A GNSS Terrestrial Water Storage Inversion Method Based on GRACE Spatial Constraints

Abstract

The Laplace smoothing operator is used to constrain the relationship between the target grid and neighboring grids in the terrestrial water storage (TWS) inversion using global navigation satellite system (GNSS) observations. We propose an enhancement to the smoothing constraint matrix used in GNSS TWS inversion with prior spatial constraints from gravity recovery and climate experiment (GRACE) data and invert vertical GNSS displacement data for TWS changes in the Sichuan–Yunnan region. We focus on inverting multiyear seasonal TWS changes in the Sichuan–Yunnan region from January 2013 to June 2023, integrating GNSS, GRACE, and global land data assimilation system (GLDAS) data. Our findings demonstrate the consistency of spatiotemporal patterns between GNSS-inferred TWS and GRACE and GLDAS data. Comparing the estimated results with smoothing constraints, the proposed GNSS inversion utilizing the GRACE constraint enhances the capture of local TWS signals, improving spatial agreement with GRACE and GLDAS. The correlation coefficient with GRACE improves from 0.655 to 0.723, and with GLDAS, it improves from 0.730 to 0.779. We further integrate water balance equations for precipitation, runoff, and evapotranspiration in the Sichuan–Yunnan, validating our approach by aligning with established datasets and improving the spatial understanding of TWS dynamics. These enhancements underscore the effectiveness of our GNSS inversion strategy under the spatial constraint of GRACE and enable a more coherent and meaningful interpretation of GNSS-derived TWS changes.

Keywords

• Global land data assimilation system (GLDAS)
• global navigation satellite system (GNSS) inversion theory
• gravity recovery and climate experiment (GRACE)
• terrestrial water storage (TWS) spatial constraints