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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 2
Hydrol. Earth Syst. Sci., 16, 375–390, 2012
https://doi.org/10.5194/hess-16-375-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Latest advances and developments in data assimilation for...

Hydrol. Earth Syst. Sci., 16, 375–390, 2012
https://doi.org/10.5194/hess-16-375-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 08 Feb 2012

Research article | 08 Feb 2012

The importance of parameter resampling for soil moisture data assimilation into hydrologic models using the particle filter

D. A. Plaza et al.

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Cited articles

Andersson, L.: Improvement of runoff models, what way to go?, Nord. Hydrol., 23, 315–332, 1992.
Andrieu, C., de Freitas, J. F. G., and Doucet, A.: Sequential Bayesian Estimation And Model Selection Applied To Neural Networks, CUED-F-INFENG-TR-341, Cambridge University Engineering Department, March 1999.
Arulampalam, M. S., Maskell, S., and Gordon, N.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE T. Signal Proc., 50, 174–188, 2002.
Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893, https://doi.org/10.5194/hess-14-1881-2010, 2010.
Caparrini, F., Castelli, F., and Entekhabi, D.: Variational estimation of soil and vegetation turbulent transfer and heat flux parameters from sequences of multisensor imagery, Water Resour. Res., 40, W12515, https://doi.org/10.1029/2004WR003358, 2004.
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