Modeling Hydrologic Change Statistical Methods

About this book

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.

Contents

DATA, STATISTICS, AND MODELINGWatershed ChangesEffect on Flood RecordWatershed Change and Frequency AnalysisDetection of NonhomogeneityModeling of NonhomogeneityINTRODUCTION TO TIME SERIES MODELINGComponents of a Time SeriesMoving-Average FilteringAutocorrelation AnalysisCross-Correlation AnalysisIdentification of Random ComponentsAutoregression and Cross-Regression ModelsSTATISTICAL HYPOTHESIS TESTINGProcedure for Testing HypothesesRelationships among Hypothesis Test ParametersParametric and Nonparametric TestsOUTLIER DETECTIONChauvener's MethodDixon-Thompson TestRosner's Outlier TestLog Pearson Type III Outlier Detection: Bulletin 17bPearson Type III Outlier DetectionSTATISTICAL FREQUENCY ANALYSISFrequency Analysis and SynthesisPopulation ModelsAdjusting Flood Record for UrbanizationGRAPHICAL DETECTION OF NONHOMOGENEITY Graphical AnalysesCompilation of Causal InformationSupporting Computational AnalysesSTATISTICAL DETECTION OF NONHOMOGENEITYRuns TestKendall Test for TrendPearson Test for Serial IndependenceSpearman Test for TrendSpearman-Conley TestCox-Stuart Test for TrendNoether's Binomial Test for Cyclical TrendDurbin-Watson Test for AutocorrelationEquality of Two Correlation CoefficientsDETECTION OF CHANGE IN MOMENTSGraphical AnalysisThe Sign TestTwo-Sample t-TestMann-Whitney TestThe t-Test for Two Related SamplesThe Walsh TestWilcoxan Matched-Pairs, Signed-Ranks TestOne-Sample Chi-Square TestTwo-Sample F-TestSiegel-Tukey Test for ScaleDETECTION OF CHANGE IN DISTRIBUTIONChi-Square Goodness-of-Fit TestKolmogorov-Smirnov One-Sample TestThe Wald-Wolfowitz Runs TestKolmogorov-Smirnov Two-Sample TestMODELING CHANGEConceptualizationModel FormulationModel CalibrationModel VerificationAssessing Model ReliabilityHYDROLOGIC SIMULATIONComputer Generation of Random NumbersSimulation of Discrete Random VariablesGeneration of Continuously Distributed Random VariatesApplications of SimulationSENSITIVITY ANALYSISMathematical Foundations of Sensitivity AnalysisTime Variation of SensitivitySensitivity in Model FormulationSensitivity and Data Error AnalysisSensitivity of Model CoefficientsWatershed ChangeFREQUENCY ANALYSIS UNDER NONSTATIONARY LAND USE CONDITIONSData RequirementsDeveloping a Land-Use Time SeriesModeling IssuesComparison of Flood Frequency AnalysesSummaryAppendix A: Statistical TablesAppendix B: Data MatricesReferencesIndexEach chapter begins with and Introduction and ends with a "Problems" Section

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