Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach

Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach provides comprehensive and detailed descriptions of the approaches and techniques used in multivariate frequency analysis (including but not limited to copula functions), with illustrative examples and real-life case studies. The multivariate frequency analysis framework allows for a realistic modeling of hydro-meteorological variables (e.g. floods, droughts, low-flows, rainstorms), and so leads to accurate risk assessment and a flexible framework. This book provides a solid platform for the integration of multivariate frequency analysis tools in hydro-meteorological practice and helps fill the gap between theory and practice and the advancement of the field of statistical hydro-meteorology. Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach presents all background material and new developments in one place and also to presents this material in a homogeneous and pedagogical way in order to allow students, engineers and researchers to access and use efficiently all the information about this topic. This reference can be used as a guide to apply the available and recent approaches to evaluate hydro-meteorological risks, to design hydraulic structures, teaching (faculty members), as a literature review to go to the next steps in their research projects (graduate students and postdocs). 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

• | Author: Fateh Chebana
• | Publisher: Elsevier
• | Publication Date: Nov 18, 2022
• | Number of Pages: 216 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0323959083
• | ISBN-13: 9780323959087