Ground Surface Temperature Monitoring Data Interpretation and Implications for Subsurface Heat Flux in Southern Mount Meager, Western Canada

Abstract

Previous studies showed that ground surface temperature (GST) monitoring data contain information indicative of subsurface geothermal flux in the Mount Meager Volcanic Complex (MMVC) of western Canada. This paper reviews the statistical methods for GST feature extraction, characterization, and environmental impact suppression. The resulting ground surface anomalies from GST data were examined against the geothermal drilling results and an inverted resistivity model from AMT data, in conjunction with areal infrared thermal images of the same area to investigate possible links between the GST anomalies and subsurface heat flux. The temporal variation of GST time series recorded at 22 stations across the study area is divided into three segments: pre- snow curtain (Pre-SC), snow curtain (SC) and post-snow curtain (post-SC) for the convenience of data analysis. The intensity of daily GST variation of the recorded GST time series in the snow free seasons shows predominantly seasonal and daily air temperature fluctuations in responding to heat energy from solar radiation and climate forcing with clear environmental footprints and complicated by soil properties. During the snow curtain period, all GST records leveled off, staying almost constant around 0 °C as the solar radiation has been greatly reduced by effective insolation from thick winter snow. Subtle differences among GST time series at different stations may reflect the spatial variation of the subsurface heat flux. Comparison with subsurface temperature data and groundwater discharge, the measured mean GST (SC) and duration of the SC show a close spatial affinity with subsurface heat flow and shallow ground water circulation revealed by drilling results and warm spring swarms along the margin of the volcanic complex and is consistent with the spatial distribution of low resistivity zones of the inverted resistivity model from AMT data.