This book presents an overview of copula theory and its application in hydrology, and provides valuable insights, useful methods and practical applications for multivariate hydrological analysis using copulas. In addition, it extends the traditional bivariate model to trivariate or multivariate models. The specific applications covered include the study of flood frequency analysis, drought frequency analysis, dependence analysis, flood coincidence risk analysis and statistical simulation using copulas. The book offers a valuable guide for researchers, scientists and engineers working in hydrology and water resources, and will also benefit graduate or doctoral students with a basic grasp of copula functions who want to learn about the latest research developments in the field.

Autorentext
Dr. CHEN Lu is an Associate Professor (11/2015present) Huazhong University of Science and Technology, Wuhan, China. She holds the Ph.D. in Hydrology and water resources from Wuhan University. Her Research Interests include:-Copula-based modelling;-Entropy-based modeling;-Stochastic modeling;-Streamflow forecasting;-Hydrology modelling;
Her research projects include:-Risk analysis of multi-reservoir flood control operation considering multiple uncertainties (financially supported by National Natural Science Foundation of China)-Design flood and risk analysis for Cascade reservoir systems. (financially supported by National Natural Science Foundation of China)-Flood coincidence risk analysis in cascade reservoir systems and its impact on downstream area. (financially supported by Natural Science Foundation of Hubei province)
Professor GUO Shenglian is a professor at Dept. of Hydrology and Water Resources Engineering, Wuhan University. Since 2005, he is Vice Governor, People's Government of Hubei Province.

Inhalt

Introduction.- Copula function.- Copula-based seasonal design flood calculation.- Drought analysis using copulas.- Copula-based flood coincidence risk analysis.- Copula-based multi-site streamflow simulation.- Copula-based forecast uncertainty evolution model for flood risk analysis.- Copula entropy.- Determination of input for Artificial Neural Networks for flood forecasting using the copula entropy method.- Measures of correlations among rivers using copula entropy.