
Multivariate Frequency Analysis of Hydro-Meteorological Variables
A Copula-Based Approach
Description
Key Features
- Presents methods for analysis of hydro-meteorological risks followed by illustrative examples based on real life data sets
- Provides definitions throughout on all new topics and key terms
- Includes case studies and real examples covering a variety of situations and showing how this work can be applied in the reader’s own work
Readership
Hydrologists at researcher level and above Meteorologists, Statisticians and Civil-Engineers
Table of Contents
1: Introduction
1.1 What is the object of the book?
1.2 Why the multivariate framework in general and in hydro-meteorology?
1.3 Who can benefit from this book?
1.4 What is covered (and not) in this book?
1.5 How to read this book?
References2: Hydro-Meteorological Frequency Analysis (HFA)
2.1 General aims of hydro- Meteorological frequency analysis
2.2 From univariate to multivariate HFA
2.3 Main steps of a complete multivariate HFA
2.4 Hydro-Meteorological events and their main features
Flood features
Drought features
Rainfall storm features
Sediment features
References3: Multivariate preliminary analysis
3.1 Context and motivation
3.2 Visualisation
3.3 Cross-Dependence measures
3.4 Outliers
3.5 Location measures
3.6 Scale measures
3.7 Asymmetry
3.8 Kurtosis
References4: Checking basic assumptions for multivariate HFA
4.1 Introduction and general considerations
4.2 Non-stationarity/trend
4.2.1 Definitions
4.2.2 Multivariate trend tests
4.2.3 Performance evaluation
4.2.4 Discussion
4.2.5 Examples
4.3 Heterogeneity/shift
4.3.1 Definitions
4.3.1 Multivariate shift detection tests
4.3.2 Examples
4.4 Serial dependence
4.4.1 Definitions
4.4.2 Serial independence tests
4.4.3 Examples
References5: Multivariate modeling
5.1 Introduction
5.2 Description of copula models
5.3 Classes of copula
5.3.1 Archimedean copulas
5.3.2 Extreme-value copulas
5.3.3 Meta-elliptical copulas
5.3.4 Other classes of copulas
5.4. Dependence measures
5.4.1 Overall dependence measures
5.4.2 Tail dependence measures
5.5. Parameter estimation
5.5.1 Inference Functions for Margins Method (IFM)
5.5.2 Maximum Pseudo-likelihood Method (MPL)
5.5.3 Moment-Based Method (MM)
5.5.4 Multi-parameter copula estimation
5.6. Copula selection
5.6.1 Preliminary step
5.6.2 Copula goodness-of-fit testing
5.6.3 Selection criteria for copula
5.6.5 Margin modeling
References6: Multivariate return period and quantile
6.1 Risk assessment in hydro-meteorology
6.2 Multivariate Return Period and multivariate quantile
6.3 Methods to select combinations
6.4 Illustrations
References7: Multivariate regional analysis
7.1 Aims and general steps of regional frequency analysis
7.2 Region delineation
7.3 Regional estimation
7.4 Index-flood model
7.5 Example
References8: Multivariate non-stationary HFA
8.1 General aspects: Non-stationary HFA
8.2 Multivariate non-stationary HFA: literature
8.3 Multivariate non-stationary models
8.4 Example
ReferencesAppendices
1. Depth function
2. Multivariate L-moments
3. Copula simulations
Product details
- No. of pages: 350
- Language: English
- Copyright: © Elsevier 2022
- Published: November 1, 2022
- Imprint: Elsevier
- Paperback ISBN: 9780323959087
About the Author
Fateh Chebana
Affiliations and Expertise
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