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Application of Agent-Based Modeling in Agricultural Productivity in Rural Area of Bahir Dar, Ethiopia

Author

Listed:
  • Sardorbek Musayev

    (The Center for Sustainable Agriculture, University of Vermont, Burlington, VT 05405, USA)

  • Jonathan Mellor

    (Department of Civil and Environmental Engineering, University of Massachusetts Dartmouth, Dartmouth, MA 02747, USA)

  • Tara Walsh

    (Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06268, USA)

  • Emmanouil Anagnostou

    (Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06268, USA)

Abstract

Effective weather forecast information helps smallholder farmers improve their adaptation to climate uncertainties and crop productivity. The main objective of this study was to assess the impact of weather forecast adoption on crop productivity. We coupled agent-based and crop productivity models to study the impact of farmers’ management decisions on maize productivity under different rainfall scenarios in Ethiopia. A household survey was conducted with 100 households from 5 villages and was used to validate the crop model. The agent-based model (ABM) analyzed the farmers’ behaviors in crop management under different dry, wet, and normal rainfall conditions. ABM results and crop data from the survey were then used as input data sources for the crop model. Our results show that farming decisions based on weather forecast information improved yield productivity from 17% to 30% under dry and wet seasons, respectively. The impact of adoption rates due to farmers’ intervillage interactions, connections, radio, agriculture extension services, and forecast accuracy brought additional crop yields into the Kebele compared to non-forecast users. Our findings help local policy makers to understand the impact of the forecast information. Results of this study can be used to develop agricultural programs where rainfed agriculture is common.

