1st Edition

Groundwater Optimization Handbook Flow, Contaminant Transport, and Conjunctive Management

By Richard C. Peralta Copyright 2012
    532 Pages 16 Color & 202 B/W Illustrations
    by CRC Press

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

    Optimization with Uncertainty
    Addressing Uncertainty
    Stochastic Modeling Tools
    Robustness Optimization

    Multiobjective Optimization Approaches
    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
    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
    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
    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
    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
    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

    PART V Applications

    Hydraulic S-O Modeling Applications
    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
    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)




    Each chapter includes a bibliography.


    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.

    "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