The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

The vertical motion of the Earth’s surface is dominated by hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into regional geophysical process. Although Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across globe, posing challenge to obtaining information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from Gravity Recovery Climate Experiment (GRACE) GRACE Follow-On (GRACE-FO)) have been successfully used improve spatial coverage. While combining model estimates GRACE/GRACE-FO via assimilation (DA) framework potentially accuracy resolution estimates, approach has rarely considered or investigated thus far. This study assesses performance displacement from GRACE/GRACE-FO, PCRaster Water Balance (PCR-GLOBWB) hydrology model, DA (assimilating PCR-GLOBWB) CSEA, where six sites available for validation. results show that PCR-GLOBWB, accurately capture regional-scale hydrologic- flood-induced displacements, with correlation value RMS reduction relative up 0.89 53%, respectively. analyses also confirm DA’s effectiveness providing consistent while maintaining high-spatial details PCR-GLOBWB highlighting benefits regions.