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As the world struggles with climate change and energy crises, understanding the role of soil in the food–water–energy nexus becomes increasingly critical. Accurately estimating the soil thermal conductivity drying curve is essential for assessing the impacts of temperature on soil biota and crop growth, environmental changes due to forest fires and global warming, and for designing geo-energy extraction techniques such as geothermal energy piles. Existing empirical models often fail to accurately estimate the soil thermal conductivity (TC), particularly in pendular soil moisture regimes where they do not capture sharp changes in TC. This study introduces a novel approach using a pore unit cell network model to more accurately describe the dynamics of TC in variably saturated soils. A quadratic parallel scheme within each soil pore unit cell links the TCs of solid, water, and air to the overall effective conductivity. By modeling air invasion in the pore network model and employing the proposed equation, we determined the unsaturated soil TC based on varying local conductivities. The model effectively captures the significant decrease in conductivity in the pendular saturation regime, associated with the shrinkage of the spanning-wetting cluster. Quantitative analyses showed a substantial improvement in prediction accuracy compared to existing models, especially under varying moisture conditions. Our findings have significant implications for better characterizing soil thermal and hydraulic properties, which are crucial for resource management in a changing climate and advancing geo-energy technologies.