DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-5,Issue-1, Spl. Iss-1 ( Jan, 2017 ) | |||||||||
Paper Title |
Determining Probability Distribution For Streamflow Regions Using Partial-Moments | |||||||||
Author Name |
Zahrahtul Amani Zakaria, Ani Shabri, Mohd Khalid Awang | |||||||||
Affilition |
Faculty Informatics and Computing, Univeristi Sultan Zainal Abidin, Terengganu, Malaysia. Faculty of Science, Univeristi Teknologi Malaysia, Johor, Malaysia. | |||||||||
Pages |
41-44 | |||||||||
Abstract |
An attempt has been made to model the annual maximum streamflow, utilizing the guidelines in the regional flood frequency analysis. The Partial L-moments (PL-moments) at several censoring levels are employed to estimate the regional parameters of three extreme value distributions, namely; generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA) distributions. A total number of 18 streamflow stations located throughout the eastern region of Peninsular Malaysia were used as a case study. Firstly, the data is screening out for data verification and quality control. Next, identification of homogeneous regions is made using homogeneity test based on PL-moments. The PL - diagram is then constructed and GEV and GLO distributions appeared to be the acceptable distributions for representing the regional data. However, it is relatively difficult to identify a particular distribution that most fitted the regional data.Thus, goodness-of-fit test (Z-test) is used and the result showed that the most appropriate distribution for modeling maximum streamflow in the East Coast of Peninsular Malaysia, based on PL-moments is the GLO distribution. Keywords— Partial L-Moments, Frequency Analysis, Parameter Estimation, Censoring Level. | |||||||||
| View Paper | ||||||||||
