Science Inventory

Autonomous glider-based observations for understanding Lake Erie hypoxia

Citation:

McKinney, P., T. Hollenhorst, B. Alsip, S. Miller, AND J. Hoffman. Autonomous glider-based observations for understanding Lake Erie hypoxia. International Association of Great Lakes Research (IAGLR) Virtual Conference, Duluth, MN, May 17 - 21, 2021. https://doi.org/10.23645/epacomptox.14754321

Impact/Purpose:

Low dissolved oxygen levels pose an increasing risk to water quality in both freshwater and coastal areas and threaten fisheries and drinking water supplies. Our understanding of basic features of hypoxia zones, including their spatial extent, poses a challenge because detecting and monitoring dissolved oxygen levels over regional scales typically depends on models that are informed by sparse point observations. To help fill this gap, USEPA, as part of the 2019 Lake Erie CSMI, conducted a three-week autonomous glider deployment in Lake Erie’s central basin to monitor and characterize the hypoxia layer over a broad area (100’s of km2).

Description:

In the Great Lakes, detecting and monitoring dissolved oxygen levels over regional scales typically depends on models that are informed by sparse point observations. As part of the 2019 Lake Erie CSMI, USEPA deployed an autonomous glider in the lake’s central basin to monitor and characterize the hypoxia layer over a broad area (100’s of km2). In addition to its dissolved oxygen sensor, the glider was outfitted with a CTD and optical sensors for measuring chlorophyll, CDOM and optical backscatter. We present observations of the thickness of the hypoxia layer and associated parameters gained over the three-week glider deployment and discuss the challenges and pitfalls encountered as well as opportunities for incorporating glider-based observations of hypoxia and other dynamic properties into water quality models.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:05/21/2021
Record Last Revised:06/09/2021
OMB Category:Other
Record ID: 351900