Articles | Volume 18, issue 7
Hydrol. Earth Syst. Sci., 18, 2543–2557, 2014
https://doi.org/10.5194/hess-18-2543-2014
Hydrol. Earth Syst. Sci., 18, 2543–2557, 2014
https://doi.org/10.5194/hess-18-2543-2014

Research article 04 Jul 2014

Research article | 04 Jul 2014

Kalman filters for assimilating near-surface observations into the Richards equation – Part 3: Retrieving states and parameters from laboratory evaporation experiments

H. Medina et al.

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Cited articles

Camporese, M., Paniconi, C., Putti, M., and Salandin, P.: Ensemble Kalman filter data assimilation for a process based catchment scale model of surface and subsurface flow, Water Resour. Res., 45, W10421, https://doi.org/10.1029/2008WR007031, 2009.
Carsel, R. F. and Parrish, R. S.: Developing joint probability distributions of soil water retention characteristics, Water Resour. Res., 24, 755–769, https://doi.org/10.1029/WR024i005p00755, 1988.
Chirico, G. B., Medina, H., and Romano, N.: Functional evaluation of PTF prediction uncertainty: An application at hillslope scale, Geoderma, 155, 193–202, 2010.
Chirico, G. B., Medina, H., and Romano, N.: Kalman filters for assimilating near-surface observations into the Richards equation – Part 1: Retrieving state profiles with linear and nonlinear numerical schemes, Hydrol. Earth Syst. Sci., 18, 2503–2520, https://doi.org/10.5194/hess-18-2503-2014, 2013.
De Lannoy, G. J. M., Houser, P. R., Pauwels, V. R. N., and Verhoest, N. E. C.: State and bias estimation for soil moisture profiles by an ensemble Kalman filter: Effect of assimilation depth and frequency, Water Resour. Res., 43, W06401, https://doi.org/10.1029/2006WR005100, 2007a.
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