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  Information - HS27 Times series analysis in hydrology (co-listed in NP)

Event Information
Statistical and other mathematical time series methods have been widely used in hydrology. In the last twenty years many different approaches were developed for extreme values analysis, rainfall simulation in time and space, and runoff forecasting and management. In addition to classical linear parametrical models and univariate inference statistical procedures, a variety of procedures were developed, including non-linear (chaotic) time series modelling, neural network approaches, space-time simulation methods, multivariate distribution analyses, etc..
This session collects presentations describing theory, procedures and applications of the above approaches used in hydrology mainly focusing the attention on time series analysis and on rainfall and runoff simulation procedures. Presentations on theory description of innovation approaches and advanced statistical and mathematical methods, and poster contributions with applications of mentioned procedures are encouraged. Evaluating different methods applied to hydrological series simulation, in the univariate and multivariate case and in the downscaling problem, to compare their performance is one of the expected results of the session.

Preliminary List of Solicited Speakers
Marcella Corduas, Dipartimento di Scienze Statistiche, Università di Napoli Federico II - Italy
"Short and long memory unobserved components in hydrological time series"(EGU05-A-01831),

Carsteanu, A.A., Cinvestav - Mathematics Department, Mexico
"Estimation of breakdown coefficients in time series sampled from multifractal measures" (co-authors:Castro, J.J.; Angulo, C.)

Co-Sponsorship

General Statement
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