期刊
WATER RESOURCES RESEARCH
卷 51, 期 10, 页码 8362-8379出版社
AMER GEOPHYSICAL UNION
DOI: 10.1002/2015WR017058
关键词
-
资金
- Australian Postgraduate Award
- CSIRO Land & Water Flagship Scholarship
- NCCARF Water Network Scholarship
From similar to 1997 to 2009 the Murray-Darling Basin (MDB), Australia's largest water catchment and reputed ``food bowl,'' experienced a severe drought termed the ``Millennium Drought'' or ``Big Dry'' followed by devastating floods in the austral summers of 2010/2011, 2011/2012, and 2012/2013. The magnitude and severity of these extreme events highlight the limitations associated with assessing hydroclimatic risk based on relatively short instrumental records (similar to 100 years). An option for extending hydroclimatic records is through the use of paleoclimate records. However, there are few in situ proxies of rainfall or streamflow suitable for assessing hydroclimatic risk in Australia and none are available in the MDB. In this paper, available paleoclimate records are reviewed and those of suitable quality for hydroclimatic risk assessments are used to develop preinstrumental information for the MDB. Three different paleoclimate reconstruction techniques are assessed using two instrumental rainfall networks: (1) corresponding to rainfall at locations where rainfall-sensitive Australian paleoclimate archives currently exist and (2) corresponding to rainfall at locations identified as being optimal for explaining MDB rainfall variability. It is shown that the optimized rainfall network results in a more accurate model of MDB rainfall compared to reconstructions based on rainfall at locations where paleoclimate rainfall proxies currently exist. This highlights the importance of first identifying key locations where existing and as yet unrealized paleoclimate records will be most useful in characterizing variability. These results give crucial insight as to where future investment and research into developing paleoclimate proxies for Australia could be most beneficial, with respect to better understanding instrumental, preinstrumental and potential future variability in the MDB.
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