An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models
Type
ArticleKAUST Department
Applied Mathematics and Computational Science ProgramEarth Fluid Modeling and Prediction Group
Earth Science and Engineering Program
Environmental Science and Engineering Program
Physical Science and Engineering (PSE) Division
Date
2014-09Permanent link to this record
http://hdl.handle.net/10754/563724
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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.2014.05.001Publisher
Elsevier BVJournal
Advances in Water Resourcesae974a485f413a2113503eed53cd6c53
10.1016/j.advwatres.2014.05.001