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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 1
Hydrol. Earth Syst. Sci., 20, 555–569, 2016
https://doi.org/10.5194/hess-20-555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 555–569, 2016
https://doi.org/10.5194/hess-20-555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Feb 2016

Research article | 01 Feb 2016

Joint inference of groundwater–recharge and hydraulic–conductivity fields from head data using the ensemble Kalman filter

D. Erdal and O. A. Cirpka

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Cited articles

Aschenbrenner, F. and Ostin, A.: Automatic parameter estimation applied on a groundwater model: The problem of structure identification, Environ. Geol., 25, 205–210, https://doi.org/10.1007/BF00768550, 1995.
Bailey, R. T., and Baù, D.: Estimating geostatistical parameters and spatially-variable hydraulic conductivity within a catchment system using an ensemble smoother, Hydrol. Earth Syst. Sci., 16, 287–304, https://doi.org/10.5194/hess-16-287-2012, 2012.
Bocquet, M., and Sakov, P.: Joint state and parameter estimation with an iterative ensemble Kalman smoother, Nonlinear Process. Geophys., 20, 803–818, https://doi.org/10.5194/npg-20-803-2013, 2013.
Brunner, P., Hendricks Franssen, H.-J., Kgotlhang, L., Bauer-Gottwein, P., and Kinzelbach, W.: How can remote sensing contribute in groundwater modeling?, Hydrogeol. J., 15, 5–18, https://doi.org/10.1007/s10040-006-0127-z, 2006.
Burgers, G., van Leeuwen, P. V., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, https://doi.org/10.1175/1520-0493(1998)126<1719:ASITEK>2.0.CO;2, 1998.
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Short summary
Groundwater recharge and hydraulic conductivity are both important properties of a groundwater system. However, models using an erroneous conductivity field can be compensated by a false recharge field to construct the same type of hydraulic head observations. In this work we show that prior knowledge is very important when estimating parameter fields from ambiguous data (such as head observations). If the prior information is reasonable, the joint parameter estimation can be possible.
Groundwater recharge and hydraulic conductivity are both important properties of a groundwater...
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