<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
        <Journal>
            <PublisherName>Scienceline Publications</PublisherName>
            <JournalTitle>Journal of Civil Engineering and Urbanism</JournalTitle>
            <ISSN>2252-0430</ISSN>
            <Volume>10</Volume>
            <Issue>3</Issue>
            <PubDate PubStatus="epublish">
             <Year>2020</Year>
             <Month>May</Month>
            </PubDate>
        </Journal>
        <ArticleTitle>Comparison of Estimators of Probability Distributions for Selection of Best Fit for Estimation of Extreme Rainfall</ArticleTitle>
        <FirstPage>24</FirstPage>
        <LastPage>31</LastPage>
        <ELocationID EIdType="url">https://www.ojceu.com/main/attachments/article/76/JCEU%2010(3)%2024-31,%202020.pdf</ELocationID>
        <Language>EN</Language>
        <AuthorList>
			<Author>
                <FirstName>Vivekanandan</FirstName>
                <MiddleName> </MiddleName>
                <LastName>N</LastName>
                <Affiliation>Central Water and Power Research Station, Pune, Maharashtra, India</Affiliation>
			</Author>
			        </AuthorList>
            
        <Abstract>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., Chisquare
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</Abstract>
        <KeywordsList>
                <Keyword>Chi-square</Keyword>
                <Keyword>Extreme value analysis</Keyword>
		<Keyword>Extreme Value Type-1</Keyword>
		<Keyword>Kolmogorov-Smirnov</Keyword>
		<Keyword>L-Moments</Keyword>
		<Keyword>Method of moments</Keyword>
  <Keyword>Rainfall, Root mean squared error</Keyword>
	</KeywordsList>
 </Article>
</ArticleSet>
