Bote, N.L.Shinde Neeta Eknath2019-10-042019-10-042007http://krishikosh.egranth.ac.in/handle/1/5810130243Rainfall 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.ennullThesis