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Impact of future climate on Tasmanian rivers


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Bennett, JC (2013) Impact of future climate on Tasmanian rivers. Research Master thesis, University of Tasmania.

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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. This thesis describes changes to surface water availability in Tasmania for the 21st century assessed from a series of high-resolution regional climate and hydrological models. Surface water projections are generated by bias-correcting regional climate model (RCM) simulations, passing the bias-corrected RCM simulations through rainfall-runoff models, and then passing runoff through river models that simulate water diversions and consumption.
The bias-correction applied to daily RCM simulations is a quantile mapping technique that aligns empirical frequency distributions of RCM variables to observations. We show that quantile mapping of empirical distributions can be highly effective in correcting biases in RCM outputs. Cross-validation shows biases are effectively reduced across the range of cumulative frequency distributions, with few exceptions. The bias-correction is not as effective at correcting biases for values at or near zero (e.g. in rainfall simulations), although even here the bias-correction improves biases in the uncorrected simulations. In addition, the bias-correction improves frequency characteristics of variables such as the number of rain days.
The bias-correction effectively preserves long-term changes (e.g. to the mean and variance) to variables projected by the uncorrected RCM simulations. Correlations between key variables are also largely preserved, thus the bias-corrected outputs largely reflect the dynamics of the underlying RCM. However, the bias-corrected simulations still exhibit some of the deficiencies of the RCM simulations, for example the tendency to underestimate both the magnitude and duration of large, multi-day rain events.
Bias-corrected outputs from six fine-scale (10 km2) simulations of daily rainfall and potential evapotranspiration generated with the CSIRO Conformal Cubic Atmospheric Model (CCAM), a variable-resolution RCM, are used as direct inputs to the hydrological models AWBM, IHACRES, Sacramento, SIMHYD and SMAR-G to project Tasmanian runoff. 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.
Changes to rivers are assessed by passing runoff projections through models that account for water diversions and water use, including hydro-electric power generation. Of the 78 rivers modelled, on average 32 are projected to have changes to mean annual flows of more than ±10% by 2100. On average, 28 of the 78 rivers modelled are projected to have decreased flows by 2100. The likely reduction in runoff to the central highlands will mean reduced inflows to irrigation storages. For example, the mean inflows to Lake Crescent/Sorell and Meander Dam are likely to fall by 20% and 13% respectively. Conversely, large irrigation storages supplying the Macquarie and Coal river catchments are projected to experience increased inflows by 2100. Hydropower generation is projected to decrease by 6%, mainly caused by decreased runoff from the central highlands.
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. The fine spatial resolution of the runoff projections allows us to generate plausible scenarios of river flows at the catchment scale, which is most relevant to water managers. The surface-water projections generated in this study are being used to inform water planning and policy by the Tasmanian government.

Item Type: Thesis (Research Master)
Keywords: regional climate model, surface water availability, rainfall-runoff modelling, bias-correction, climate change
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Copyright 2013 the author

Additional Information:

Chapter 3 appears to be the equivalent of a pre-peer reviewed version of the following article: Bennett, J. C., Grose, M. R., Corney, S. P., White, C. J., Holz, G. K., Katzfey, J. J., Post, D. A., Bindoff, N. L., 2013. Performance of an empirical bias-correction of a high-resolution climate dataset, International journal of climatology, 34(7), 2189-2204, which has been published in final form at This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Chapter 4 appears to be the equivalent of a pre-print version of the following article: Bennett, J. C., Ling, F. L. N., Post, D. A., Grose, M. R., Corney, S. P., Graham, B., Holz, G. K., Katzfey, J. J., Bindoff, N. L., 2012. High-resolution projections of surface water availability for Tasmania, Australia, Hydrology and Earth system sciences, 16, 1287-1303

Appendix A has been removed for copyright or proprietary reasons. It has been published online as: Bennett, J. C., Grose, M. R., Post, D. A., Ling, F. L. N., Corney, S. P., Bindoff, N. L., 2011. Performance of quantile-quantile bias-correction for use in hydroclimatological projections. MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand: Perth. Available online at:

Date Deposited: 29 Jan 2014 04:44
Last Modified: 29 May 2017 00:17
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