Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 21, issue 9
Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4927-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-4927-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 21, issue 9
Research article
 | 
29 Sep 2017
Research article |  | 29 Sep 2017

State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter

Hongjuan Zhang, Harrie-Jan Hendricks Franssen, Xujun Han, Jasper A. Vrugt, and Harry Vereecken

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Short summary
Applications of data assimilation (DA) arise in many fields of geosciences, perhaps most importantly in weather forecasting and hydrology. We want to investigate the roles of data assimilation methods and land surface models (LSMs) in joint estimation of states and parameters in the assimilation experiments. We find that all DA methods can improve prediction of states, and that differences between DA methods were limited but that the differences between LSMs were much larger.
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