Abstract This study comprehensively used Remote Sensing (RS) and GIS for independently monitoring crop water adequacy in response to existing irrigation management system in Bari Doab, Pakistan. Canals’ rotation plan is developed before start of each cropping season to distribute water on fixed turn basis. The study combines the moderate (Landsat-8) and low resolution (MODIS) satellite imagery to assess near real time crop water deficit in canal command areas (CCAs) of the study area. Landsat imagery were used to develop crop classification and determine cropping pattern using time series of NDVI. MODIS’ NDVI product was employed to monitor the current crop health and develop annual reference NDVI cycle based on last 13 years’ imagery. Climatic data of WMO stations combined with DEM have also been used to determine reference evapotranspiration based on Penman-Monteith method. These inputs were combined to estimate average crop water deficit in CCAs for ongoing cropping season on 08-day interval, the interval parallel to the canal rotation plan. RS based reflectance crop coefficients (KCR) of current and reference crop cycle were developed to calculate potential and actual evapotranspiration, and then translated their difference into crop water deficit. Lag time of 08–10 days is limitation of the study due to satellites overpass time, but it can still prove very helpful considering the crop season spanned over 160–180 days. Results revealed that maximum crop water deficit (up to 9 mm) occurred in CCAs during crop growing (mid) stage. Crop water deficit showed inverse relation when plotted against intense rainfall months. Crop water deficit results could be helpful for irrigation managers to modify canals’ rotation plan in near real time according to crop health and growing stage. It would not only help in achieving equitable water distribution but also assuring supplies when required by the crops.

中文翻译：

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近实时作物缺水评估的 GIS 和遥感范例，以改进灌溉分配计划

摘要 本研究综合利用遥感 (RS) 和 GIS 对巴基斯坦巴里多阿布现有灌溉管理系统的作物水分充足性进行独立监测。运河的轮作计划是在每个作物季节开始之前制定的，以固定轮流分配水。该研究结合了中等 (Landsat-8) 和低分辨率 (MODIS) 卫星图像，以评估研究区运河指挥区 (CCA) 中近乎实时的作物缺水情况。Landsat 影像用于开发作物分类并使用 NDVI 时间序列确定作物模式。MODIS 的 NDVI 产品用于监测当前作物的健康状况，并根据过去 13 年的图像制定年度参考 NDVI 周期。WMO 站的气候数据结合 DEM 也被用于基于 Penman-Monteith 方法确定参考蒸发量。将这些输入结合起来，以 08 天为间隔估算正在进行的作物季节的 CCA 平均作物水分亏缺，该间隔与运河轮作计划平行。开发了当前和参考作物周期的基于 RS 的反射率作物系数 (KCR) 来计算潜在和实际蒸发量，然后将它们的差异转化为作物水分亏缺。由于卫星通过时间，08-10 天的滞后时间是研究的限制，但考虑到跨度超过 160-180 天的作物季节，它仍然可以证明是非常有用的。结果表明，在作物生长（中期）阶段，CCA 中出现了最大的作物水分亏缺（高达 9 毫米）。当与强降雨月份作图时，作物水分亏缺呈负相关。作物缺水结果有助于灌溉管理者根据作物健康状况和生长阶段近乎实时地修改运河轮作计划。它不仅有助于实现公平的水分配，而且还可以确保作物需要时的供水。