Boser Anna, Caylor Kelly, Larsen Ashley, Pascolini-Campbell Madeleine, Reager John T, Carleton Tamma
Bren School of Environmental Science and Management, UC Santa Barbara, 2400 Bren Hall, Santa Barbara, 93106, CA, USA.
Department of Geography, UC Santa Barbara, Ellison Hall, Santa Barbara, 93106, CA, USA.
Nat Commun. 2024 Mar 25;15(1):2366. doi: 10.1038/s41467-024-46031-2.
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.
在气候变化的背景下，有效管理农业灌溉对于当今及未来的粮食安全至关重要。然而，由于缺乏作物耗水量的田间尺度数据，评估农业的水文影响及其减少策略仍具有挑战性。在此，我们开发了一种利用遥感和机器学习来填补这一空白的方法，并利用该方法评估加利福尼亚中央谷地的节水策略。我们发现，改种需水量较低的作物可使用水量减少多达93%，但这需要采用不常见的作物类型。北部县的灌溉效率明显低于南部县，这表明了另一个节水潜力来源。其他不改变土地覆盖的做法可节省高达11%的用水量。这些结果揭示了实现可持续用水的多种途径，强调了田间尺度作物耗水量地图在指导加利福尼亚及其他地区水资源管理方面的潜力。
