Articles | Volume 22, issue 9
https://doi.org/10.5194/hess-22-4605-2018
https://doi.org/10.5194/hess-22-4605-2018
Research article
 | 
03 Sep 2018
Research article |  | 03 Sep 2018

Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation

Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu

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Cited articles

Al-Yaari, A., Wigneron, J. P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A., Albergel, C., Muñoz-Sabater, J., Richaume, P., and Mialon, A.: Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates, Remote Sens. Environ., 149, 181–195, https://doi.org/10.1016/j.rse.2014.04.006, 2014. 
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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. 
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Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.