An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models |
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| Institution: | 1. Earth Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia;2. Subsurface and Groundwater Systems, Deltares, Princetonlaan 6, 3584 CB Utrecht, The Netherlands;3. Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia;1. Consiglio Nazionale delle Ricerche, Istituto di Ricerca Sulle Acque, Via Salaria km 29.300, 00015 Monterotondo, RM, Italy;2. Dipartimento DICATAM, Università degli Studi di Brescia, Via Branze 43, 25123 Brescia, Italy;3. Consiglio Nazionale delle Ricerche, Istituto di Ricerca Sulle Acque, UOS Brugherio, Via del Mulino, 19, 20861 Brugherio, MB, Italy;1. School of Electrical & Automatic Engineering, Changshu Institute of Technology, 215500 Changshu, China;2. School of Automation, Nanjing University of Science & Technology, 210094 Nanjing, China;1. Comsol Multiphysics GmbH, 37073 Gottingen, Germany;2. Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China;3. Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Catania, Italy;1. Departamento de Electrónica, Automática e Informática Industrial, UPM, Ronda de Valencia 3, 28012 Madrid, Spain;2. Departamento de Ingeniería Eléctrica, Electrónica y de Control, UNED, Juan del Rosal, 12 – Ciudad Universitaria, 28040 Madrid, Spain;1. Laboratory of Theoretical Spectroscopy, V.E. Zuev Institute of Atmospheric Optics, SB, Russian Academy of Science, 1, Akademician Zuev square, 634021 Tomsk, Russia;2. Mathematical Physics Department, Tomsk Polytechnic University 30, Lenin av., 634050 Tomsk, Russia;3. Université Grenoble 1/CNRS, UMR5588 LIPhy, Grenoble F-38041, France |
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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. |
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| Keywords: | Contaminant transport modeling Ensemble Kalman filter (EnKF) Optimal interpolation (OI) Hybrid EnKF-OI State-parameter estimation |
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