Performance of Different Ensemble Kalman Filter Structures to Assimilate GRACE Terrestrial Water Storage Estimates Into a High‐Resolution Hydrological Model: A Synthetic Study

Abstract

Among all remote sensing missions, the Gravity Recovery and Climate Experiment (GRACE) was unique as it measured the change in total water content across all terrestrial water storages (TWS) including subsurface, deep soil moisture, and groundwater. However, its coarse resolution is a major challenge for practical applications. Ensemble Kalman filters (EnKFs) are useful tools to combine observations with models to reduce prediction errors. But due to the coarse resolution of the GRACE products, the EnKF does not work well in its usual form. Accordingly, different EnKF structures have been proposed and employed but a comparison between them has not yet been attempted. Here we assessed these structures using a synthetic problem. Alternative structures were formed using different increment calculation and updating strategies, observation operators, and the types of observation fed to the filter. It was found that all available structures led to an improvement in model performance when measured against a synthetic reference. However, the degree of improvement was strongly dependent on the assimilation strategy. Assimilating absolute TWS values (the summation of the TWS anomalies and an unbiased baseline) gave the best model performance when combined with an increment calculation strategy in which the increments are calculated and applied to all days of the month. However, without an unbiased baseline, assimilating TWS changes still leads to an acceptable improvement in model performance. Among the observation operators, those that predict the observations as an average of multiple days had the best performance.

On the Use of Adaptive Ensemble Kalman Filtering to Mitigate Error Misspecifications in GRACE Data Assimilation

“…The model was calibrated using the patient rule induction method parameter estimation (Shokri, Walker, van Dijk, Wright & Pauwels, ) using streamflow observations from 190 unregulated catchments within the MDB (Zhang et al, ) from 1990 to 2000. Similar to Shokri, Walker, van Dijk, and Pauwels (), two independent “good enough” parameter sets were found. One of them was used to generate the truth data (in the synthetic experiments), while the other was used for the simulation (for more details refer to Shokri, Walker, van Dijk, Wright & Pauwels ; Shokri, Walker, van Dijk & Pauwels ).…”

“…Similar to Shokri, Walker, van Dijk, and Pauwels (), two independent “good enough” parameter sets were found. One of them was used to generate the truth data (in the synthetic experiments), while the other was used for the simulation (for more details refer to Shokri, Walker, van Dijk, Wright & Pauwels ; Shokri, Walker, van Dijk & Pauwels ).…”

“…Following Tian et al () and Shokri, Walker, van Dijk, and Pauwels (), the hydrological model used here was the AWRA‐L version 0.5 (van Dijk, ). This model simulates a variety of state and flux variables on a daily basis.…”

“…The groundwater storage is also simulated as a linear storage without any lateral flow between pixels. Surface and groundwater storage, soil moisture of different layers, evapotranspiration, and the flux between different storages are the model outputs (for more details refer to van Dijk et al, , ; Renzullo et al, ; Shokri, Walker, van Dijk & Pauwels ; Shokri et al, ; Van Dijk & Warren, ).…”

“…The model was forced with meteorological data from the Australian Water Availability Project (AWAP; http://www.bom.gov.au/jsp/awap/index.jsp), including daily precipitation, minimum and maximum temperature, and radiation. The remaining input data, including wind and land use, are identical with those of Shokri, Walker, van Dijk, and Pauwels (). The model was calibrated using the patient rule induction method parameter estimation (Shokri, Walker, van Dijk, Wright & Pauwels, ) using streamflow observations from 190 unregulated catchments within the MDB (Zhang et al, ) from 1990 to 2000.…”