A Two-Stage Model for Rice Cultivation Preparation Considering Dynamic Uncertainty: A Case Study in Iran

Document Type : Original Article

Authors

1 Master student, Iran University of Science and Technology

2 Associate Professor, Iran University of Science and Technology.

Abstract

As one of the essential commodities in the agricultural sector, rural farmers generally cultivate rice based on experience in agricultural fields. This method of cultivation has led to a waste of natural resources. In this study, the aim is to find suitable areas and determine the pattern of rice cultivation using a two-phase methodology. In the first phase, GIS integration and the best-worst method have been used to classify suitable areas for rice cultivation in Iran. The first phase's result is considered an input to the second phase, i.e., the optimization model to determine the pattern of rice cultivation. A multi-stage stochastic optimization approach has been used in the second phase to consider the weather uncertainty in all periods. Climatic conditions in each period are modeled in three scenarios. The application of the proposed model has been investigated in a case study in Iran. As a result, it has been observed that most of the suitable areas for rice cultivation are located in the north and western parts of Iran. Also, the suitable cultivation pattern for most rice farmers is the high-yield cultivation using the transplanting method.

Keywords

Main Subjects

References

1.Antoine, J., Fischer, G., & Makowski, M. (1997). Multiple criteria land use analysis. Applied Mathematics and Computation, 83(2–3), 195–215.
2. Asadi, A., Kalantari, K., & Choobchian, S. (2012). Structural analysis of factors affecting agricultural sustainability in Qazvin Province, Iran. Journal of Agricultural Science and Technology, 15(1), 11–22.
3. Babazadeh, R., Razmi, J., Pishvaee, M.S., & Rabbani, M. (2015). A non-radial DEA model for location optimization of Jatropha curcas L. cultivation. Ind. Crops Prod. 69, 197–203.
4. Bagamba, F., Bashaasha, B., Claessens, L., Antle, J., & Economics, R. (2012). Assessing climate change impacts and adaptation strategies for smallholder agricultural systems in Uganda. Assessing Climate Change Impacts and Adaptation Strategies for Smallholder Agricultural Systems in Uganda, 20(2), 303–316.
5. Ceballos-Silva, A., & López-Blanco, J. (2003). Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and land use/cover mapping: A case study in Central Mexico. Agricultural Systems, 77(2), 117–136.
6. Collins, M. G., Steiner, F. R., & Rushman, M. J. (2001). Land-use suitability analysis in the United States: Historical development and promising technological achievements. Environmental Management, 28(5), 611–621.
7. Dantzig, G. B., & Infanger, G. (1993). Approaches to Stochastic Programming with Application to Electric Power Systems. In Optimization in Planning and Operation of Electric Power Systems (pp. 125–138).
8. Dedeoğlu, M., & Dengiz, O. (2019). Generating of land suitability index for wheat with hybrid system aproach using AHP and GIS. Computers and Electronics in Agriculture, volume 167,105062.
9. Dengiz, O. (2013). Land suitability assessment for rice cultivation based on GIS modeling. Turkish Journal of Agriculture and Forestry, 37(3), 326–334.
10. Dengiz, O., Özyazici, M. A., & Sağlam, M. (2013). Multi-criteria assessment and geostatistical approach for determination of rice growing suitability sites in Gokirmak catchment. Paddy and Water Environment, 13(1), 1–10.
11. FAO. (1976). A framework for land evaluation. Rome: Food and Agricultural Organization of the United Nations. In FAO soils bulletin n.32. https://doi.org/M-51
12. FAO. (1996). Guidelines for Land-use Planning - Food and Agriculture Organization of the United Nations. Retrieved from
13. Getachew Tesfaye Ayehu, S. A. (2015a). Land Suitability Analysis for Rice Production: A GIS Based Multi-Criteria Decision Approach. American Journal of Geographic Information System, 4(3), 95–104.
14. Gregory, P. J., & George, T. S. (2011). Feeding nine billion: The challenge to sustainable crop production. Journal of Experimental Botany, 62(15), 5233–5239.
15. Hossain, M. S., Chowdhury, S. R., Das, N. G., & Rahaman, M. M. (2007). Multi-criteria evaluation approach to GIS-based land-suitability classification for tilapia farming in Bangladesh. Aquaculture International, 15(6), 425–443.
16. Jafarnezhad, A., Kazemi, A., & Aarab, A. (2016). Location with Geographic Information System and maximum weight coverage model. Journal of Industrial Management  erspective, 10(39), 143-170 (In Persian)
17. Kashanian, M., Pishvaee, M. S., & Sahebi, H. (2020). Sustainable biomass portfolio sourcing plan using multi-stage stochastic programming. Energy, 204, 117923.
