Groundwater temperature is a useful hydrogeological parameter that is easy to measure and can provide much insight into groundwater flow systems, but can be difficult to interpret. For measuring temperature directly in the ground, dedicated specifically designed monitoring wells are recommended since conventional groundwater wells are not optimal for temperature monitoring. Multilevel monitoring of groundwater temperature is required to identify contributions of different possible heat inputs (sources) on measured temperature signals. Interpreting temperature data as a cosine function, including period, average temperature, amplitude, and phase offset, is helpful. Amplitude dampening and increasing phase shift with distance from a boundary can be used for estimation of transport parameters. Temperature measurements at different depths can be used for evaluation of unknown parameters of analytical functions by optimization of regression fits in Python. These estimated parameters can be used to calculate temperatures at known water table depths which can be applied as a fixed transient boundary condition in MT3DMS to overcome the limitations of MT3DMS heat transport modeling in the unsaturated zone. In this study, temperature monitoring and modeling was used to evaluate the influence of a department store's heated basement foundation on groundwater temperature within a green space (city park), with the main outcome that 17 years after construction, the department store foundation has increased the mean groundwater temperature by 3.2 °C. Heat input evaluated by the MT3DMS model varied from 0.1 W/m2 at a distance of 100 m up to 12 W/m2 next to the building.
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