SPECIAL PUBLICATION NO. 43
Thompson (1977) and tidal data from nearby adjacent sites are required to assure Balsillie (1987a). To the result, one standard quantification of representative shoreline deviation was added to yield a predicted change. seasonal variability measure of 50.5 m.
Starting with the most recent data and Project Design and moving back in time, regression techniques Performance Assessmnent are used to determine a trend line (solid line
in Figure 12) about which plus and minus Both long-tenm changes and extreme one-half the seasonal variability measure is event impacts have long been considered in affixed in the vertical direction (dashed lines assessing coastal development design in Figure 12). The slope of the trend line of activities (until recently the former has bythe time series is the rate of erosion or and-large been qualitative). In proper order, accretion (a zero slope or horizontal line long-term changes should first be represents stability). Now the seasonal determined, followed by the design extreme variability measure becomes a valuable asset event impact. The first determination allows towards identifying spurious data or long- for prudent siting of the development term change segments in shoreline behavior, activity, and the second for responsible For instance, if a point lies outside the structural design solutions to withstand seasonal variability envelop in the middle of storm tide, wave, and erosion event impacts. segment d, one would conclude that either However, without knowledge of seasonal seasonal variability was extreme for that asreve safits for a particular locality, year (for which there are undoubtedly no uncertainty will be introduced into such records) or the survey was made assessment. Following long-term immediately following extreme event impact determination of where the shore will be (either storm tide or wave event for which (e.g., say, a standard 30-year mortgage there are probably no records). In either period) it would, for instance, be prudent to case, we have reason to not include the data adjust the beach width of a given point in our analysis, since there are topographic survey to its narrowest expected sufficient data points for the segment to seasonal dimension, then to apply extreme suggest a strong trend. Interactively, trends event analyses. Considering the significant in segment d at localities up- and down- outlay of resources for beach nourishment coast can be used to verify such a trend in projects, it would seem appropriate to the spatial component of the change rate consider seasonal shoreline variability both in analysis. project design and in assessing performance.
We also can use historical information The controversial issue of whether about the area to assist in analysis. For coastal hardening structures (e.g., seawalls, instance, we know that the inlet was bulkheads, revetments) promote the erosion artificially constructed in 1951, and jetty of beaches fronting them, is one of complex construction began in 1953. Furthermore, proportions. Without being long-winded, the artificial nourishment south of the inlet began issue might finally be resolved by inspecting in 1974. Each of these events is coincident long-term shoreline location data. Again, with a new episode in shoreline behavior, however, seasonal shoreline shifts would and may be verified with similar analyses at require quantification and application in the nearby up- and down-coast sites. Note that analysis. At the very least, methodology there are too few data points to quantify the developed here would allow one to shoreline change trend for segment c; either determine if seasonal shoreline change was additional data points are required or of significant proportions that it should be verification/readjustment from analyses at considered in design applications. Using
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