Analyses of extreme flooding in Austria over the period 1951-2006

被引:89
作者
Villarini, Gabriele [1 ,2 ]
Smith, James A. [1 ]
Serinaldi, Francesco [3 ]
Ntelekos, Alexandros A. [2 ,4 ]
Schwarz, Ulrich [2 ,5 ]
机构
[1] Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA
[2] Willis Res Network, London, England
[3] Univ Tuscia, Dipartimento GEMINI, Viterbo, Italy
[4] Willis Analyt, London, England
[5] Fluvius, Vienna, Austria
关键词
flooding; Austria; extreme event; POT; stationarity; GAMLSS; NAO; climate change; NORTH-ATLANTIC OSCILLATION; CLIMATE-CHANGE; ATMOSPHERIC CIRCULATION; PRECIPITATION VARIABILITY; CHANGING CLIMATE; ANNUAL MAXIMUM; TREND ANALYSIS; MANN-KENDALL; RIVER; FREQUENCY;
D O I
10.1002/joc.2331
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Analyses of extreme flooding in Austria is performed using daily discharge time series from 27 stations over the period 1951-2006. The main research questions revolve around: (1) temporal non-stationarities in the flood record, (2) upper tail and scaling properties of the flood peak records, and (3) relation between magnitude and frequency of flooding and the North Atlantic Oscillation (NAO). Two datasets are derived from the daily discharge time series: annual maximum daily discharge and peaks-over-threshold (POT) data. The validity of the stationarity assumption in the annual maximum discharge record is assessed by investigating the presence of abrupt and slowly varying changes using nonparametric tests. The time series are tested for abrupt changes both in the mean and variance of the flood peak distributions by means of the Pettitt test. The presence of monotonic trends is investigated by means of the Mann-Kendall and Spearman tests. Violations of the stationarity assumption are associated with abrupt rather than gradual changes. These step changes generally involve river regulation through construction of dams or other major engineering works. It is not possible to make conclusive statements about the presence of an anthropogenic climate change signal in the flood peak record. Similar conclusions are obtained when focussing on the frequency of POT floods. The Generalised Extreme Value distribution is used to study the upper tail and scaling properties of annual maximum daily discharge records. The location and scale parameters exhibit power-law behaviour as a function of drainage area. The shape parameters indicate that the flood peak distributions for Austria have a heavy tail. Non-stationary modelling of the annual maximum daily discharge and POT time series is used to explore the relation between flood magnitude and frequency and NAO. The results indicate that NAO is a significant covariate in explaining the magnitude and frequency of occurrence of flooding over a large part of Austria. Copyright (C) 2011 Royal Meteorological Society
引用
收藏
页码:1178 / 1192
页数:15
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