Quantitative analysis of nearshore morphological variability based on video imaging Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/4f16c5261

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  • In the past, classification systems for the analysis of morphodynamic variability have been developed in an attempt to understand large scale coastal behavior. The motivation behind the creation of these classification systems has been to provide a framework of analysis, in order to understand large scale response to seasonal variability, changes in incident wave conditions such as wave angle and height, and other forcing parameters. These schemes have, in general, been based upon subjective observation of wave breaking patterns and subsequent classification into discrete morphological states. Although these systems provide understanding into the morphodynamics of beaches, they are limited by their qualitative nature and by the inability to describe subtle changes in conditions as beaches progress within a given state. In this study, an objective and quantitative evaluation system of morphodynamics was developed, thus allowing for a more complete analysis of beach variability. The data for this study was provided by the Argus network, a series of video cameras with aerial views of beaches around the world. Intensity contrasts in time exposure images reveal areas of preferential wave breaking, which research has shown is closely tied to the underlying bed morphology. Morphometric statistics describing the range of variability within theses breaking patterns were developed, thus allowing quantitative differentiation of morphological condition. Because each of the numerical statistics is continuous, morphodynamic change could be analyzed over the entire range of conditions without losing information to the process of catagorization. Once statistics were developed, the analysis system was applied to images from four of the Argus camera sites. Relationships between changing wave conditions and alteration in morphometric statistics were analyzed, along with cyclical patterns in seasonal variability. Large scale response patterns found at each site were compared to each other, thus allowing for some broad generalizations to be made about large scale coastal response to changing environmental conditions.
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