Morphodynamic data assimilation used to understand changing coasts
Morphodynamic data assimilation blends observations with model predictions and comes in many forms, including linear regression, Kalman filter, brute-force parameter estimation, variational assimilation, and Bayesian analysis. Importantly, data assimilation can be used to identify sources of prediction errors that lead to improved fundamental understanding. Overall, models incorporating data assimilation yield better information to the people who must make decisions impacting safety and wellbeing in coastal regions that experience hazards due to storms, sea-level rise, and erosion. We present examples of data assimilation associated with morphologic change. We conclude that enough morphodynamic predictive capability is available now to be useful to people, and that we will increase our understanding and the level of detail of our predictions through assimilation of observations and numerical-statistical models.
Citation Information
Publication Year | 2015 |
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Title | Morphodynamic data assimilation used to understand changing coasts |
DOI | 10.1142/9789814689977_0244 |
Authors | Nathaniel G. Plant, Joseph W. Long |
Publication Type | Conference Paper |
Publication Subtype | Conference Paper |
Index ID | 70148394 |
Record Source | USGS Publications Warehouse |
USGS Organization | St. Petersburg Coastal and Marine Science Center |