张弛

个人信息Personal Information

教授

博士生导师

硕士生导师

任职 : 副校长、党委常委

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:建设工程学院

学科:水文学及水资源. 人工智能. 计算机应用技术. 软件工程

办公地点:综合实验4号楼 411室

联系方式:0411-84708900

电子邮箱:czhang@dlut.edu.cn

扫描关注

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

Applicability of Wakeby distribution in flood frequency analysis: a case study for eastern Australia

点击次数:

论文类型:期刊论文

发表时间:2015-02-15

发表刊物:HYDROLOGICAL PROCESSES

收录刊物:SCIE、EI、Scopus

卷号:29

期号:4

页面范围:602-614

ISSN号:0885-6087

关键字:Wakeby distribution; probability plot correlation coefficient test; plotting position formula; flood frequency analysis; floods

摘要:Parametric method of flood frequency analysis (FFA) involves fitting of a probability distribution to the observed flood data at the site of interest. When record length at a given site is relatively longer and flood data exhibits skewness, a distribution having more than three parameters is often used in FFA such as log-Pearson type 3 distribution. This paper examines the suitability of a five-parameter Wakeby distribution for the annual maximum flood data in eastern Australia. We adopt a Monte Carlo simulation technique to select an appropriate plotting position formula and to derive a probability plot correlation coefficient (PPCC) test statistic for Wakeby distribution. The Weibull plotting position formula has been found to be the most appropriate for the Wakeby distribution. Regression equations for the PPCC tests statistics associated with the Wakeby distribution for different levels of significance have been derived. Furthermore, a power study to estimate the rejection rate associated with the derived PPCC test statistics has been undertaken. Finally, an application using annual maximum flood series data from 91 catchments in eastern Australia has been presented. Results show that the developed regression equations can be used with a high degree of confidence to test whether the Wakeby distribution fits the annual maximum flood series data at a given station. The methodology developed in this paper can be adapted to other probability distributions and to other study areas. Copyright (c) 2014 John Wiley & Sons, Ltd.