Simulated Impacts of Climate Change on Groundwater Recharge in the Subtropics of Queensland, Australia

Abstract

Increased atmospheric concentrations of CO2 could affect Australia’s groundwater resources via changes in rainfall and potential evapotranspiration regimes. The extent to which groundwater resources are affected by climate change will depend upon the local soils and vegetation. As a case study, we assess the potential impacts of climate change on groundwater recharge beneath North Stradbroke Island off the subtropical east coast of Queensland, Australia The simulated climates come from equilibrium (constant CO2 concentration) runs of the CSIRO9 general circulation model (GCM) for present and double-CO2 conditions. Based on the GCM output for each climate, a stochastic point weather generator, MWGEN, produces realisations of the daily climate variables. This climate “data” drives a numerical simulator, WAVES, of rainfall infiltration, variably saturated flow and evapotranspiration, producing temporal distributions of the daily groundwater recharge rate for various soil-vegetation environments. The transformation from rainfall infiltration to groundwater recharge can amplify the effects of climate change because of flow and storage in soils and dynamic plant water use. The simulation results indicate that double-CO2 climate change could more than double the net groundwater recharge; this increase is disproportionate to a 37 percent rise in mean annual rainfall, with ratios of the change in recharge to change in rainfall ranging from 0.76 to 1.05 for different soil-vegetation combinations. Such increases in recharge are enhanced by the dynamic growth and die-back of vegetation. The mean recharge rate, inter-annual variability and persistence in deviations from the mean are related to the soil and vegetation characteristics. Further improvements in estimating future climate and plant-water use should increase our understanding of the sensitivity of groundwater resources to expected climate change and climate variability.