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Birhan Getachew
Debre Tabor University Department of Geography and Environmental Studies

Menberu Teshome
Debre Tabor University, Research and Community Service vice President, P.O. Box 272, Debre Tabor, Ethiopia

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Markov chain modeling of daily rainfall in Lay Gaint Woreda, South Gonder Zone, Ethiopia

Birhan Getachew, Menberu Teshome
  J. Degrade. Min. Land Manage. , pp. 1141-1152  
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Information on seasonal Kiremet and seasonal Belg rainfall amount is important in the rain fed agriculture of Ethiopia since more than 85% of the population is dependent on agriculture particularly on rain fed farming practices. The distribution pattern of rainfall rather than the total amount of rainfall within the entire period of time is more important for studying the pattern of rainfall occurrence. A two-state Markov chain was used to describe the characteristics of rainfall occurrences in this woreda. The states, as considered were; dry (d) and rainy (r). The overall chance of rain and the fitted curve tells us that the chance of getting rain in the main rainy season is about twice as compared to the small rainy season. The first order Markov chain model indicates that the probability of getting rain in the small rainy season is significantly dependent on whether the earlier date was dry or wet. While the second order Marko chain indicates that the main rainy season the dependence of the probability of rain on the previous two dates’ conditions is less as compared with the small rainy season. Rainfall amounts are very variable and are usually modeled by a gamma distribution. Therefore, the pattern of rainfall is somewhat unimodial having only one extreme value in August.  Onset, cessation and length of growing season of rainfall for the main rainy season show medium variation compared to the small rainy season.


cessation; gamma distribution; length of growing season; Markov chain; onset

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Araya, A. and Stroosnijder, L. 2011. Assessing drought risk and irrigation need in northern Ethiopia. Journal of Agricultural Meteorology 151: 425-436.

Ayalew, D., Tesfaye, K., Mamo, G., Yitaferu, B. and Bayu, W. 2012.Variability of rainfall and its current trend in Amhara Region, Ethiopia. African Journal of Agricultural Research 7(10):1475–1486.

Barkotulla, M.A.B. 2010. Stochastic generation of the occurrence and amount of daily rainfall. Pakistan Journal of Statistics and Operation Research 6(1): 61-73.

Barron, J.2004. Dry spell mitigation to upgrade semi-arid rainfed agriculture: Water harvesting and soil nutrient management for smallholder maize cultivation in Machakos, Kenya. Doctoral thesis in Natural Resource Management. Department of Systems Ecology, Stockholm University, S-106 91 Stockholm, Sweden.

Bewket, W. 2009. Rainfall variability and crop production in Ethiopia; Case study in the Amhara region. Proceeding of the 16th International Conference of Ethiopian Studies, Addis Ababa, Ethiopia.

Engida, M. 2005.Agroclimatic determination of the growing season over Ethiopia. Ethiopian Journal of Agricultural Sciences 18:13-27.

Gabriel, K.R. and Neumann, J. 1962. A Markov chain model for daily rainfall occurrences at Tel Aviv. Quarterly Journal of Royal Meteorological Society 88:90-95.

Garg, V.K. and Singh, J.B. 2010. Markov chain approach on the behavior of rainfall. International Journal of Agricultural and Statistical Sciences 6(1).

Getachew, B. 2017. Impacts of climate change on crop yields in South Gonder Zone, Ethiopia. World Journal of Agricultural Research 5 (2):102-110. doi: 10.12691/wjar-5-2-6.

Hadgu, G., Tesfaye, K., Mamo, G. and Kassa, B. 2013. Trend and variability of rainfall in Tigray, Northern Ethiopia: Analysis of meteorological data and farmers’ perception. Academia Journal of Environmental Sciences 1(8): 159-171.

Hare, F.K. 1983. Climate and Desertification. Revised analysis (WMO-UNDP) WCP-44 pp5-20. Geneva, Switzerland.

Hussain, Z. 2004. Analysis of daily rainfall data of different sites in Khyber pakhtunkhwa to give agronomically useful results. Higher Education Commision (HEC), Islamabad Project Report.

IPCC (2007). Climate Change 2007. The Physical Science Basis. Cambridge: Cambridge University Press.

IPCC (Intergovernmental Panel on Climate Change). 2014. Climate change 2014: Impacts, adaptation, and vulnerability. Working Group II contribution to the IPCC Fifth Assessment Report. Cambridge, United Kingdom: Cambridge University Press.

