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  • Extreme value analysis dile...
    Tabari, Hossein

    Journal of hydrology (Amsterdam), February 2021, 2021-02-00, Volume: 593
    Journal Article

    •The large-scale patterns of changes are congruous between the BM and POT methods.•There is discrepancy between the BM and POT results at the local scale.•The discrepancies increase with event extremity and vary with season and space.•The differences are statistically significant for longer return periods.•The differences get larger seasonally for summer and spatially for arid regions. A reliable estimation of hydrological extremes with potentially severe socio-economic impacts is of crucial importance for efficient planning and design of hydraulic structures. Extreme value theory provides a firm theoretical foundation for the statistical modelling of extreme hydrological events. The dilemma in the modelling is on whether to use block maxima (BM) or peak-over-threshold (POT) method, each with its own cons and pros. It remains unexplored to what extent future projected changes in extreme hydrological events are influenced by the method choice, especially when some simplifications are made to lessen the computational burden for large-scale studies. This study addresses this research question by a comparative analysis between the BM and POT methods on future climate change impact on global flood and extreme precipitation. The extreme precipitation analysis is performed using 24 CMIP5 general circulation models (GCMs), while the flood analysis is based on a multi-model ensemble of 20 members including five global impact models forced by four CMIP5 GCMs. The results reveal that the BM and POT methods agree on the sign of changes in flood and extreme precipitation intensities, but disagree on the magnitude. The discrepancy between the BM and POT results increases with event extremity. The difference also varies with season, where the difference in the global land area with increasing signals peaks in winter at the rates of 11% for extreme precipitation and in summer at the rates of 3.5% for flood.