Abstract: Soil temperature and humidity influence soil biology growth and development, making them important environmental factors in regulating ecological processes. Understanding soil temperature and humidity and their patterns of change is one of the foundations for conducting agricultural, forestry, climate, and environmental work. Long-term monitoring of soil temperature and humidity in various regions is challenging, but modeling simulations offer a more feasible approach. Existing models are limited by systematic differences between local and grid-based data, as well as complex parameter tuning mechanisms, and their ability to accurately simulate soil temperature and humidity at large scales remains imperfect. To address this, this study developed the topographic elevation correction(TEC) soil temperature model, which corrects reanalyzed air temperature data to simulate the daily average temperature at a 10 cm depth; and the Gauss convergence with steady state(GCSS) soil moisture model, which uses atmospheric precipitation as the driving factor, sets steady-state convergence boundary conditions based on hydrological characteristics, and undergoes north-south dual-mode testing. In the simulation of soil moisture during the growing season in Dongling Mountain, the downward migration of the moist front was captured, and the simulation accuracy was good, coefficient of determination R²=0.74. This study also simulated temperature and humidity conditions in soil profiles of Dongling Mountain during periods of significant climate change, providing a reference for reconstructing paleoenvironments and predicting future agricultural and forestry development.

Key words: soil temperature model, soil moisture model, Dongling Mountain, paleoenvironment, physical mechanism modeling