Geothermal resource assessment has been conducted by the Geological Survey of Canada (GSC) in the Garibaldi Geothermal Volcanic Belt area in supporting the Geoscience for New Energy Supply Program. Near surface ground temperature datasets were collected using new geothermal exploration methods in Mount Meager and Mount Cayley geothermal areas during the 2021 and 2022 summer fieldwork seasons. Research work is ongoing to analyze and evaluate the temperature records by building numerical models of heat balance of the shallow underground and analytical heat conservation models. The objective of this study is to undertake a numerical modeling approach to gain a better understanding of heat balance system during the winter snow covering period and analyze the temperature data for calculating the subsurface geothermal heat flux. The results from this work provide insights for analyzing field data and eventually benefit the geothermal resources assessment in this area. The ground temperature is affected by many environmental and soil properties and physical processes, such as geothermal heat flux, solar radiation, water evaporation and condensation, snowmelt, rain and advective heat flux by the movement of subsurface ground water flow. From the collected ground surface temperature datasets from temperature sensors placed in the topsoil of Mount Meager geothermal field, a relatively stable temperature period is generally identifiable during the snow covering (snow-curtain) period, which may help eliminate major environmental effects and reveal the contribution of the geothermal energy heat flux. To better understanding the temperature variation in the datasets, the 22 temperature time series recorded in the 2020-21 winter period were organized in three groups and presented accordingly, depending on the range of the measured temperature and the trends of variation. Then Simple and Ordinary Kriging (SK and OK) were applied to generate temperature maps at equal spaced temporal points to reveal the dynamics of temperature variation of the Mount Meager geothermal field. It is found that our general understanding based on the categorized sampled data is consistent with the insights revealed through the temporal temperature field mapping and that the heat sources hidden underneath the covering snow can be clearly identified through temporal geostatistical mapping. In order to achieve a better matching and consider the complexity of the problem, a simplified 2D numerical model using COMSOL multiphysics software was constructed to help identify the heat flux range and the temperature distribution for the targeted area. The results show the sensitivities of various geological and environmental factors that affect the ground temperature. We believe that the output from this research provide insights from data analysis and interpretation, and will be of importance for the future research work of the Mount Meager geothermal field. The recommendation for future research is to build an accurate multiphysics model that can simultaneously consider the snow accumulating and melting processes under more realistic conditions.

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