A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

被引:30
|
作者
Jeong, Dae Il [1 ]
Sushama, Laxmi [1 ]
Khaliq, M. Naveed [1 ,2 ,3 ]
Roy, Rene [1 ,4 ,5 ]
机构
[1] Univ Quebec, Ctr ESCER Etud & Simulat Climat Echelle Reg, 201 Ave President Kennedy, Montreal, PQ H3C 3P8, Canada
[2] Univ Saskatchewan, Sch Environm & Sustainabil, Saskatoon, SK, Canada
[3] Univ Saskatchewan, Global Inst Water Secur, Saskatoon, SK, Canada
[4] Ouranos, Montreal, PQ H3A 1B9, Canada
[5] Hydroquebec, Varennes, PQ J3X 1S1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Climate change; Copula function; Floods; Frequency analysis; Northeastern Canada; Regional climate modeling; REGIONAL CLIMATE MODEL; FREQUENCY-ANALYSIS; RIVER-BASIN; BIVARIATE; IMPACTS; VALIDATION; SIMULATION; STREAMFLOW; RAINFALL;
D O I
10.1007/s00382-013-1851-4
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
In the present work, climate change impacts on three spring (March-June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak-volume, peak-duration and volume-duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970-1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970-1999) and future (2041-2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.
引用
收藏
页码:2045 / 2066
页数:22
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