The Great Lakes’ 10,000-plus miles of coastline provide millions of beachgoers with recreational opportunities, support 158 coastal counties, and serve as an economic engine for the region. Unfortunately, this coastline, including its beaches, watersheds, and nearshore waters, is highly vulnerable to pollution. Excessive nutrient loading, agricultural and stormwater runoff, industrial pollution, and wildlife waste all degrade water quality. Bacteria and other pathogens can threaten both human health and the integrity of the Great Lakes ecosystem. For this reason, the GLRI Action Plan IV has identified nonpoint source pollution, and nearshore health and protection of watersheds from polluted runoff as one of five issues requiring urgent attention.
Read on to learn about NOAA’s work in this Focus Area:
Decision Support Tools for Nutrients and Harmful Algal Blooms (HABs)
GLRI funds have helped NOAA to monitor phosphorus loading and develop models that forecast the locations of HABs, in turn giving resource managers the tools to make more timely actions to protect human health. This includes the HAB Data Explorer.
Contact: Reagan.Errera@noaa.gov
Developing a Great Lakes Quagga Mussel Bioenergetic and Nutrient Cycling Model to Predict Responses of Harmful and Nuisance Algae to Tributary Nutrient Inputs
Development of the Great Lakes quagga mussel DEB bioenergetic model will: 1) improve effectiveness of nonpoint source nutrient control and refine management efforts, and 2) address a cross-focus area science priority by enabling biophysical models used to support nutrient management decisions to better predict impacts of quagga mussels on promoting HABs through selective feeding, nuisance algae (e.g., Cladophora) through enhancing water clarity, HABs and nuisance algae through nutrient excretion, and controlling phytoplankton abundance and productivity.
Contact: Ashley.Elgin@noaa.gov
Enhancements to Decision Support Tools to Link Nutrient Reductions to Harmful Algal Blooms and Source Water Protection
The scope of proposed work includes monitoring, experiments, satellite remote sensing and modeling and forecasting -- all aimed at enhancing current work under ‘Decision support tools to link nutrient reductions of HABs and source water’ projects.
Contact: Reagan.Errera@noaa.gov
Leveraging new satellite assets to improve remote sensing and modeling tools for monitoring and prediction of nearshore water quality in the Great Lakes
This project will extend the Color Producing Agent Algorithm (CPA-A) to nearshore regions using new satellite technology. These new nearshore remote sensing and modeling tools generate a suite of unique products that can be used to plan and assess upstream management efforts made to improve nearshore water quality, as outlined in Annex 4 of the Great Lakes Water Quality Agreement.
Contact: Mark.Rowe@noaa.gov
Model Development for Great Lakes Nutrient Adaptive Management
This project will develop and assess models that relate lake ecosystem objectives to nutrient concentrations and loading from the watershed, which may be used for decision support in implementation of the Great Lakes Water Quality Agreement.
Contact: Mark.Rowe@noaa.gov
Saginaw Ecosystem and Algal DYNamics (SEA-DYN): Saginaw Bay Nutrients and Algae Monitoring and Assessment
This project aims to assess Saginaw Bay’s nutrient dynamics and ecosystem ecology during ice-free periods, and to provide the empirical basis to develop models that will inform management scenarios.
Contact: Reagan.Errera@noaa.gov
Tracking HABs With Time-series Observations in the Muskegon River Estuary
The significance of this project lies in harnessing the power of high-frequency, time-series observatory data to describe the patterns of processes occurring in Muskegon Lake. Findings from Muskegon Lake may potentially be used to better understand and address issues in Green Bay, Saginaw Bay and Lake Erie, which suffers similar anthropogenic impacts.
Contact: Steve.Ruberg@noaa.gov