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

----- 地下水和结膜管理中的最优化模拟模型实践

ISBN: 9781439838068 出版年：2012 页码：509 Peralta, Richard C CRC Press

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.