Use of Probability Distribution in Rainfall Analysis

The daily rainfall data of 37 years were collected from the IMD approved Meteorological Observatory situated at GB Pant University of Agriculture and Technology, Pantnagar, India. The data were then processed to identify the maximum rainfall received on any one day (24hrs duration), in any week (7 days), in a month (4 weeks), in a monsoon season (4 months) and in a year (365 days period). The data were also analyzed to find out the standard deviation and coefficient of variation during all the four periods of study. The data showed that the annual daily maximum rainfall received at any time ranged between 49.32mm (minimum) to 229.40mm (maximum) indicating a very large range of fluctuation during the period of study. The rainfall data were analysed to identify the best fit probability distribution for each period of study and the trend has been presented in this study. Three statistical goodness of fit test were carried out in order to select the best fit probability distribution on the basis of highest rank with minimum value of test statistic. Fourth probability distribution was identified using maximum overall score based on sum of individual point score obtained from three selected goodness of fit test. Random numbers were generated for actual and estimated maximum daily rainfall for each period of study using the parameters of selected distributions. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The lognormal and gamma distribution were found as the best fit probability distribution for the annual and monsoon season period of study, respectively. Generalized extreme value distribution was observed in most of the weekly period as best fit probability distribution. The best fit probability distribution of monthly data was found to be different for each month. The scientific results clearly established that the analytical procedure devised and tested in this study may be suitably applied for the identification of the best fit probability distribution of weather parameters. [New York Science Journal 2010;3(9):40-49]. (ISSN: 1554-0200).