Simulation of long-term spatiotemporal variations in regional-scale groundwater recharge: Contributions of a water budget approach in southern Quebec

Abstract

Abstract. Groundwater recharge (GWR) is recognized to be a strategic hydrologic variable, necessary to estimate when implementing sustainable groundwater management, especially within a global change context. However, its simulation at the regional scale and for long-term conditions is challenging, especially due to the limited availability of spatially-distributed calibration data and to the rather short observed time series. The use of a superficial water budget model to estimate recharge is appropriate for this task. A reliable regional-scale estimate of GWR that can be updated relatively easily using widely-available data is essential for the implementation of long-term water use policies and is clearly lacking in southern Quebec (Canada; 36 000 km2). This study aims to test the ability of a spatially-distributed water budget model, automatically calibrated with river flow rates and baseflow estimates, to simulate GWR at a regional-scale from 1961 to 2017 in southern Quebec (monthly time step, 500 m × 500 m spatial resolution). The novelty of this work lies in the simulation of the first regional-scale GWR estimate for southern Quebec and in the development of a robust approach to implement a superficial water budget model at the regional-scale and for a long period. The HydroBudget model was specifically developed by a team at Université du Québec à Montréal for regional-scale simulation and cold climate conditions, and uses parsimonious input data (distributed precipitation, temperature, and runoff curve numbers). The model was regionally calibrated with river flows and baseflows (recursive filter on river flow data), and the automatic calibration procedure of the R package caRamel allowed a satisfying calibration quality (KGE = 0.72) to be reached. Across the study area and based on the exceptionally long spatialized time series, the simulated water budget was divided into 41 % runoff (444 mm/yr), 47 % actual evapotranspiration (501 mm/yr), and 12 % potential groundwater recharge (139 mm/yr). This partitioning was influenced by precipitation, temperature, soil texture, land cover, and topography. Groundwater recharge peaked during spring (44 % of annual recharge) and winter (32 % of annual recharge). A novel and particularly useful result from this work was to show that the seasonality of recharge was driven by the regional temperature gradient, with decreasing temperatures from west to east, and that winter GWR presented a statistically significant increasing trend since 1961 due to increased precipitation and warming temperatures. Another original contribution of this work was to show that at the regional scale, water budget models, such as HydroBudget, can be easily calibrated with river flow measurements and baseflows, and therefore represent a good option with which to acquire knowledge about regional hydrological dynamics. Being accessible, they are a useful approach for scientists, modellers, and stakeholders alike to understand regional-scale groundwater renewal rates, especially if they can be easily adapted to specific study needs and environments.

Groundwater recharge over the past 100 years: Regional spatiotemporal assessment and climate change impact over the Saguenay‐Lac‐Saint‐Jean region, Canada

“…The overall annual variability in PGR over time is linked to that of temperature and VI. Here, the observed relationships between PGR, VI and temperature patterns are consistent with that reported in other studies undertaken under similar climate conditions and comparable geological environments (Chemingui et al, 2015; Dubois et al, 2021; Hayashi & Farrow, 2014).…”

“…The annual increase in PGR simulated in this study for the consistent with the results from the PGR study conducted by Dubois et al (2021) in the Montreal region of Southern Quebec. In this comparable study, Dubois et al (2021) found that PGR presented a statistically significant increasing trend over 56 years (1961–2017). In this study, O.P.#4 shows a steep increase in PGR rates, whereas O.P.#1 shows the most modest increase in PGR rates.…”

“…Some of the uncertainties regarding the AET estimates can be related to the simplification of the approach, which does not consider important AET factors such as soil moisture or air vapour saturation. If these observations were available, a more complex approach for estimating AET could be implemented using an energy budget (Dubois et al, 2021). The SCS/CN method has received some criticism related mostly to its empirical origin developed for specific US context (Ogden et al, 2017; Ponce & Hawkins, 1996).…”

“…The implementation of sustainable groundwater management strategies are required to anticipate and mitigate groundwater deficit scenarios and to sustain or increase current qualities of life. Knowledge of groundwater recharge potential and its distribution (mapping) are necessary for sustainable groundwater management (Ashaolu et al, 2020; Dubois et al, 2021). The groundwater recharge can be defined as the water infiltrating into the subsurface and travelling through the unsaturated zone to reach the water table.…”

Vadose zone modeling to identify controls on groundwater recharge in an unconfined granular aquifer in a cold and humid environment with different meteorological data sources

“…Under a wide variety of conditions, GR is still considered to be one of the most challenging water-balance components to quantify (Dripps and Bradbury 2007) because it is difficult to measure directly and it is strongly influenced by climate, soil heterogeneity and land use. A wide range of methods (Scanlon et al 2002) has been shown to be useful in assessing the quantity of water actually replenishing an aquifer, including isotopic profiles (Barbecot et al 2018;Mattei et al 2020a, b), remote sensing techniques (Jackson 2002), chloride mass balance (Szilagyi et al 2011), base flow separation (Hung Vu and Merkel 2019), unsaturated zone modeling (Hu et al 2019;Mattei et al 2020a), water balance models (Dubois et al 2021) and water table fluctuations (Crosbie et al 2005). The reliability of these methods depends on a variety of factors, including the availability of field data to describe site characteristics, such as soil type, vegetation and depth to the water table (Scanlon et al 2002).…”