Water resources systems management tools

MCGRAW-HILL PROFESSIONAL ENGINEERING

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Water

Resources

Systems

Management

Tools Thu VIen DHKTCN-TO

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✓ Optimal control methods

✓ Risk methods

Larry W. Mays

WATER RESOURCES

SYSTEM S M ANAGEM ENT

TOOLS

WATER RESOURCES

SYSTEMS MANAGEMENT

TOOLS

Larry W. Mays, Ph.D., P.E., P.H.

Editor-in-Chief

Department o f Civil a n d Environm ental Engineering

Arizona State University

Tempe. Arizona

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CONTENTS

Contributors

Preface ix

Chapter 1. S ystem s Analysis Larry W. Mays and Yeou-Koung Tung

1.1 Systems Concept / 1.1

1.2 Linear Programming (LP) / 1.3

1.3 Nonlinear Programming (NLP) / ¡.8

1.4 Dynamic Programming (DP) / 1.15

1.5 Optimal Control / 1.23

1.6 Interfacing Optimizers with Process Simulators / 1.26

1.7 Multiobjective Programming / 1.27

1.8 Global Optimization Techniques / 1.32

1.9 Selected Applications in Water Resources / 1.37

References / /.42

C hapter 2. Uncertainty and Reliability Analysis Yeou-Koung Tung

2.1 Introduction / 2./

2.2 Review of Pertinent Probability and Statistical Theories / 2.3

2.3 Methods for Uncertainty Analysis / 2.7i

2.4 Load Resistance Interference Reliability Analysis / 2.2i

2.5 Reliability Analysis: Time-to-Failure Analysis / 2.35

2.6 Monte Carlo Simulation / 2.i«

2.7 System Reliability / 2.4i

2.8 Risk-Based Design of Water Resources Systems / 2.50

References / 2.57

C hapter 3. Regional W ater S up ply Planning and Capacity Expansion M odels

Messele Z. Ejeta and Larry W. Mays

3.1 Introduction / 3.1

3.2 Model Formulations / 3.2

3.3 Applications to the Rio Grande Project and the City of El Paso Water Supply / 3.10

3.4 Model Results / 3.2«

References / 3.34

C hapter 4. River-Reservoir System Operation for Sedim ent C ontrol

John W. Nicklow

4.1 Problem Statement / 4./

4.2 Problem Formulation / 4.2

4.3 Solution Techniques / 4.5

4.4 Example Applications / 4.8

Appendix 4.A: SALQR Algorithm / 4.13

Appendix 4.B: Genetic Algorithm / 4.17

References / 4.18

C hapter 5. W ater Distribution S yste m O peration: A pplication of

Sim ulated Annealing Fred E. Goldman and Larry W. Mays _________ ^

5.1 Introduction / 5.1

5.2 General Problem Statement / 5.2

5.3 Solution Methodology / 5.3

5.4 Development of Software / 5.7

5.5 Applications / 5.8

5.6 Summary and Conclusions / 5.14

References / 5.15

Chapter 6. O p tim a l Feedback C on trol of Irrigation W ater D elivery S ystem s

R T. Wahlin 6.1

6.1 Introduction / 6.1

6.2 Irrigation Water Delivery Systems / 6.2

6.3 Control of Irrigation Water Delivery Systems / 6.3

6.4 Basic Control Definitions / 6.8

6.5 TVpes of Automatic Control / 6.10

6.6 Integrator-Delay Model (Process Model) / 6.13

6.7 Fundamentals of Automatic Control Systems / 6.17

6.8 Optimal Feedback Control Of Irrigation Water Delivery Systems / 6.24

6.9 Overall Control Schemes for Irrigation Water Delivery Systems / 6.35

References / 6.36

Chapter 7. O p tim a l Location of Isolation Valves in W ater D istribution System s:

