Analysing the Variability of Rainfall Threshold Values for Drought Prognosis in Bangladesh

Abstract

The Rainfall plays a significant role in the agriculture of country. Rainfall is the most important weather parameter affecting non-irrigate crop areas for Bogra, Jessore and Feni water deficits and excess water are the greatest constraints for rainfall rice yields in this region. The daily rainfall data for 30 years during the period 1981-2010 of the rainfall stations in Bogra, Jessore and Feni are considered in this study. The daily data were reduced in the weekly form and the drought index has been calculated using the probability of Markov chain model. Drought is temporary but complex feature of the climate system. Agricultural drought is mainly concerned with inadequacy of rainfall. Markov chain model have been used to evaluate probabilities of getting a sequence of wet-dry weeks over this region. An index based on the parameters of this model has been suggested for agricultural drought measurement in this region. The results of our Bogra district annually rainfall data we observed the moderate drought, pre-kharif rainfall data we observed the mild occasional and moderate drought, kharif rainfall data we observed the occasional and rabi rainfall data we observed the chronic prone. As a result failure of rains and the occurrence of drought during any particular growing season lead to severe food shortages. A Markov Chain model is established to fit daily rainfall data for the various aspects of rainfall occurrence patterns and could be mathematically derived from the Markov Chain by using maximum likelihood estimate and these were also established to fit the observed data. The rainfall probability was not found to very much during rabi (November- February) season. But much more variation of rainfall probabilities was observed during both kharif (June-October) and pre-kharif (March- May) seasons. Obviously, one would presume conditions variation in these probabilities also yearly, seasonally and annually. Based on these findings and using chi-square test, it could be concluded that the model fit was good. This study investigates the methods to obtain estimates of the conditional probabilities, the probability of success and its probability distribution to describe the yearly, seasonal and annual variability. The limited data set the results are quite good and the model is doing a reasonably good job of daily rainfall.