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dc.contributor.authorChu, Kai
dc.contributor.authorBreugem, Willem Alexander
dc.contributor.authorLeyssen, Gert
dc.contributor.authorCornu, Tijs
dc.contributor.authorDecrop, Boudewijn
dc.date.accessioned2026-08-20T21:03:57Z
dc.date.available2026-08-20T21:03:57Z
dc.date.copyright2026/02/04
dc.date.issued2026
dc.identifier.otherJWPED5.WWENG-2421.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313895
dc.description.abstractAbstract Data assimilation improves the accuracy of numerical models by integrating observational data into model predictions, with the ensemble Kalman filter (EnKF) being a widely used technique. Despite its effectiveness, EnKF is often computationally ... Practical Applications This study presents a fast and reliable data assimilation method to improve predictions of salinity in estuaries by integrating field measurements into hydrodynamic models. During the tunnel immersion project in the Scheldt Estuary ...
dc.publisherAmerican Society of Civil Engineers
dc.titleOptimization of Salinity Data Assimilation for an Accurate Prediction of Density Variations during Marine Works
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue3
dc.journal.titleJournal of Waterway, Port, Coastal, and Ocean Engineering
dc.identifier.doi10.1061/JWPED5.WWENG-2421
dc.journal.fristpage04026004-1
dc.journal.lastpage04026004-11
dc.page11
dc.treeJournal of Waterway, Port, Coastal, and Ocean Engineering:;2026:;Volume ( 152 ):;issue: 003
dc.contenttypeFulltext


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