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Advances in Multivariate Analysis of Environmental Phenomena: Celebrating the 15th Anniversary of Copulas in Hydrology

Special Issue Information

Dear Colleagues,

In 2003, a seminal paper introduced the notion of Copula in hydrology: The target was to provide a new statistical tool to conveniently deal with the modeling of multivariate environmental phenomena. Since then, thousands of works have used Copulas to approach awkward and tricky problems involving the (joint) random behavior of non-independent variables, coming up with new models and techniques of an unprecedented reach and scope. Several are the areas of hydrological sciences that have taken advantage of the power of Copulas: Among others, the study of floods, droughts, rainfall, and sea storms can now benefit from an increased capacity of (statistically) explaining the complex interactions of a number of variables. In turn, the predictive ability of many models has greatly improved, and the assessment of environmental risk has made substantial progresses. In addition, new findings concerning the quantification of hydrologic uncertainty have been obtained, and the assessment of basin similarities and regionalization techniques has received a great impulse. Moreover, thanks to innovative techniques of multivariate design, new cost-benefit strategies have been developed, resulting in less expensive structures as compared, e.g., to those planned via a traditional univariate approach.

However, the multivariate analysis via Copulas is yet in its infancy: several are the questions that are still open, and further startling discoveries are expected in the near future. The aim of this Special Issue is to present the most recent advances concerning the multivariate analysis of environmental phenomena (and especially the hydrological ones), with an eye to applications, and to provide a critical discussion of several important related issues.

Dr. Gianfausto Salvadori
Prof. Carlo De Michele
Guest Editors

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Keywords

  • Copula
  • Multivariate Analysis
  • Multivariate Design
  • Risk Assessment
  • Hydrology
  • Flood
  • Drought
  • Rainfall
  • Sea Storm

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Water - ISSN 2073-4441Creative Common CC BY license