Abstract In the face of a sparse global river gauging station network in decline, new approaches are needed to reconstruct and monitor river discharge from satellite observations. Where in-situ river discharge measurements are not available, it may be possible to use discharge estimates from a hydrological model, provided the model simulations are of sufficient quality, to construct satellite-based discharge gauging. We tested this approach by developing model- and gauge-based satellite gauging reaches (SGRs) using 0.05° MODIS optical remote sensing at ~10,000 gauged and ~370,000 ungauged river reaches globally. Model-based SGRs are aimed to infer temporal flow patterns and reflect unusually high or low river discharge behavior (i.e. flood or drought conditions), if not necessarily absolute discharge volumes. The model-based SGRs achieved a discharge prediction skill that was often similar to gauge-based SGRs, and sometimes better than the model itself. Our results showed promising opportunities to develop model-based SGRs in sparsely gauged basins in South America, Africa, and Asia. We selected river reaches, with mean widths ranging from 67 to 3105 m, representing both poor and successful SGRs in different environments for case studies to analyze conditions for successful SGR development. River size and morphology were the main factors determining the performance of SGRs. Wide channels with strong temporal variations, broad floodplains and multiple braided or anastomosing channels provided the best conditions for SGRs. The probability of constructing a successful SGR could be predicted from high-resolution inundation summary data available globally, and can thus be predicted anywhere. Ongoing increases in the spatial and temporal resolution of remote sensing will further increase the number of river reaches for which satellite-based discharge gauging will become possible.

中文翻译：

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全球卫星河道测量及其河流形态对其应用的影响

摘要 面对日益稀疏的全球河流测站网络，需要新的方法通过卫星观测重建和监测河流流量。如果无法进行原位河流流量测量，则可以使用来自水文模型的流量估计值，前提是模型模拟的质量足够好，以构建基于卫星的流量测量。我们通过使用 0.05° MODIS 光学遥感在全球约 10,000 条测量河段和约 370,000 条未测量河段开发基于模型和测量仪的卫星测量河段 (SGR) 来测试这种方法。基于模型的 SGR 旨在推断时间流模式并反映异常高或低的河流流量行为（即洪水或干旱条件），如果不一定是绝对流量。基于模型的 SGR 实现了通常与基于仪表的 SGR 相似的排放预测技能，有时甚至比模型本身更好。我们的结果显示了在南美洲、非洲和亚洲的稀疏盆地中开发基于模型的 SGR 的有希望的机会。我们选择了平均宽度从 67 米到 3105 米不等的河段，代表不同环境中的不良和成功的 SGR 进行案例研究，以分析成功开发 SGR 的条件。河流大小和形态是决定 SGR 性能的主要因素。具有强烈时间变化的宽阔河道、广阔的洪泛区和多条编织或吻合的河道为SGRs提供了最佳条件。可以从全球可用的高分辨率淹没汇总数据预测构建成功 SGR 的概率，因此可以在任何地方进行预测。遥感空间和时间分辨率的不断提高将进一步增加基于卫星的流量测量成为可能的河段数量。