农业
作物
比例(比率)
消费(社会学)
用水量
环境科学
大田作物
领域(数学)
用水
农业经济学
农业工程
农学
水资源管理
经济
地理
生物
生态学
数学
工程类
社会科学
地图学
社会学
纯数学
作者
Anna Boser,K. K. Caylor,Ashley E. Larsen,Madeleine Pascolini‐Campbell,J. T. Reager,Tamma Carleton
标识
DOI:10.1038/s41467-024-46031-2
摘要
Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture's hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California's Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.
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