Peralta | Groundwater Optimization Handbook | E-Book | www.sack.de
E-Book

E-Book, Englisch, 532 Seiten

Peralta Groundwater Optimization Handbook

Flow, Contaminant Transport, and Conjunctive Management
1. Auflage 2012
ISBN: 978-1-4398-3807-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

Flow, Contaminant Transport, and Conjunctive Management

E-Book, Englisch, 532 Seiten

ISBN: 978-1-4398-3807-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)



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.

Peralta Groundwater Optimization Handbook jetzt bestellen!

Zielgruppe


Hydrologists; hydrogeologists; irrigation, agronomic, conservation, environmental, and natural resources scientists; civil, agricultural, irrigation, environmental, geotechnical, and systems engineers; natural resources and environmental regulators and decision makers; and companies designing, building, or owning well systems for water supply, dewatering, drainage, environmental protection, and remediation.


Autoren/Hrsg.


Weitere Infos & Material


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.


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.



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