Abstract

Quantitative estimates on the magnitude and dynamics of vadose and groundwater zones in subarctic conditions are rare. Furthermore, knowledge on the constraints of different data on numerical groundwater recharge estimates (i.e., data worth analyses) is limited. We built a process-based three-dimensional hydrological model to describe and analyze the dynamics and magnitude of groundwater recharge, vadose zone, and related key hydrological components in subarctic conditions. Three-year time series of daily groundwater level and soil moisture (five different depths) data were used to identify plausible model realizations. Thereafter, long-term simulations over 6 years were conducted. The model adequately corresponded with the magnitude and dynamics of the observations, even though the simulations and observations occasionally differed. Simulations with several different plausible parameterizations showed how soil moisture and groundwater level fluctuations, as well as recharge estimates, are sensitive to water retention parameter variations, whereas precipitation and evapotranspiration controlled the recharge magnitude. Recharge showed clear interannual variability (annual mean 0.28–0.60 m). The fraction of annual mean recharge over precipitation was 39%–66% during our simulation period. We showed how groundwater level data can set more constraints on the recharge estimates than soil moisture data, and how both of the data types together constrained the recharge estimates the most. We showed how the vadose zone had modest dynamics and storage properties (typically 2%–8% of the total soil water) in terms of the bulk soil water storage. However, the average amount of the air-filled pore space (0.70 m) and water (0.38 m) in the vadose zone were proportional to annual precipitation and evapotranspiration, respectively. Thus, the vadose zone can form an important boundary between the soil surface and groundwater zone, and its role is not highly sensitive to hydrometeorological fluctuations. Data worth analyses provide a potential opportunity to move toward increasingly reliable model-based groundwater recharge estimates and system understanding.

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