Groundwater Optimization Handbook

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Groundwater Optimization Handbook: Flow, Contaminant Transport, and Conjunctive Management

Groundwater Optimization Handbook: Flow, Contaminant Transport, and Conjunctive Management

Published:

April 26, 2012 by CRC Press - 532 Pages

Author(s):

Richard C. Peralta, Utah State University, Logan, USA

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$129.95

ISBN 9781439838068

Cat# K11724

eBook

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ISBN 9781439838075

Cat# KE11746

Features

Presents a thorough introduction to groundwater systems analysis and optimization terminology, principles, and techniques
Identifies which S-O approaches are appropriate for different types of groundwater quantity (hydraulic optimization) and quality (contaminant transport optimization) problems, whether they be deterministic, stochastic, single-objective, or multiobjective in nature
Teaches you how to build your own S-O model or how to choose from available transferrable S-O models
Offers guidance and flowcharts for simplifying and solving real-world optimization problems
Uses a systems analysis approach to emphasize clear goals, inputs, stimuli, processes, responses, and outputs
Teaches you how to develop and adapt optimal management strategies, for implementation or use as metrics (such as for performance-based contracting)
Reinforces learning with numerous flowcharts, examples, illustrations, case studies, and a glossary
Supplies ancillary material online, including spreadsheets performing as S-O models, PowerPoint slides, reference materials, numerical simulation programming instructions, and a simulator

Summary

Existing and impending water shortages argue for improving water quantity and quality management. Groundwater Optimization Handbook: Flow, Contaminant Transport, and Conjunctive Management helps you formulate and solve groundwater optimization problems to ensure sustainable supplies of adequate quality and quantity. It shows you how to more effectively use simulation-optimization (S-O) modeling, an economically valuable groundwater management tool that couples simulation models with mathematical optimization techniques.

Written for readers of varying familiarity with groundwater hydrology and mathematical optimization, the handbook approaches complex problems realistically. Its techniques have been applied in many legal settings, with produced strategies providing up to 57% improvement over those developed without S-O modeling. These techniques supply constructible designs, planning and management strategies, and metrics for performance-based contracts.

Learn how to:

Recognize opportunities for applying S-O models
Lead client, agency, and consultant personnel through the strategy design and adaptation process
Formulate common situations as clear deterministic/stochastic and single/multiobjective mathematical optimization problems
Distinguish between problem nonlinearities resulting from physical system characteristics versus management goals
Create an S-O model appropriate for your specific needs or select an existing transferrable model
Develop acceptable feasible solutions and compute optimal solutions
Quantify tradeoffs between multiple objectives
Evaluate and adapt a selected optimal strategy, or use it as a metric for comparison

Drawing on the author’s numerous real-world designs and more than 30 years of research, consulting, and teaching experience, this practical handbook supplies design procedures, detailed flowcharts, solved problems, lessons learned, and diverse applications. It guides you through the maze of multiple objectives, constraints, and uncertainty to calculate the best strategies for managing flow, contamination, and conjunctive use of groundwater and surface water.

Ancillary materials are available from the Downloads tab on the book page at www.crcpress.com.

PART I Introduction to S-O Concepts

Essence of Optimizing Groundwater Management
Book Goals
The Need for and Benefits of Optimization
Considerations When Using Optimization
Groundwater Systems Analysis Perspective and Tools
Specific Reader Goals

Introduction to Mathematical Optimization for Groundwater Strategy Design
Simulation (S) and S-O Modeling and Basic Optimization Terminology
Simple Optimization Problem
Manual Simplex Solution

PART II Optimization Theory

Optimization Problem Types and Categories
Introduction
Common Optimization Problem Types (LP, QP, IP, MIP, NLP, MINLP)
Linearity and Nonlinearity in S-O Modeling
Single-Objective and Multiobjective Optimization
Deterministic and Stochastic Optimization
Optimization of Multiple Physical Processes
Variable, Constraint, and Objective Function Flexibility

Deterministic Optimization
Introduction
Solution Space Geometry
Overview of Optimizer Type Options
Classical Optimization Types
Non-Classical Optimization Types
Simplifying Optimization Techniques

Optimization with Uncertainty
Introduction
Addressing Uncertainty
Stochastic Modeling Tools
Robustness Optimization

Multiobjective Optimization Approaches
Introduction
Multiobjective Optimization
Illustrative Multiobjective LP and QP Problems

PART III Exact and Approximation Simulator Theory

Embedded Numerical and Analytical Equations
Introduction and Terminology
Embedded Numerical Equation
Embedded Analytical Equation
Embedded Discretized Numerical Model

Response Matrix Simulators
Introduction
Discretized Convolution Integrals (Response Matrix or Approximator)
Example: Predicting Head Changes Resulting from Assumed Transient Pumping Strategy
Influence Coefficient Development Process
Influence Coefficient Computation

Approximation and Other Simulators
Introduction
Statistical Regression Equations and Power Functions
Artificial Neural Networks
Basic Economic and Fiscal Simulators

