Summary
Modeling hydrologic changes and predicting their impact on watersheds is a dominant concern for hydrologists and other water resource professionals, civil and environmental engineers, and urban and regional planners. As such changes continue, it becomes more essential to have the most up-to-date tools with which to perform the proper analyses and modeling of the complex ecology, morphology, and physical processes that occur within watersheds. An application-oriented text, Modeling Hydrologic Change: Statistical Methods provides a step-by-step presentation of modeling procedures to help you properly analyze and model real-world data. The text addresses modeling systems where change has affected data that will be used to calibrate and test models of the system. The use of actual hydrologic data will help you learn how to handle the vagaries of real-world hydrologic-change data. All four elements of the modeling process are discussed: conceptualization, formulation, calibration, and verification. Although the book is oriented towards the statistical aspects of modeling, a strong background in statistics is not required. The statistical and modeling methods discussed here will be of value to all disciplines involved in modeling change. With approximately 100 illustrations, Modeling Hydrologic Change will equip you with an understanding with which to perform the proper analyses and modeling of the complex processes that occur across various disciplines.
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Table of Contents
DATA, STATISTICS, AND MODELING
Watershed Changes
Effect on Flood Record
Watershed Change and Frequency Analysis
Detection of Nonhomogeneity
Modeling of Nonhomogeneity
INTRODUCTION TO TIME SERIES MODELING
Components of a Time Series
Moving-Average Filtering
Autocorrelation Analysis
Cross-Correlation Analysis
Identification of the Random Component
Autoregression and Cross-Regression Models
STATISTICAL HYPOTHESIS TESTING
A Procedure for Testing Hypotheses
Relationship between Hypothesis Test Parameters
Parametric and Nonparametric Tests
OUTLIER DETECTION
Chauvener's Method
Dixon-Thompson Test
Rosner's Outlier Test
Log Pearson Type III Outlier Detection: Bulletin 17B
Pearson Type III Outlier Detection
FREQUENCY ANALYSIS
Frequency Analysis and Synthesis
Population Models
Adjusting a Flood Record for Urbanization
GRAPHICAL DETECTION OF NONHOMOGENEITY Graphical Analysis
Compilation of Causal Information
Supporting Computational Analyses
STATISTICAL DETECTION OF NONHOMOGENEITY
Runs Test
Kendall Test for Trend
Pearson Test for Serial Independence
Spearman Test for Trend
Spearman-Conley Test
Cox-Stuart Test for Trend
Noether's Binomial Test for Cyclical Trend
Durbin-Watson Test
Equality of Two Correlation Coefficients
DETECTION OF CHANGE IN MOMENTS
Graphical Analysis
The Sign Test
Two-Sample t-Test
Mann-Whitney Test
The t-Test for Two Related Samples
The Walsh Test
The Wilcoxan Matched-Pairs Signed-Ranks Test
One-Sample Chi-Square Test
Two-Sample F-Test
Siegel-Tukey Test for Scale
DETECTION OF CHANGE IN DISTRIBUTION
Chi-Square Goodness-of-Fit Test
Kolmogorov-Smirnov One-Sample Test
The Wald-Wolfowitz Runs Test
Kolmogorov-Smirnov Two-Sample Test
MODELING CHANGE
Conceptualization
Model Formulation
Model Calibration
Model Verification
Assessing Model Reliability
HYDROLOGIC SIMULATION
Computer Generation of Random Numbers
Simulation of Discrete Random Variables
Generation of Continuously Distributed Random Variates
Applications of Simulation
SENSITIVITY ANALYSIS
Mathematical Foundations of Sensitivity Analysis
Time Variation of Sensitivity
Sensitivity in Model Formulation
Sensitivity and Data Error Analysis
Sensitivity of Model Coefficients
Watershed Change
FREQUENCY ANALYSIS UNDER NON-STATIONARY LAND USE CONDITIONS
Data Requirements
Developing a Land Use Time Series
Modeling Issues
Comparison of Flood Frequency Analyses
Summary
Appendix A: Statistical Tables
Appendix B: Data Matrices
References
Index
Each chapter begins with and Introduction and ends with a "Problems" Section
INV STAT: Normal
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