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

Bruneau, Sabrina; Barbecot, Florent; Larocque, Marie; Horoi, Viorel; Coquet, Yves; Guillon, Sophie

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 | Modélisation de la zone non saturée pour identifier les contrôles sur la recharge des eaux souterraines dans un aquifère granulaire libre dans un environnement froid et humide avec différentes sources de données météorologiques Modelado de la zona vadosa para identificar los controles de la recarga de agua subterránea en un acuífero granular no confinado en un clima frío y húmedo con diferentes fuentes de datos meteorológicos 采用不同气象数据源的包气带模拟确定寒冷和潮湿环境中潜水颗粒含水层地下水补给控制因素 Modelagem da zona vadosa para identificar controles de recarga de água subterrânea em um aquífero granular não confinado em um ambiente frio e úmido com diferentes fontes de dados meteorológicos

2022

Groundwater recharge (GR) is a complex process that is difficult to quantify. Increasing attention has been given to unsaturated zone modeling to estimate GR and better understand the processes controlling it. Continuous soil-moisture time series have been shown to provide valuable information in this regard. The objectives of this study were to (i) analyze the processes and factors controlling GR in an unconfined granular aquifer in a cold and humid environment and (ii) assess the uncertainties associated with the use of data from different sources. Soil moisture data monitored over three years at three experimental sites in southern Quebec (Canada) were used to calibrate the HYDRUS-1D model and to estimate ranges of possible GR in a region where groundwater is increasingly used as a source of fresh water. The simulations identified and quantified important factors responsible for the near-surface water balance that leads to GR. The resulting GR estimates from 2016 to 2018 showed marked differences between the three sites, with values ranging from 347 to 735 mm/y. Mean GR for the three sites was 517 mm/y for 2016–2018 and 455 mm/y for the previous 12-year period. GR was shown to depend on monthly variations in precipitation and on soil textural parameters in the root zone, both controlling soil-water retention and evapotranspiration. Monthly recharge patterns showed distinct preferential GR periods during the spring snowmelt (38–45% of precipitation) and in the fall (29% of precipitation). The use of different meteorological datasets was shown to influence the GR estimates.

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