ANALYSIS OF ANNUAL MAXIMUM ONE DAY AND EXTENDED DAYS RAINFALL FOR PLAIN ZONE OF MAHARASHTRA
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Date
2007
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Mahatma Phule Krishi Vidyapeeth, Rahuri.
Abstract
Rainfall is one of the important factors responsible for
increase in agricultural production. The agricultural production
can be increased significantly with proper management of rain
water, application of irrigation in time and drainage of
agricultural field. The distribution of rainfall in time and space is
erratic in nature. For thorough study of hydrology of the area and
for planning and evolving certain drainage criteria for different
crops, study of duration and amount of maximum rainfall of
various return periods is required. The knowledge of consecutive
days maximum rainfall can lead to successful crop planning.
Analysis of consecutive days maximum rainfall of different return
periods is a basic tool for safe and economical planning and
design of structural and non structural measures, small and
medium hydraulic structures such as dams, bridges, culverts,
spillways, check dams , ponds, irrigation and drainage works in watershed management and command area development. For
prediction of design rainfall fairly accurately, various probability
distribution functions are used.
The study was undertaken with a specific objectives of
determination of D-days rainfall total, compare plotting positions
obtained by using Weibull’s and Gringorten’s formulae, obtain the
relationship between one day and D-days rainfall totals and fit
the probability distributions of D-days rainfall totals in Plain
Zone. For this purpose daily rainfall data of Kasbe Digraj, Niphad
and Pune were used.
The analysis was carried out for maximum values of
rainfall of one day and extended days (2 day to 6 day). Three
widely used probability distributions for extreme events, viz., Log
Pearson Type-III, Log Normal and Gumbel were fit the observed
data.
The results showed that the Weibull’s formula is better
to use than Gringorten’s formula for plotting positions for the
observed data at three stations. The relationships between one
day and D-day annual maximum values of rainfall were found to
be logarithmic in nature for Kasbe Digraj, fourth order polynomial
in nature for Niphad and exponential in nature for Pune. The
probability analysis showed that the Log Pearson Type-III
distribution is the best fit for observed one day maximum rainfall
data at Kasbe Digraj and Pune whereas Log Normal distribution
gave close fit for observed one day maximum rainfall data at
Niphad.
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