relation: http://eprints.science-line.com/id/eprint/983/
title: Comparison of Estimators of Probability Distributions for Selection of Best Fit for Estimation of Extreme Rainfall.
creator: Vivekanandan, N.
subject: TA Engineering (General). Civil engineering (General)
description: Extreme Value Analysis (EVA) of rainfall is considered as one of the important aspects to arrive at a design value for planning, design and management of civil and hydraulic structures. This can be achieved by fitting Probability Distribution (PDs) to the series of observed annual 1-day maximum rainfall data wherein the parameters of PDs are determined by method of moments and L-Moments (LMO). In this paper, a study on comparison of Extreme Value Type-1 (EV1), Extreme Value Type-2, Generalized Extreme Value (GEV) and Generalized Pareto distributions adopted in EVA of rainfall for Anakapalli, Atchutapuram, Kasimkota and Parvada sites is carried out. The selection of best fit PD for EVA of rainfall is made through quantitative assessment by using Goodness-of-Fit (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic (viz., root mean squared error) tests; and qualitative assessment by using the fitted curves of the estimated rainfall. On the basis of evaluation of EVA results through quantitative and qualitative assessments, the study indicates the extreme rainfall given by EV1 (LMO) distribution could be used for the purpose of economical design. The study also indicates the extreme rainfall obtained from GEV (LMO) distribution may be considered for the design of civil and hydraulic structure with little risk involvement.
publisher: Scienceline Publication, Ltd
date: 2020-05-25
type: Article
type: PeerReviewed
format: text
language: en
identifier: http://eprints.science-line.com/id/eprint/983/1/JCEU%2010%283%29%2024-31%2C%202020.pdf
identifier:    (2020)     Comparison of Estimators of Probability Distributions for Selection of Best Fit for Estimation of Extreme Rainfall.   Journal of Civil Engineering and Urbanism.  pp. 24-31.  ISSN 2252-0430   
relation: https://doi.org/10.29252/scil.2020.jceu4
relation: doi:10.29252/scil.2020.jceu4