Articles | Volume 25, issue 4
https://doi.org/10.5194/hess-25-1689-2021
https://doi.org/10.5194/hess-25-1689-2021
Research article
 | 
06 Apr 2021
Research article |  | 06 Apr 2021

Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations

Chuan-An Xia, Xiaodong Luo, Bill X. Hu, Monica Riva, and Alberto Guadagnini

Related authors

Towards automation of river water surface detection
Stefano Conversi, Daniela Carrion, Francesco Gioia, Alessandra Norcini, and Monica Riva
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 19–27, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-19-2024,https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-19-2024, 2024
Relative importance of uncertain model parameters driving water fluxes in a Land Surface Model
David Luttenauer, Aronne Dell'Oca, Alberto Guadagnini, Sylvain Weill, and Philippe Ackerer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-73,https://doi.org/10.5194/hess-2024-73, 2024
Preprint under review for HESS
Short summary
INTEGRATING OPTICAL AND RADAR IMAGERY TO ENHANCE RIVER DROUGHT MONITORING
S. Conversi, D. Carrion, A. Norcini, and M. Riva
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1363–1371, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1363-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1363-2023, 2023
A Comprehensive Framework for Stochastic Calibration and Sensitivity Analysis of Large-Scale Groundwater Models
Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-268,https://doi.org/10.5194/hess-2023-268, 2023
Revised manuscript accepted for HESS
Short summary
Feedback mechanisms between precipitation and dissolution reactions across randomly heterogeneous conductivity fields
Yaniv Edery, Martin Stolar, Giovanni Porta, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 25, 5905–5915, https://doi.org/10.5194/hess-25-5905-2021,https://doi.org/10.5194/hess-25-5905-2021, 2021
Short summary

Related subject area

Subject: Groundwater hydrology | Techniques and Approaches: Stochastic approaches
An ensemble-based approach for pumping optimization in an island aquifer considering parameter, observation and climate uncertainty
Cécile Coulon, Jeremy T. White, Alexandre Pryet, Laura Gatel, and Jean-Michel Lemieux
Hydrol. Earth Syst. Sci., 28, 303–319, https://doi.org/10.5194/hess-28-303-2024,https://doi.org/10.5194/hess-28-303-2024, 2024
Short summary
A Comprehensive Framework for Stochastic Calibration and Sensitivity Analysis of Large-Scale Groundwater Models
Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-268,https://doi.org/10.5194/hess-2023-268, 2023
Revised manuscript accepted for HESS
Short summary
Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles
Chloé Fandel, Ty Ferré, François Miville, Philippe Renard, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 4205–4215, https://doi.org/10.5194/hess-27-4205-2023,https://doi.org/10.5194/hess-27-4205-2023, 2023
Short summary
The effects of rain and evapotranspiration statistics on groundwater recharge estimations for semi-arid environments
Tuvia Turkeltaub and Golan Bel
Hydrol. Earth Syst. Sci., 27, 289–302, https://doi.org/10.5194/hess-27-289-2023,https://doi.org/10.5194/hess-27-289-2023, 2023
Short summary
Characterization of the highly fractured zone at the Grimsel Test Site based on hydraulic tomography
Lisa Maria Ringel, Mohammadreza Jalali, and Peter Bayer
Hydrol. Earth Syst. Sci., 26, 6443–6455, https://doi.org/10.5194/hess-26-6443-2022,https://doi.org/10.5194/hess-26-6443-2022, 2022
Short summary

Cited articles

Alfonzo, M. and Oliver, D. S.: Seismic data assimilation with an imperfect model, Comput. Geosci., 24, 889–905, https://doi.org/10.1007/s10596-019-09849-0, 2020. 
Bauser, H. H., Berg, D., Klein, O., and Roth, K.: Inflation method for ensemble Kalman filter in soil hydrology, Hydrol. Earth Syst. Sci., 22, 4921–4934, https://doi.org/10.5194/hess-22-4921-2018, 2018. 
Bianchi Janetti, E., Riva, M., Straface, S., and Guadagnini, A.: Stochastic characterization of the Montalto Uffugo research site (Italy) by geostatistical inversion of moment equations of groundwater flow, J. Hydrol., 381, 42–51, 2010. 
Bianchi Janetti, E., Guadagnini, L., Riva, M., Guadagnini, A.: Global sensitivity analyses of multiple conceptual models with uncertain parameters driving groundwater flow in a regional-scale sedimentary aquifer, J. Hydrol., 574, 544–556, 2019. 
Bocquet, M. and Sakov, P.: An iterative ensemble Kalman smoother, Q. J. Roy. Meteorol. Soc., 140, 1521–1535, 2014. 
Download
Short summary
Our study shows that (i) monitoring wells installed with packers provide the (overall) best conductivity estimates; (ii) conductivity estimates anchored on information from partially and fully screened wells are of similar quality; (iii) inflation of the measurement-error covariance matrix can improve conductivity estimates when a simplified flow model is adopted; and (iv) when compared to the MC-based EnKF, the MEs-based EnKF can efficiently and accurately estimate conductivity and head fields.