کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
856042 1470710 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Analyses of Shoreline Retreat by Peak Storms using Hasaki Coast Japan Data
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی (عمومی)
پیش نمایش صفحه اول مقاله
Analyses of Shoreline Retreat by Peak Storms using Hasaki Coast Japan Data
چکیده انگلیسی

The prediction of shoreline retreat due to storms is important for coastal management. Previous studies have analyzed the relationship between shoreline retreat by storms and offshore energy flux of waves Ef to estimate shoreline position. In the present study, the combined effect of the maximum wave run-up level of sea waves R on beaches and Ef was used to analyze shoreline retreat. Eighteen peak storms were selected from shoreline data for Hasaki Coast, Japan, from 1987 to 2006, and shoreline retreat was analyzed for two phases of erosion: storm phase and post-storm phase. The R.Ef concept was shown to be applicable for estimating shoreline retreat in both phases of erosion. Because berm erosion tends to occur during storm-phase erosion, shoreline retreat is likely to occur during storm-phase rather than during post-storm erosion. Therefore, R.Ef per meter in storm-phase erosion, and particularly for peak storms, is much less than that in post-storm phase. It was also found that R.Ef per meter increases with landward shoreline retreat in both phases of erosion. The maximum annual shoreline position at Hasaki Coast was also analyzed statistically, and returns period (RP) was determined using cumulative frequency techniques. RP versus maximum shoreline position was plotted to determine the probable eroded shoreline position that would likely occur within a given period of time. It was found that the trend of the return period changes at 5 years and that the RP of the maximum shoreline position at a distance of 36 m landward from the foot of Hasaki pier is 24 years.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Engineering - Volume 116, 2015, Pages 575-582