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- W384599194 abstract "As an attempt to improve flood risk prediction we investigate the relations between the stochastic processes of daily rainfall and runoff. We consider a simple stochastic model of the extreme precipitation in which the occurrences are mutually independent and the distribution of marks can be derived through the analysis of the Peak Over Threshold (POT) process. Our initial interest concentrates on the relationships between the mean annual number of rainfall and runoff peak events (Λp and Λq) at various thresholds: the mechanism of flood production and its changes are investigated by analysing the nature of these relationships. To this aim we consider that the watershed operates as a stochastic filter on the rainfall process, producing a filtered point process that reproduces occurrence and magnitude of floods. The analysis of the filter mechanism provides the relationships between stochastic parameters of maximum rainfall and discharge. Particularly, we consider a simple filter wherein the runoff peaks are produced after a volume abstraction on precipitation, which essentially limits the number of runoff events. Since Λp and Λq are parameters playing a significant role in Poisson-derived flood frequency distributions, we investigate the possible dependence of the obtained results on the hypothesis of Poissonian occurrences and on the distribution of marks, We derived relations between the frequency of rainfall and flood events at varying thresholds for several observed series of rainfall and runoff. The different patterns of the basin transformation found seem to confirm the stochastic nature of the basin filter and its strong relations with the hydro-geologic and climatic characteristics of the basin." @default.
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- W384599194 date "2002-01-01" @default.
- W384599194 modified "2023-09-26" @default.
- W384599194 title "Assessment of extreme flood production mechanisms through POT analysis of daily data" @default.
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