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dc.contributor.authorEl Gharamti, Mohamad
dc.contributor.authorValstar, Johan R.
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2015-08-03T12:07:52Z
dc.date.available2015-08-03T12:07:52Z
dc.date.issued2014-09
dc.identifier.issn03091708
dc.identifier.doi10.1016/j.advwatres.2014.05.001
dc.identifier.urihttp://hdl.handle.net/10754/563724
dc.description.abstractReactive contaminant transport models are used by hydrologists to simulate and study the migration and fate of industrial waste in subsurface aquifers. Accurate transport modeling of such waste requires clear understanding of the system's parameters, such as sorption and biodegradation. In this study, we present an efficient sequential data assimilation scheme that computes accurate estimates of aquifer contamination and spatially variable sorption coefficients. This assimilation scheme is based on a hybrid formulation of the ensemble Kalman filter (EnKF) and optimal interpolation (OI) in which solute concentration measurements are assimilated via a recursive dual estimation of sorption coefficients and contaminant state variables. This hybrid EnKF-OI scheme is used to mitigate background covariance limitations due to ensemble under-sampling and neglected model errors. Numerical experiments are conducted with a two-dimensional synthetic aquifer in which cobalt-60, a radioactive contaminant, is leached in a saturated heterogeneous clayey sandstone zone. Assimilation experiments are investigated under different settings and sources of model and observational errors. Simulation results demonstrate that the proposed hybrid EnKF-OI scheme successfully recovers both the contaminant and the sorption rate and reduces their uncertainties. Sensitivity analyses also suggest that the adaptive hybrid scheme remains effective with small ensembles, allowing to reduce the ensemble size by up to 80% with respect to the standard EnKF scheme. © 2014 Elsevier Ltd.
dc.publisherElsevier BV
dc.subjectContaminant transport modeling
dc.subjectEnsemble Kalman filter (EnKF)
dc.subjectHybrid EnKF-OI
dc.subjectOptimal interpolation (OI)
dc.subjectState-parameter estimation
dc.titleAn adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models
dc.typeArticle
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Division
dc.contributor.departmentEnvironmental Science and Engineering Program
dc.contributor.departmentEarth Fluid Modeling and Prediction Group
dc.contributor.departmentEarth Sciences and Engineering Program
dc.identifier.journalAdvances in Water Resources
dc.contributor.institutionSubsurface and Groundwater Systems, Deltares, Princetonlaan 6, 3584 CB Utrecht, Netherlands
kaust.personEl Gharamti, Mohamad
kaust.personHoteit, Ibrahim


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