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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 3, issue 1
Geosci. Model Dev., 3, 1–12, 2010
https://doi.org/10.5194/gmd-3-1-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 3, 1–12, 2010
https://doi.org/10.5194/gmd-3-1-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  07 Jan 2010

07 Jan 2010

Streamflow data assimilation for soil moisture analysis

K. Warrach-Sagi and V. Wulfmeyer K. Warrach-Sagi and V. Wulfmeyer
  • Institute for Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

Abstract. Streamflow depends on the soil moisture of a river catchment and can be measured with relatively high accuracy. The soil moisture in the root zone influences the latent heat flux and, hence, the quantity and spatial distribution of atmospheric water vapour and precipitation. As numerical weather forecast and climate models require a proper soil moisture initialization for their land surface models, we enhanced an Ensemble Kalman Filter to assimilate streamflow time series into the multi-layer land surface model TERRA-ML of the regional weather forecast model COSMO. The impact of streamflow assimilation was studied by an observing system simulation experiment in the Enz River catchment (located at the downwind side of the northern Black Forest in Germany). The results demonstrate a clear improvement of the soil moisture field in the catchment. We illustrate the potential of streamflow data assimilation for weather forecasting and discuss its spatial and temporal requirements for a corresponding, automated river gauging network.

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