Analysis of Field Data of Coastal Morphological Evolution over Yearly and Decadal Timescales. Part 2: Non-Linear Techniques

Journal of Coastal Research

Volumn 19, Issue 4, 2003, Pages 776-789

  Southgate, Howard N ^a,f   Wijnberg, Kathelijne M ^b   Larson, Magnus ^c   Capobianco, Michele ^d   Jansen, Henk ^e  

^a HR WALLINGFORD   (United Kingdom)

^b UTRECHT UNIVERSITY   (Netherlands)

^c LUND UNIVERSITY   (Sweden)

^d Tecnomare SpA   (Italy)

^e DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^f NONE   (United Kingdom)

Author keywords

Coastal morphology; Forecasting signatures; Fractal analysis; Neural networks; Non linear data analysis; Singular spectrum analysis; Time series; Time delay embedding

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COASTAL EVOLUTION; DATA INTERPRETATION; DECADAL VARIATION; MORPHOLOGY; TIME SERIES ANALYSIS;

EID: 0345258521     PISSN: 07490208     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (32)

1. BAK, P.; TANG, C., and WEISENFELD, K., 1987. Self-organized criticality: An explanation of 1/f noise. Phys. Rev. Lett., 59, 381-385.
2. BREEDON, J. L. and PACKARD, N. H., 1992. Nonlinear analysis of data sampled nonuniformly in time, Physica D, 58, 273-283.
3. CHATFIELD, C., 1996. The Analysis of Time Series. An Introduction. London: Chapman and Hall.
4. CORNE, S.; KNEALE, P.; OPENSHAW, S., and SEE, L., 1998. The use and evaluation of artificial neural networks in flood forecasting, Proceedings 33rd MAFF Conference of River and Coastal Engineers (Keele, UK), pp. 6.4.1-6.4.10.
5. COWELL, P. J.; STIVE, M. J. F.; NIEDORODA, A. W.; SWIFT, D. J. P.; DE VRIEND, H. J.; BUIJSMAN, M. C.; NICHOLLS, R. J.; ROY, P. S.; KAMINSKY, G. M.; CLEVERINGA, J.; REED, C. W., AND DE BOER, P. L., 2003. The coastal tract, Parts 1 and 2. Journal of Coastal Research, 19(3), xxx-xxx.
6. DE VRIEND, H. J.; CAPOBIANCO, M.; CHESHER, T.; DE SWART, H. E.; LATTEUX, B., and STIVE, M. J. F., 1993. Approaches to long-term modeling of coastal morphology: a review. Coastal Engineering, 21, 225-269.
7. DIKS, C.; VAN ZWET, W. R.; TAKENS, F., and DEGOEDE, J., 1996. Detecting differences between delay vector distributions. Phys. Rev. E, 53(3), 2169-2176.
8. DODD, N.; BLONDEAUX, P.; CALVETE, D.; DE SWART, H. E.; FALQUES, A.; HULSCHER, S. J. M. H.; ROZYNSKI, G., and VITTORI, G., 2003. Understanding coastal dynamics using stability methods, Journal of Coastal Research, 19(3), xxx-xxx.
9. FRAEDRICH, K., 1986. Estimating the dimensions of weather and climate attractors. Journal of the Atmospheric Sciences, 43(5), 419-432.
10. GRASSBERGER, P. and PROCACCIA, I., 1983. Characterization of strange attractors. Phys. Rev. Lett., 59, 381-384.
11. HANSON, H.; AARNINKHOF, S.; CAPOBIANCO, M.; JIMENEZ, J. A.; LARSON, M.; NICHOLLS, R. J.; PLANT, N. G.; SOUTHGATE, H. N.; STEETZEL, H. J.; STIVE, M. J. F., and DE VRIEND, H. J., 2003. Modelling of coastal evolution on yearly and decadal time scales. Journal of Coastal Research, 19(3), xxx-xxx.
12. HASTINGS, H. M. and SUGIHARA, G., 1993. Fractals: A User's Guide for the Natural Sciences. Oxford: Oxford University Press.
13. JAFFE, B.E.; RUBIN, D. M., and SALLENGER, A. JR., 1994. How much velocity information is necessary to predict sediment suspension in the surf zone? Proceedings 24th International Conference Coastal Engineering 1994 (Kobe, Japan, ASCE), pp. 2085-2099.
