Evaluating Options to Reduce Lake Erie HABs with Watershed Models, Stakeholders and Surveys

Session: 41b. - Great Lakes Harmful Algal Blooms Research from Watershed Influence to Ecosystem Effects

Jay Martin, The Ohio State University-FABE, [email protected]
Margaret Kalcic, Ohio State University, [email protected]
Robyn Wilson, Ohio State University, [email protected]
Noel Aloysius, University of Missouri, [email protected]
Chelsie Boles, Limnotech, [email protected]
Todd Redder, LimnoTech, [email protected]
Rebecca Muenich, Arizona State University, [email protected]
Awoke Dagnew, University of Michigan, [email protected]
Colleen Long, University of Michigan, [email protected]
Yu-Chen Wang, University of Michigan, [email protected]
Remegio Confesor, Heidelberg College, NCWQR, [email protected]
Richard Becker, University of Toledo, [email protected]
Jeffrey Kast, The Ohio State University, [email protected]
Anna Apostel, The Ohio State University, FABE, [email protected]
Haley Kujawa, Ohio State University, [email protected]

Abstract

In early 2016, the United States and Canada formally agreed to reduce phosphorus inputs to Lake Erie by 40% to reduce the severity of annual Harmful Algal Blooms (HABs). These blooms have become more severe, with record events occurring in 2011 and 2015, and have compromised public safety, shut down drinking water supplies, and negatively impacted the economy of the western Lake Erie basin. Now, a key question is what management options should be pursued to reach the 40% reduction. This presentation will highlight interdisciplinary research to compare the amount and types of practices needed for this reduction to the current and projected levels of adoption. Multiple models of the Maumee watershed identified management plans and adoption rates needed to reach the reduction targets. For example, one scenario that reached the reduction targets included adoption rates of 50% for subsurface application of fertilizer on row crops, 58% for cover crops, and 78% for buffer strips. However, stakeholder input indicated these adoption levels were not all feasible. This information was then used to guide another round of watershed modeling analysis to evaluate scenarios that represented more realistic scenarios based on more feasible levels of management adoption.

1. Keyword
watersheds

2. Keyword
eutrophication

3. Keyword
management