Effective Groundwater Model Calibration With Analysis of Data, Sensitivities, Predictions, and Uncertainty

About this book

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 of data
- Data assessment to identify (a) existing measurements that dominate model development and predictions and (b) potential measurements likely to improve the reliability of predictions
- Calibration to develop models that are consistent with the data in an optimal manner
- Uncertainty evaluation to quantify and communicate errors in simulated results that are often used to make important societal decisions

Most of the methods are based on linear and nonlinear regression theory. Fourteen guidelines show the reader how to use the methods advantageously in practical situations. Exercises focus on a groundwater flow system and management problem, enabling readers to apply all the methods presented in the text. The exercises can be completed using the material provided in the book, or as hands-on computer exercises using instructions and files available on the text's accompanying Web site.

Throughout the book, the authors stress the need for valid statistical concepts and easily understood presentation methods required to achieve well-tested, transparent models. Most of the examples and all of the exercises focus on simulating groundwater systems; other examples come from surface-water hydrology and geophysics.

The methods and guidelines in the text are broadly applicable and can be used by students, researchers, and engineers to simulate many kinds systems.

Contents

Preface

1 Introduction
2 Computer Software and Groundwater Management Problem Used in the Exercises
3 Comparing Observed and Simulated Values Using Objective Functions
4 Determining the Information that Observations Provide on Parameter Values using Fit-Independent Statistics
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 Through 8-Model Development
12 Guidelines 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

Customer Reviews

Biography

Mary C. Hill, PhD, is Project Chief for the U.S. Geological Survey (USGS) and a recipient of the USGS Meritorious Service Award, the ASCE Walter Huber Research Prize, and the NGWA M. King Hubbert Award. Dr. Hill is President of the International Commission for Ground Water. She is Adjunct Professor at the University of Colorado at Boulder and the Colorado School of Mines.

Claire R. Tiedeman, MS, is a Research Hydrologist at the U.S. Geological Survey, where her work involves calibrating and evaluating models of complex groundwater flow systems, developing methods to evaluate prediction uncertainty, and characterizing flow and transport in fractured-rock aquifers. She is a recipient of the USGS Superior Service Award and an Associate Editor of the journal Ground Water.