Inversion of terrestrial water storage changes from GNSS vertical displacements using a priori constraint: A case study of the Yunnan Province, China

Abstract

Global Navigation Satellite System (GNSS) is an effective means to monitor surface deformations associated with changes in terrestrial water storage (TWS). In this study, we introduced a priori constraint matrix and estimated the regularization parameter through an iterative least-squares method to infer the TWS changes using GNSS vertical displacements from December 2010 to February 2021 in the Yunnan Province (YNP), China. The GNSS-inferred TWS changes were validated through the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) estimates, the Global Land Data Assimilation System (GLDAS) hydrological model, and the meteorological data (i.e., precipitation and Drought Severity Index (DSI)). The results demonstrate that the spatial resolution of TWS changes derived from 45 GNSS stations can reach 2°×2° in the YNP, and the a priori constraint is better than the traditional Laplacian matrix constraint for solving the discrete ill-conditioned problem of GNSS inversion. The GNSS-inferred TWS changes are consistent with the TWS changes derived from GRACE/GFO and GLDAS estimates in the spatio-temporal domains over the YNP, but the GNSS inversion results show stronger amplitudes. Furthermore, the ground-based GNSS observations are more sensitive to the TWS changes, and the correlation between precipitation and GNSS-inferred TWS changes is improved by about 11 % and 5 % compared to GRACE/GFO and GLDAS estimates in the YNP, respectively. The GNSS-inferred DSI can well reveal the two severe drought events in the YNP during the study period, which is consistent with the DSI derived from GRACE/GFO and GLDAS estimates, as well as the published self-calibrating Palmer Drought Severity Index (scPDSI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). The GNSS observations can compensate the limitations of GRACE/GFO observations (e.g., bridging the data gap between GRACE and GFO missions), and help to better investigate the TWS changes in the YNP, which has significant potentials for regional water resource management and extreme climate changes monitoring.