Efficient water management is pivotal for viticulture sustainability. Decision support tools can advise on how to optimize irrigation or on the feasibility of growing grapes in rainfed conditions, but reliable algorithms for assessing vine water status are required. In this context, the aim of the current study was to upgrade a soil water balance model specific for vineyards by incorporating meteorological, soil and vine vigor in equations that transform the fraction of transpirable soil water into midday stem water potential (Ψstem). The model's sensitivity to variations in the magnitude of input parameters was analyzed. Furthermore, the model was tested in a broad scope of Spanish vineyards with different grapevine cultivars (both red and white), rootstocks, plant age, soil and climatic conditions, and water regimes, totaling 129 scenarios. The model was only slightly sensitive to variations in the magnitude of most inputs, except for the fraction of transpirable water at which leaf stomatal conductance begin to decline. Moreover, the model satisfactorily reproduced the evolution of Ψstem over the growing season, although it slightly overestimated the measured Ψstem values, as the slopes of the fitted regression lines were lesser than 1 on most occasions, 76 out of 129. Nonetheless, the coefficients of determination for these relationships were greater than 0.9, except for 21 datasets. Mean errors averaged 0.024 ± 0.015 MPa, while root mean square errors averaged 0.27 ± 0.01 MPa. The index of agreement was greater than 0.75 in 51 datasets, with only three datasets showing an index of agreement lower than 0.5. Nevertheless, the deviations between observed and simulated Ψstem values did not alter the classification of the water stress undergone by grapevines. This upgraded model could constitute the core of a decision support system for water management in vineyards, applicable to both rainfed and irrigated conditions.

中文翻译：

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升级和验证土壤水分平衡模型以预测葡萄园的茎水分潜力


高效的水资源管理是葡萄栽培可持续性的关键。决策支持工具可以就如何优化灌溉或在雨养条件下种植葡萄的可行性提供建议，但需要可靠的算法来评估葡萄藤水分状况。在此背景下，本研究的目的是通过将气象、土壤和葡萄藤活力纳入方程式中，将可蒸腾土壤水分的分数转化为正午茎水势 （Ψstem），从而升级特定于葡萄园的土壤水分平衡模型。分析了该模型对输入参数量级变化的敏感性。此外，该模型在西班牙的广泛葡萄园中进行了测试，这些葡萄园具有不同的葡萄品种（红葡萄和白葡萄）、砧木、植物年龄、土壤和气候条件以及水分状况，共 129 种情景。该模型对大多数输入量级的变化仅略微敏感，除了叶片气孔导度开始下降的可蒸腾水部分。此外，该模型令人满意地再现了 Ψstem 在生长季节的演变，尽管它略微高估了测得的 Ψstem 值，因为拟合回归线的斜率在大多数情况下小于 1,129 分中的 76 分。尽管如此，除了 21 个数据集外，这些关系的决定系数大于 0.9。平均误差平均为 0.024 ± 0.015 MPa，而均方根误差平均为 0.27 ± 0.01 MPa。在 51 个数据集中，一致性指数大于 0.75，只有 3 个数据集的一致性指数低于 0.5。然而，观测和模拟的 Ψstem 值之间的偏差并没有改变葡萄藤所经历的水分胁迫的分类。 这种升级后的模型可以构成葡萄园水资源管理决策支持系统的核心，适用于雨养和灌溉条件。