Paper Type

Master's Thesis


College of Computing, Engineering & Construction

Degree Name

Master of Science in Civil Engineering (MSCE)



NACO controlled Corporate Body

University of North Florida. School of Engineering

First Advisor

Dr. William R. Dally

Second Advisor

Dr. Raphael W. Crowley

Third Advisor

Dr. Ryan Shamet

Department Chair

Dr. Raphael Crowley

College Dean

Dr. William Klostermeyer


Designers and other practitioners confront a wide range of problems in the coastal zone, which often require long-term nearshore wave data. However, such data are usually quite scarce. Consequently, either wave measurements from buoys deployed in deep water, or archived deepwater wave hindcast information, must be utilized by rigorous, physics-based transformation to the site of interest using one of many available numerical models. A main issue in conducting such an effort is accounting for losses in wave energy due to bottom friction, for which establishing a suitable bed friction coefficient (Cf) can be problematic. In the present study, a methodology is proposed in which a limited record of nearshore in situ measurements is used to guide the selection of an appropriate friction factor by using a combination of Quantile-Quantile (Q-Q) and “scatter-plot” techniques. The methodology is tested using 1) five months (July 2013 to December 2013) of directional wave measurements taken in the nearshore (~ 9m depth) off of Mayport, Florida, and 2) concurrent deepwater hindcast information that was archived at a location nominally 38 km off the coast (24.5m depth). The nearshore wave data were collected using an Acoustic Doppler Current Profiler (ADCP), and the deepwater hindcast information was developed and supplied by Oceanweather, Inc. A version of the well-known spectral wave transformation model “STWAVE”, modified to include wave energy losses due to bed friction, is used to transform the deepwater hindcast record to the site of the nearshore wave gauge. By running the model across a range of friction factors for a single month of the wave record (October, 2013), the proposed calibration method is demonstrated and the most appropriate coefficient selected (Cf = 0.015 in this instance). The calibrated model is then run for the entire five months of ADCP record to validate the proposed methodology.