A Reliability/Optim ization A pproach Sukru Ozger and Larry W. Mays 7.1

7.1 Introduction / 7.1

7.2 Demand-Driven Analysis versus Pressure-Driven Analysis / 7.3

7.3 Semi-Pressure-Driven Analysis (SPDA) Framework / 7.8

l A ReliabiHty Models / 7.11

7.5 Optimization Model / 7.15

7.6 Example Application of Reliability/Optimization Model / 7.22

References / 7.25

Chapter 8. G ro un dw ate r R em ediation Design U sing Sim ulated A nnealing

Richard L. Skaggs and Larry W. Mays 8.1

8.1 Introduction / 8.1

8.2 Enhanced Annealing / 8.3

8.3 Annealing with Directional Search / 8.6

8.4 Annealing with Memory / 8.8

8.5 Memory Components / 8.1/

8.6 Overall Enhanced Annealing Algorithm / 8.12

8.7 Application of Algorithm: N-Springs Site Description / 8.12

8.8 Summary and Conclusions / 8.22

References / 8.23

Index 1.1

CONTRIBUTORS

M essele Z . E je ta California Department o f Water Resources, Sacramento, California (C h a r 3)

F re d E . G o ld m an Kennedy/Jenks Consultants, Phoenix, Arizona (Chap. 5)

L a rry W. M ay s Department O f Civil A n d Environmental Engineering, A rizona State University,

Tempe. Arizona (Chaps. 1, 3, 5, 7, 8)

Jo h n W, N icklow Southern Illinois University. Carbondale. Illinois (Chap. 4)

S u k ru O zg er Carollo Engineers, Phoenix, Arizona (Chap. 7)

R ic h a rd L . S kaggs Pacific Northwest National Laboratory, Richland. Washington (Chap. 8)

Y eou-K oung 'n in g Department o f Civil Engineering, Hong Kong University o f Science and Tech￾nology, Kowloon. Hong Kong (Chaps. 1, 2)

B. T. W ahlin W EST Consultants, Inc., Tempe, A rizona (Chap. 6 )

vil

PREFACE

This book is the third book in a series o f books dealing with management tools for water. The titles of

the first two books in this series are Urban Water Supply M anagement Tools and Urban Stormwater

M anagement Tools, both published by M cGraw-Hill in 2004. This third book, first and foremost, is

intended to be a reference book for those wishing to expand their knowledge o f state-of-the-art tech￾niques for the management o f various types o f water resources systems. This book focuses upon the

use o f optimization techniques, in many cases interfaced with simulation models, to operate water sys￾tems such as river-reservoir systems, water distribution systems, and irrigation canals. Also this book

looks at the use o f optimization techniques for remediation design o f groundwater systems and the

operation and capacity expansion o f regional water supply systems. A second major focus is the use

o f uncertainty and reliability analysis for the analysis o f water resources systems. This book will be of

value to engineers, managers, operators, and analysts involved with the various aspects o f analysis and

operation o f various water resource systems. Another use o f this book will be as a text for graduate level

courses in water resource systems analysis.

Preparation o f this book has been a special treat for me because all o f the authors (Drs. M essele Z.

Ejeta, Fred Goldman, John Nicklow, Sukru Ozger, Richard Skaggs, Y.K. Tung, and Brian W halin) are

form er Ph.D. students and close firiends o f mine. Each o f these chapter authors has become a leading

expert in the field o f water resource systems. The authors were chosen, not only because they are for￾m er students o f mine, but because o f their proven knowledge in die specific area o f their contribution.

Chapters I and 2 are updated versions, respectively, o f Chapters 6 and 7 o f the Water Resources

Handbook, published in 1996 by M cGraw-Hill, for which I was also the Editor-in-Chief.

One o f the quotes that I used in the Water Resources Handbook was by C hief Seattle, chief o f the

Suquam ish tribe, who lived across Puget Sound from the site o f the city that later arose in Seattle’s

nam e, “M an did not weave the web o f life, he is m erely a strand in it. W iatever he does, to the web,

he does to himself.” Humans have obviously done some fairly m ajor changes to affect this web that

w ill have serious consequences for the future. Am ong these changes on Earth are those that affect

our water resources and environment. Humans have created some very interesting and challenging

water resource problems that will challenge us for m any decades and centuries into the future. These

include the challenges that we face from global climate change, the challenges that we face for sus￾tainability, the challenges related to w ater supply system s security from terrorist activity, ju st to name

a few. Hopefully the types o f methodologies discussed in this book will at least fulfill some small

advancem ent in the solution o f our future water resources challenges.

