Building the High-Precision Combined Hydrological Load Model GHLW1.0 via Least-Squares Scale Factors and Its Assessment for GNSS Deformation Correction

Global terrestrial water storage change (TWSC) induces hydrological loading, a core driver of nonlinear deformations in GNSS benchmark coordinate time series. High-precision hydrological load models are essential for refining the Terrestrial Reference Frame (TRF) and investigating global climate change mechanisms. To address GRACE's coarse spatiotemporal resolution, discrepancies among reanalysis models, and the common reliance on single-source fusion without uncertainty quantification, we propose an LS-based scale-factor fusion scheme. Integrating GRACE Mascon data with the multi-model ACH-VCE product, we develop GHLW1.0. On a 1°×1° grid, LS determines optimal scale factors between GRACE and ACH-VCE, calibrating GRACE TWSC and fusing with ACH-VCE to produce the GHLW1.0 dataset (2000–2016). Multi-dimensional validation shows GHLW1.0 matches GRACE Mascon in linear trend, RMS of temporal signals, seasonal amplitude, and phase lag. Its phase difference relative to GRACE is ~15 days, substantially better than ACH-VCE's ~30 days, and captures finer spatial details. Applying GHLW1.0-derived vertical displacements to correct 300 GNSS stations, over 90% show correlation >0.7 between modeled and observed. Average correction efficiency is 76%, peaking at 79% (3% above ACH-VCE), with only 5% fluctuation across tests, indicating superior stability. Our LS fusion strategy compensates single-source deficiencies, enhancing TWSC retrieval and GNSS correction, and offers a novel pathway for high-precision stable hydrological load models. Future work will use Singular Spectrum Analysis to decompose homogeneous signals and optimize performance.