Some best-fit probability distributions for at-site flood frequency analysis of the Ume River

被引:20
作者
Kousar, Samara [1 ]
Khan, Abrar Raza [2 ]
Ul Hassan, Mahmood [3 ]
Noreen, Zahra [4 ]
Bhatti, Sajjad Haider [1 ]
机构
[1] Govt Coll Univ Faisalabad, Dept Stat, Faisalabad, Pakistan
[2] Tips Coll Commerce, Dept Stat, Faisalabad, Pakistan
[3] Stockholm Univ, Dept Stat, Stockholm, Sweden
[4] Univ Educ, Div Sci & Technol, Lahore, Pakistan
来源
JOURNAL OF FLOOD RISK MANAGEMENT | 2020年 / 13卷 / 03期
关键词
generalised extreme value; generalised logistic; Gumbel; L-moments; log-normal; maximum likelihood; ANNUAL MAXIMUM;
D O I
10.1111/jfr3.12640
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
At-site flood frequency analysis is a direct method of flood estimation at a given site. The choice of an appropriate probability distribution and parameter estimation method plays a vital role in at-site frequency analysis. In the current article, flood frequency analysis is carried out at five gauging sites of the Ume River in Sweden. Generalised extreme value, three-parameter log-normal, generalised logistic and Gumbel distributions are fitted to the annual maximum peak flow data. The L-moment and the maximum likelihood methods are used to estimate the parameters of the distributions. Based on different goodness-of-fit tests and accuracy measures, the three-parameter log-normal distribution has been identified as the best-fitted distribution by using the L-moments method of estimation for gauging sites Harrsele Krv, Gardiken and overuman Nedre. The generalised extreme value distribution with the L-moments estimation provided the best fit to maximum annual streamflow at gauging sites Solberg and Stornorrfors Krv. Finally, the best-fitted distribution for each gauging site is used to predict the maximum flow of water for return periods of 5, 10, 25, 50, 100, 200, 500, and 1000 years.
引用
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页数:11
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