Suggested Citation

  • Sardorbek Musayev & Jonathan Mellor & Tara Walsh & Emmanouil Anagnostou, 2022. "Application of Agent-Based Modeling in Agricultural Productivity in Rural Area of Bahir Dar, Ethiopia," Forecasting, MDPI, vol. 4(1), pages 1-22, March.
    • Handle: RePEc:gam:jforec:v:4:y:2022:i:1:p:20-370:d:770122
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    1. Happe, K. & Hutchings, N.J. & Dalgaard, T. & Kellerman, K., 2011. "Modelling the interactions between regional farming structure, nitrogen losses and environmental regulation," Agricultural Systems, Elsevier, vol. 104(3), pages 281-291, March.
    2. Rashid, Shahidur & Minot, Nicholas, 2010. "Are Staple Food Markets in Africa Efficient? Spatial Price Analyses and Beyond," Food Security Collaborative Working Papers 58562, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    3. Bert, Federico E. & Laciana, Carlos E. & Podesta, Guillermo P. & Satorre, Emilio H. & Menendez, Angel N., 2007. "Sensitivity of CERES-Maize simulated yields to uncertainty in soil properties and daily solar radiation," Agricultural Systems, Elsevier, vol. 94(2), pages 141-150, May.
    4. Narayan, Deepa & Pritchett, Lant, 1999. "Cents and Sociability: Household Income and Social Capital in Rural Tanzania," Economic Development and Cultural Change, University of Chicago Press, vol. 47(4), pages 871-897, July.
    5. Franklin Nantui Mabe & Prince Nketiah & Daniel Darko, 2014. "Farmers’ willingness to pay for weather forecast information in Savelugu-Nanton municipality of the Northern region," Russian Journal of Agricultural and Socio-Economic Sciences, CyberLeninka;Редакция журнала Russian Journal of Agricultural and Socio-Economic Sciences, vol. 36(12), pages 34-44.
    6. Sardorbek Musayev & Jonathan Mellor & Tara Walsh & Emmanouil Anagnostou, 2021. "Development of an Agent-Based Model for Weather Forecast Information Exchange in Rural Area of Bahir Dar, Ethiopia," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    7. Magreta, Ruth & Edriss, Abdi-Khalil & Mapemba, Lawrence D. & Zingore, S., 2013. "Economic Efficiency of Rice Production in Smallholder Irrigation Schemes: A Case of Nkhate Irrigation Scheme in Southern Malawi," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 161636, African Association of Agricultural Economists (AAAE).
    8. Omulo, Godfrey & Kumeh, Eric Mensah, 2020. "Farmer-to-farmer digital network as a strategy to strengthen agricultural performance in Kenya: A research note on ‘Wefarm’ platform," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. Oecd, 2009. "Climate Change and Africa," OECD Journal: General Papers, OECD Publishing, vol. 2009(1), pages 5-35.
    10. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad & Sahrbacher, Christoph, 2008. "Does structure matter? The impact of switching the agricultural policy regime on farm structures," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 431-444, August.
    11. Tsedeke Abate & Bekele Shiferaw & Abebe Menkir & Dagne Wegary & Yilma Kebede & Kindie Tesfaye & Menale Kassie & Gezahegn Bogale & Berhanu Tadesse & Tolera Keno, 2015. "Factors that transformed maize productivity in Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(5), pages 965-981, October.
    12. Fadare, Olusegun Ayodeji & Akerele, Dare & Toritseju, Begho, 2014. "Factors Influencing Adoption Decisions Of Maize Farmers In Nigeria," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 2(3), pages 1-10, July.
    13. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    14. Ziervogel, Gina & Bithell, Mike & Washington, Richard & Downing, Tom, 2005. "Agent-based social simulation: a method for assessing the impact of seasonal climate forecast applications among smallholder farmers," Agricultural Systems, Elsevier, vol. 83(1), pages 1-26, January.
    15. Reidsma, Pytrik & Janssen, Sander & Jansen, Jacques & van Ittersum, Martin K., 2018. "On the development and use of farm models for policy impact assessment in the European Union – A review," Agricultural Systems, Elsevier, vol. 159(C), pages 111-125.
    16. van Rijn, Fédes & Bulte, Erwin & Adekunle, Adewale, 2012. "Social capital and agricultural innovation in Sub-Saharan Africa," Agricultural Systems, Elsevier, vol. 108(C), pages 112-122.
    17. Maurizio Bacci & Youchaou Ousman Baoua & Vieri Tarchiani, 2020. "Agrometeorological Forecast for Smallholder Farmers: A Powerful Tool for Weather-Informed Crops Management in the Sahel," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    18. Hansen, James W. & Mishra, Ashok & Rao, K.P.C. & Indeje, Matayo & Ngugi, Robinson Kinuthia, 2009. "Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya," Agricultural Systems, Elsevier, vol. 101(1-2), pages 80-90, June.
    19. Hammer, G. L. & Hansen, J. W. & Phillips, J. G. & Mjelde, J. W. & Hill, H. & Love, A. & Potgieter, A., 2001. "Advances in application of climate prediction in agriculture," Agricultural Systems, Elsevier, vol. 70(2-3), pages 515-553.
    20. Mark Brady & Konrad Kellermann & Christoph Sahrbacher & Ladislav Jelinek, 2009. "Impacts of Decoupled Agricultural Support on Farm Structure, Biodiversity and Landscape Mosaic: Some EU Results," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(3), pages 563-585, September.
    21. Kenkel, Philip L. & Norris, Patricia E., 1995. "Agricultural Producers' Willingness To Pay For Real-Time Mesoscale Weather Information," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(2), pages 1-17, December.
    22. Happe, Kathrin & Kellermann, Konrad & Balmann, Alfons, 2006. "Agent-based analysis of agricultural policies: An illustration of the agricultural policy simulator AgriPoliS, its adaptation and behavior," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(1).
    23. Block, P. J., 2008. "Mitigating the effects of hydrologic variability in Ethiopia: an assessment of investments in agricultural and transportation infrastructure, energy and hydroclimatic forecasting," IWMI Working Papers H042798, International Water Management Institute.
    24. Tepic, M. & Trienekens, Jacques H. & Hoste, R. & Omta, S.W.F. (Onno), 2012. "The Influence of Networking and Absorptive Capacity on the Innovativeness of Farmers in the Dutch Pork Sector," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(3), pages 1-34, September.
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