Some Selected Case Studies

Kirshen [12] used MODFLOW [13] to study the impact of climate change on a highly permeable aquifer in the northeastern United States. Groundwater recharge was estimated using a separate model based on precipitation and potential evapotranspiration. Both hypothetical and GCM-predicted changes to the input parameters were used, resulting in higher, no different, and significantly lower recharge rates and groundwater elevations, depending on the climate scenario used.

In another study, Croley and Luukkonen [14] investigated the impact of climate change on groundwater levels in Lansing, MI, USA. The groundwater recharge rates were based on an empirical streamflow model which was calibrated using the results from two GCMs.

Scibek and Allen [9] developed a different approach by downscaling GCM model results using the Statistical Downscaling Model (SDSM) and then applying the resulting change factors in the LARS-WG weather generator to obtain future climate conditions. The HELP model was applied as the recharge model and a transient groundwater flow model was used to simulate four climate scenarios. Groundwater levels were compared to the present and it was found that the effect of spatial distribution of recharge on groundwater levels, compared to that of a single uniform recharge zone, is much larger than that of temporal variation in recharge, compared to a mean annual recharge representation. A very similar modeling approach was taken by Jyrkama and Sykes [8] who studied the Grand River watershed in Ontario, Canada. The difference in their approach was that recharge zoning was not used and recharge values were calculated for each grid cell.

Woldeamlak et al. [15] studied the potential impacts of climate change on the Grote-Nete basin in Belgium. Wet, cold and dry future climate scenarios were formulated by assigning percentage and absolute changes on current precipitation and temperature, respectively. Based on these scenarios and present climate, recharge was simulated with a distributed water-balance model. Annual, summer and winter recharge rate maps were obtained and used as recharge boundaries for the steady-state MODFLOW model. Simulated changes in groundwater head, discharge rates and discharge areas were presented.

Hsu et al. [16] applied a different method in the recharge estimation for the Pingtung Plain in Taiwan. Records of historical precipitation data were analyzed to determine the long-term pattern of climate change. Regression equations were obtained to predict future precipitation. Methods of water-table fluctuation and model inversion were combined to estimate recharge in this study. An annual precipitation rate reduction of 7.8 mm/year and its corresponding reflection in the decrease of recharge were applied in the groundwater flow modeling.

In another study, a groundwater flow model was developed for the Okanagan basin in British Columbia, Canada, by Toews and Allen [17], where irrigation return flow was considered in the determination of current and future recharge. Downscaling of GCM results was performed with multi-linear regression and recharge was estimated using the HELP model. It was also used to explicitly calculate irrigation return flow for present and future conditions. Transient groundwater flow simulations were performed with MODFLOW.

Rozell and Wong [18] investigated the relationship between climate change and seawater intrusion for an island with a variable-density transient groundwater flow model. Global predictions from the IPCC for changes in precipitation and sea-level rise over the next century were used to create two future climate scenarios, therefore no downscaling was performed.

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