PART IV S-O Processes and Guidance

Formulating Optimization Problems and Selecting S-O Tools
Introduction
Identify the S-O Model Purpose
State the Optimization Problem Conceptually and Refine It
Prepare Preliminary Optimization Problem Formulation(s), without Selecting S-O Approach
Clarify Linearity-Nonlinearity of Physical System and Management Problem
Select an S-O Approach
Select S-O Modeling Tool and Obtain or Develop S-O Model and Postprocessor

Preparing Data Input and Implementing S-O Tool
General Concepts
Flow Optimization Illustration
Transport Optimization Illustrations
Select Candidate Stimuli Locations
Prepare Initial Feasible Solution (Strategy) and Optimization Parameters as Input Data
Run S-O Model
Analyze Results and Sensitivity
Report Results
Implement Strategy and Monitor System

Groundwater and Conjunctive Management S-O Application Guidance
Introduction
Water Supply and Flow Hydraulic Management for Nonlinear River-Aquifer System (with Multiobjective)
Flow Optimization: Limiting Surface Water Depletion in Dynamic Stream-Aquifer System
Flow Optimization: Conjunctive Management of Dynamic Stream-Aquifer System
Containment Optimization: Plume Management via Hydraulic Optimization
Optimal Site Dewatering System Design

Groundwater Contamination and Transport Management S-O Application Guidance
Overview
Background Situation and Optimization Needs
S-O Approach Selection
Initial Screening Runs
Optimization Scenarios Overview
Solving MINLP Minimizing Residual Mass Optimization Problem Using GA-TS
Illustrating the Effect of Minimizing Total Pumping on Maximum Concentration and Residual Mass
The Effect of Minimizing Cost on the Optimal Result
Contrasting Minimizing Mass Remaining, Pumping, and Cost
Solving MINLP Minimizing Residual Mass Optimization Problem Using ANN-GA
Closure

PART V Applications

Hydraulic S-O Modeling Applications
Introduction
Arkansas Grand Prairie and Northeastern Arkansas—Sustainable Conjunctive Use
Cache Valley, Utah—Safe Yield Practice While Protecting Surface Water Resources
Norton Air Force Base, Southwest Boundary TCE Plume—Hydraulic Plume Containment (California)

Contaminant Transport S-O Modeling Applications
Introduction
Massachusetts Military Reservation, Chemical Spill 10 Plume (Massachusetts)
Blaine Naval Ammunition Depot Multiple Plume Management (Nebraska)
Optimal Robust Pumping Strategy Design for Umatilla Chemical Depot (Oregon)
Multiple Realization Pump and Treat System Optimization (California)

Closure

Glossary

Index

Each chapter includes a bibliography.

Author Bio(s)

Richard Peralta, PhD, PE, has used S-O modeling to design strategies for more than 20 sites or real-world projects. As a Utah Cooperative Extension Service water quality coordinator, he optimized nonpoint and point source contamination management, and collaborated with state and federal agencies in technology transfer and public education. Through the University of Arkansas, and subsequently Utah State University, private work, and the U.S. Air Force Reserve, he worked in 25 U.S. states and in numerous countries. For the military, he participated in and led many environmental contamination remediation evaluation teams and helped provide optimal solutions that were successfully implemented in the field. After several years of advising on environmental matters in the Pentagon, Colonel Peralta retired from the U.S. Air Force Reserve as a chief bioenvironmental engineer. He is a professor in the Civil and Environmental Engineering Department at Utah State University, consults privately, and is the distributor of SOMOS software. For more information, see Dr. Peralta’s page at the College of Engineering at Utah State University.

Contributing author Ineke M. Kalwij, PhD, PEng, collaborates with Dr. Peralta, working on groundwater optimization software development and publications. She also provides consulting services to clients, primarily in the area of groundwater system management. For more information, see Kalwij Water Dynamics Inc.

Editorial Reviews

"In my experience, most text books only cover the theory behind a topic and go into great detail on the research and derivation of various methodologies. However, practitioners in the field also need to know how the theoretical underpinnings of the science get applied in the real world. Few books actually accomplish this and thus are not really all that useful to those of us who "get our hands dirty". Dr. Peralta's book covers both aspects quite well. The theory behind various optimization techniques is presented along with how these theories and methods are used to solve real problems. The examples in the book are not just small synthetic problems that bear no resemblance to reality. They illustrate the solution to large-scale, real optimization"
—James Rumbaugh, Environmental Simulations, Inc., Reinholds, Pennsylvania, USA

"The book provides a good summary of the fundamental optimization techniques from the classical approaches to the current state-of-the-art methods, but provides excellent guidance on the appropriate application to ground water problems. The book illustrates most of the important concepts with simple theoretical examples and/of real-world applications of the techniques. The efficient application of these techniques requires experience and perhaps intuition, and Dr. Peralta has tried his best to convey some of the insights from his extensive portfolio of successful optimization projects to the reader. The strength of the book really lies beyond the early chapters covering the basics of optimization; it is in the discussion of these actual applications."
—David J. Becker, University of Nebraska at Omaha