最 低 价：￥776.70
定 价：￥863.00
作 者：Mary C. Hill，Claire R. Tiedeman 著 著
出 版 社：Oversea Publishing House
出版时间：2007-1-1
I S B N：9780471776369
| Preface 1 Introduction 1.1 Book and Associated Contributions: Methods, Guidelines,Exercises, Answers, Software, and PowerPoint Files 1.2 Model Calibration with Inverse Modeling 1.2.1 Parameterization, 1.2.2 Objective Function 1.2.3 Utility of Inverse Modeling and Associated Methods 1.2.4 Using the Model to Quantitatively Connect Parameters,Observations, and Predictions 1.3 Relation of this Book to Other Ideas and Previous Works 1.3.1 Predictive Versus Calibrated Models 1.3.2 Previous Work 1.4 A Few Definitions 1.4.1 Linear and Nonlinear 1.4.2 Precision, Accuracy, Reliability, and Uncertainty~ 1.5 Advantageous Expertise and Suggested Readings 1.6 Overview of Chapters 2 Through 15 2 Computer Software and Groundwater Management Problem Used in the Exercises 2.1 Computer Programs MODFLOW-2000, UCODE 2005 and PEST 2.2 Groundwater Management Problem Used for the Exercises, 2.2.1 Purpose and Strategy, 2.2.2 Flow System Characteristics, 2.3 Exercises, Exercise 2.1: Simulate Steady-State Heads and Perform Preparatory Steps 3 Comparing Observed and Simulated Values Using Objective Functions 3.1 Weighted Least-Squares Objective Function, 3.1.1 With a Diagonal Weight Matrix 3.1.2 With a Full Weight Matrix 3.2 Alternative Objective Functions 3.2.1 Maximum-Likelihood Objective Function 3.2.2 La Norm Objective Function 3.2.3 Multiobjective Function 3.3 Requirements for Accurate Simulated Results 3.3.1 Accurate Model 3.3.2 Unbiased Observations and Prior Information 3.3.3 Weighting Reflects Errors 3.4 Additional Issues 3.4.1 Prior Information 3.4.2 Weighting 3.4.3 Residuals and Weighted Residuals 3.5 Least-Squares Objective-Function Surfaces 3.6 Exercises Exercise 3.1 : Steady-State Parameter Definition Exercise 3.2: Observations for the Steady-State Problem Exercise 3.3: Evaluate Model Fit Using Starting Parameter Values 4 Determining the Information that Observations Provide on Parameter Values using Fit-Independent Statistics 4.1 Using Observations 4.1.1 Model Construction and Parameter Definition 4.1.2 Parameter Values …… 5 Estimating Parameter Values 6 Evaluating Model Fit 7 Evaluating Estimated Parameter Values and parameter Uncertainty 8 Evaluating Model Predictions,Data Needs,and Prediction Uncertainty 9 Calibrating Transient and Transport Models and Recalibrating Existing Models 10 Guidelines for Effective Modeling 11 Guidelines 1 Through8-Model Development 12 Guideines 9 and 10-Model Testing 13 Guidelines 11 and 12-Potential New Data 14 Guidelines 13 and 14-Prediction Uncertainty 15 Using and Testing the Methods and Guidelines Appendix A: Objective Function Issues Appendix B:Calculation Details of the Modified Gauss-Newton Method Appendix C:Two Important Properties of Linear Regression and the Effects of Nonlinearity Appendix D:Selected Statistical Tables References Index |
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