- Jilin University, China (gyin@jlu.edu.cn)
Northeast China is an important industrial base and grain production region. Understanding terrestrial water storage (TWS) variations in Northeast China is crucial for the sustainable development of water resources and food security. TWS retrievals from the Gravity Recovery and Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions provide invaluable information to monitor TWS variations in the study domain. However, GRACE TWS retrievals have a coarse resolution in both space and time, which limits their application at finer scales. The study investigated the capability of ground-based Global Navigation Satellite System (GNSS) vertical displacement measurements to represent TWS variations in Northeast China with a finer spatial resolution. Afterward, TWS retrievals from GRACE and vertical displacements from GNSS will be assimilated into a land surface model to improve the hydrological process modeling in Northeast China. Preliminary results showed that after removing the non-hydrologic loading effects (e.g., non-tidal ocean loading, glacier isostatic adjustment, and thermal expansion) from GNSS data, the processed GNSS vertical displacement can reflect the seasonal and inter-annual variation of TWS in the study domain. However, the agreements of vertical displacements between GNSS and GRACE are inferior to findings in other regions, which may be explained by the weaker TWS variability, complex freeze-thaw process of ground, and extensive anthropogenic in this region. GRACE data assimilation (GRACE DA) in northeast China showed improved estimates of TWS and its constituent components, particularly across mountain regions. However, the degraded snow estimation from GRACE DA was also revealed. It is anticipated that the dual-assimilation of GRACE and GNSS data can take advantage of both data sets and benefit the estimates of snow, soil moisture, and groundwater in Northeast China.
How to cite: Yin, G., Hu, W., and Zhang, Z.: Toward Dual-Assimilation of Terrestrial Water Storage for Improving Land Hydrological Modeling in Northeast China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4151, https://doi.org/10.5194/egusphere-egu26-4151, 2026.