You are here:
Ensuring Safe Drinking Water in Lake Erie: Quantifying Extreme Weather Impacts on Cyanobacteria and Disinfection Byproducts (DPBs)EPA Grant Number: R835192
Title: Ensuring Safe Drinking Water in Lake Erie: Quantifying Extreme Weather Impacts on Cyanobacteria and Disinfection Byproducts (DPBs)
Investigators: Lee, Jiyoung , Liang, Song , Shum, C.K.
Institution: The Ohio State University
EPA Project Officer: Hiscock, Michael
Project Period: June 1, 2012 through September 30, 2014 (Extended to May 31, 2016)
RFA: Extreme Event Impacts on Air Quality and Water Quality with a Changing Global Climate (2011) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Global Climate Change , Water and Watersheds , Climate Change , Air , Water
The Great Lakes hold 95% of our Nation's and 20% of World's fresh water supply, and it is home to 30% of the US population. II million people rely on drinking water from Lake Erie, the most southern and biologicaJiy productive lake among the Great Lakes. Under increasing anthropogenic warming, with postulated consequences of intensified extreme weather events, Lake Erie, already with excessive nutrients from intensive agriculture and sewer overflows from metropolitan areas, is prone to see its drinking water quality further impaired. The central hypotheses ofthe proposed studies are: (1) global warming- induced extreme weather events (heavier snow/rainstorms, increased flooding, excessive heat and prolonged droughts) are correlated with increased nutrients, turbidity and harmful algal bloom (HAB) in the proposed Lake Erie study regions: Toledo and Painesville, (2) increased HABs in source water will increase cyanotoxin concentrations in finished drinking water, and (3) HABs in Lake Erie source water will interact with chlorine disinfectants used in water treatment process, which in turn will increase harmful disinfectant byproducts (DPBs) concentrations in finished drinking water. This grave concern has not been considered before.
Our scientific objectives are: (1) to assess the link between historic and current extreme weather events and water quality indicators using satellite and field work data, including water color (photosynthetically available radiation, chlorophyll concentration), temperature, turbidity, precipitation, river discharge, ice/snow/flood extents, (2) to understand the linkages of extreme weather events with source and finished water quality including cyanobacteria densities, cyanotoxins, DBPs, and nutrient concentrations, and (3) to model and predict adverse impacts to source and finished water to understand the future impact of extreme weather events on water safety in Lake Erie.
Specifically, this application will: (1) quantify parameters associated with extreme weather events using satellite remote sensing (MODIS, SAR, altimetry) data and reanalysis (ERA-Interim) models, (2) determine the cyanobacteria profile using molecular tools, and measure chemical-physical parameters including toxins and DBPs, and (3) integrate the above results using models to improve our ability to quantify risks to Lake Erie drinking water, which has not been considered before.
The planned work will contribute to better understanding of the patterns of extreme events and their impact on Lake Erie water quality, with particular emphasis on measures of water quality used in the regulatory framework that are known to be associated with health relevant end points. This innovative interdisciplinary approach using historic and current satellite remote sensing data, molecular microbiology tools, and modeling, will result in potentially transformative scientific findings that can be used by policy makers to help formulate adaptive policies to improve drinking water safety.
Publications and Presentations:Publications have been submitted on this project: View all 6 publications for this project
Supplemental Keywords:Lake Erie water quality, cyanobacteria, toxin, disinfection byproducts, molecular tools, satellite remote sensing, chlorophyll concentration, water color, semi-mechanistic models
Progress and Final Reports:2012 Progress Report
2013 Progress Report
2014 Progress Report