Prediction of Infra-gravity Swash Motions on Natural Beaches using Model Trees

Document Type : Research Article

Authors

School of Civil Engineering, Iran University of Science & Technology, Tehran, Iran

Abstract

Occurrence of extreme storm waves predisposes natural beaches to erosion. During occurrence of these storm waves, infra-gravity swash energy plays an important role in the amount of erosion created. The available formula for infra-gravity swash is only based on wave heights and wave length and its accuracy is low. Recently, model trees have been introduced as one of the new methods in the data mining approaches that give all possible relations between the involved parameters. In this paper, a new model based on hydrodynamic parameters including the surf similarity, momentum flux and non-dimensional characteristic velocity parameters is presented by using the M5′ and MARS model trees. To generate and evaluate models, all of 579 field data available in literature was used. The results indicated that the developed MARS model improves the RMSE and R values by 42% and 26%, respectively, and the M5′ model improves these values by 16% and 12%, respectively, in respect to the most common empirical model. According to sensitivity analysis of MARS model and also results of M5′ model, the non-dimensional characteristic velocity parameter showed the most correlation and the surf similarity parameter showed the least correlation with infra-gravity swash motions. The performance of developed models is also compared with a numerical study implemented on Tizimin beaches in Mexico.

Keywords

Main Subjects


[1] H.F., Stockdon, R.A., Holman, P.A., Howd, H., Asbury, A.H., Sallenger, Empirical parameterization of setup, swash, and runup, Coast Engineering, 53(7) (2006) 573-588.
[2] B.G., Ruessink, M.G., Kleinhans, P.G.L., Van den Beukel, Observations of swash under highly dissipative conditions, Geophysical Research, 103 (C2) (1998) 3111-3118.
[3] I.A., Hunt, Design of seawalls and breakwaters, Waterways, Harbors, Coastal Engineering, 85(3) (1959) 123-152.
[4] R.T., Guza, E.B., Thornton, Swash oscillations on a natural beach, Geophysical Research, 87 (C1) (1982) 483-491.
[5] Hughes, S.A., Estimation of wave run-up on smooth, impermeable slopes using the wave momentum flux parameter, Coastal Engineering, 51 (2004) 1085–1104.
[6] N., Senechal, G., Coco, K.R., Bryan, R., Holman, Wave runup during extreme storm conditions, Geophysical Research, 116 (C7) (2011) 1-13.
[7] Y., Wang, I.H., Witten, Inducing model trees for continuous classes, Proceedings 9th European Conference on Machine Learning, (1997) 128-137.
[8] I.H., Witten, E., Frank, Data mining-practical machine learning tools and techniques, Morgan Kaufmann publisher (2005) 621.
[9] J.R., Quinlan, Learning with continuous classes, Proceeding 5th Australian joint Conference on Artificial Intelligence, (1992) 343-348.
[10] J.H., Friedman, Multivariate adaptive regression splines, Annals Statistics, 19(1) (1991) 1-141.
[11] P.D., Komar, M.K., Gaughan, Airy Wave Theory and Breaker Height Prediction”. Proceeding 13th International Conference of Coastal Engineering, ASCE (1973) 405-418.
[12] J.R., Weggel, Maximum Breaker Height, Waterways, Harbors, Coastal Engineering, 98 (WW4) (1972) 529-548.
[13] J.A., Brinkkemper, A., Torres-Freyermuth, E.T., Mendoza, B.G., Ruessink, Parameterization of wave run-up on beaches in Yucatan, Mexico: a numerical study, Coastal Dynamics, 25 (2013) 225-233.