MPhil Thesis

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Analysing the Variability of Rainfall Threshold Values for Drought Prognosis in Bangladesh
(University of Rajshahi, 2013) Alam, Md. Mahbub; Rahman, M. Sayedur; Hossain, Md. Ripter
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.
Pattern of Migration in Joypurhat District of Bangladesh: A Case Study
(University of Rajshahi, 2010) Talukder, Md. Ashraful Alom; Hossain, Md. Ripter; Rahman, Md. Mostafizur
This study is based on primary data. The primary data were collected from Joypurhat district by PPS sampling method. The main purpose of this study is to identify the effects of demographic and socio-economic variables on rural migration, trends and volume of migration and constructed some probability models on such data in J oypurhat district, Bangladesh. Both unvaried and multivariate techniques have been used to study the differentials and determinants of migration. The study reveals that the migration rate was found significantly higher for the people age groups 15-29 (about 28 per cent). The age distribution of migrants clearly shows that majority of them were very young at the time of their first migration. Education of migrants show that the 58 per cent of migrants were passed both SSC to graduate and above. The pre-migration occupation are 41 per cent of migrants were involved with studies, but after migration it was found 48 per cent of migrants were employed in job/service. In study area we found that about 44 per cent of migrants were migrated in Dhaka city. We also observed that more than 51 per cent of migrants were migrated with influencing of their family members (puss factor) and it is remarkable that about 74 per cent of migrants were migrated due to job/service at a particular place of destination(pull factor). The findings indicate that the variables 'education', 'occupation', and 'family size' included in the analysis have had significant effect on rural out-migration. The risk of out-migration was remarkably higher for the households whose member(s) attained at least primary education and the risk of out-migration was significantly higher for the household with occupation as non-agricultural labour. The multivariate logistic regression analysis has been used to identify the determinants of out-migration at household level. The risk of migration was 1.85, 5.00, 10.83 and 10.69 times higher for the households with educational level- primary, secondary, SSC/HSC (secondary school certificate/higher secondary certificate) and graduate respectively as compared to households with no education. The volume of migration showed that a positive relationship with diversity of social status(.307), education(.373) and occupation(.539). Only the education and occupation diversity have been found to be significantly related with volume of outmigration. The migration model proposed by Sivamurthy and Kadi (1984) were found suitable to describe the volume of out-migration for Bangladesh. Finally, we found that the probability distribution under such assumptions fitted well. The distribution of male migrants aged 15 years and above and the probability model have been worked out to describe the distribution of households according to total number of migrants under different assumptions.
Study of Climate Variability and Agriculture Drought in Bangladesh
(University of Rajshahi, 2013) Matin, Md. Abdul; Rahman, M. Sayedur; Hossain, Md. Ripter
The climate plays significant role in the agriculture of a country. Rainfall is the most important climate parameter affecting non-irrigated crop areas for Rangpur, Faridpur and Mymensingh. Water deficits and excess water are the greatest constraints for rain fed rice yields in this region. The daily rainfall data for 30 years during the period 1981-2010 of the station Rangpur, Faridpur and Mymensingh districts are considered in this study. This study also considered weekly rainfall for 5 mm and 10 mm. The daily data were reduced in the weekly form and the drought index has been calculated using the probability of Markov chain model and goodness of fit using chi-square test. Drought is temporary but complex feature of the climate system. Agriculture 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 best on the parameters of this model has been suggested for agriculture drought measurement in this region. The results indicate that the Rangpur, Faridpur and Mymensingh districts are as follows: For Drought Index of Rainfall 5 mm and 10 mm in Rangpur District: the results indicate that the Rangpur region were found the mild drought in Annual, the occasionally drought in pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. For Drought Index Rainfall 5 mm and 10 mm in Faridpur District: the Faridpur region were found the occasionally drought in Annual, pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. For Drought Index Rainfall 5 mm and 10 mm in Mymensingh District: the results indicate that the region were found the mild drought in Annual, the occasionally drought in pre-kharif and kharif season, and the chronic drought Proneness in Rabi season. This study will be constructive to agricultural planners and irrigation engineers to identifying there as where agricultural development should be focused as a long –term drought improvement strategy. The level of drought proneness helps the early detection of agricultural drought and the crop production that is useful for talking timely release and remedy measures and other decisions by several organization of Bangladesh. It will also contribute toward a better understanding of the climatology of drought in major monsoon region of the world.