Geodetic methods can monitor changes in terrestrial water storage (TWS) across large regions in near real-time. Here, we investigate the effect of assumed Earth structure on TWS estimates derived from Global Navigation Satellite System (GNSS) displacement time series. Through a series of synthetic tests, we systematically explore how the spatial wavelength of water load affects the error of TWS estimates. Large loads (e.g., >1,000 km) are well recovered regardless of the assumed Earth model. For small loads (e.g., <10 km), however, errors can exceed 75% when an incorrect model for the Earth is chosen. As a case study, we consider the sensitivity of seasonal TWS estimates within mountainous watersheds of the western U.S., finding estimates that differ by over 13% for a collection of common global and regional structural models. Errors in the recovered water load generally scale with the total weight of the load; thus, long-term changes in storage can produce significant uplift (subsidence), enhancing errors. We demonstrate that regions experiencing systematic and large-scale variations in water storage, such as the Greenland ice sheet, exhibit significant differences in predicted displacement (over 20 mm) depending on the choice of Earth model. Since the discrepancies exceed GNSS observational precision, an appropriate Earth model must be adopted when inverting GNSS observations for mass changes in these regions. Furthermore, regions with large-scale mass changes that can be quantified using independent data (e.g., altimetry, gravity) present opportunities to use geodetic observations to refine structural properties of seismologically derived models for the Earth's interior structure.

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GNSS 得出的陆地水储量估算对假定地球结构的敏感性

大地测量方法可以近乎实时地监测大区域陆地水储存（TWS）的变化。在这里，我们研究了假设的地球结构对全球导航卫星系统 (GNSS) 位移时间序列得出的 TWS 估计的影响。通过一系列综合测试，我们系统地探讨了水负荷的空间波长如何影响TWS估计的误差。无论假设的地球模型如何，大负载（例如，>1,000 km）都可以很好地恢复。然而，对于小负载（例如，<10 km），如果选择了错误的地球模型，误差可能会超过 75%。作为一个案例研究，我们考虑了美国西部山区流域内季节性 TWS 估计的敏感性，发现一组常见的全球和区域结构模型的估计差异超过 13%。恢复的水负载中的误差通常与负载的总重量成比例；因此，储存的长期变化会产生显着的抬升（沉降），从而增加误差。我们证明，根据地球模型的选择，经历系统性和大规模蓄水变化的区域（例如格陵兰冰盖）在预测位移（超过 20 毫米）方面表现出显着差异。由于这些差异超出了 GNSS 观测精度，因此在反演 GNSS 观测结果以了解这些区域的质量变化时，必须采用适当的地球模型。此外，可以使用独立数据（例如测高、重力）进行量化的大规模质量变化的区域提供了利用大地测量观测来细化地震推导的地球内部结构模型的结构特性的机会。