Analysisof fault-zone-hosted thermal springs provides insights into deep fault-zone processes and crustal-scale fluid movements. However, shallow groundwater mixing obscures chemical signatures associated with deeply sourced groundwater, reducing the utility of thermal spring data for understanding deep fault-zone processes. The Upper Hot Spring (UH) in the Banff Hot Spring system exhibits substantial seasonal variability and is a valuable case for investigating shallow groundwater mixing in fault zones. UH chemistry aligns with binary mixing of cold tritium-rich groundwater from Sulphur Mountain and hot tritium-depleted water from the Sulphur Mountain Thrust (SMT) fault zone. Geochemical and isotopic data from lower elevation springs suggest the extension of binary mixing dynamics to lower elevations. Applying a Monte Carlo-based regression approach, strontium isotope mass balance models simulate one year of 87Sr/86Sr time series at UH within the margin of uncertainty. Utilizing mixing proportions derived from the model, tritium mass balance models successfully simulate the tritium time series at UH over the same period, providing cross-validation. Using relationships between mixing proportions and sulfate, hydrographs for the three highest elevation springs are separated into two components, revealing that the seasonal variability of both components decreases northward as spring elevation decreases. Utilizing common environmental tracers and bypassing direct sampling of inaccessible endmembers, the modeling approach used here may find global applicability for characterizing mixing in fault zones.
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