Articles | Volume 22, issue 8
Hydrol. Earth Syst. Sci., 22, 4251–4266, 2018
Hydrol. Earth Syst. Sci., 22, 4251–4266, 2018
Research article
13 Aug 2018
Research article | 13 Aug 2018

Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope

Anna Botto et al.

Related authors

Different coastal marsh sites reflect similar topographic conditions under which bare patches and vegetation recovery occur
Chen Wang, Lennert Schepers, Matthew L. Kirwan, Enrica Belluco, Andrea D'Alpaos, Qiao Wang, Shoujing Yin, and Stijn Temmerman
Earth Surf. Dynam., 9, 71–88,,, 2021
Short summary
Technical note: an alternative approach to laboratory benchmarking of saltwater intrusion in coastal aquifers
Elena Crestani, Matteo Camporese, and Paolo Salandin
Hydrol. Earth Syst. Sci. Discuss.,,, 2019
Preprint withdrawn
Short summary

Related subject area

Subject: Hillslope hydrology | Techniques and Approaches: Modelling approaches
Spatiotemporal changes in flow hydraulic characteristics and soil loss during gully headcut erosion under controlled conditions
Mingming Guo, Zhuoxin Chen, Wenlong Wang, Tianchao Wang, Qianhua Shi, Hongliang Kang, Man Zhao, and Lanqian Feng
Hydrol. Earth Syst. Sci., 25, 4473–4494,,, 2021
Short summary
Estimation of rainfall erosivity based on WRF-derived raindrop size distributions
Qiang Dai, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv
Hydrol. Earth Syst. Sci., 24, 5407–5422,,, 2020
Short summary
Physically based model for gully simulation: application to the Brazilian semiarid region
Pedro Henrique Lima Alencar, José Carlos de Araújo, and Adunias dos Santos Teixeira
Hydrol. Earth Syst. Sci., 24, 4239–4255,,, 2020
Short summary
Assessing the perturbations of the hydrogeological regime in sloping fens due to roads
Fabien Cochand, Daniel Käser, Philippe Grosvernier, Daniel Hunkeler, and Philip Brunner
Hydrol. Earth Syst. Sci., 24, 213–226,,, 2020
Short summary
A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates
Rubianca Benavidez, Bethanna Jackson, Deborah Maxwell, and Kevin Norton
Hydrol. Earth Syst. Sci., 22, 6059–6086,,, 2018
Short summary

Cited articles

Baatz, D., Kurtz, W., Franssen, H. H., Vereecken, H., and Kollet, S.: Catchment tomography – An approach for spatial parameter estimation, Adv. Water Resour., 107, 147–159,, 2017. a
Bailey, R. and Baù, D.: Ensemble smoother assimilation of hydraulic head and return flow data to estimate hydraulic conductivity distribution, Water Resour. Res., 46, w12543,, 2010. a
Bauser, H. H., Jaumann, S., Berg, D., and Roth, K.: EnKF with closed-eye period – towards a consistent aggregation of information in soil hydrology, Hydrol. Earth Syst. Sci., 20, 4999–5014, 10.5194/hess-20-4999-2016, 2016. a
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436,<0420:ASWTET>2.0.CO;2, 2001. 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
Short summary
We present a multivariate application of the ensemble Kalman filter (EnKF) in hydrological modeling of a real-world hillslope test case with dominant unsaturated dynamics and strong nonlinearities. Overall, the EnKF is able to correctly update system state and soil parameters. However, multivariate data assimilation may lead to significant tradeoffs between model predictions of different variables, if the observation data are not high quality or representative.