1. General Lecture 1. Modeling and Sustainability CE5504 Surface Water Quality Modeling

2. Sustainability In our every deliberation we must consider the impact of our decisions on the next seven generations. Iroquois Confederacy http://www.interspecies.com/pages/7th_gen.html http://www.bathtram.org/tfb/tE04.htm Meeting the needs of the present without compromising the ability of future generations to meet their own needs. World Commission on Environment and Development, 1987

3. …a mathematical model is an idealized formulation that represents the response of a physical system to external stimuli. Chapra 1997, p. 10 Modeling

4. Toward Sustainability 1) a knowledge of the way a system works. We might think of this as a research model. To provide a better understanding of the mechanisms and interactions that give rise to various types of water quality behavior, such understanding to be sharpened by the formulation and testing of hypotheses of the cause-effect relationships between residual inputs and resulting water quality. Decisions supporting a sustainable future require: Thomann and Mueller 1987)

5. Toward Sustainability 2) a manner of predicting cause and effect. We might think of this as a management model. To provide a more rational basis for making water quality control decisions, such a basis to include a defensible, credible, predictive framework, within the larger framework of cost-benefit analysis. Decisions supporting a sustainable future require: Thomann and Mueller 1987)

6. The Regulatory Basis for Water Quality Management Everybody lives downstream.

7. The Regulatory Basis for Water Quality Management Historically …

8. The Regulatory Basis for Water Quality Management The Clean Water Act Objective: restore and maintain the chemical, physical and biological integrity of the Nation’s waters. Goals: (1)elimination of the discharge of pollutants into navigable waters by 1985 (zero discharge) (2)achieving an interim water quality level that would protect fish, shellfish and wildlife while providing for recreation in and on the water wherever attainable (fishable, swimmable).

9. The Regulatory Basis for Water Quality Management The Clean Water Act Technology-Based Approach existing dischargers: best practicable control technologies new dischargers: best available control technologies (including ‘green’) indirect dischargers: pre-treatment standards POTWs: biological or 2° treatment; BOD/SS/coliform bacteria $60 billion in construction grants; $74 billion in lost interest loans

10. The Regulatory Basis for Water Quality Management The Clean Water Act Water Quality-Based Approach water quality standards (conventional and toxic pollutants) permits (National Pollutant Discharge Elimination System, NPDES)  penalties ($32,500 per day per violation) antidegradation (where WQ standards are attained)  protect existing uses  maintain high quality waters  protect outstanding waters Total Maximum Daily Loads (TMDLs, where WQ standards are not attained)

11. The Role of Modeling in Water Quality Management Implementing the Water Quality-Based Approach NPDES) TMDLs Antidegradation What provides guidance for the decision-making process?

12. The Role of Modeling in Water Quality Management A Water Quality Management Plan Identify beneficial use Set water quality standards Determine cause and effect Evaluate control options Consider economic conditions Consider stakeholder response

13. The Role of Modeling in Water Quality Management A Water Quality Management Plan Determine cause and effect

14. The Role of Modeling in Water Quality Management A Water Quality Management Plan Evaluate control options … avoiding Build and Measure

15. The Role of Modeling in Water Quality Management A Water Quality Management Plan Evaluate control options underdesign - …the environmental engineering equivalent of building a bridge that falls down. www.civil.columbia.edu/ce4210/bridgecollapse.html (Thomann and Mueller 1987, p. ix)

16. The Role of Modeling in Water Quality Management A Water Quality Management Plan Evaluate control options overdesign - …the environmental engineering equivalent of building a bridge to nowhere. http://www.zen39641.zen.co.uk/ps/ (Thomann and Mueller 1987, p. ix)

17. The Role of Modeling in Water Quality Management A Water Quality Management Plan Consider economic conditions

18. The Role of Modeling in Water Quality Management A Water Quality Management Plan Consider stakeholder response ohioej.org

19. The Role of Modeling in Water Quality Management A Water Quality Management Plan Identify beneficial use Set water quality standards Determine cause and effect Evaluate control options Consider economic conditions Consider stakeholder response models

