Office of Research and Development Publications

Assessing the impact of cyanobacterial harmful algal blooms on drinking water intakes across the United States.

Citation:

Schaeffer, B., M. Amanatides, J. Darling, E. Urquhart, AND W. Salls. Assessing the impact of cyanobacterial harmful algal blooms on drinking water intakes across the United States. 2018 AGU Fall Meeting, Washington, DC, December 10 - 14, 2018.

Impact/Purpose:

Blue-green algae is another word for cyanobacteria which can create thick blankets of algae in lakes. These algae blooms can be harmful to humans and animals who are exposed to them. Humans are typically exposed to blue-green algae by either swimming in or drinking contaminated water. Previous research has shown that satellite data can be an effective way to monitor blue-green algae across many locations and in a timely manner. This study used data from two satellites that spanned the years 2008-2011 and 2017 to monitor over 2,000 of the largest lakes across the United States. At each lake, we calculated how frequently bloom events occur. We then used these results to assess how often blue-green algae affects intake locations where drinking water is collected. We found that the frequency of bloom events varied greatly across intakes, with some intake locations rarely containing blue-green algae and others nearly always containing blue-green algae. Results from this research can help scientists and managers prioritize which lakes are most likely to be affected by blue-green algae which can allow for the effective distribution of resources to control and manage bloom events.

Description:

Satellite data has been found to be an effective way to quantify cyanobacterial harmful algal blooms (cyanoHAB). CyanoHABs are a significant environmental concern. High abundances of cyanoHABs in aquatic ecosystems can be detrimental to human health through exposure during recreational activities or the consumption of contaminated drinking water. CyanoHAB events may cause water treatment facilities to issue “Do Not Drink” orders and increase drinking water treatment costs. We analyzed the frequency of cyanoHAB occurrence across 2,370 National Hydrography Dataset (NHD) lakes within the continental United States (CONUS), excluding the Great Lakes, for the years 2008-2011 and 2017. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was used for 2008-2011 and the Copernicus Sentinel-3 Ocean and Land Colour Imager (OLCI) was used for 2017. Lakes containing at least three valid satellite pixels (300 m2) were included for analysis. CyanoHAB frequency was calculated for each year of data as the proportion of satellite weekly composites in which a satellite pixel indicated a detectable bloom (microsystis equivalent > 10,230 cells mL-1) out of all valid satellite weekly composites. We selected from all U.S. public water surface intakes (PWSI) locations those that intersected or were proximate to a valid lake. This resulted in evaluation of over 25% of all PWSI locations across CONUS. Our initial results suggest a wide range in the frequency of cyanobacterial blooms across the approximately 800 PWSI locations considered, ranging from intakes that virtually never experience a cyanobacterial bloom to intakes that are nearly consistently experiencing a cyanobacterial bloom. The frequency of cyanoHAB blooms at each individual intake remained relatively stable over time meaning that intakes with high bloom frequency for a given year tended to have high bloom frequency across all years. Quantitative insight into the frequency of cyanobacterial events at drinking water intakes in inland lakes can assist stakeholders in identifying sites with a history of high cyanoHAB occurrence. The locations can then be prioritized for effective distribution of resources to control and manage bloom events.

URLs/Downloads:

https://fallmeeting.agu.org/2018/   Exit EPA's Web Site

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:12/14/2018
Record Last Revised:01/31/2019
OMB Category:Other
Record ID: 343831