Inversion of GNSS Vertical Displacements for Terrestrial Water Storage Changes Using Slepian Basis Functions

Abstract

The surface displacements measured by the Global Navigation Satellite System (GNSS) provide a unique insight for studying terrestrial water storage (TWS) changes. In this study, we recovered the TWS changes from GNSS vertical displacements in Southwest China (SWC) using Slepian basis function (SBF) from January 2011 to December 2020. The performance of the TWS changes estimated by SBF was validated against the Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow‐On (GFO) and the GNSS‐inverted TWS changes estimated by Green's function method. The results showed that the spatial patterns, seasonal, and linear trends of the TWS changes derived from GNSS using SBF agreed with the GRACE/GFO estimates. However, there are still evident differences in the local scope, and the GNSS‐derived TWS changes presented stronger amplitudes and more details in the spatio‐temporal domains than the GRACE/GFO estimates in SWC. The unconstrained GNSS inversion results using SBF also presented stronger signal amplitudes than those estimates with Green's function, and the TWS changes estimated by SBF were more reliable than Green's function method for regions with sparsely distributed GNSS stations in SWC. Additionally, the average distance between the GNSS stations can be considered as a reasonable filtering radius of SBF, and the SBF‐estimated TWS changes with different Gaussian filtering radii had comparable signal amplitudes and spatial patterns with the estimates of Green's function and GRACE/GFO.

GNSS2TWS_Slepian: A software to recover daily GNSS-inverted terrestrial water storage changes based on Slepian basis functions

“…However, this inversion of global GNSS data using the global spherical harmonic functions is generally applicable to the determination of low degree/order components of surface mass changes (Han and Razeghi 2017). In the medium scale (regional and continental), the Slepian basis functions (or localized spherical harmonic functions) are an alternative to traditional global spherical harmonics functions to realize the inversion of sparsely instrumented GNSS network for relatively large-scale surface mass changes (Han and Razeghi 2017; Jiang et al 2021a;Li et al 2023). On the small scale (local and regional), the dense GNSS network is emerging as an additional tool to estimate ne-scale TWS variations based on the spatial-domain Green's function method (Argus et ).…”

Water Storage Variations Recovered from Global Navigation Satellite System Network Using Spatial Constraints: A Case Study of the Contiguous United States

“…Tang et al developed a hydrological drought index at multiple scales based on the TWS using the SBF and found that it is more robust in quantifying Brazil's hydrological drought [24]. Li et al inverted the TWS variations in southwest China; they found that the amplitudes of the TWS using the SBF are larger than those of GRACE/GFO, and the filter radius of the SBF inversion method can be determined according to the average distance between the GNSS stations [25].…”