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  Information - HS34 Dependence modelling in geosciences (co-listed in NP & Union Session)

Event Information
In many geosciences problems several are the variables that play a significant role in the modelization of the phenomenon under investigation, and such variates are generally not independent. For instance, different combinations of rainfall intensity and storm duration may generate storms showing quite different characteristics, and the river management may strongly depend upon the joint features of flood peak and flood volume. Therefore, it is often of fundamental importance to be able to relate the marginal distributions of different variables in order to obtain a joint law describing the main features of the observed events. Recent advances in applied mathematics have shown that "Copulas" may represent an useful tool for investigating the statistical behavior of dependent variables.
This session is focused on illustrating and discussing the recent findings in modelling the statistical dependence in geosciences. Particular emphasis will be paid towards papers that are going to:
i. model the dependence among several variables;
ii. build bi-variate and multivariate probability distribution of extreme events (rainfall, soil moisture, floods, droughts, wind, earthquakes, tsunami etc.);
iii. develop techniques to estimate model parameters;
iv. evaluate the model uncertainty;
v. consider the risk and reliability analysis (measure of reliability, multiple failure models, uncertainty in reliability assessments).

Preliminary List of Solicited Speakers

Co-Sponsorship

General Statement
The information contained hereafter has been compiled and uploaded by the Session Organizers via the "Organizer Session Form". The Session Organizers have therefore the sole responsibility that this information is true and accurate at the date of publication, and the conference organizer cannot accept any legal responsibility for any errors or omissions that may be made, and he makes no warranty, expressed or implied, with regard to the material published.



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