Investigation of climatic factors affecting Canola production using TOPSIS multicriteria decision making approach in Ahar region

Document Type : Original Article

Authors

1 university of tabriz

2 Environmental Research Institute

Abstract

Considering the effect of climatic factors on Canola production in Ahar region, north west of Iran, a study was conducted to prioritize climatic and environmental criteria including 21 effective sub-criteria involved in canola production decrease. The required meteorlogical and agronomic data and information were collected directly or via questionnaires prepared by local experts. The relative importance of each sub-criteria was determined by TOPSIS method. The significat climate variables were downscaled by LARS-WG model under A1B, A2 and B1 scenarios. The results showed that the inadequate water availability and air temperature variations were rankied as the first and second most signficat contributors in canola yield reduction. The baseline period (2000-2017) mean annual rainfall of Ahar region is 270.8 mm. The projected mean annual rainfall under A1B, A2 and B1 scenarios were 53.2, 50.4 and 52.8 mm, respectively. Selecting proper adaption measures for cope with these changes is recommended for sustainable production of this crop in Ahar region.

Keywords

Main Subjects


Abedi, T., Mohammadi Limaei, S. 2018. Multi criteria decision making in forestry (models, methods and application. Environmental Research Institute. Guilan, Pp: 103. (In Farsi).
Akbari, M. 2014. Analysis of farmers adaptation strategies with climate change in Chamriz watershed. Thesis of the Department of Extension and Education, University of Tehran. (In Farsi).
Asgarpour, M. J. 2018. Multiple criteria decision making. University of Tehran press. Tehran. 15th Edition, Pp: 400.
Azari, M., Moradi, H. R., Saghafian, B., Faramarzi, M. 2013. Assessment of hydrological effects of climate change in Gourganroud River Basin. Journal of Water and Soil, 27(3): 537-547.
Azizi-Khalkheili, T., Zamani, Gh., Karami, E. 2016. Farmers adaptation to climate variation: barriers and suggested solutions. Agricultural Economics and Development, 30(3): 83-105. (In Farsi).
Babaiyan, I., modireyan, R., karimi, M. 2008. The assessment of climate change in Iran between 2070-2100 using the precis climate model. Third conference of water management in Iran, Tabriz.
Bagli, S., Terres, J. M., Gallego, J., Annoni, A., Dallemand, J. 2003. Agro Pedoclimatological Zoning of Italy, Definition of Homogeneous Pedo-climatic Zoning for Agriculture, Application to Maize, Durum Wheat, Soft Wheat, Spring Barley, Sugar Beet, Rapeseed, Sunflower, Soybean, Tomato, EUR 20550/EN, p 82.
Cercis, I., Beyaz, K. 2007. Climate conditions impact on canola cultural plant growing in turkey. http//: web.sakarya.edu.tr/~cikiel/ climatic conditions–impact-on–canola-ciltural-plant-growing-inturkey.pdf.
Chen, I. C., Hill, J. K., Ohlemüller, R., Roy, D. B., Thomas, C. D. 2011. Rapid range shifts of species associated with high levels of climate warming. Science, 333: 1024.
Cradock-Henry, N. 2008. Exploring perceptions of risks and vulnerability to climate change in New Zealand agriculture. Political Science, 60(1): 151 -1 55.
Dadashian Saray, M., Dashti, Gh., Hayati, B., Ghahremanzadeh, M. 2015. The Combined use of AHP and TOPSIS technique for determining the weighted criteria and evaluation of agricultural sustainability (Case Study: selected counties of East Azarbaijan province). Journal of Agricultural Science and Sustainable Production, 25(1): 145-157. (In Farsi).
Daneshkar Arasteh, P., Shokohi, A. R. 2008. Investigating the effects of climate change on meteorological conditions and surface water resources in Iran, 3rd Iranian national conference of water resources management, Tabriz, 48 pp. (In Farsi)
