identify key controls on model performance.
Model accurately simulated deep permafrost temperatures with RMSE < 0.2 °C.
Near-surface temperature errors ranged from RMSE of 0.84–1.63 °C, nearly doubling during validation at the Lola borehole.
Hydraulic-thermal coupling identified as key driver for ground temperature dynamics.

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An integrated model identifies key factors affecting ground temperature in permafrost areas, suggesting improved simulation strategies.

Alphonse et al. (2026) studied this question.

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