Optimizing GNSS-derived terrestrial water storage anomaly retrieval: a spatial correlation accuracy crustal load inversion framework for enhanced hydrologic monitoring

Terrestrial water storage anomaly (TWSA) is one of the key indicators reflecting the temporal variations of terrestrial water storage (TWS). Although traditional methods such as runoff monitoring achieve high precision, their spatial coverage limitations impede the comprehensive capture of large-scale hydrological patterns. The global navigation satellite system (GNSS) provides an innovative method for TWSA inversion. However, existing studies predominantly adopt a spatial resolution of 0.25° × 0.25° for GNSS-based TWSA inversion, which falls short of the resolution required for refined water resource analysis. Although this resolution adequately captures regional-scale TWSA variation patterns, it remains limited in characterizing local aquifer dynamics, sub-basin-scale water storage fluctuations, and hydrological response processes in complex topography areas. To address this gap, this study investigates the optimal trade-off between spatial resolution and accuracy in GNSS-based TWSA inversion through a threefold methodology. First, we integrate Pearson's correlation coefficient ( PCC ) and root mean square error ( RMSE ) to formulate the spatial correlation accuracy ( SCA ), which underpins the development of the Multi-resolution Green function-based Terrestrial water storage anomaly Inversion Method (MGTIM). Second, the MGTIM-derived TWSA was systematically compared with traditional GNSS inversion results, GLDAS, and GRACE datasets, and the optimal spatial resolution of 0.05° × 0.05° was determined through SCA metric evaluation. Third, we apply the optimized MGTIM to invert and analyze the spatiotemporal evolution of TWSA in Southwest China (2011∼2022), integrating precipitation data for mechanistic interpretation. The results demonstrate that the PCC s between the optimal MGTIM and traditional GNSS inversion, GRACE/GRACE-FO, and GLDAS are 0.99, 0.88, and 0.83, respectively. The corresponding RMSE s are 7.87 mm, 12.57 mm, and 13.56 mm, confirming the effectiveness of MGTIM in TWSA inversion. In addition, the spatiotemporal consistency between TWSA and precipitation data obtained based on the optimal MGTIM is notable. MGTIM overcomes the limitations of traditional GNSS inversion methods and offers a novel approach for TWSA inversion with higher spatial resolution and accuracy.