Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4251-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4251-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Aug 2018
Research article |
| 13 Aug 2018
| 13 Aug 2018
Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope
Anna Botto
CORRESPONDING AUTHOR
Department of Civil, Environmental and Architectural Engineering,
University of Padua, Padua, Italy
Enrica Belluco
Department of Civil, Environmental and Architectural Engineering,
University of Padua, Padua, Italy
Matteo Camporese
Department of Civil, Environmental and Architectural Engineering,
University of Padua, Padua, Italy
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Cited
19 citations as recorded by crossref.
- Assimilation of Groundwater Level and Soil Moisture Data in an Integrated Land Surface‐Subsurface Model for Southwestern Germany C. Hung et al. 10.1029/2021WR031549
- Real-time simulation of surface water and groundwater with data assimilation X. He et al. 10.1016/j.advwatres.2019.03.004
- Combining Models of Root-Zone Hydrology and Geoelectrical Measurements: Recent Advances and Future Prospects B. Mary et al. 10.3389/frwa.2021.767910
- Evaluation of short-term streamflow prediction methods in Urban river basins X. Huang et al. 10.1016/j.pce.2021.103027
- <i>STH-net:</i> a soil monitoring network for process-based hydrological modelling from the pedon to the hillslope scale E. Martini et al. 10.5194/essd-13-2529-2021
- Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. 10.5194/hess-25-1617-2021
- Field scale computer modeling of soil moisture with dynamic nudging assimilation algorithm O. Kozhushko et al. 10.23939/mmc2022.02.203
- Richards Equation at the Hillslope Scale: Can We Resolve the Heterogeneity of Soil Hydraulic Material Properties? H. Bauser et al. 10.1029/2022WR032294
- Estimation of hydraulic parameters in a heterogeneous low‐lying farmland near Venice E. Zancanaro et al. 10.1002/hyp.14791
- Challenges with effective representations of heterogeneity in soil hydrology based on local water content measurements H. Bauser et al. 10.1002/vzj2.20040
- Inflation method for ensemble Kalman filter in soil hydrology H. Bauser et al. 10.5194/hess-22-4921-2018
- Real-time reservoir flood control operation enhanced by data assimilation J. Zhang et al. 10.1016/j.jhydrol.2021.126426
- Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations C. Xia et al. 10.5194/hess-25-1689-2021
- State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management M. Pezij et al. 10.1016/j.hydroa.2019.100040
- A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation Q. Zhang et al. 10.1016/j.advwatres.2019.103407
- A regional ionospheric assimilation study with GPS and COSMIC measurements using a 3D-var algorithm (IDA4D) S. Jeong et al. 10.1016/j.asr.2021.12.049
- Recent advances and opportunities in data assimilation for physics-based hydrological modeling M. Camporese & M. Girotto 10.3389/frwa.2022.948832
- Iterative filter based estimation of fully 3D heterogeneous fields of permeability and Mualem-van Genuchten parameters A. Chaudhuri et al. 10.1016/j.advwatres.2018.10.023
- Covariance resampling for particle filter – state and parameter estimation for soil hydrology D. Berg et al. 10.5194/hess-23-1163-2019
19 citations as recorded by crossref.
- Assimilation of Groundwater Level and Soil Moisture Data in an Integrated Land Surface‐Subsurface Model for Southwestern Germany C. Hung et al. 10.1029/2021WR031549
- Real-time simulation of surface water and groundwater with data assimilation X. He et al. 10.1016/j.advwatres.2019.03.004
- Combining Models of Root-Zone Hydrology and Geoelectrical Measurements: Recent Advances and Future Prospects B. Mary et al. 10.3389/frwa.2021.767910
- Evaluation of short-term streamflow prediction methods in Urban river basins X. Huang et al. 10.1016/j.pce.2021.103027
- <i>STH-net:</i> a soil monitoring network for process-based hydrological modelling from the pedon to the hillslope scale E. Martini et al. 10.5194/essd-13-2529-2021
- Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. 10.5194/hess-25-1617-2021
- Field scale computer modeling of soil moisture with dynamic nudging assimilation algorithm O. Kozhushko et al. 10.23939/mmc2022.02.203
- Richards Equation at the Hillslope Scale: Can We Resolve the Heterogeneity of Soil Hydraulic Material Properties? H. Bauser et al. 10.1029/2022WR032294
- Estimation of hydraulic parameters in a heterogeneous low‐lying farmland near Venice E. Zancanaro et al. 10.1002/hyp.14791
- Challenges with effective representations of heterogeneity in soil hydrology based on local water content measurements H. Bauser et al. 10.1002/vzj2.20040
- Inflation method for ensemble Kalman filter in soil hydrology H. Bauser et al. 10.5194/hess-22-4921-2018
- Real-time reservoir flood control operation enhanced by data assimilation J. Zhang et al. 10.1016/j.jhydrol.2021.126426
- Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations C. Xia et al. 10.5194/hess-25-1689-2021
- State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management M. Pezij et al. 10.1016/j.hydroa.2019.100040
- A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation Q. Zhang et al. 10.1016/j.advwatres.2019.103407
- A regional ionospheric assimilation study with GPS and COSMIC measurements using a 3D-var algorithm (IDA4D) S. Jeong et al. 10.1016/j.asr.2021.12.049
- Recent advances and opportunities in data assimilation for physics-based hydrological modeling M. Camporese & M. Girotto 10.3389/frwa.2022.948832
- Iterative filter based estimation of fully 3D heterogeneous fields of permeability and Mualem-van Genuchten parameters A. Chaudhuri et al. 10.1016/j.advwatres.2018.10.023
- Covariance resampling for particle filter – state and parameter estimation for soil hydrology D. Berg et al. 10.5194/hess-23-1163-2019
Latest update: 14 Dec 2024
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.
We present a multivariate application of the ensemble Kalman filter (EnKF) in hydrological...
