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

Regional groundwater flow strongly depends on groundwater recharge and hydraulic conductivity. Both are spatially variable fields, and their estimation is an ongoing topic in groundwater research and practice. In this study, we use the ensemble Kalman filter as an inversion method to jointly estimat...

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Bibliographic Details
Published in:Hydrology and earth system sciences 2016-02, Vol.20 (1), p.555-569
Main Authors: Erdal, D, Cirpka, O. A
Format: Article
Language:English
Subjects:
Aquifers
Boundary conditions
Fields
Groundwater
Groundwater flow
Groundwater recharge
Head
Hydraulic conductivity
Hydraulics
Hydrogeology
Hydrology
Kalman filters
Knowledge
Parameter estimation
Trends
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Summary:Regional groundwater flow strongly depends on groundwater recharge and hydraulic conductivity. Both are spatially variable fields, and their estimation is an ongoing topic in groundwater research and practice. In this study, we use the ensemble Kalman filter as an inversion method to jointly estimate spatially variable recharge and conductivity fields from head observations. The success of the approach strongly depends on the assumed prior knowledge. If the structural assumptions underlying the initial ensemble of the parameter fields are correct, both estimated fields resemble the true ones. However, erroneous prior knowledge may not be corrected by the head data. In the worst case, the estimated recharge field resembles the true conductivity field, resulting in a model that meets the observations but has very poor predictive power. The study exemplifies the importance of prior knowledge in the joint estimation of parameters from ambiguous measurements.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-20-555-2016