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Congress: 2008
Author(s): Rafael S. Seoane(1,4), Patricia M. López (2) Marta García Ben (3) and Ana Callaú(1)
Instituto Nacional del Agua, (1) Dirección de Servicios Hidrológicos, (2) Centro Regional Andino (3) Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales (4) Consejo Nacional de Investigaciones Científicas y Técnicas Address: AU Ezeiz

Keyword(s): low flows, climate change, autocorrelation
AbstractAn important research program in Hydrology is the statistical analysis of extreme events. This analysis involves the definition of criteria to select a probability distribution that describes the statistics of the series and the selection of a method for estimating the parameters of the distribution. Some studies have been done in order to establish procedures for regional frequency analysis. Low flow series were analyzed in several countries because of their importance on water resources management and the study of changes in frequency and severity of hydrologic droughts due to climate change will be relevant. Annual minimum daily mean flow series in various regions of Argentina were studied to detect changes with time due to climatic variability. In general, the series have shown statistically significant autocorrelation of lag-one and trend. The nonparametric Mann- Kendall test was used to identify trend and a pre-whitening procedure for eliminating the effect of serial correlation on the test was used. The influence of autocorrelation on the statistical tests used for detecting changes in the distribution of the series between periods was assessed using autoregressive models. The results show the large influence of autocorrelation on the aptitude of the statistical tests to assess changes in the distribution of the series.
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