Agricultural drought analysis of Chapai Nawabganj district in Bangladesh

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Research Paper 01/09/2012
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Agricultural drought analysis of Chapai Nawabganj district in Bangladesh

M. A. B. Barkotulla
J. Bio. Env. Sci.2( 9), 60-67, September 2012.
Certificate: JBES 2012 [Generate Certificate]

Abstract

The occurrence of agricultural drought is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop production. The stochastic behaviors of the largest rainfall amounts were predicted using a first order Markov model. The analysis was carried out using mean, variance, simple and conditional probabilities of dry and wet days. An analysis of variance (ANOVA) was carried out on the rainfall data of some studied areas established and it was found that the annual and seasonal rainfall variability between the stations were insignificant. The daily rainfall data was used to represent the rainfall features of the Chapai Nawabganj district in this study. The monthly rainfall analysis of the different rainy seasons showed high variability. There was also significant monthly variability in rainy days. The analysis of rainfall found that approximately 75% rainfall amount occurred in the months June to September. The seasonal probabilities of occurrencr of rainfall amount were derived from the cumulative distribution function of rainfall amount. During the Kharif season, there were the highest rainfall amounts when compared with other seasons.

VIEWS 22

Ahmed A, Shibasaki R. 2000. Climate change and agricultural food production of Bangladesh: an impact assessment using gis-based biophysical crop simulation model. In: The 21st Asian Conference on Remote Sensing held on December 4-8, Taipei, Taiwan (AARS).

Anderson TW, Goodman LA. 1957. Statistical inference about Markov Chains. Annals of Mathematicals Statistics 28, 89-110.

BBS (Bangladesh Bureau of Statistics). 1996. Bangladesh Bureau of Statistics. Statistics Division, Government of the People’s Republic of Bangladesh, Dhaka, Bangladesh.

Biamah EK, Nagaya LM, Gichangi EM, Cherogony RKK. 1994. Microscale effects of Tillage and Organic Manure on Infiltration and Erosion of a Crusting Soil. vol. 1:387-405. Proceedings of 13th International Soil Tillage research Conference, July, Aalborg, Denmark.

Biamah EK, Sterk G, Sharma TC. 2004. Analysis of agricultural drought in Liuni,Eastern Kenya: Application of Markov model. Journal of Hydrological Processes 19(6), 1307-1322.

Bogardi JJ, Duckstein L, Ruhambo 0H. 1988. Practical generation of synthetic rainfall event series in a semi-arid climate zone, Journal of Hydrology 103, 357-313.

Bonacci 0. 1993. Hydrological identification of drought, Journal of Hydrological Processes 7, 249-262.

Gabriel UK, Neumann J. 1957. Distribution of weather cycles by lengths. Quarterly Journal of Royal Metorologycal Society 83, 375-380.

Gabriel UK, Neumann J. 1961. A Markov chain model for daily rainfall occurrence at Tel Aviv. Quarterly Journal of Royal Metorologycal Society 88, 90-95.

Katz RW. 1974. Computing probabilistic associate /for precipitation. Journal of Applied Meteorology 13, 953.

Kottegoda NT. 1980. Stochastic Water Resources Technology, London, McMillan, p. 288.

Llamas J. 1987. Risk of drought and future water requirements on a regional scale, Water Resources Development 3(4), 260-265.

Nieuwolt S. 1978. Rainfall variability and drought frequencies in East Africa. Erdkunde 32, 81-88.

Ochola WO, Kerkides P. 2003. A Markov chain simulation model for predicting critical wet and dry sells in Kenya: Analysing rainfall events in the Kano plains. Irrigation and Drainage 52, 327-342

Rahman MS, Alam MS. 1997. Patterns of rainfall variability and trend in the high Barind region. Rajshahi University Studies Journal of Science, Part-B, 23-24, 135-148.

Rahman MS. 1999a. A stochastic simulated Markov Chain Model for daily rainfall at Barind, Bangladesh. Journal of Interdisciplinary Mathematics 2(1), 7-32.

Rahman MS. 1999b. Logistic regression estimation of a simulated Markov Chain Model for daily rainfall in Bangladesh. Journal of Interdisciplinary Mathematics 2(1), 33-40.

Razzaque MG. 2006. An overview of disasters and disaster communications in Bangladesh. ITU/ESCAP Disaster Communications Workshop, 12-15 Dec. Bangkok, Thailand.

Sen Z. 1978. Auto-run analysis of hydrologic time series, Journal of Hydrology 36, 75-85.

Sen Z. 1980. Statistical analysis of hydrological critical droughts, Journal of Hydraulics Division, ASCE 106, 99-l 15.

Sharma TC. 1994. Stochastic features of drought in Kanya. East Africa. 1, 125-137. Kluwer Academic Publishers. The Netherlands.

Sharma TC. 1996. A Markov-Weibull Rain-Sum Model for Designing Rain Water Catchment Systems. Water Resources Management 10, 147-162.

Todorovic P, Woolhiser DA. 1975. A stochastic model of n day precipitation, Journal of Applied Meteorology 14, 125-137.

Yevjevich V. 1967. An objective approach to definitions and investigations of continental hydrologic droughts. Hydrology Paper 23, Colorado State University, Fort Collins, Colorado, U.S.A. p. 18.

Yevjevich V. 1972. Stochastic Processes in Hydrology, Water Resources Publications, Fort Collins, Colorado, U.S.A., p. 186-192.