Simulation of long-term spatiotemporal variations in regional-scale groundwater recharge: contributions of a water budget approach in cold and humid climates

Abstract

Abstract. Groundwater recharge (GWR) is a strategic hydrologic variable, and its estimate is necessary to implement sustainable groundwater management. This is especially true in a global warming context that highly impacts key winter conditions in cold and humid climates. For this reason, long-term simulations are particularly useful for understanding past changes in GWR associated with changing climatic conditions. However, GWR simulation at the regional scale and for long-term conditions is challenging, especially due to the limited availability of spatially distributed calibration data and due to generally short observed time series. The objective of this study is to demonstrate the relevance of using a water budget model to understand long-term transient and regional-scale GWR in cold and humid climates where groundwater observations are scarce. The HydroBudget model was specifically developed for regional-scale simulations in cold and humid climate conditions. The model uses commonly available data such as runoff curve numbers to describe the study area, precipitation and temperature time series to run the model, and river flow rates and baseflow estimates for its automatic calibration. A typical case study is presented for the southern portion of the Province of Quebec (Canada, 36 000 km2). With the model simultaneously calibrated on 51 gauging stations, the first GWR estimate for the region was simulated between 1961 and 2017 with very little uncertainty (≤ 10 mm/yr). The simulated water budget was divided into 41 % runoff (444 mm/yr), 47 % evapotranspiration (501 mm/yr), and 12 % GWR (139 mm/yr), with preferential GWR periods during spring and winter (44 % and 32 % of the annual GWR, respectively), values that are typical of other cold and humid climates. Snowpack evolution and soil frost were shown to be a key feature for GWR simulation in these environments. One of the contributions of the study was to show that the model sensitivity to its parameters was correlated with the average air temperature, with colder watersheds more sensitive to snow-related parameters than warmer watersheds. Interestingly, the results showed that the significant increase in precipitation and temperature since the early 1960s did not lead to significant changes in the annual GWR but resulted in increased runoff and evapotranspiration. In contrast to previous studies of past GWR trends in cold and humid climates, this work has shown that changes in past climatic conditions have not yet produced significant changes in annual GWR. Because of their relative ease of use, water budget models are a useful approach for scientists, modelers, and stakeholders alike to understand regional-scale groundwater renewal rates in cold and humid climates, especially if they can be easily adapted to specific study needs and environments.

Impact of land cover changes on Long‐Term Regional‐Scale groundwater recharge simulation in cold and humid climates

“…Studies in cold climates with seasonal snowpack have emphasized the role of snow accumulation and melting in GWR (Aygün et al, 2020; Dubois et al, 2022, 2021a; Greenwood & Buttle, 2018; Morgan et al, 2021; Wright & Novakowski, 2020; Young et al, 2019). Winter‐related model parameters (snowmelt coefficient, melting temperature, freezing soil) are also known to be very sensitive when simulating cold region hydrology (Dubois et al, 2021a; Mai et al, 2022; Nemri & Kinnard, 2020). More research therefore needs to be dedicated to refining the calibration of winter‐related model parameters in LC change contexts.…”

“…In order to understand the effect of LC changes on long‐term GWR simulations, the results obtained using HB LC were compared to the GWR simulated with HB over the 1990–2010 period (Dubois et al, 2021a) and over the 1951–2100 period (Dubois et al, 2022) (Figure 2). The performance of HB and HB LC were compared using the Kling–Gupta Efficiency (KGE) calculated (1) with monthly measured and simulated total flow (KGE qtot ) and (2) with the monthly baseflow (estimated using the Lyne and Hollick recursive filter) and simulated GWR (KGE qbase ).…”

“…Over the same study area, Dubois et al (2021a) (Hopkinson et al, 2011;Hutchinson et al, 2009) and downscaled to the reference 10 km  10 km resolution using the quantile mapping approach of Mpelasoka and Chiew (2009).…”

“…However, this study showed that the intense afforestation simulated for RCP4.5 scenarios produced significant changes in HB LC for smaller changes in climate conditions than were observed for RCP8.5 scenarios (Figure 7). Studies in cold climates with seasonal snowpack have emphasized the role of snow accumulation and melting in GWR (Aygün et al, 2020;Dubois et al, , 2021aGreenwood & Buttle, 2018;Morgan et al, 2021;Wright & Novakowski, 2020;Young et al, 2019).…”

Data-driven Estimation of Groundwater Level Time-Series Using Comparative Regional Analysis

“…• If the percentage of broadleaved forests exceeds approximately 10%, groundwater levels become flashier in wet states, which can be linked to higher soil moisture, preferential flow and recharge than other land cover types, reducing surface runoff (Brinkmann et al, 2019;Dubois et al, 2021).…”