This paper presents future runoff projections across Australia, modelled using climate change projections from 42 CMIP5 global climate models (GCMs) used in the most recent Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The empirical delta scaling method is used to scale the observed historical climate data, informed by the change signal in the GCM (for 2046–2075 relative to 1976–2005 for RCP8.5), to reflect a future climate series. The historical and future runoffs are simulated using a daily hydrological model at 0.05o grid cells, using parameter values from the geographically nearest calibration catchment (the model is calibrated against streamflow data from more than 700 catchments). The plots in Figure 1 show the median and 10th to 90th percentile range of projections for mean summer, winter and annual runoffs. The median projection for Northern Australia is about 5% reduction in mean annual runoff, with a 10th to 90th percentile uncertainty range of –40% to +30%. The median projection for eastern Australia is about 15% reduction in mean annual runoff with an uncertainty range of –40% to +20%. There is stronger agreement in the projections for declining runoff in the far south-west and far south-east where the large majority of GCMs project a drier future winter when most of the runoff in these regions occur. In the far southwest, the median projection is a decline of mean annual runoff of 50% (with an extreme dry projection of –70%), and in the far south-east, the median projection is a decline of mean annual runoff of 20% (with an extreme dry projection of –40%). The paper also discusses the limitations, science challenges and opportunities in producing the next generation hydroclimate projections.
CITATION STYLE
Chiew, F. H. S., Zheng, H., Potter, N. J., Ekstrom, M., Grose, M. R., Kirono, D. G. C., … Vaze, J. (2017). Future runoff projections for Australia and science challenges in producing next generation projections. In Proceedings - 22nd International Congress on Modelling and Simulation, MODSIM 2017 (pp. 1745–1751). Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). https://doi.org/10.36334/modsim.2017.l16.chiew
Mendeley helps you to discover research relevant for your work.