During the past 28 years o f my academic career as a professor, I have received help and encour￾agement from so many people that it is not possible to name them all. These people represent a wide

range o f universities, research institutions, government agencies, and professions around the world.

To all o f you I express my deepest and sincerest thanks.

Each book that I have developed has been a part o f m y lifelong journey in w ater resources and

this book certainly is no exception. I have gained m ore from my experiences in developing books

than can ever be m easured in words. To develop a book such as this one, with all the authors being

form er Ph.D. students has been a very special experience. All o f these authors, I consider a part of

my extended family, which includes all o f my form er Ph.D. students. They have represented a very

valuable part o f my life.

I m ust acknowledge my three children, Travis, Elyssa. and Tyler for their love and willingness to

enjoy the water-related sports with m e, especially at our second home in Pagosa Springs. Colorado.

Probably they will never read any part o f this book, but they do represent the m ost valuable part of

my life.

This book has been a part o f m y personal journey in life to learn as much as possible about walCT

and to use this knowledge in my teaching, research, and writing. I hope that you will be able to use this

book in your own journey o f learning about water. As I continue my efforts in the study and photogra￾phy o f ancient water structures, especially those built by the Romans, I am placing many o f my photo￾graphs on my web site (www.public.asu.edu/~lwmays/). Take a look, these m ay be o f interest to some

o f you readers.

I dedicate this book to humanity and hum an welfare.

L a r ry W. M ays

Scottsdale, A rizona

Pagosa Springs, Colorado

WATER RESOURCES

SYSTEM S M ANAGEM ENT

TOOLS

CHAPTER 1

SYSTEMS ANALYSIS

Larry W. Mays

D epartm ent o f Civil and Environmental Engineering

Arizona State University

Tempe, Arizona

Yeou-Koung Tung

Department o f Civil Engineering

H ong Kong University o f Science <6 Technology

Kowloon, Hong Kong

1.1 SYSTEMS CONCEPT

1.1.1 W h a t Is O ptim ization?

The m ajor types o f water resources problem s that m ust be solved for various hydrosystem s include

(Buras, 1972):

1. D eterm ination o f the optimal scale o f project development

2. D eterm ination o f the optimal dim ensions o f system components

3. D eterm ination o f the optimal operation o f the system

W ater resource problem s deal with both design and analysis. Analysis is concerned with deter￾m ining the behavior o f an existing system or a trial system that is being designed. In many cases,

study o f the system behavior is to determine operation o f the system o r the response o f a system

under specified inputs. The design problem is to determine the sizes o f system components. As an

example, the design o f a reservoir system determines the size and location o f reservoirs. Analysis of

a reservoir system is the process o f determining operation policies for the reservoir system. In other

words, a design is form ulated and followed by an analysis to see if it performs according to specifi￾cations. If a design satisfies the specifications, then an acceptable design is found. New designs can

be form ulated and then analyzed.

Conventional procedures for design and analysis are iterative. The effectiveness o f conventional

procedures is dependent upon an engineer’s intuition, experience, skill, and knowledge o f the

hydrosystem under investigation. Therefore, conventional procedures are highly related to the human

elem ent which could lead to inefficient design and analysis o f complex systems. Conventional pro￾cedures are typically based on sim ulation models in a trial and error process. Som etimes a sim ula￾tion model is applied iteratively in an attempt to arrive at an optimal solution.

Optimization procedures elim inate the trial and error process o f changing a design and resimu￾lating with each new design change. Instead, an optim ization model autom atically searches for the

optim um design param eters. An optim ization procedure has m athematical expressions that describe

the system and its response to the system inputs for various design param eters. These mathematical

expressions include constraints to define the limits o f the design variables, and objective functions

for evaluating system performance.

An advantage o f the conventional process is that the engineer’s experience and intuition are used

in m aking changes in the system or to make additional specifications. But the conventional proce￾dure can lead to nonoptimal, or uneconomical, designs and operation policies. Also, the convention￾al procedure can be very time consum ing and labor intensive. An optimization procedure requires