Dang, H. L., Li, E., Nuberg, I., Bruwer, J. 2014. A structural equation modelling study in the Mekong delta, Vietnam. Environmental Science & Policy, 41: 11-22.
Dastorani, M. T., Massah Bavani, A. R., Poormohammadi, S. 2010. Evaluation of the effects of climate change on drought in the future in Yazd area. Research project report, Faculty of Natural Resources, Yazd University, Iran. 52 pp. (In Farsi).
Esmaeili, R., Gandimkar, A., Ghayoor, A. 2011. Zoning of climate changes rate base on agriculture approach in future climatic period (case study Khorasan Razavi province). Geography and Environmental Planning Journal, 41(1): 35-52.
Fallah Heki, M. H., Yadavi, A., Movahhedi Dehnavi, M., Bonyadi, M. 2012. Effect of planting date on physiological and morphological characteristics of four canola cultivars in Yasouj. Journal of Crop Production and Processing, 2(4): 53-66.
Food and Agriculture Organization (FAO). 2017. Food outlook: Biannual report on global food markets. FAO Trade and Markets Division, Rome.
Farajzadeh Asl, M., kashki, A. R., Shayan, S. 2009. Analaysis of rain-fed wheat yield product variability using climate change approach (Case study area: Khorasan Razavi province). Quartery Modarres Human Sciences, 13(3): 227-256. (In Farsi).
Fu, C., Yang, S. 2012. The combination of dependence-based interval-valued evidential reasoning approach with balanced scorecard for performance assessment. Expert Systems with Applications, 39(3): 3717-3730.
Ghareli, A. A. 2001. Determining the value of agricultural water and optimum planting model in water shortage situation (Lands under the Doroudzan dam). Department of agricultural economics, Shiraz University. (In Farsi).
Hajarpour, A., Soltani, A., Zeinali, E., Sayyedi, F. 2013. Simulating the impact of climate change on production of Chickpea in rainfed and irrigated condition of Kermanshah. Journal of Plant Production, 20(2): 235-252. (In Persian).
Hwang, C. L., Yoon, K. 1981. Multiple attribute decision making: methods and applications. Springer-Verlag, New York.
Independent Police Complaints Commission (IPCC), Climate change). 2014. The physical Science Basis: Contribation of working Grepe I to the fifth assessment repert of the intergever mental panol on climate change, Cambridge university Press, Cambridge, unifend kigdem.
Kazemi rad, L., Mohammadi, H. 2016. Climate change assessment by using LARS-WG model in Gilan province (Iran). Geography and Environmental Hazards, 4(16): 55-73.
Kazemi Rad, L., Ghamgosar, M., Haghygh, M. 2014. Applying multiple-criteria decision-making of TOPSIS in droughts zoning of Guilan province. Geographic Space, 13(44): 203-217. (In Farsi).
Kenter, C., Hoffmann, C. M., Marlander, B. 2005. The effects of weather variableson-sugar beet yield development (Beta vulgaris L). European Journal of Agronomy, 24: 157-169.
Keshavarz, M. 2019. Addressing Compatibility of the farm management strategies with climate change: The case of Fars province. Iranian Agricultural Extension and Education Journal, 14(2): 107-123. (In Farsi).
Keshavarz, M., Karami, E., Zibaie, M. 2014. Adaptation of Iranian farmers to climate variability and change. Regional Environmental Change, 14(3): 1163-1174.
Khoush Akhlagh, F., Ranjbar Firouz Toulabi, S., Masoumpour Samakoush, J. 2010. Astudy on drought and its effects on water resources and agriculture in hydrologic water year of 1386-1387 (Case Study: Marvdasht county). Geography, 8(24): 119-136. (In Farsi).
Lobell, D. B., Sibley A and Ortiz-Monasterio J. 2012. Extreme heat effects on wheat senescence in India. Nature Climate Change, 2: 186–189.
Mohsenpour, R., Zibaei, M. 2010. Assessing the consequences of drought at farm level: A case study ofmarvdasht region. Quarterly Water and Soil Science, 14(52): 49-62. (In Farsi).
Mohsenzadeh, S., Namazi, N. R., Kardani Isfahani, A. S., Ahoomanesh, Z. 2017. Useing of TOPSIS technique in economic ranking of some kind cultivated wheat in Iran. Agricultural Economics, 11(1): 163-183. (In Farsi).
