Water table depth assimilation in integrated terrestrial system models at the larger catchment scale - Li, Fang; Kurtz, Wolfgang; Hung, Ching Pui; Vereecken, Harry; Hendricks Franssen, Harrie-Jan (Frontiers in Water, 2023)
As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modelling Platform (TSMP) for improving hydrological modelling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5km, 5km and 10km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA (i.e., open loop (OL) runs). The best results at the assimilated locations are obtained for a localization radius of 10km, with an 81% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5km and 2.5km radius. The validation with independent WTD data showed the best results for a localization radius of 10km, but groundwater table characterization could only be improved for sites less than 2.5km from measurement locations. In case of a localization radius of 10km the RMSE-reduction was 30% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).