18. Kihoro, J., Bosco, N. J., & Murage, H. (2013). Suitability analysis for rice growing sites using a multicriteria evaluation and GIS approach in great Mwea region, Kenya. SpringerPlus, 2(1), 1–9.
19. Kiker, G. A., Bridges, T. S., Varghese, A., Seager, P. T. P., & Linkov, I. (2005, April 1). Application of multicriteria decision analysis in environmental decision making. Integrated Environmental Assessment and Management, 1, 95–108.
20. King, R. P., & Robison, L. J. (1984). Risk efficiency models. In Risk Management in Agriculture (pp. 68–75).
21. Konan-Waidhet, A., Dibi, B., Kouadio, Z., & Savane, I. (2015). Modeling of Suitable Areas for Rainfed Rice Growing Using Multicriteria Approach in Geographic Information System: Case of Denguele (North West of Côte d’Ivoire). British Journal of Applied Science & Technology, 6(1), 95–104.
22. Kunwar, P., Kachhwaha, T. S., Kumar, A., Agrawal, A. K., Singh, A. N., & Mendiratta, N. (2010). Use of high-resolution IKONOS data and GIS technique for transformation of landuse/landcover for sustainable development. Current Science, 98(2), 204–212.
23. Maddahi, Z., Jalalian, A., Zarkesh, M. M. K., & Honarjo, N. (2017). Land suitability analysis for rice cultivation using a GIS-based fuzzy multi-criteria decision making approach: Central part of amol district, Iran. Soil and Water Research, 12(1), 29–38.
24. Malczewski, J. (2004, July 1). GIS-based land-use suitability analysis: A critical overview. Progress in Planning, 62, 3–65.
25. Mohaghar, A., & Ariyai, S.(2017). Location Selection of Solar Power Plants, Wind and Distributed Generation and Degisn of Electrical Distribution Network. Journal of Industrial Management Perspective, 10(39), 143-170 (In Persian)
26. Mostafa Abbasi, A., Pishvaee, M.S., & Bairamzadeh, S. (2020). Land suitability assessment for Paulownia cultivation using combined GIS and Z-number DEA: A case study. Computers and Electronics in Agriculture, 176, 56-66
27. Nielsen, S., & Möller, B. (2013). GIS based analysis of future district heating potential in Denmark. Energy, 57, 458–468.
28. Nyeko, M. (2012). GIS and Multi-Criteria Decision Analysis for Land Use Resource Planning. Journal of Geographic Information System, 04(04), 341–348.
29. Raza, S. M. H., Mahmood, S. A., Khan, A. A., & Liesenberg, V. (2018). Delineation of Potential Sites for Rice Cultivation Through Multi-Criteria Evaluation (MCE) Using Remote Sensing and GIS. International Journal of Plant Production, 12:1-11
30. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega (United Kingdom), 53, 49–57.
31. Ristić, V., Maksin, M., Nenković-Riznić, M., & Basarić, J. (2018). Land-use evaluation for sustainable construction in a protected area: A case of Sara mountain national park. Journal of Environmental Management, 206, 430–445.
32. Robinson, S., Toulmin, C., Muir, J. F., Godfray, H. C. J., Pretty, J., Haddad, L., … Crute, I. R. (2010). Food Security: The Challenge of Feeding 9 Billion People. Science, 327(5967), 812–818
33. Selim, S., Koc-San, D., Selim, C., & San, B. T. (2018). Site selection for avocado cultivation using GIS and multi-criteria decision analyses: Case study of Antalya, Turkey. Computers and Electronics in Agriculture, 154, 450–459.
34. Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., Ghorbani, M. A., & Shahbazi, F. (2018). Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma, 310, 178–190.
35. Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., & McDowell, R. W. (2019). Development of a model using matter element, AHP and GIS techniques to assess the suitability of land for agriculture. Geoderma, 352, 80–95.
36. Shahbazi, F., Sahebi, H., & Makui, A. (2020). Location Selection of Solar Power Plants, Wind and Distributed Generation and Degisn of Electrical Distribution Network.
, 10(39), 143-170 (In Persian)
37. Sharifi, M. A., Boerboom, L., Shamsudin, K. B., & Veeramuthu, L. (2006). Spatial Multiple Criteria Decision Analysis in Integrated Planning for Public Transport and Land Use Development Study in Klang Valley , Malaysia. ISPRS Technical Commission II Symposium, (July), 85–94. Retrieved from
38. Surmaini, Runtunuwu, L. (2010). Upaya Sektor Pertanian Dalam Menghadapi. (98), 1–7.
39. Thompson, J. A., Bell, J. C., & Butler, C. A. (2001). Digital elevation model resolution: Effects on terrain attribute calculation and quantitative soil-landscape modeling. Geoderma, 100(1–2), 67–89.
40. Xu, E., & Zhang, H. (2013). Spatially-explicit sensitivity analysis for land suitability evaluation. Applied Geography, 45, 1–9.
41. Zhang, J., Su, Y., Wu, J., & Liang, H. (2015). GIS based land suitability assessment for tobacco production using AHP and fuzzy set in Shandong province of China. Computers and Electronics in Agriculture, 114, 202–211.
42. Zeng, X., Kang, S., Li, F., Zhang, L., Guo, P., 2010. Fuzzy multi-objective linear programming applying to crop area planning. Agric. Water Manag., 98, 134–142.

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