Sachinda Ekanayake, John Boland, Baden Myers, Guna A. Hewa
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引用次数: 0
Abstract
The Murray Mallee (MM) and Upper Eyre Peninsula (UEP) are two important regions to the South Australian agricultural economy. The UEP is dominated by agricultural land use with a semi-arid Mediterranean-type climate, with low, variable annual rainfall. The climate is similar, with significant farming production around the Murray Mallee, adjacent to the Murray River. When investigating rainfall trends in the UEP region, annual rainfall has decreased considerably in the last 73 years, from 1950 to 2023, at all rain monitoring stations. From the 15 stations in the MM, most of the locations' rainfall is decreasing, but three stations, including Callington, Murray Bridge, and Mannum, show an increasing trend in annual rainfall. Monarto Safari Park station had only recent rainfall records; however, it also shows an increasing trend. The records for MM, particularly for gauges where rainfall has seen an increasing trend, seem to correspond with a revegetation program on the Monarto Plateau during the 1970s, and this may have been significant enough to increase rainfall in the surrounding regions, including Callington and Murray Bridge. Each station's annual rainfall, mean minimum temperature, and mean maximum temperature data are analyzed separately using trend analysis with exponential smoothing and three robust change-point analysis methods in the MM and UEP regions. The significant change points observed in annual rainfall and temperature in each location and the overall reduction in rainfall may be attributed to industrial expansion, climate change, and shifts in land use patterns driven by urbanization, which have likely impacted water resources. This study investigated the relationship between land use and climate change that may impact South Australian rainfall patterns and increases in temperature over the last few decades.
期刊介绍:
Environmetrics, the official journal of The International Environmetrics Society (TIES), an Association of the International Statistical Institute, is devoted to the dissemination of high-quality quantitative research in the environmental sciences.
The journal welcomes pertinent and innovative submissions from quantitative disciplines developing new statistical and mathematical techniques, methods, and theories that solve modern environmental problems. Articles must proffer substantive, new statistical or mathematical advances to answer important scientific questions in the environmental sciences, or must develop novel or enhanced statistical methodology with clear applications to environmental science. New methods should be illustrated with recent environmental data.