Assimilating models and data to enhance predictions of shoreline evolution

By:  and 
Edited by: Jane McKee Smith and Patrick Lynett

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Abstract

A modeling system that considers both long- and short-term process-driven shoreline change is presented. The modeling system is integrated into a data assimilation framework that uses sparse observations of shoreline change to correct a model forecast and to determine unobserved model variables and free parameters. Application of the assimilation algorithm also provides quantitative statistical estimates of uncertainty that can be applied to coastal hazard and vulnerability assessments. Significant attention is given to the estimation of four non-observable quantities using the data assimilation framework that utilizes only one observable process (i.e. ,shoreline change). The general framework discussed here can be applied to many other geophysical processes by simply changing the model component to one applicable to the processes of interest.

Additional publication details

Publication type Conference Paper
Publication Subtype Conference Paper
Title Assimilating models and data to enhance predictions of shoreline evolution
DOI 10.9753/icce.v32.sediment.91
Year Published 2010
Language English
Publisher International Conference on Coastal Engineering
Contributing office(s) St. Petersburg Coastal and Marine Science Center
Larger Work Type Conference Paper
Larger Work Title Proceedings of 32nd International Conference on Coastal Engineering
Conference Title 32nd International Conference on Coastal Engineering
Conference Location Shanghai, China
Conference Date June 30-July 5 2010
Online Only (Y/N) N
Additional Online Files (Y/N) N