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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
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Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(6): 1390-1396
DOI: https://doi.org/10.20546/ijcmas.2019.806.168


Frequency Analysis of Rainfall Data Using Probability Distribution Models
H. Baghel*, H.K. Mittal, P.K. Singh, K.K. Yadav and S. Jain
Department of Soil and Water Engineering, CTAE, MPUAT, Udaipur 313001, India
*Corresponding author
Abstract:

Rainfall is a prime input for various engineering design such as hydraulic structures, water conservation structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. The present study comprises statistical analysis i.e. frequency analysis of daily maximum rainfall data of Udaipur district. The daily rainfall data for a period of 56 years is collected to evaluate designed value of rainfall using probability distribution models. Around 07 different probability distributions (Gamble’s extreme value type I, Logpearson type III, Lognormal, Normal, Exponential, Pearson type III and Gamma distribution) were used to evaluate maximum daily rainfall. Chi-squared tests were used for the goodness of fit of the probability distributions. Results showed that Lognormal distribution and Gumbel distribution found to be have least critical values in the tests hence consider as the best fit distribution for given sample population. Also maximum daily expected value of rainfall for various return periods were evaluated using all distribution model under consideration.


Keywords: Rainfall, distribution models, frequency analysis
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How to cite this article:

Baghel, H., H.K. Mittal, P.K. Singh, K.K. Yadav and Jain, S. 2019. Frequency Analysis of Rainfall Data Using Probability Distribution Models.Int.J.Curr.Microbiol.App.Sci. 8(6): 1390-1396. doi: https://doi.org/10.20546/ijcmas.2019.806.168