Shallow groundwater temperature patterns revealed through a regional monitoring well network

Abstract

Groundwater temperature is a critical control on groundwater quality, geothermal system efficiency and ecosystem dynamics in receiving surface waters. Despite the known importance of groundwater temperature, there is a lack of dedicated aquifer thermal monitoring across spatial and temporal scales. Pressure transducers and other sensors installed in groundwater monitoring well networks often record temperature as a secondary function, but these comprehensive groundwater temperature data sets are seldom analysed. In this study, we analysed seasonal, interannual and spatial patterns of shallow groundwater temperatures from a regional groundwater monitoring network in Nova Scotia, Canada and compared these subsurface temperature data to air temperature data from nearby climate stations using linear regressions and Fourier analysis. The results showed that seasonal groundwater temperatures were damped (with seasonal amplitudes 3.6%–42% of air temperature amplitudes) and lagged (phase shifted 43–145 days) compared to air temperature, with notable year‐to‐year variations in both damping and lagging. Results also highlighted the role of snowpack thickness on the lowest mean monthly groundwater temperatures. Given potential impacts of climate change, land cover change, urbanization and geothermal energy development on groundwater temperatures, we encourage water authorities and regulators to begin or enhance aquifer thermal monitoring and provide guidance for capitalizing on existing monitoring well infrastructure to track temperature dynamics and changes.

Understanding hydrological connectivity: an empirical study of river-aquifer interaction across Brazil

“…There is a slight variation when the minimum water levels from these wells were used, likely attributed to seasonal and meteorological conditions affecting some river-aquifer systems, causing shifts from export water to import water at different times. It is important to note that minimum values are more sensitive to observational errors, such as changes in sensor depth or measurements taken when the sensor is not fully submerged (e.g., Smith et al, 2023). Despite observed variations, they are relatively small compared to the magnitude of the data, suggesting that the median effectively represents the aquifer's condition and can be used for the analysis of river-aquifer interactions.…”