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    An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models

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    Type
    Article
    Authors
    El Gharamti, Mohamad cc
    Valstar, Johan R.
    Hoteit, Ibrahim cc
    KAUST Department
    Applied Mathematics and Computational Science Program
    Earth Fluid Modeling and Prediction Group
    Earth Science and Engineering Program
    Environmental Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2014-09
    Permanent link to this record
    http://hdl.handle.net/10754/563724
    
    Metadata
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    Abstract
    Reactive 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.
    Citation
    Gharamti, M. E., Valstar, J., & Hoteit, I. (2014). An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models. Advances in Water Resources, 71, 1–15. doi:10.1016/j.advwatres.2014.05.001
    Publisher
    Elsevier BV
    Journal
    Advances in Water Resources
    DOI
    10.1016/j.advwatres.2014.05.001
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.advwatres.2014.05.001
    Scopus Count
    Collections
    Articles; Environmental Science and Engineering Program; Applied Mathematics and Computational Science Program; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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