Study on the vertical deformations induced by terrestrial water storage changes in Huang-Huai-Hai river basin

Terrestrial water storage(TWs)variations are associated with water mass movements,which may cause the deformation displacements of the Global Navigation Satellite System(GNSS)stations.This study investigates the spatio-temporal Tws variations and addresses the relationship between deformation variations observed in the Huang-Huai-Hai River Basin(HHHRB)and local hydrological features.Results indicate that the vertical velocities at the GNSS stations induced by TWS changes are relatively small,and the impacts of the terrestrial water storage changes are mainly reflected in the changes of seasonal characteristics.Although there is a downward TWS trend from 2011 to 2022 in most HHHRB areas,velocities from the vertical displacements of both Gravity Recovery and Climate Experiment(GRACE)and GRACE Follow-On(GFO)and the GNSS reflect that the HHHRB is undergoing an uplift process,while the magnitude of the GRACE/GFO derived velocities is much smaller than that of the GNSS solutions.Common hydrological deformations estimated from GRACE/GFO and GNSS measurements reveal that the TWS-derived displacements can explain 54.5%of the GNSS seasonal variations,with the phases of terrestrial water storage advancing by about one month relative to GNss common signal phases.Moreover,the decrease of the groundwater storage in the HHHRB has been accelerating since 2008.After reaching its lowest level around mid-2020,it began to rise rapidly,which might be closely related to the implementation of the South-North Water Transfer Central Project.

Comparative analysis of recent hydrological models and an attempt to generate new combined products for monitoring terrestrial water storage change

Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.