Jones, P.G. and Thornton, P.K. 2002.Spatial modeling of risk in natural resource management.Conservation Ecology 5(2): 27. [online]

Kassie, B.T., Rotter, R.P., Hengsdijk, H., Asseng, S., VanIttersum, M.K., Kahiluoto, H. and Van Keulen, H. 2014. Climate variability and change in the Central Rift Valley of Ethiopia: challenges for rain fed crop production. Journal of Agricultural Science 152: 58-74.

Larsen, G.A. and Pense, R.B. 1982. Stochastic simulation of daily climatic data for agronomic models. Agronomy Journal 74:510-514.

Medhi, J. 1981. Stochastic Process.John Wiley & Sons.

Mekasha, A., Tesfaye, K. and Duncan, A.J. 2014.Trends in daily observed temperature and precipitation extremes over three Ethiopian eco-environments. International Journal of Climatology 34:1990-1999.

Michael, C. 2006.World Wide Fund for Nature Climate Change Scientist, Gland, Switzerland.

Mugalavai, E.M. 2007. A study of rainfall characteristics in a rainfed agricultural establishment: case study of the Kenyan Lake Victoria basin region. M.Phil. Thesis. Moi University, Kenya, pp. 116.

Muluneh, G. 2015. Analysis of Past and Future Intra-Seasonal Rainfall Variability and its Implications for Crop Production in the North Eastern Amhara Region, Ethiopia. MA. Thesis

NMA. 2007. Climate Change National Adaptation program of Action (NAPA) of Ethiopia. Addis Ababa: NMA, Oxfam International.

Reddy, G.V.S., Bhaskar,S.R., Purohit, R.C. and. Chittora, A.K. 2008. Markov Chain Model probability of dry, wet weeks and statistical analysis of weekly rainfall for agricultural planning at Bangalore. Karnataka Journal of Agricultural Sciences 21 (1): 12-16.

Richardson, C.W. 1985. Weather simulation for crop management models. Transactions of the ASAE 28:1602-1606.

Roldan, J. and Woolhiser, D.A. 1982. Stochastic daily precipitation models, 1. A comparison of occurrence processes. Water Resources Research 18:1461-1468.

Senthilvelan, A., Ganesh, A. and Banukumar, K. 2012. Markov Chain Model for probability of weekly rainfall in Orathanadu Taluk, Thanjavur District, Tamil Nadu. International Journal of Geomatics and Geosciences 3 (1): 191-203.

Sharda, V.N. and P.K Das. 2005. Modelling weekly rainfall data for crop planning in a sub-humid climate of India. Agricultural Water Management 76(2); 120-138.

Siddiqi, M.J. 1992. Gamma distribution function for modeling rainfall amounts of Faisalabad. Journal of Engineering and Applied Sciences 11 (2): 69-76.

Simelton, E., Quinn, C.H., Batisani, N., Dougill, A.J., Dyer, J. C., Fraser, E.D.G., Mkwambisi, D., Sallu, S. and Stringer, L.C. 2013. Is rainfall really changing? Farmers’ perceptions, meteorological data, and policy implications. Climate and Development 5 (2): 123-138. doi: 10.1080/ 17565529.2012.751893

Stern, R.D. and Coe, R. 1984. A model fitting analysis of daily rainfall data. Journal of the Royal Statistical Society Series A (General)147 (1): 1-34.

Stern, R.D., Dennett,M.D. and Dale, I.C. 1982: Analysing daily rainfall measurements to give agronomically useful results, II. A modelling approach. ExperimentalAgriculture 18: 237-253.

Taye, M., Zewdu, F. and Ayalew, D. 2013. Characterizing the climate system of Western Amhara, Ethiopia: a GIS approach.American Journal of Research Communication 1(10): 319-355.

Travis, L. and Daniel, S. 2010: Agricultural Technologies for Climate Change Mitigation and Adaptation in Developing Countries: Policy Options for Innovation and Technology Diffusion. International Centre for Trade and Sustainable Development -IPC Platform on Climate Change, Agriculture and Trade. Issue Brief No. 6. 33 p.

Udom. A. 2010. Element of Applied Mathematical Statistics. ICIDR Publishing House.

Umoh, A.A, Akpan, A.O. and Jacob, B.B.2013. Rainfall and relative humidity occurrence patterns in Uyo Metropolis, AkwaIbom State,South-South Nigeria.IOSR Journal of Engineering 3(8): 27-31.

UN-OHRLLS, 2009.The impact of climate change on the development project of the least developed countries and small island developing states.


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