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Số người truy cập: 38,003,692

 Regional flood frequency studies in flash flood Prone areas: possibilities and risks
Tác giả hoặc Nhóm tác giả: CONG N'Guyen Chi , Payrastre Olivier, Gaume Eric
Nơi đăng: 6th Hymex Workshop, Primõsten, Croatia, 7-10 Mai 2012.; Số: 670;Từ->đến trang: 1-2;Năm: 2012
Lĩnh vực: Kỹ thuật; Loại: Báo cáo; Thể loại: Quốc tế
TÓM TẮT
Regional flood frequency analyses are often conducted to evaluate the possible magnitude of the peak discharge or any other characteristic of extreme flood events, i.e. high return period events (Hosking and Wallis, 1997 ; Gaume et al. 2010). These methods consist in merging data from different gauged or even ungauged sites of a region considered as statistically homogeneous, to build a larger regional data set enabling more robust statistical derivations. Such methods are particularly well suited in flash flood prone areas where available measured series are often relatively short and where the coefficient of variation of the peak discharge distributions appears to be high. They may nevertheless be misleading if only gauged series are considered because the statistical distributions of peak discharges may significantly differ from the distributions generally fitted to the data. This will be illustrated on some examples from the south Mediterranean part of France. The only way to avoid dramatic errors consists in taking into account as much information as possible on extreme floods that have occurred in the region even if they have affected ungauged areas. Statistics is only a way to summarize information contained in the studied data set. This set should contain some extreme events to inform about extremes.
ABSTRACT
Regional flood frequency analyses are often conducted to evaluate the possible magnitude of the peak discharge or any other characteristic of extreme flood events, i.e. high return period events (Hosking and Wallis, 1997 ; Gaume et al. 2010). These methods consist in merging data from different gauged or even ungauged sites of a region considered as statistically homogeneous, to build a larger regional data set enabling more robust statistical derivations. Such methods are particularly well suited in flash flood prone areas where available measured series are often relatively short and where the coefficient of variation of the peak discharge distributions appears to be high. They may nevertheless be misleading if only gauged series are considered because the statistical distributions of peak discharges may significantly differ from the distributions generally fitted to the data. This will be illustrated on some examples from the south Mediterranean part of France. The only way to avoid dramatic errors consists in taking into account as much information as possible on extreme floods that have occurred in the region even if they have affected ungauged areas. Statistics is only a way to summarize information contained in the studied data set. This set should contain some extreme events to inform about extremes.
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