is low-pass filtered through a two-pole filter with a cutoff of 5 Hz. The pore- 

 pressure signal was not susceptible to electronic noise, and because it was 

 desirable to have a rapid response on this instrument, this sensor remained 

 unfiltered. 



Data Analysis 



Analysis and interpretation methods 



To simplify analysis of the data, data from each run were stored in two 

 separate files, one file containing acoustic profiler data and the other 

 containing data from all of the additional instruments. Analysis of the data 

 from all of the instruments was performed using the software package Matlab 

 from Math works, Inc. 



Statistical values, including the mean value, the standard deviation, the 

 minimum value, and the maximum value, were computed for each of the slow 

 instruments for each experimental run. Because some of the data runs 

 included time intervals in which waves were not being generated, these 

 statistical values were computed over only the time period during which waves 

 were being generated. Variable names for these statistical values, as well as 

 all other calibrated and uncalibrated data values for each of the slow 

 instruments, are found in Table 10-3. 



To determine the wave energy spectrum, a fast Fourier transform was 

 applied to the calibrated pressure signal, and from this the pressure spectrum 

 was determined. To correct for the attenuation of higher frequency pressure 

 measurements with depth, the pressure response factor K p was determined for 

 each run (Dean and Dalrymple 1984) 



K ( Z ) = cosh k (h + z) (10 . 9) 



p cosh k h 



where 



k = wave number for particular frequency 



h = water depth 



z = depth of pressure sensor 



Wave frequencies greater than 1 Hz were filtered out from the pressure spec- 

 trum to remove instrument noise. Each discrete frequency component of the 

 pressure spectrum was then multiplied by 1/A^, for that frequency to obtain the 

 final wave energy spectrum. 



The high-resolution pore pressure was then calibrated by examining the 

 low-resolution return signal and then determining in which range the high- 



Chapter 10 Intermittent Near-Bed Sediment Suspension 



197 



