Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 20, 4341-4357, 2016
https://doi.org/10.5194/hess-20-4341-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
26 Oct 2016
Multivariate hydrological data assimilation of soil moisture and groundwater head
Donghua Zhang1, Henrik Madsen2, Marc E. Ridler2, Jacob Kidmose3, Karsten H. Jensen1, and Jens C. Refsgaard3 1Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
2DHI, Hørsholm, Denmark
3Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Abstract. Observed groundwater head and soil moisture profiles are assimilated into an integrated hydrological model. The study uses the ensemble transform Kalman filter (ETKF) data assimilation method with the MIKE SHE hydrological model code. The method was firstly tested on synthetic data in a catchment of less complexity (the Karup catchment in Denmark), and later implemented using data from real observations in a larger and more complex catchment (the Ahlergaarde catchment in Denmark). In the Karup model, several experiments were designed with respect to different observation types, ensemble sizes and localization schemes, to investigate the assimilation performance. The results showed the necessity of using localization, especially when assimilating both groundwater head and soil moisture. The proposed scheme with both distance localization and variable localization was shown to be more robust and provide better results. Using the same assimilation scheme in the Ahlergaarde model, groundwater head and soil moisture were successfully assimilated into the model. The hydrological model with assimilation showed an overall improved performance compared to the model without assimilation.

Citation: Zhang, D., Madsen, H., Ridler, M. E., Kidmose, J., Jensen, K. H., and Refsgaard, J. C.: Multivariate hydrological data assimilation of soil moisture and groundwater head, Hydrol. Earth Syst. Sci., 20, 4341-4357, https://doi.org/10.5194/hess-20-4341-2016, 2016.
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Short summary
We present a method to assimilate observed groundwater head and soil moisture profiles into an integrated hydrological model. The study uses the ensemble transform Kalman filter method and the MIKE SHE hydrological model code. The proposed method is shown to be more robust and provide better results for two cases in Denmark, and is also validated using real data. The hydrological model with assimilation overall improved performance compared to the model without assimilation.
We present a method to assimilate observed groundwater head and soil moisture profiles into an...
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