In the context of water management in agriculture, irrigation scheduling is critically important as it optimises water application to crops and can also target specific production goals. However, there is no consensus on the ideal irrigation scheduling strategy regarding crop water use efficiency (WUE_c). In a premium Cabernet Sauvignon vineyard in Coonawarra, South Australia, over three growing seasons, irrigation scheduling strategies based on experience or historical knowledge (‘GROW’ treatment) were compared to data-driven strategies including crop evapotranspiration, and plant and soil water status thresholds to evaluate their effects on leaf- and vine-level WUEs. A final treatment, GROW + , that doubled the GROW level of irrigation was also evaluated in the third season. The WUE metrics were determined at the leaf, vine, and fruit scales as intrinsic WUE (WUE_i), crop WUE (WUE_c), and carbon isotope ratio (δ¹³C), respectively. Furthermore, the irrigation strategies were evaluated in the background of two contrasting soil types: Terra Rossa (light clay, well-drained) and Rendzina (heavier clay, poorly drained). Seasonal soil and vine water status, leaf gas exchange, and light interception were measured, and yield components and pruning weights were obtained following harvest. The amount of seasonal irrigation water based on the data-driven strategies was up to 65% lower across both soil types compared with the GROW or GROW + approaches. WUE_i and δ¹³C were largely similar between treatments. However, for vines grown on Terra Rossa soil, little to no yield penalty was observed when data-driven irrigation scheduling was applied, in addition to increased WUE_c values of up to 41%. It can be concluded that irrigation scheduling decisions based on data were superior to the conventional irrigation scheduling method on account of reducing irrigation water volume and increasing WUE, particularly in Terra Rossa soils.

在农业用水管理的背景下，灌溉调度至关重要，因为它可以优化对作物的用水，还可以针对特定的生产目标。然而，关于作物水分利用效率的理想灌溉调度策略尚未达成共识（WUE _c). 在南澳大利亚库纳瓦拉的优质赤霞珠葡萄园中，在三个生长季节中，将基于经验或历史知识（“GROW”处理）的灌溉调度策略与数据驱动策略（包括作物蒸发蒸腾、植物和土壤水分状况阈值）进行了比较评估它们对叶级和藤级 WUE 的影响。在第三季中还评估了最终处理 GROW + ，它使 GROW 灌溉水平翻了一番。WUE 指标在叶、藤和果实尺度上确定为固有 WUE ( WUE _i )、作物 WUE ( WUE _c ) 和碳同位素比 (δ ¹³C），分别。此外，在两种截然不同的土壤类型背景下评估了灌溉策略：Terra Rossa（轻粘土，排水良好）和 Rendzina（重粘土，排水不良）。测量了季节性土壤和葡萄树的水分状况、叶片气体交换和光拦截，并在收获后获得了产量构成和修剪重量。与 GROW 或 GROW + 方法相比，基于数据驱动策略的季节性灌溉水量在两种土壤类型中最多减少 65%。WUE _i和 δ ¹³ C 在处理之间基本相似。然而，对于在 Terra Rossa 土壤上生长的葡萄树，除了增加WUE外，在应用数据驱动的灌溉计划时几乎没有观察到产量损失_c值高达41%。可以得出结论，基于数据的灌溉调度决策优于传统的灌溉调度方法，因为它减少了灌溉水量并增加了 WUE，特别是在 Terra Rossa 土壤中。