Analysis of Consecutive Days Maximum Rainfall Together With Dry, Wet Spell Rainfall for Crop Planning at Jorhat (Assam), India
Keywords:Markov chain, Probability, Distribution, Probabilistic model, Onset, Withdrawal
In this study, frequency analyses of 1 to 6 consecutive days maximum rainfalls have been carried out. For this purpose, the daily rainfall data for 23 years has been collected from the Indian Meteorological Department (IMD), Guwahati for Jorhat Station. Based on L-moment, we consider the probability distributions like Log Normal (LN), Pearson Type III (P III), Log-Pearson Type III (LP III), and Extreme Value Type I (EVI). The best-fitting probability distribution for consecutive days maximum rainfall is discussed for estimating the rainfall in different return periods such as 2 to 100 years. Also, the daily rainfall data are converted to 52 standard meteorological weeks (SMW) to use the Markov Chain Probability model. Then average, maximum, minimum, standard deviation, and covariance of rainfall are calculated. By using this model, initial and conditional probabilities of dry and wet weeks are calculated. The probability of onset and withdrawal rainy season are calculated which are 95.83% chance during 23rd and 47th weeks. And, we find a relation of average rainfall and effective rainfall (ER) of the station.
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