Predictor equations for beach processes and responses | Zendy

Harrison W. | Zendy; Pore N. A. | Zendy; Tuck D. R. | Zendy

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Predictor equations for beach processes and responses

Author(s) -

Harrison W.,

Pore N. A.,

Tuck D. R.

Publication year - 1965

Publication title -

journal of geophysical research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.67

H-Index - 298

eISSN - 2156-2202

pISSN - 0148-0227

DOI - 10.1029/jz070i024p06103

Subject(s) - intertidal zone , storm , shoaling and schooling , geology , regression analysis , wind wave , wave setup , storm surge , meteorology , linear regression , coastal erosion , longshore drift , wave height , significant wave height , wind speed , regression , coastal engineering , deposition (geology) , shore , oceanography , sediment transport , statistics , geomorphology , mathematics , wave propagation , sediment , geography , longitudinal wave , physics , quantum mechanics , mechanical wave

A stepwise (linear) multiple regression procedure is applied to 11 environmental variables (or predictors) in the beach‐ocean‐atmosphere system at Virginia Beach, Virginia, for the following five predictands: mean longshore current velocity, mean bottom slope in the shoaling‐wave zone, average mean grain size in the shoaling‐wave zone, and beach deposition and beach erosion on the lower foreshore. Predictors consist of variables related to beach geometry, local water properties, local wind conditions, tidal fluctuations, and wave characteristics. The resultant equations are tested against a set of independent data and, with one exception, agree reasonably. It is believed that if the data set were increased to include at least one year's continuous measurements, the procedure outlined would yield valid equations for all but stormy‐weather conditions. It is presupposed that some provision will have to be made for preconditioning the data, as ‘storm’ and ‘nonstorm’ data will probably have to be analyzed separately.

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