2. Water Quality in Catchments and its Impact on Human and Ecological Health Kenneth H. Reckhow Duke University

3. Primary Theme: Improvements in basic scientific understanding and advances in predictive modeling are essential for effective water quality management. Secondary Theme: There exist a number of useful practical strategies in the areas of technology, economics, government institutions, and stakeholder involvement.

4. Ref: Peters and Meybeck

5. ISSUES Scientific understanding Abatement technologies Economic approaches Political institutions Predictive modeling Approach - use a case study to illustrate issues

7. Facts About the Neuse River 3rd Largest River Basin in NC (16,000 Km 2 ) 320 kilometers long, 5000 stream kilometers Estuary in lower 80 kilometers 1.5 million people in basin, mostly near headwaters

17. Low DO and Fish Kills: 94-96 Cherry Point Streets Ferry

18. TMDLs – The US Approach for Basinwide Water Quality Management Total Maximum Daily Load (TMDL) For water bodies that do not meet water quality standards, states will be required to develop a management plan and determine the allowable pollutant loading (the TMDL) necessary to achieve compliance with the standard.

22. Application of Water Quality Standards North Carolina Dissolved Oxygen Standard - “not less than average of 5.0 mg/l with a minimum instantaneous value of not less than 4.0 mg/l” How can this standard be effectively implemented when natural water quality is variable and predictions are uncertain?

23. 5 mg/l Probabilistic Water Quality Standards Actual Violations - based on a specified fraction of samples exceeding the numeric limit (5 mg/l) Predicted Violations - based on specified fraction of the posterior density function exceeding the numeric limit

24. As an alternative, we are developing a probability (Bayes) network model using a set of simple mechanistic expressions that are identifiable using available data. As necessary, this model is being extended to incorporate judgmental probability assessment for narrative endpoints characterizing consequences of particular concern to stakeholders (e.g., harmful algal blooms and Pfiesteria).

26. Example: A probability network for a subset of the relationships -- Nutrient Load Algal Growth Frequency of Mixing Events Sediment Oxygen Demand Fish Health Frequency of Hypoxia Water Temperature Frequency of Mixing Events Sediment Oxygen Demand Frequency of Hypoxia Water Temperature

27. RdRd RvRv C CuCu

28. 8 Years of bi-weekly measurements at multiple mid-channel locations Oxygen Concentration Water Temperature Salinity  Nonlinear regression parameter estimation R 2 =0.79 RSE=1.49 mg/l

29. 4 mg/l

30. Probability Predicted Number of Summer Days DO < 4 mg/l DO < 2 mg/l mean = 46.8 days mean = 23.8 days Days s = 4.7 days s = 4.2 days

31. Nutrient Load Algal Growth Fish Health Frequency of Mixing Events Sediment Oxygen Demand Frequency of Hypoxia Water Temperature Water Clarity Nutrient Recycling Pfiesteria Presence Human Health

32. Some Useful Practical Lessons: Low cost technologies (stream buffers) Economic strategies (pollutant trading) Political institutions (watershed associations) Citizen involvement Scientific Needs: Improved process understanding at the basin scale Better approaches to uncertainty in predictive modeling and WQ standards