Due to the impacts of climate change and human activities on scarcity and uneven spatial distribution of water resources, water use efficiency (WUE) has gained significant attention. Currently, there is a lack of research on estimating WUE with higher accuracy and stronger mechanism on the large regional scale. This study systematically reviewed the status and hotspots from an amount of studies and analyzed various concepts and estimation methods of WUE at different scales. Additionally, we discussed the limitations and challenges of these studies to point out the future opportunities. WUE at different scales could not be directly scale transferred as WUE varied at various scales. Recently, the remote sensing gross primary productivity (GPP) and evapotranspiration (ET) products, the remote sensing crop distribution recognition models, remote sensing ET and yield estimation models have improved the accuracy of WUE estimation at the regional scale, but lack of mechanical explanation. However, data assimilation provided a stronger mechanistic interpretation of WUE estimation at the regional scale by coupling remote sensing data and crop models. Optimized data assimilation method for coupling multi-source remote sensing fusion platform, unmanned aerial vehicle (UAV) platform and crop model would be a better approach to quantify WUE of the large area in the future. It is also necessary to incorporate crop types and irrigation allocations into high spatial resolution crop-specific WUE modeling. Therefore, integrating multi-source remote sensing data, ensemble using multi-crop models, innovating near-real-time seamless efficient data assimilation algorithms at the regional scale, and refining multi-variables assimilation at different crop growth stages are the research hotspots in the future. This study will provide useful guidance for optimizing water resource management in precision agriculture and improving the efficient utilization of water resources.

中文翻译：

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作物水分利用效率评价方法现状：综述

由于气候变化和人类活动对水资源稀缺性和空间分布不均的影响，水资源利用效率（WUE）受到广泛关注。目前，缺乏大区域尺度上精度更高、机制更强的WUE估算研究。本研究系统回顾了大量研究现状和热点，分析了不同尺度下WUE的各种概念和估算方法。此外，我们还讨论了这些研究的局限性和挑战，并指出了未来的机遇。不同尺度的WUE不能直接进行尺度转换，因为WUE在不同尺度上存在差异。近年来，遥感总初级生产力（GPP）和蒸散量（ET）产品、遥感作物分布识别模型、遥感ET和产量估算模型提高了区域尺度WUE估算的准确性，但缺乏机械解释。然而，数据同化通过耦合遥感数据和作物模型，为区域尺度的 WUE 估算提供了更有力的机械解释。多源遥感融合平台、无人机平台和作物模型耦合的优化数据同化方法将是未来量化大面积WUE的更好方法。还有必要将作物类型和灌溉分配纳入高空间分辨率作物特定 WUE 模型中。因此，整合多源遥感数据、多作物模型集成、创新区域尺度近实时无缝高效数据同化算法、精细化作物不同生长阶段的多变量同化是当前的研究热点。未来。该研究将为优化精准农业水资源管理、提高水资源高效利用提供有益指导。