Soil moisture (SM) is a key variable in hydrometeorology and climate systems. With the growing interest in capturing fine-scale SM variability for effective hydroclimate applications, spaceborne L-band bistatic radar systems using Global Navigation Satellite System-Reflectometry (GNSS-R) technology hold great potential to meet the demand for high spatiotemporal resolution SM data. Although primarily designed for tropical cyclone monitoring purposes, the first GNSS-R satellite constellation – Cyclone Global Navigation Satellite System (CYGNSS) mission, has demonstrated the benefits of reliably monitoring diurnal SM dynamics through its initial stage of seven-year data record, thanks to its high revisit frequency at sub-daily intervals. Nevertheless, knowledge of SM retrieval from CYGNSS, particularly linked with its distinctive features, remains poorly understood, while numerous existing uncertainties and open issues can restrict its effective SM retrieval and practical applications in the next operating stages. Unlike other review papers, this work aims to bridge this knowledge gap in CYGNSS SM retrieval by highlighting noteworthy design properties based on analyses of its real-world data, while providing a synthesis of recent advances in eliminating external uncertainty factors and improving SM inversion methods.

中文翻译：

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从理论到水文实践：利用 CYGNSS 七年的数据进行高级土壤水分监测


土壤湿度 （SM） 是水文气象和气候系统中的关键变量。随着人们对捕获精细 SM 变化以用于有效水文气候应用的兴趣日益浓厚，使用全球导航卫星系统反射计 （GNSS-R） 技术的星载 L 波段双基地雷达系统在满足高时空分辨率 SM 数据需求方面具有巨大潜力。虽然主要为热带气旋监测目的而设计，但第一个 GNSS-R 卫星星座——气旋全球导航卫星系统 （CYGNSS） 任务已经展示了通过其七年数据记录的初始阶段可靠监测昼夜 SM 动态的好处，这要归功于其在次日间隔的高重访频率。然而，人们对从 CYGNSS 中检索 SM 的知识，特别是与其独特特征相关的知识，仍然知之甚少，而许多现有的不确定性和开放性问题可能会限制其 SM 检索的有效和下一个操作阶段的实际应用。与其他综述论文不同，这项工作旨在通过基于真实数据分析突出值得注意的设计特性来弥合 CYGNSS SM 检索中的这一知识差距，同时提供消除外部不确定性因素和改进 SM 反演方法的最新进展的综合。