Cantitate/Preț
Produs

Copulas and Its Application in Hydrology and Water Resources: Springer Water

Autor Lu Chen, Shenglian Guo
en Limba Engleză Hardback – 12 iul 2018
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.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 96141 lei  6-8 săpt.
  Springer Nature Singapore – 29 dec 2018 96141 lei  6-8 săpt.
Hardback (1) 96720 lei  6-8 săpt.
  Springer Nature Singapore – 12 iul 2018 96720 lei  6-8 săpt.

Din seria Springer Water

Preț: 96720 lei

Preț vechi: 117951 lei
-18% Nou

Puncte Express: 1451

Preț estimativ în valută:
18511 19528$ 15426£

Carte tipărită la comandă

Livrare economică 02-16 ianuarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9789811305733
ISBN-10: 9811305730
Pagini: 337
Ilustrații: X, 290 p. 87 illus., 73 illus. in color.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.6 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seria Springer Water

Locul publicării:Singapore, Singapore

Cuprins

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.

Notă biografică

Dr. CHEN Lu is an Associate Professor (11/2015–present) 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.


Textul de pe ultima copertă

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.

Caracteristici

Shares the latest studies on the concept and methods of copulas for multivariate hydrological analysis Enriches readers’ understanding of determining the input for artificial neural networks for flood forecasting using the copula entropy method Covers various applications of flood frequency analysis, drought frequency analysis, dependence analysis, and flood coincidence risk analysis