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

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General Lecture 1. Modeling and Sustainability

CE5504 Surface Water Quality Modeling

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.htmlhttp://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

…a mathematical model is an idealized formulation that represents the response of a physical system to external stimuli.

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Chapra 1997, p. 10

Modeling

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)

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)

The Regulatory Basis for Water Quality Management

Everybody lives downstream.


Historically …


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).


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


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)

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?


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




… avoiding Build and Measure




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)




overdesign -

…the environmental engineering equivalent of building a bridge to nowhere.

http://www.zen39641.zen.co.uk/ps/

(Thomann and Mueller 1987, p. ix)




ohioej.org



• Identify beneficial use

• Set water quality standards





models

The Water Quality Modeling Process


Problem Specification

• client objectives

• data

• coastal marshes• beachfront recreation sites• drinking water intake • power plant water intake

• stormwater discharges• tributaries (nonpoint runoff)• WPCP outfall


Model Selection

• empirical

• mechanisticSecchi disk - chlorophyll


Model Selection

• empirical

• mechanisticMass Balance

in out reactiondm

m m mdt


Model Selection

• off-the-shelf

• de novo


De novo theoretical development

Segmentation



Resolution

Spatiotemporal



Resolution

Kinetic

TotalPhosphorus

AvailableParticulate

Phosphorus

RefractoryParticulate

Phosphorus

DissolvedOrganic

Phosphorus

SolubleReactive

Phosphorus



Resolution

Kinetic



Complexity and Reliability

Things should be made as simpleas possible -- but no simpler.

Albert Einstein

image source: www.physik.uni-frankfurt.de/~jr/physpiceinstein.html




unlimited cost

cost

cost + $

desired reliability

Model Complexity

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Model Complexity

Screening Management Research



Numerical specification and testing

• identify state variables• write equations of state (mass balances)• numerical approach

analytical solution numerical solution

•validation of numerical approach



Preliminary application

• data deficiencies• theoretical gaps (missing sources/sinks)• important parameters (monitoring, experiments• sensitivity analysis



Calibration

• forcing conditions and physical parameters• initial conditions• boundary conditions• loads• environmental conditions• kinetics• calibration parameters



Calibration (continued)• calibration

Adjustment of kinetic coefficients within statistically defined

bounds seeking the best fit of model to field data.



Calibration (continued)

• testing model performance

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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.



Management Applications

• test control options

shoreline

outfall length

outfall length →

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Post Audit

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


1960-1970 (Computerization)

• Problems: primary and secondary effluent• Pollutants: BOD• Systems: streams and estuaries (1D/2D)• Kinetics: linear, feed forward• Solutions: analytical and numerical


1970-1977 (Biology)• Problems: eutrophication• Pollutants: nutrients• Systems: streams, lakes and estuaries

(1D/2D/3D)• Kinetics: nonlinear, feedback• Solutions: numerical


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


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


2010 – present (Linked Hydrodynamic – Water Quality)

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

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