Author: Daniela  Gurlin,  Natural Resources Research Scientist (Wisconsin Department of Natural Resources)

Description:
Remote sensing presents a cost-efficient complementary approach for a more comprehensive assessment of our freshwater resources and has been utilized to estimate the water clarity, expressed as Secchi depth, for Wisconsin's large number of lakes for almost two decades. The use of remote sensing to assist in the characterization of Wisconsin’s lakes started in 1999 when Citizen Lake Monitoring Network (CLMN) volunteers assisted in a collaborative research effort with the University of Wisconsin-Madison Environmental Remote Sensing Center (ERSC) to develop a model for the retrieval of water clarity data from satellite images. CLMN volunteers collected on-the-ground Secchi depth data when the satellites were overhead to develop image acquisition date specific algorithms which were used to estimate over 10,000 water clarity values for lakes across Wisconsin from 1999 to 2001. The continuation of this research-turned-operational effort at the Wisconsin DNR made it possible to leverage remotely sensed data from the NASA/USGS Landsat Program to complement traditional water quality data in trophic state assessments for the State of Wisconsin and provided over 150,000 water clarity values through 2017. The results are shared within the Wisconsin DNR for the Wisconsin Water Quality Reports to Congress in compliance with Section 305(b) of the Clean Water Act and with state and local water quality managers, lake organizations, and the public. This presentation explores the practical use of remote sensing in a water quality monitoring program, the recently completed transition of the image processing chain to the cloud-based Google Earth Engine (GEE) platform, and the latest satellite retrieved water clarity data for the State of Wisconsin.

Category: Scientific Program Abstract > Special Session > SS58 Big data ecology: leveraging large scale data sets to understand aquatic ecosystem structure and dynamics at macrosystem scales