Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

Abstract

[1] Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software ''HydroGeoSphere.'' This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions. Citation: Goderniaux, P., S. Brouyère, S. Blenkinsop, A. Burton, H. J. Fowler, P. Orban, and A. Dassargues (2011), Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios, Water Resour. Res., 47, W12516,

Spatio-temporal impact of climate change on the groundwater system

“…Woldeamlak et al (2007) stated that climate change impact studies based on steady-state groundwater simulation have limitations in representing boundary conditions and can only be used for assessing sensitivities. A few recent studies have applied transient methods to estimate the impact of climate changes on the groundwater system (Goderniaux et al, 2009;van Roosmalen et al, 2009;Goderniaux et al, 2011;Jackson et al, 2011;Stoll et al, 2011). However, van Roosmalen et al (2009), Goderniaux et al (2009, Jackson et al (2011) and Stoll et al (2011) limit the analysis of the transient results to the predicted head change in some observation wells or to the average change in groundwater head of the basin without analyses of the spatial variation.…”

Potential climate change impacts on the water balance of regional unconfined aquifer systems in south-western Australia

“…Pirani, 2011;Taylor et al, 2012) and simulation results from downscaled global circulation models have been used for regional studies of the impact on the hydrological cycle by integrated hydrological models (e.g. van Roosmalen et al, 2007van Roosmalen et al, , 2009Goderniaux et al, 2009Goderniaux et al, , 2011 including water quality issues .…”

A watershed-scale study of climate change impacts on groundwater recharge (Annapolis Valley, Nova Scotia, Canada)

“…As with other studies, these authors also found that recharge would increase subtantially during the winter. Stoll et al (2011) and Goderniaux et al (2011) also used coupled integrated surface/subsurface models (MIKE SHE (Système Hydrologique Européen) and HydroGeoSphere, respectively) to study the potential impacts of climate change on groundwater for small-to moderate-size catchments (9 and 480 km 2 ). Stoll et al (2011) used eight GCM/RCM combinations and concluded that the downscaling process was an important source of uncertainty in hydrological impact studies.…”

“…They recommended that downscaling techniques be verified before applying them to climate model data. Goderniaux et al (2011) used a stochastic weather generator to obtain 30 transient climatic scenarios for each of six different RCMs. They showed that the climate change signal becomes stronger than that of natural climate variability by 2085.…”