Indexing Metadata

1 Title of the Article Modelling of Annual Extreme Rainfall, Temperature and Wind Speed Using OSA of EV1 and EV2 Distributions
2 Author's name N. Vivekanandan: Assistant Research Officer, Hydrometeorology Division, Central Water and Power Research Station, Pune 411024, Maharashtra; Phone: (020) 24103367; E-mail: anandaan@ rediffmail.com
3 Author's name
4 Subject Central Water and Power Research
5 Keyword(s) Anderson-Darling, Correlation, Frechet, Gumbel, Kolmogorov-Smirnov, Mean square error
6 Abstract

Prediction of rainfall, temperature and wind speed is of utmost importance for planning, design and management of the civil structures at the project site. This can be carried out by fitting of probability distributions to the observed data. This paper illustrates the adoption of Gumbel (EV1) and Frechet (EV2) distributions for modelling of annual extreme rainfall, temperature and wind speed for Kanyakumari. Order Statistics Approach is used for determination of parameters of EV1 and EV2 distributions. Goodness-of-Fit (GoF) tests viz., Anderson-Darling and Kolmogorov-Smirnov are used for checking the adequacy of fitting of the distributions. Model Performance Indicators (MPIs) such as root mean square error and correlation coefficient are used for evaluating the performance of the probability distributions adopted in modelling of rainfall, temperature and wind speed. Based on GoF tests results and MPIs, the study recommends the EV1 distribution is better suited distribution for modelling of annual extreme rainfall and temperature whereas EV2 for annual extreme wind speed for Kanyakumari.

7 Publisher Innovative Research Publication
8 Journal Name; vol., no. International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-3 Issue-4
9 Publication Date July 2015
10 Type Peer-reviewed Article
11 Format PDF
12 Uniform Resource Identifier https://ijircst.org/view_abstract.php?title=Modelling-of-Annual-Extreme-Rainfall,-Temperature-and-Wind-Speed-Using-OSA-of-EV1-and-EV2-Distributions&year=2015&vol=3&primary=QVJULTIyNg==
13 Digital Object Identifier(DOI)  
14 Language English
15 Page No 57-60

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