CLWA is in the enviable position of having a deep bench of trained volunteers collecting various water quality parameters through the multiple programs directed by the Aquatic Citizen Science Committee.

Celebrating its 14th anniversary this year, our longest-running effort is the Secchi Disk Program which measures water clarity. CLWA volunteers take weekly water clarity measurements from prescribed GPS locations in this program. As you might expect, changes have occurred since the inception of this program including online reporting, taking surface temperature readings, and piloted in 2023 a “temperature at depth” initiative with a subset of Secchi volunteers. In 2023, 18 volunteers entered 228 Secchi reports starting as early as April with the last report entered in November. Cumulatively, over a 14-year program that creates a lot of data!

So what happens to all that data? Our partner, the Canandaigua Lake Watershed Council, and the municipal water purveyors use the near real-time reports to help inform of changing water conditions which might impact a water purveyors’ filtration needs due to suspended sediments or signal an impending cHAB (Cyanobacterial Harmful Algal Bloom) due to increased plankton growth. But the usefulness of the data doesn’t stop there.

In 2022, CLWA provided our long-term secchi data set to the Department of Environmental Resources Engineering at SUNY-ESF to support their optical remote sensing research. Optical remote sensing is an evolving science that uses satellites or drones to gather water quality parameters without direct contact using multi-spectral imaging. Though remote sensing has been successfully used in marine environments and larger freshwater systems, like the Great Lakes, to estimate “water clarity, Chl-a, colored dissolved organic matter and suspended particulate matter”, smaller inland lakes pose some unique challenges to this technique. This is especially true for oligotrophic lakes like Canandaigua where water clarity is relatively high and water-leaving radiance is low. (Think there are fewer constituents in the water to reflect to the satellite.) ESF employed the CLWA secchi disk data set to help overcome this challenge by ground-truthing with our empirical data various machine learning algorithms used to estimate water clarity via optical remote sensing and evaluate the accuracy of those algorithms. This work resulted in a research paper published in the IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 17, 2024 titled “Mapping Water Clarity in Small Oligotrophic Lakes Using Sentinel-2 Imagery and Machine Learning Methods: A Case Study of Canandaigua Lake in Finger Lakes, New York” .

It would have been hard to imagine when this program started in 2010 that the wealth of our Secchi data would be used to assist the honing of optical remote sensing when used on smaller inland lakes. The strength of the Secchi program and the accessibility to our data attracted this research to Canandaigua Lake. Dr. Bahram Salehi and PhD student Rabia Kahn who co-authored the above paper intend to expand and continue work on Canandaigua Lake this coming season.

Article By Sally Napolitano