Deep waters of Lake Erie’s central basin have areas of low dissolved oxygen. Weather conditions can determine if this low oxygen (hypoxic) water will be taken up by treatment plants, which require different methods for treating low and higher oxygen water. Incorrect treatment results in poor drinking water and damages treatment systems. Our model will predict the water’s oxygen content so treatment plants can operate accordingly, maintain good water quality, and prevent equipment damage.
Why We Care
In Lake Erie, it is common for strong water quality differences to exist between surface and bottom water during the summer. Weather-driven dynamics during this time can cause water intakes to be alternately exposed to surface or bottom water, requiring public water systems to adapt treatment processes to changing water quality. Surface water has higher pH, and may have high concentrations of phytoplankton, dissolved organic matter, and algal toxins. In contrast, bottom water is usually hypoxic (low dissolved oxygen), with a low pH and elevated iron and manganese concentrations, requiring more expensive treatment. Improper treatment of lake water can cause corrosion in a plant’s pipe system and result in drinking water with poor taste, bad odor, and discoloration that can stain plumbing fixtures and laundry.
What We Are Doing
This project is developing an operational dissolved oxygen forecast model for Lake Erie, coupled to an existing real-time, fine-scale hydrodynamic model. The forecast will give public water systems advance warning of lake circulation events that are likely to cause changes in raw water quality. This coupled system will allow drinking water managers to prepare when conditions that promote hypoxic water movement into the vicinity of water intakes occur. The proposed models will be an extension of the existing, next-generation Lake Erie Operational Forecasting System that will become operational at NOAA’s National Ocean Service Center for Operational Oceanographic Products and Services in 2016. The first new model will be physically based, requiring the addition of a dissolved oxygen (DO) component to the existing hydrodynamic model. The model will provide an experimental real-time, forecast product in the second year of the project, and be skill-assessed to begin transition to operational status near the end of the five-year project. The second new model will require addition of the chemical and biological drivers of hypoxia (nutrients, phytoplankton) to the physical DO model. Additionally, the development of the biophysical model in tandem with the physical model will offer an opportunity to address a current, pressing management question and a broader philosophical question regarding model complexity.
NOAA Great Lakes Environmental Research Laboratory, U. S. Geological Survey, , Cooperative Institute for Limnology and Ecosystems Research, City of Cleveland Division of Water, Purdue University
Benefits of our Work
Once the forecast developed through this work is completed, it will give public water systems advance warning of lake circulation events that are likely to cause changes in raw water quality. This coupled system will allow drinking water managers to prepare for when conditions that promote hypoxic water movement into the vicinity of water intakes occur.
The models resulting from this project will be incorporated into the Lake Erie Operational Forecast System. The updated Finite Volume Community Ocean Model will also improve our ability to forecast harmful algal blooms in Lake Erie.