Abstract
Abstract. Changes to streamflows caused by climate change may have major impacts on the management of water for hydro-electricity generation and agriculture in Tasmania, Australia. We describe changes to Tasmanian surface water availability from 1961–1990 to 2070–2099 using high-resolution simulations. Six fine-scale (∼10 km2) 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. 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. There is much greater variation in projections between RCM simulations than between hydrological models. 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. 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.
Highlights
Human-induced climate change has been shown to contribute to changes in the spatial distribution of precipitation in the 20th century (Zhang et al, 2007)
Biases of uncorrected regional climate model (RCM) rainfalls are larger than ±30 % for much of Tasmania, and exceed 150 % in some cells
We had 47 yr of synchronous simulations and observations, which allowed 23 yr to train the quantile mapping for the cross-validation tests. 23 yr may be an insufficiently long period to sample the natural variance in rainfall
Summary
Human-induced climate change has been shown to contribute to changes in the spatial distribution of precipitation in the 20th century (Zhang et al, 2007). In a warmer future world, understanding the local and regional implications of changes in the hydrological cycle is critical to planning for water security (Oki and Kanae, 2006). Dynamical regional climate models (RCMs) have been used to assess climate change impacts on spatial distributions of rainfall (Kilsby, 2007), seasonal changes to rainfall (Kendon et al, 2010), and changes. Bennett et al.: High-resolution projections of surface water availability to rainfall intensity (Berg et al, 2009) and frequency (Mailhot et al, 2007) at spatial scales relevant to water managers
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