[1] Considering that past climate changes have significantly impacted groundwater resources, quantitative predictions of climate change effects on groundwater recharge may be valuable for effective management of future water resources. This study used 16 global climate models (GCMs) and three global warming scenarios to investigate changes in groundwater recharge rates for a 2050 climate relative to a 1990 climate in the U.S. High Plains region. Groundwater recharge was modeled using the Soil-Vegetation-AtmosphereTransfer model WAVES for a variety of soil and vegetation types representative of the High Plains. The median projection under a 2050 climate includes increased recharge in the Northern High Plains (þ8%), a slight decrease in the Central High Plains (À3%), and a larger decrease in the Southern High Plains (À10%), amplifying the current spatial trend in recharge from north to south. There is considerable uncertainty in both the magnitude and direction of these changes in recharge projections. Predicted changes in recharge between dry and wet future climate scenarios encompass both an increase and decrease in recharge rates, with the magnitude of this range greater than 50% of current recharge. On a proportional basis, sensitivity of recharge to changes in rainfall indicates that areas with high current recharge rates are least sensitive to change in rainfall and vice versa. Sensitivity analyses indicate an amplification of change in recharge compared to change in rainfall, and this amplification is in the range of 1-6 with an average of 2.5-3.5 depending upon the global warming scenario.

The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.

Droughts have significant environmental and socio-economic impacts in Australia. This emphasizes Australia's vulnerability to climate variability and limitations of adaptive capacity. Two drought indices are compared for their potential utility in resource management. The Rainfall Deciles-based Drought Index is a measure of rainfall deficiency while the Soil-Moisture Deciles-based Drought Index is a measure of soil-moisture deficiency attributed to rainfall and potential evaporation. Both indices were used to assess future drought events over Australia under global warming attributed to low and high greenhouse gas emission scenarios (SRES B1 and A1F1 respectively) for 30-year periods centred on 2030 and 2070. Projected consequential changes in rainfall and potential evaporation were based on results from the CCCma1 and Mk2 climate models, developed by the Canadian Climate Center and the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) respectively. A general increase in drought frequency associated with global warming was demonstrated by both indices for both climate models, except for the western part of Australia. Increases in the frequency of soil-moisture-based droughts are greater than increases in meteorological drought frequency. By 2030, soil-moisture-based drought frequency increases 20-40% over most of Australia with respect to 1975-2004 and up to 80% over the Indian Ocean and southeast coast catchments by 2070. Such increases in drought frequency would have major implications for natural resource management, water security planning, water demand management strategies, and drought relief payments.

[1] The impact of climate change upon groundwater has an increasing profile in the literature but there is little guidance on selecting Global Climate Models (GCMs), downscaling methods or hydrological models. This paper quantifies the relative uncertainties inherent in projections of future recharge contributed by multiple GCMs, downscaling methods and hydrological models at three locations across southern Australia. Results highlight that the choice of GCM is the largest source of uncertainty, with a median range between the highest and lowest GCM of 53% of the historical recharge for a given downscaling method and hydrological model. The downscaling method is the next largest source of uncertainty with a median range of 44% and the choice of hydrological model is the source of the least uncertainty with a median range of 24%. These results strongly suggest that impact studies should use multiple GCMs and give careful consideration to the choice of downscaling methods.

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