Abstract In this study, wavelet support vector machine (WSWM) model is proposed for daily suspended sediment (SS) prediction. The WSVM model is achieved by combination of two methods; discrete wavelet analysis and support vector machine (SVM). The developed model was compared with single SVM. Daily discharge (Q) and SS data from Yadkin River at Yadkin College, NC station in the USA were used. I...

0022-1694/$ see front matter 2012 Elsevier B.V. A http://dx.doi.org/10.1016/j.jhydrol.2012.09.011 ⇑ Corresponding author. Tel.: +1 617 627 4260; fax E-mail addresses: [email protected] (D.C. Ro du (R.M. Vogel), [email protected] (G.E. Schwarz). 1 Present address: Geosyntec Consultants, 1330 Beaco MA 02446, United States. Estimates of mean annual watershed sediment discharge, derived from lon...