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PROBABILITY DISTRIBUTION ANALYSIS OF CONSECUTIVE DAYS RAINFALL DATA FOR SABARKANTHA DISTRICT OF NORTH GUJARAT REGION, INDIA
Various probability distributions and transformations can be applied to estimate one day and two to seven consecutive days rainfall of various return periods. In the present study 16 different types of continuous probability distributions were tested using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for goodness of fit of an estimated statistical model for Sabarkantha district of Gujarat, India. For the present study daily rainfall data from 42 raingauge stations for 45 years (1961–2005) are obtained from State Water Data Centre, Gandhinagar, Gujarat. Inverse Gaussian distribution is best fitted to one day and consecutive 2,3,4,5,6 and 7 days rainfall dataset by both the AIC and BIC criterions.
PROBABILITY DISTRIBUTION ANALYSIS OF CONSECUTIVE DAYS RAINFALL DATA FOR SABARKANTHA DISTRICT OF NORTH GUJARAT REGION, INDIA
Various probability distributions and transformations can be applied to estimate one day and two to seven consecutive days rainfall of various return periods. In the present study 16 different types of continuous probability distributions were tested using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for goodness of fit of an estimated statistical model for Sabarkantha district of Gujarat, India. For the present study daily rainfall data from 42 raingauge stations for 45 years (1961–2005) are obtained from State Water Data Centre, Gandhinagar, Gujarat. Inverse Gaussian distribution is best fitted to one day and consecutive 2,3,4,5,6 and 7 days rainfall dataset by both the AIC and BIC criterions.
PROBABILITY DISTRIBUTION ANALYSIS OF CONSECUTIVE DAYS RAINFALL DATA FOR SABARKANTHA DISTRICT OF NORTH GUJARAT REGION, INDIA
Patel, N. R. (author) / Shete, D. T. (author)
ISH Journal of Hydraulic Engineering ; 14 ; 43-55
2008-01-01
13 pages
Article (Journal)
Electronic Resource
Unknown
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