Quantifying Water Level Change Through Time in the North American Great Lakes

Anthropogenic and natural fluctuations including precipitation, runoff, snowmelt, water retention time, evaporation, and outflow all contribute to changes in water levels recorded in the North American Great Lakes. Changes in water levels and tides have been used as an index for physical parameters such as temperature, density, and circulation (Keeling and Whorf, 1997; Denny and Paine, 1998). In this study, NOAA verified hourly water level data ranging from 20 to 30 years in duration for five stations in Lake Michigan and four stations in Lake Superior were analyzed. Power Spectral Density calculated from a Fourier transform of the time series were found to exhibit power law scaling. The power-scaling exponent (β) was determined by fitting a power function to a log-log plot of frequency (f) or period (1/f) versus power in the frequency domain. Four distinct regions of scaling are observed with inflection points at approximately 1 day, 5 days, and 30 - 60 days. For time scales of less than one day, the power-scaling exponent (β) ranges from 0.1 to 0.5, indicating a white noise. From 1 day to 5 - 7 days, β ranges from 1.5 to 2.6, indicating moderate to strong persistence which we propose is due to frontal movements of weather systems. On timescales between 5 days and 30 - 60 days, β ranges from 0.1 to 0.4, again indicating a white noise which we propose is due to monthly and seasonal weather variations within the Great Lakes System. Beyond 30 - 60 days, all stations exhibit persistence, with β-values between 1.6 and 2.7.