LONG-TERM PREDICTION OF BEACH PROFILE AND SEDIMENT GRAIN SIZE CHARACTERISTIC AT LOW ENERGY BEACH
ICCE 2012 Cover Image
PDF

Keywords

principal component analysis
quadratic polynomial equations

How to Cite

Tsujimoto, G., Tamai, M., & Yamada, F. (2012). LONG-TERM PREDICTION OF BEACH PROFILE AND SEDIMENT GRAIN SIZE CHARACTERISTIC AT LOW ENERGY BEACH. Coastal Engineering Proceedings, 1(33), sediment.14. https://doi.org/10.9753/icce.v33.sediment.14

Abstract

Artificial sandy beach profiles and vertical distributions of sediment grain size were measured monthly along two cross-shore lines at Azure Maiko Beach for 2 years. All measured profiles and vertical distributions are approximated using quadratic profiles. To interpret temporal variations of these profiles, six parameters are introduced. Principle component analysis was applied to evolution of the six parameters to detect major variation modes. Relationships between the detected modes and external forces, wave height and tidal level are expressed using multiple linear regression analysis. The first mode was found to be caused by tidal oscillations and the second by energetic wave motions. Long-term prediction of the modes is examined using these regression results.
https://doi.org/10.9753/icce.v33.sediment.14
PDF

References

Goda, Y. 2002. A simple wind wave estimation based on Wilson's prediction formulas, ECOH/YG Technical Report No.1.

Jackson, N. L., K. L. Nordstrom, I. Eliot and G. Masseilink 2002. Low-energy sandy beaches in marine and estuarine environments; a review, Geomorphology, Vol.47, pp.147-162http://dx.doi.org/10.1016/S0169-555X(02)00179-4

Tsujimoto Gozo, F. Yamada, D. Sakai, H. Kaida and T. Kakinoki 2010. Seasonal variation of cross-shore beach profile with a filter layer, Annual Journal of Civil Engineering in the Ocean, JSCE, Vol.26,pp.1209-1214 (in Japanese).

Yamada Fumihiko and N. Kobayashi 2004: Annual variations of tide level and mudflat profile, Journal of Waterway, Port, Costal and Ocean Eng., ASCE,Vol.130,No.3,pp.119-126

Rubin D. M. 2004. A simple autocorrelation algorithm for determining grain size from digital image of sediment, Journal of Sedimentary Research, Vol.74, No.1,pp.160-165http://dx.doi.org/10.1306/052203740160

Authors retain copyright and grant the Proceedings right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this Proceedings.