Mollaie, F., hosseini, S. M., Hejazi, S. Y., Pishbin, S. A. 2019. Explaining the adaptation strategies of farmers to climate change in South Khorasan Province. Iranian Agricultural Extension and Education Journal, 14(2): 83-105. (In Farsi).
Nazari, B., Liaghat, A., Akbari, M. R., Keshavarz, M. 2018. Irrigation water management in Iran: strategic planning for improving water use efficiency. Agricultural Water Management, 208: 7-18.
Omidvar, K., Mazidi, A., Doostmoradi, S. 2014. Climatic feasibility of rapeseed cultivation in Kermanshah province. Geography and Development Iranian Journal, 12(35): 97-116.
Ozturk, G., Dogan, M., Toker, O. S. 2014. Physicochemical, functional and sensory properties of mellorine enriched with different vegetable juices and TOPSIS approach to determine optimum juice concentration. Food Bioscience, 7: 45-55.
Pakdin Amiri, M., Pakdin Amiri, M., Pakdin Amiri, A. 2010. Prioritize effective financial factors on price stock in Tehran stock exchange with using TOPSIS method. Financial Research Journal, 10(26): 7-16. (In Farsi).
Park, J. S. Park, J. B. 2002. Maximum likelihood estimation of the 4-parameter Kappa distribution using the penalty method, Journal of Computersand Geosciences, 28: 65-68.
Pidgeon, J. D., Werker, A. R., Jaggard, K. W., Richter, G. M., Lister, D. H., Jones, P. D. 2001. Climatic impact on the productivity of sugar beet in Europe, 1961-1995, Agricultural and Forest Meteorology, 109.
Rahimi, D., Rahimi, Y. 2016. Resources in the impact’s climate change on floods in north of Iran. Geography and Environmental Planning, 27(1): 89-102.
Robertson, M. J., Holland, J. F., Bambach, R. 2004. Response of canola and Indian Musterd to sowing date in the grain belt of north- eastern Australia. Australian Journal of Experimental Agriculture, 44: 43-52.
Semenov, M. A. 2008. Simulation of extreme weather events by a stochastic weather generator. Climate Research, 35: 203-212.
Semenov, M. A., Brooks, R. J. 1999. Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain. Climate Research, 11: 137-148.
Sun, Y. F., Liang, Z. S., Viernstein, C. J., Unger, F. 2011. Comprehensive evaluation of natural antioxidants and antioxidant potentials in Ziziphus jujube Mill. var. spinosa (Bunge) Hu ex H. F. Chou fruits based on geographical origin by TOPSIS method. Food Chemistry, 124: 1612-1619.
Thiyam-Holländer, U., Eskin, N. A. M., Matthäus, B. 2012. Canola and rapeseed: production, processing, food quality, and nutrition. CRC Press. 374 P.
Thomas, D. L. 1990. Planting date effect and double cropping potential of rape in the south eastern V. S. Applied. Agricultural Research, 1(3): 205-211.
Vernon, L., Van Gool, D. 2006. Potential impacts of climate change on agricultural land use suitability canola. Resource Management Technical Report 303, http://www.agric.wa.gov.au/objtwr/imported _assets/content/lwe/cli/tr2006_canola_climate01.pdf.
Williams, A. G. 1991. Modeling future climates: From GCMs to statistical downscaling approaches. University of Toronto at Scarborough. 56p.
Withers, P. J. A., Evans, E. J., Bilsborrow, P. E., Milford, G. F. J., McGrath, S. P., Zaho, F. Walker, K. C. 1995. Development and prediction of sulphur deficiency in winter oilseed raps. H.G.C.A. Project Report, No. OS11, PP 22. www. Canola- council. Org.
Yalcin, N., Bayrakdaroglu, A., Kahraman, C. 2012. Application of Fuzzy multicriteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Systems with Applications, 39: 350-364.
Zavadskas, E. K., Vilutiene, T., Turskis, Z., Tamosaitiene, J. 2010. Contractor selection for construction works by applying SAW-G and TOPSIS Grey techniques. Journal of Business Economics and Management, 11:34-55.
Zhang, L., Zhang, Z., Chen, Y., Wei, X., Song, X. 2018. Exposure, vulnerability, and adaptation of major maize-growing areas to extreme temperature. Natural Hazards, 91(3): 1257-1272.