Effective Groundwater Model Calibration : With Analysis of Data, Sensitivities, Predictions, and Uncertainty
Mary C. Hill
Bok Engelsk 2006 · Electronic books.
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| Utgitt | Hoboken : : Wiley, , 2006.
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| Omfang | 1 online resource (475 p.)
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| Opplysninger | Description based upon print version of record.. - EFFECTIVE GROUNDWATER MODEL CALIBRATION; CONTENTS; 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 Nonlinear1.4.2 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 Function3.1.1 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 L(1) 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. - 4.3.3 Dimensionless Scaled Sensitivities (dss)4.3.4 Composite Scaled Sensitivities (css); 4.3.5 Parameter Correlation Coefficients (pcc); 4.3.6 Leverage Statistics; 4.3.7 One-Percent Scaled Sensitivities; 4.4 Advantages and Limitations of Fit-Independent Statistics for Sensitivity Analysis; 4.4.1 Scaled Sensitivities; 4.4.2 Parameter Correlation Coefficients; 4.4.3 Leverage Statistics; 4.5 Exercises; Exercise 4.1: Sensitivity Analysis for the Steady-State Model with Starting Parameter Values; 5 Estimating Parameter Values; 5.1 The Modified Gauss-Newton Gradient Method; 5.1.1 Normal Equations. - 5.1.2 An Example. - Exercise 3.1: Steady-State Parameter DefinitionExercise 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; 4.2 When to Determine the Information that Observations Provide About Parameter Values; 4.3 Fit-Independent Statistics for Sensitivity Analysis; 4.3.1 Sensitivities; 4.3.2 Scaling. - Methods and guidelines for developing and using mathematical models Turn to Effective Groundwater Model Calibration for a set of methods and guidelines that can help produce more accurate and transparent mathematical models. The models can represent groundwater flow and transport and other natural and engineered systems. Use this book and its extensive exercises to learn methods to fully exploit the data on hand, maximize the model's potential, and troubleshoot any problems that arise. Use the methods to perform:Sensitivity analysis to evaluate the information content o
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| Dewey | |
| ISBN | 047177636X. - 9780471776369
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