Abstract The Evaporative Stress Index (ESI) quantifies temporal anomalies in a normalized evapotranspiration (ET) metric describing the ratio of actual-to-reference ET (fRET) as derived from satellite remote sensing. At regional scales (3–10 km pixel resolution), the ESI has demonstrated the capacity to capture developing crop stress and impacts on regional yield variability in water-limited agricultural regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded due to spatial and temporal limitations in the standard ESI products. In this study, we investigated potential improvements to ESI by generating maps of ET, fRET, and fRET anomalies at high spatiotemporal resolution (30-m pixels, daily time steps) using a multi-sensor data fusion method, enabling separation of landcover types with different phenologies and resilience to drought. The study was conducted for the period 2010–2014 covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of maize yield were investigated at both the field and county level to assess the potential of ESI as a yield forecasting tool. To examine the role of crop phenology in yield-ESI correlations, annual input fRET time series were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). At the resolution of the operational U.S. ESI product (4 km), adjusting fRET alignment to a regionally reported emergence date prior to anomaly computation improves r2 correlations with county-level yield estimates from 0.28 to 0.80. At 30-m resolution, where pure maize pixels can be isolated from other crops and landcover types, county-level yield correlations improved from 0.47 to 0.93 when aligning fRET by emergence date rather than calendar date. Peak correlations occurred 68 days after emergence, corresponding to the silking stage for maize when grain development is particularly sensitive to soil moisture deficiencies. The results of this study demonstrate the utility of remotely sensed ET in conveying spatially and temporally explicit water stress information to yield prediction and crop simulation models.

中文翻译：

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作物产量蒸发胁迫指标的田间尺度制图：在美国内布拉斯加州米德的应用

摘要 蒸发应力指数 (ESI) 量化了标准化蒸散量 (ET) 指标中的时间异常，描述了从卫星遥感得出的实际与参考 ET (fRET) 的比率。在区域范围内（3-10 公里像素分辨率），ESI 已经证明了捕捉发展中的作物压力和对缺水农业地区区域产量变化的影响的能力。然而，由于标准 ESI 产品的空间和时间限制，它在一些植被周期集中管理的地区的表现似乎有所下降。在这项研究中，我们通过使用多传感器数据融合方法以高时空分辨率（30 米像素，每日时间步长）生成 ET、fRET 和 fRET 异常图，研究了对 ESI 的潜在改进，能够分离具有不同物候和抗旱能力的土地覆盖类型。该研究于 2010 年至 2014 年期间进行，涵盖内布拉斯加州米德附近的一个地区，包括雨育和灌溉作物。在田间和县级调查了 ESI 与玉米产量测量值之间的相关性，以评估 ESI 作为产量预测工具的潜力。为了检查作物物候在产量-ESI 相关性中的作用，年度输入 fRET 时间序列按日历日和生物物理相关日期（例如自种植或出苗后的天数）对齐。在操作美国 ESI 产品（4 公里）的分辨率下，在异常计算之前将 fRET 对齐调整到区域报告的出现日期可将 r2 与县级产量估计值的相关性从 0.28 提高到 0.80。在 30 米分辨率下，在纯玉米像素可以与其他作物和土地覆盖类型分离的情况下，当按出苗日期而不是日历日期对齐 fRET 时，县级产量相关性从 0.47 提高到 0.93。相关性峰值出现在出苗后 68 天，对应于玉米的抽丝期，此时谷物发育对土壤水分缺乏特别敏感。这项研究的结果证明了遥感 ET 在将空间和时间上明确的水分胁迫信息传达到产量预测和作物模拟模型中的效用。当谷物发育对土壤水分缺乏特别敏感时，对应于玉米的吐丝阶段。这项研究的结果证明了遥感 ET 在将空间和时间上明确的水分胁迫信息传达到产量预测和作物模拟模型中的效用。当谷物发育对土壤水分缺乏特别敏感时，对应于玉米的吐丝阶段。这项研究的结果证明了遥感 ET 在将空间和时间上明确的水分胁迫信息传达到产量预测和作物模拟模型中的效用。