14. KINGSTON, K.S. and DAVIDSON, M. A., 1999. Artificial neural network model of sand bar location for a macro-tidal beach, Perranporth, UK. Proceedings IAHR Symposium on River, Coastal and Estuarine Morphodynamics (Genoa, Italy) 227-236.
15. KROON, A., 1994. Sediment Transport and Morphodynamics of the Beach and Nearshore Zone Near Egmond, The Netherlands. Netherlands Geographical Studies 178, KNAG/Faculty of Geographical Sciences, Utrecht University, 275p.
16. LARSON, M.; CAPOBIANCO, M.; JANSEN, H.; ROZYNSKI, G.; SOUTHGATE, H. N.; STIVE, M. J. F., WIJNBERG, K. M., and HULSCHER, S. J. M. H. 2003. Analysis and modeling of field data of coastal morphological evolution over yearly and decadal time scales. Part 1. Background and linear techniques. Journal of Coastal Research, 19(3), xxx-xxx.
17. LEE, G-H.; NICHOLLS, R. J.; BIRKEMEIER, W. A., and LEATHERMAN, S. P., 1995. A conceptual fairweather-storm model of beach nearshore profile evolution at Duck, North Carolina, USA. Journal of Coastal Research, 11, 1157-1166.
18. LIPPMANN, T. C. and HOLMAN, R. A., 1989. Quantification of sand bar morphology: A video technique based on wave energy dissipation, Journal of Geophysical Research, 94(C1), 995-1011.
19. NORTH, C. P. and HALLIWELL, D. I., 1994. Bias in estimating fractal dimension with the rescaled-range (R/S) technique. Mathematical Geology, 26(5), 531-555.
20. ORESKES, N.; SHRADER-FRECHETTE, K., and BELITZ, K., 1994. Verification, validation and confirmation of numerical models in the earth sciences. Science, 263, 641-646.
21. PACKARD, N. H.; CRUTCHFIELD, J. P.; FARMER, J. D., and SHAW, R. S., 1980. Geometry from a time series. Phys. Rev. Lett., 45, 712-716.
22. PENLAND, C., 1989. Random forcing and forecasting using principal oscillation pattern analysis. Monthly Weather Review, 117, 2165-2185.
23. RUBIN, D. M., 1992. Use of forecasting signatures to help distinguish periodicity, chaos and randomness in ripples and other spatial patterns. Chaos, 2(4), 525-535.
24. RUELLE, D., 1990. Deterministic chaos: The science and the fiction. Proceedings Royal Society London A, 427, 241-248.
25. SOUTHGATE, H. N. and BELTRAN, L. M., 1996. Self-organizational processes in beach morphology. Proceedings 8th International Conference Physics of Estuarine and Coastal Seas (The Hague, The Netherlands), pp. 409-416.
26. SOUTHGATE, H. N. and MÖLLER, I., 2000. Fractal properties of coastal profile evolution at Duck, North Carolina. Journal of Geophysical Research, 105(C5), 11489-11507.
27. SUGIHARA, G., 1994. Non-linear forecasting for the classification of natural time series. Philosophical Transactions Royal Society London A., 348, 477-495.
28. SUGIHARA, G. and MAY, R. M., 1990. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature, 344, 734-741.
29. TAKENS, F., 1981. Detecting strange attractors in turbulence. In: Lecture Notes in Mathematics, No. 898. New York: Springer-Verlag, pp. 366-381.
30. TURCOTTE, D. L., 1992. Fractals and Chaos in Geology and Geophysics. Cambridge: Cambridge University Press.
31. VAUTARD, R.; YIOU, P., and GHIL, M., 1992. Singular spectrum analysis: a toolkit for short, noisy chaotic signals. Physica D, 58, 95-126.
32. WEIGEND, A. S., 1994. Paradigm changes in prediction. In: TONG, H. (ed.), Chaos and Forecasting, Proceedings Royal Society Discussion Meeting. Singapore: World Scientific, pp. 145-160.