20. The Water Quality Modeling Process

21. Problem Specification client objectives data coastal marshes beachfront recreation sites drinking water intake power plant water intake stormwater discharges tributaries (nonpoint runoff) WPCP outfall

22. The Water Quality Modeling Process Model Selection empirical mechanistic Secchi disk - chlorophyll

23. The Water Quality Modeling Process Model Selection empirical mechanistic Mass Balance

24. The Water Quality Modeling Process Model Selection off-the-shelf de novo

25. The Water Quality Modeling Process De novo theoretical development Segmentation

26. The Water Quality Modeling Process De novo theoretical development Resolution Spatiotemporal

27. The Water Quality Modeling Process De novo theoretical development Resolution Spatiotemporal

28. The Water Quality Modeling Process De novo theoretical development Resolution Kinetic

29. The Water Quality Modeling Process De novo theoretical development Resolution Kinetic

30. The Water Quality Modeling Process De novo theoretical development Complexity and Reliability Things should be made as simple as possible -- but no simpler. Albert Einstein image source: www.physik.uni-frankfurt.de/~jr/physpiceinstein.htmlwww.physik.uni-frankfurt.de/~jr/physpiceinstein.html

31. The Water Quality Modeling Process De novo theoretical development Complexity and Reliability unlimited cost cost cost +  $ desired reliability Model Complexity Model Reliability

32. The Water Quality Modeling Process De novo theoretical development Complexity and Reliability Model Complexity Screening  Management  Research

33. The Water Quality Modeling Process De novo theoretical development Numerical specification and testing identify state variables write equations of state (mass balances) numerical approach  analytical solution  numerical solution validation of numerical approach

34. The Water Quality Modeling Process De novo theoretical development Preliminary application data deficiencies theoretical gaps (missing sources/sinks) important parameters (monitoring, experiments sensitivity analysis

35. The Water Quality Modeling Process De novo theoretical development Calibration forcing conditions and physical parameters initial conditions boundary conditions loads environmental conditions kinetics calibration parameters

36. The Water Quality Modeling Process De novo theoretical development Calibration (continued) calibration Adjustment of kinetic coefficients within statistically defined bounds seeking the best fit of model to field data.

37. The Water Quality Modeling Process De novo theoretical development Calibration (continued) testing model performance

38. The Water Quality Modeling Process De novo theoretical development Confirmation and Robustness Evaluation of the performance of the model for a new set of forcing conditions and/or physical parameters with no further adjustment of model coefficients. The greater the number and diversity of confirming observations, the more probable it is that the conceptualization embodied in the model is not flawed,” Oreskes et al. 1994 as cited by Chapra 1997.

39. The Water Quality Modeling Process De novo theoretical development Management Applications test control options outfall length → ← treatment

40. The Water Quality Modeling Process De novo theoretical development Post Audit

41. Historical Development of Models 1925-1960 (Streeter-Phelps) Problems: untreated and primary effluent Pollutants: BOD Systems: streams and estuaries (1D) Kinetics: linear, feed forward Solutions: analytical

42. Historical Development of Models 1960-1970 (Computerization) Problems: primary and secondary effluent Pollutants: BOD Systems: streams and estuaries (1D/2D) Kinetics: linear, feed forward Solutions: analytical and numerical

43. Historical Development of Models 1970-1977 (Biology) Problems: eutrophication Pollutants: nutrients Systems: streams, lakes and estuaries (1D/2D/3D) Kinetics: nonlinear, feedback Solutions: numerical

44. Historical Development of Models 1977- 2000 (Toxics) Problems: toxics Pollutants: organics, metals Systems: sediment-water interactions food chain interations, streams, lakes and estuaries Kinetics: linear, feed forward Solutions: analytical

45. Historical Development of Models 2000 - 2010 (Ecosytems) Problems: ecosystem change, climate, invasives Pollutants: natural components – carbon, nutrients, organisms Systems: primary production, food web interactions Kinetics: nonlinear, feedback Solutions: numerical Benthic Invertebrates Phytoplankton Whitefish

46. Historical Development of Models 2010 – present (Linked Hydrodynamic – Water Quality)