Using wavelet analysis to identify seasonal changes in water level fluctuations

Session: Physical Processes in Lakes (1)

Carlos Alberto Arnillas, Department of Physical and Environmental Sciences - University of Toronto - Scarborough, [email protected]
Vincent Cheng, University of Toronto Scarborough, [email protected]
Aisha Javed, University of Toronto Scarborough, [email protected]
George Arhonditsis, University of Toronto Scarborough, [email protected]

Abstract

Water level fluctuations (WLF) of the Laurentian Great Lakes directly impact millions of people living ashore. WLF has even a broader impact in North America by disturbing goods transportation and power generation. Under the current climate change conditions and given the on-going land-use transformation, it is projected that the water cycle and consequently the intra- and inter-annual WLF variability will be further affected. Here, we explored the potential WLF trends in monthly data between 1951 and 2013. We used wavelet analysis to discern the patterns of the different sources of variability in the frequency domain. We identified a strong -and constantly present- seasonal signal (1-year frequency) along with a second signal around the 8-year frequency that gradually disappears over the course of our study period. Preliminary results suggest that the water level maximum is gradually occurring later in the year (~0.09 days/year) and the amplitude of the 8-year frequency is dissipating. We discuss potential mechanisms that might be driving these changes in the context of global and regional environmental changes.