GSA Annual Meeting in Indianapolis, Indiana, USA - 2018

Paper No. 181-7
Presentation Time: 9:00 AM-6:30 PM

SPATIAL PATTERNS OF ALGAL BLOOMS IN LAKE BLOOMINGTON AND EVERGREEN LAKE USING FIELD OBSERVATIONS AND REMOTE SENSING


AMBROSE-IGHO, Gare, Department of Geography-Geology-Environment, Illinois State University, 801 S University St. Apt 12, Normal, IL 61761; Department of Geography-Geology-Environment, Illinois State University, Campus Box 4400, Normal, IL 61790, SEYOUM, Wondwosen Mekonnen, Department of Geography-Geology-Environment, Illinois State University, Campus Box 4400, Normal, IL 61790, PERRY, William L., City of Bloomington, 25515 Waterside Way, Hudson, IL 61748 and O'REILLY, Catherine, Department of Geography-Geology, Illinois State University, Felmley Hall, Campus Box 4400, Normal, IL 61790

Algal blooms can cause harmful effects to freshwater ecosystems such as pollution of beaches, taste and odor problems in drinking water, and depletion of oxygen levels causing fish kills. They can have negative effects on the health of humans as well as other animals who use them for drinking or recreation. Algal blooms have been a growing water pollution problem in the Midwest, causing contamination of major reservoirs from which cities and towns draw drinking water. Algal blooms occur in freshwater when there is a sudden rise in the population of algae found in the water body and it causes the color of the water to change. The focus of this study is to examine the spatial patterns of algal blooms as well as their effect on water quality in Lake Bloomington and Evergreen Lake – the two reservoirs from which the City of Bloomington draws its water for water supply. The Bloomington water-supply system currently supplies over 80,000 people in the city of Bloomington, Hudson & Towanda Townships and half of the population of Dale and Dry Grove townships.

This project explores the effects of algal blooms in water and the environment using remote sensing data to monitor algal bloom occurrence and to develop methods that are transferable and will enable the determination of algal bloom occurrence at other locations. Monitoring of lakes using satellite remote sensing data is useful in estimating and detecting water quality problems that would have gone undetected in lakes. We are also collecting water samples, from selected locations on the lakes, to test for various water properties such as nitrate, phosphate, chlorophyll a, etc. A function derived from regression analysis conducted alongside with models/maps created will be used to predict water quality of the other locations of the lake not selected. Results have shown that blooms occur at different times of the year in each lake e.g. August for Evergreen Lake, October for Lake Bloomington. Using satellite image reflectance data from Landsat 8 images, we expect to see spatial patterns in water quality.