High-resolution projections of surface water availability for Tasmania, Australia

Abstract

Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electric generation and agriculture in Tasmania, Australia. We present high-resolution projections of Tasmanian surface water availability between 1961–1990 and 2070–2099. Six fine-scale (10 km) simulations of daily rainfall and potential evapotranspiration are generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution regional climate model (RCM). These variables are bias-corrected with quantile mapping and used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project streamflows. <br><br> The performance of the hydrological models is assessed against 86 streamflow gauges across Tasmania. The SIMHYD model is the least biased (median bias = −3%) while IHACRES has the largest bias (median bias = −22%). We find the hydrological models that best simulate observed streamflows produce similar streamflow projections. In contrast, the poorly performing IHACRES model amplifies changes more than the other hydrological models. <br><br> There is much more variation in projections between RCM simulations than between hydrological models. This shows that it is more important to consider the range of RCM simulations than the range of hydrological models used here to adequately describe uncertainty in the projections. <br><br> We use the SIMHYD model to describe future changes to streamflow in eight rivers. Changes to streamflows are projected to vary by region. Marked decreases of up to 30% are projected for annual runoff in central Tasmania, while runoff is generally projected to increase in the east. Daily streamflow variability is projected to increase for most of Tasmania, consistent with increases in rainfall intensity. Inter-annual variability of streamflows is projected to increase across most of Tasmania. <br><br> This is the first major Australian study to use high-resolution bias-corrected rainfall and potential evapotranspiration projections as direct inputs to hydrological models. Our study shows that these simulations are capable of producing realistic streamflows, allowing for increased confidence in assessing future changes to surface water variability

An appraisal of downscaling methods used in climate change research

“…This topic is not discussed further here other than remarking that there are numerous bias correcting methods involving various degrees of complexity. [82][83][84][85][86][87][88] It is worth noting that some researchers express concern that bias correction acts to blur the interpretation of climate change signal by altering the spatiotemporal field of consistency, and modify relationships among variables by violating conservation principles. 89 Further, researchers note that it is important to use historical data of similar spatial scale to that of the RCM output for bias correction.…”