Waterlogging is an increasingly important issue in irrigated agriculture that has a detrimental impact on crop productivity. The above-ground effect of waterlogging on crops is hard to distinguish from water deficit stress with remote sensing, as responses such as stomatal closure and leaf wilting occur in both situations. Currently, waterlogging as a source of crop stress is not considered in remote sensing-based evaporation algorithms and this may therefore lead to erroneous interpretation for irrigation scheduling. Monitoring waterlogging can improve evaporation models to assist irrigation management. In addition, frequent spatial information on waterlogging will provide agriculturalists information on land trafficability, assist drainage design, and crop choice. This article provides a scientific perspective on the topic of waterlogging by consulting literature in the disciplines of agronomy, hydrology, and remote sensing. We find the solution to monitor waterlogging lies in a multi-sensor approach. Future scientific routes should focus on monitoring waterlogging by combining remote sensing and ancillary data. Here, drainage parameters deduced from high spatial resolution Digital Elevation Models (DEMs) can play a crucial role. The proposed approaches may provide a solution to monitor and prevent waterlogging in irrigated agriculture.

中文翻译：

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面向可持续灌溉农业的遥感监测内涝

内涝是灌溉农业中日益重要的问题，对作物生产力产生不利影响。土壤涝渍对作物的地上效应很难通过遥感与缺水胁迫区分开来，因为在这两种情况下都会发生气孔关闭和叶片萎蔫等反应。目前，基于遥感的蒸发算法没有考虑将涝渍作为作物压力的来源，因此这可能会导致对灌溉计划的错误解释。监测内涝可以改进蒸发模型以协助灌溉管理。此外，关于内涝的频繁空间信息将为农学家提供有关土地通行性、辅助排水设计和作物选择的信息。本文通过查阅农学、水文学和遥感学科的文献，提供了关于内涝问题的科学观点。我们发现监测积水的解决方案在于采用多传感器方法。未来的科学路线应侧重于结合遥感和辅助数据监测内涝。在这里，从高空间分辨率数字高程模型 (DEM) 推导出的排水参数可以发挥至关重要的作用。所提出的方法可以提供一种解决方案来监测和防止灌溉农业中的涝渍。在这里，从高空间分辨率数字高程模型 (DEM) 推导出的排水参数可以发挥至关重要的作用。所提出的方法可以提供一种解决方案来监测和防止灌溉农业中的涝渍。在这里，从高空间分辨率数字高程模型 (DEM) 推导出的排水参数可以发挥至关重要的作用。所提出的方法可以提供一种解决方案来监测和防止灌溉农业中的涝渍。