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Abstract

Model-based information about the global water cycle, in particular the redistribution of terrestrial water masses, is highly relevant for the understanding of Earth system dynamics. In many geodetic applications, hydrological model results play an important role by augmenting observations with a higher spatio-temporal resolution and gapless coverage. Here we demonstrate the feasibility of the high-resolution, open-source hydrological model OS LISFLOOD to simulate terrestrial water storage (TWS) variations with a spatial sampling of up to about 5 km (0.05○). Validation against data from satellite gravimetry reveals that the choice of the maximum soil depth has a significant impact on long-term trends in TWS, mainly in the deepest soil layer. We find that refining the soil depth definition effectively reduces spurious TWS trends, while preserving accuracy in modeled river discharge. Using the modified model set-up, we show that in many regions TWS from OS LISFLOOD fits better to observations than TWS from the Land Surface Discharge Model (LSDM) routinely operated at the GFZ and used in geodetic applications worldwide. The advantage of the high spatial resolution of the OS LISFLOOD implementation is shown by comparing vertical surface displacements to GNSS observations in a global network of stations. The data set presented here is the first application of OS LISFLOOD to generate quasi-global (regions south of 60○S excluded) daily 0.05○ TWS fields for a 23-year period (2000–2022).