Time series analysis is important for the detection of extreme events that occur in processes of nature. This work considers the analysis of estimated river discharge data generated from a hydrological model by comparing the properly rescaled data of the time series to a function of the Generalized Pareto Distribution (GPD) with particular parameters estimated from a GPD algorithm. Results indicate that the patterns of the rescaled data are well represented by the GPD function, and also that positive shape parameter values correspond to the presence of extreme events.

Time series analysis, river dynamics, generalized Pareto distribution, computational statistics

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