State estimation of tidal hydrodynamics using ensemble Kalman filter |
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| Institution: | 1. Works Applications Co. Ltd., Ark Mori Building 19F, 1-12-32 Akasaka, Minato-ku, Tokyo 107-6019, Japan;2. University of North Florida, School of Engineering, 1 UNF Drive, Building 50, Room 3000, Jacksonville, FL 32224, USA;3. University of Central Florida, Department of Civil, Environmental, and Construction Engineering, 4000 Central Florida Blvd., P.O. Box 162450, Orlando, FL 32816, USA;4. The Ohio State University, Department of Civil, Environmental, and Geodetic Engineering, 2070 Neil Ave., 417D Hitchcock Hall, Columbus, OH 43210, USA;1. Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l’Analisi Ambientale, C.da S.Loja, 85050 Tito (PZ), Italy;2. Instituto de Geofísica, UNAM, Mexico;3. Departamento de Ciencias Básicas, Universidad Autónoma Metropolitana-Azcapotzalco, Av. San Pablo 180, Mexico City, Mexico;1. Department of Civil and Building Engineering, and Architecture (ICEA), Università Politecnica delle Marche, Italy;2. Department of Civil, Environmental and Architectural Engineering (ICEA), University of Padova, Italy;1. Dept. of Civil & Environmental Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi, Hiroshima 739-8527, Japan;2. Dept. of Civil Engineering, University of Ottawa, University of Ottawa, 161, Louis Pasteur St., B111K, Ottawa, Ontario K1N 6N5, Canada;1. LEN Technologies, Oak Hill, VA, USA;2. Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76019-0308, USA |
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| Abstract: | This paper presents a coupling of an ensemble Kalman filter (EnKF) with a discontinuous Galerkin-based, two-dimensional circulation model (DG ADCIRC-2DDI) to improve the state estimation of tidal hydrodynamics including water surface elevations and depth-integrated velocities. The methodology in this paper using EnKF perturbs the modeled hydrodynamics and bottom friction parameterization in the model while assimilating data with inherent error, and demonstrates a capability to apply EnKF within DG ADCIRC-2DDI for data assimilation. Parallel code development presents a unique aspect of the approach taken and is briefly described in the paper, followed by an application to a real estuarine system, the lower St. Johns River in north Florida, for the state estimation of tidal hydrodynamics. To test the value of gauge observations for improving state estimation, a tide modeling case study is performed for the lower St. Johns River successively using one of the four available tide gauging stations in model-data comparison. The results are improved simulations of water surface elevations and depth-integrated velocities using DG ADCIRC-2DDI with EnKF, both locally where data are available and non-locally where data are not available. The methodology, in general, is extensible to other modeling and data applications, for example, the use of remote sensing data, and specifically, can be readily applied as is to study other tidal systems. |
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| Keywords: | DG ADCIRC-2DDI Ensemble Kalman filter State estimation Parallelized simulation Tides Hydrodynamics |
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