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  • 标题:Local land–atmosphere feedbacks limit irrigation demand
  • 本地全文:下载
  • 作者:Mark Decker ; Shaoxiu Ma ; Andy Pitman
  • 期刊名称:Environmental Research Letters
  • 印刷版ISSN:1748-9326
  • 电子版ISSN:1748-9326
  • 出版年度:2017
  • 卷号:12
  • 期号:5
  • 页码:054003
  • DOI:10.1088/1748-9326/aa65a6
  • 语种:English
  • 出版社:IOP Publishing Ltd
  • 摘要:Irrigation is known to influence regional climate but most studies forecast and simulate irrigation with offline (i.e. land only) models. Using south eastern Australia as a test bed, we demonstrate that irrigation demand is fundamentally different between land only and land–atmosphere simulations. While irrigation only has a small impact on maximum temperature, the semi-arid environment experiences near surface moistening in coupled simulations over the irrigated regions, a feedback that is prevented in offline simulations. In land only simulations that neglect the local feedbacks, the simulated irrigation demand is 25% higher and the standard deviation of the mean irrigation rate is 60% smaller. These local-scale irrigation-driven feedbacks are not resolved in coarse-resolution climate models implying that use of these tools will overestimate irrigation demand. Future studies of irrigation demand must therefore account for the local land–atmosphere interactions by using coupled frameworks, at a spatial resolution that captures the key feedbacks.
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