Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 27, issue 6
Articles | Volume 27, issue 6
https://doi.org/10.5194/hess-27-1301-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-1301-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 27, issue 6
Research article
 | 
27 Mar 2023
Research article |  | 27 Mar 2023

Impact of parameter updates on soil moisture assimilation in a 3D heterogeneous hillslope model

Natascha Brandhorst and Insa Neuweiler

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Baroni, G., Facchi, A., Gandolfi, C., Ortuani, B., Horeschi, D., and van Dam, J. C.: Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity, Hydrol. Earth Syst. Sci., 14, 251–270, https://doi.org/10.5194/hess-14-251-2010, 2010. a, b, c, d
Bauser, H. H., Riedel, L., Berg, D., Troch, P. A., and Roth, K.: Challenges with effective representations of heterogeneity in soil hydrology based on local water content measurements, Vadose Zone J., 19, e20040, https://doi.org/10.1002/vzj2.20040, 2020. a, b
Bo, S., Sahoo, S. R., Yin, X., Liu, J., and Shah, S. L.: Parameter and state estimation of one-dimensional infiltration processes: A simultaneous approach, Mathematics, 8, 134, https://doi.org/10.3390/math8010134, 2020. a
Brandhorst, N., Erdal, D., and Neuweiler, I.: Soil moisture prediction with the ensemble Kalman filter: Handling uncertainty of soil hydraulic parameters, Adv. Water Resour., 110, 360–370, 2017. a, b, c, d, e, f
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. a
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Short summary
Data assimilation aims at quantifying and minimizing model uncertainty. In hydrological models, this uncertainty is mainly caused by the uncertain soil hydraulic parameters and their spatial variability. In this study, the impact of updating these parameters along with the model states on the estimated soil moisture is investigated. It is shown that parameter updates are beneficial and that it is advisable to resolve heterogeneous structures instead of applying a simplified soil structure.
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