DOI: 10.7488/ds/2512
title: A novel technique for experimental modal analysis of barotropic seiches for assessing lake energetics
title: Random Decrement Technique for barotropic seiche analysis
title: Operational modal analysis of low frequency surface waves in lakes and reservoirs

description: In this study, the principles of operational modal analysis, through the Random Decrement Technique (RDT), currently used primarily in the analysis of high rise structures and in the aeronautical industry and not previously applied within the fields of limnology or ecology, are applied to barotropic seiches through the analysis of water level data for Lake Geneva, Switzerland, and Lake Tahoe, USA. Using this technique, the autocorrelation of the measurements is estimated using the RDT and modal analysis can then be carried out on this time-domain signal to estimate periods of the dominant surface seiches and the corresponding damping ratios. Provided within this dataset are a set of example MATLAB scripts for the application of the Random Decrement Technique to barotropic seiche analysis, alongside the water elevation data for Lake Geneva and Lake Tahoe used within "A novel technique for experimental modal analysis of barotropic seiches for assessing lake energetics" (Wynne et al, 2019).
description: Lake_Geneva_Data.mat - Water elevation data (metres above ordnance datum) for data collection locations 2026, 2027 and 2028. Data is provided as separate water elevation data for each collection location alongside a corresponding date and time file (files labelled WaterElevationDates). Date-times are provided as strings in the format YYYY:MM:DD HH:MM and are in Central European Standard Time. This data had a sampling rate of 10 minutes and was continuously collected between 00:00 on 1 January 1974 and 23:50 on 7 January 2013. Lake Geneva data is provided courtesy of the Swiss Federal Office for the Environment. -------- Lake_Tahoe_Data.mat - Data is provided as hydrostatic pressure heads (meters; equivalent to the depth of the lake at the data collection location) in separate annual datasets for 2013, 2014 and 2015. Each annual dataset has a corresponding date-time file (labelled _Dates) with date-times provided in the format DD/MM/YYYY HH:MM:SS. The sampling rate of the data is 30 seconds. The 2013 dataset spans 30 July 2013 00:00:00 to 6 December 2013 23:59:30. The 2014 dataset spans 1 January 2014 00:00:00 to 10 May 2014 23:59:30. The 2015 dataset spans 6 January 2015 00:00:00 to 15 May 2015 23:59:30. Lake Tahoe data is provided courtesy of Heather Sprague of the University of California, Davis. -------- MAIN_Random_decrement_model.m - A MATLAB script for applying the Random Decrement Technique for analysis of barotropic seiches. Provided within this file is a description of the application of the Random Decrement model. All other .m files (bandpass_filter.m, FastFourierTransform.m, fMatPen.m, RDT_level_crossing.m) are called by this script. MATLAB scripts are licensed under the CC-BY 4.0 International License. Copyright 2019 Zachariah Wynne, Thomas Reynolds, Damien Bouffard, Geoffrey Schladow, Danielle Wain. A section of the fMatPen.m script is provided with permission of Professor T Zielinski, for a full description of the marked section of code please refer to http://www.kt.agh.edu.pl/~tzielin/papers/M&MS-2011/. -------- water_elevation_2028_2018.mat - An example dataset provided for use with MAIN_Random_decrement_model.m. -------- Lakes_Geneva_and_Tahoe.png - Bathymetric maps of Lake Geneva (a) and Lake Tahoe (b). Locations of data collection sites marked. Samples of mean normalised Lake Geneva water elevation data and mean normalised Lake Tahoe water depth data shown in (c) and (d) respectively.