Agroecological zoning of agricultural lands in Golestan province for Faba bean (Vicia faba L.) cultivation by ordered weighted average (OWA)

Document Type : Original Research

Authors
Y. Komaki 1
A. Rahemi-karizaki 2
A. nakhzari moghaddam 3
H. faramarzi 4
1 Student
2 Assistance professor of Plant Production Department
3 Assistant Professor of Plant Production Department
4 PhD student of Forestry, Faculty of Natural Resources, Tarbiat Modarres University of Noor
Abstract
Introduction:

Faba bean is one of the main winter crops in Golestan province (northeast Iran), with an estimated production of about 106,284 tons of green pods and 7256 tons of dry grain while the harvesting land area is about 1838 ha. Topographic characteristics, climatic conditions and the soil quality of an area are the most important parameters to evaluate land suitability. To develop successful cropping systems, it is necessary to understand how a crop such as faba bean responds to biological, chemical, physical, and climatic variables, and how this response can be influenced by management. Accordingly, farmers can improve their production in this district, and at the end of the study, the distribution and areas of land suitable for faba bean cultivation in Aq Qala were determined. In addition, this research provides information at a local level that could be used by farmers to select cropping patterns in accordance with suitability results.

Materials and methods:

The study areas of the research include agricultural lands and rangelands of Golestan province Using 1: 50,000 maps of the national cartographic center of Iran, we created a 20 m digital elevation model (DEM) with a topo-to-raster function. In this study, the first agro-ecological requirements of faba bean were determined according to scientific resources. Several parameters were considered in this study, including the annual average, minimum and maximum temperatures, annual precipitation, slope, elevation, and some soil properties such as organic matter, pH, EC, texture, phosphorus, potassium and calcium. The last 12-year climatic data were gathered from 4 meteorological stations and 21 rain gauge stations in the Golestan province. The mean temperatures were calculated from daily mean minimum and maximum temperature data. The rainfall and temperature data of the whole province were used to interpolate and draw map of annual rainfall, and annual average, maximum and minimum temperature by geostatistical and interpolation methods. The slope and elevation information was obtained from the Digital Elevation Model (DEM) using GIS software. The standardization of data was used from fuzzy method and Analytic Hierarchy Process (AHP) was used for weighting the criteria. Finally, using ordered weighted average (OWA) in the IDRISI software, faba bean cultivation potential map was prepared.

Results and Discussion

The results indicated that the most important variables, according to their specific weighting, were annual precipitation during the growing season (0.2876), slope (0.5396) and EC (0.3913). The digital environmental layers overlaid and integration in GIS media, then zoning of lands were carried out in 4 classes (highly suitable, suitable, less suitable and non-suitable). The study area includes different classes with diverse capacities for faba been cultivation comprising: a highly suitable potential, which constitutes 55.78% of the total area; a suitable class, 27.82%; a less suitable, 12.23%; and non-suitable, 4.17%. The final maps showed that more than 80% of agricultural lands of township are suitable for faba bean production. This research provides information at a local level that could be used by farmers and decision makers to select cropping patterns in accordance with their suitability. The topography, soil characteristics and climatic conditions were the most important determinant parameters of this evaluation. Our results revealed that 86.60% of the land area is suitable for faba bean cultivation. From the land suitability analysis, it was concluded that, in general, some nutrient contents of the soil are low or high for the study region. In addition, the research results indicated that the main limiting factors are high EC and low rainfall.

Conclusion

In conclusion, a combination of GIS, AHP and OWA is a practical and applicable method for determining land suitability for faba bean crops. In this study, the time-saving during the development of the land suitability map for faba bean was considerable. This method is almost a new application in Iran for land suitability analysis. However, decision makers should consider the side effects of applying these methods in the determination of suitable areas for crop growing. The result in of this study indicated that the OWA is a valuable approach in land suitability assessment, therefore, we suggest that the OWA should be used with AHP in future land suitability evaluation. We recommend that similar studies should use other parameters such as relative humidity, wind speed, solar radiation and heavy soil metals.

Keywords

Subjects

Balkaya, A. 2004. Modeling the effect of temperature on the germination speed in some legume crops. Journal of Agronomy 3(3): 179-183.
Baniaghil, A. S., Rahemi, A., Biabani, A., and Faramarzi, H., 2015. Zoning and Physical Assessment of Land Suitability for Particular Crops (wheat, soybean) using GIS in Golestan Province. A thesis submitted to the graduate studies office in partial fulfillment of requirement for the degree of M.Sc. 94p. (In Persian with English Summary).
Boroushaki, S., and Malczewski, J., 2008. Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS. Computers & Geosciences 34 (4): 399-410.
Dengiz, O., and Usul, M., 2018. Multi-criteria approach with linear combination technique and analytical hierarchy process in land evaluation studies. Eurasian Journal of Soil Science 7(1): 20-29.
Ghobadi, M., and Ahmadi Pari, M. 2016. Site selection for petrochemical idustry based on environmental palnning approach using integrated method of PROMETHEE II and FuzzyAHP in Lorestan. The Journal of Spatial Planning 22 (4): 201-226.
Gilanipor, A., Motevli, S. 2015. Shallow landslide hazard zonation using two-tiered and GIS statistical methods (Case study: Golndrood watershed). Natural Ecosystems of Iran. 6(2): 57-78.
Hassanzadeh, A., Rahemi Karizaki, A., Nakhzari Moghadam, A., and Biabani, A., 2013. The combined effect of terminal heat the end of growth season and competition between plants on phenology, yield and components yield in faba bean. Journal of Crop Production 6 (4): 151-163.
Jamil, M., Ahmed, R., and Sajjad, H., 2018. Land suitability assessment for sugarcane cultivation in Bijnor district, India using geographic information system and fuzzy analytical hierarchy process. Geo Journal 83 (3):595-611.
Kazemi, H., Sadeghi, S., and Akinci, H., 2016. Developing a land evaluation model for faba bean cultivation using geographic information system and multi-criteria analysis (A case study: Gonbad-Kavous region, Iran). Ecological Indicators 63:37-47.
Khedri Gharibvand, H. A., Dianati Tilaki, G. A., Sohrabi, H., Mesdaghi, M., Sardari, M. 2009. Effect of soil properties, elevation and slope aspect on distribution of camphorosma monspeliaca L. in Dote- Tang Sayad region of Chaharmahal and Bakhtiari province. 3(3): 357-370.
Kumuditi, S., Hume, D. J., Chu, G. 2002. Genetic improvement in Short-season soybean (nitrogen accumulation, remobilization and partitioning). Crop Science. 42: 141-145.
Majnoon Hosseini, N. 2015. Grain Legume Production. Tehran University Press, 283 pages.
Mokarram, M., and Zarei, R., 2016. Evaluation of groundwater quality using ordered weighting average (OWA) method; case study south of Fars province. Irrigation & Water Engineering 6 (23): 142-131.
Nasrallahi, N., Kazemi, H., Kamkar, B., Sadeghi, S. 2014. Agroecological evaluation of Aq-Qala Township (Golestan Province) for dry land wheat cultivation using geographical information system (GIS). Agronomy Journal. (110): 83-94.
Pourkhabbaz, H. R., Aghdar H., Mohammadyari, F., and Javanmardi, S., 2015. Land suitability Evaluation for determining of agricultural land use by Multi Criteria Decision Making models ANP- DEMATEL and FAHP Chang (Case study: Behbahan fringe). Journal of Environmental Studies 41(2): 429-445. (In Persian).
Rahemi, K. A., Foroughi, A. (2016). Seed filling trend of faba bean (VICIA FABA L.) as affected by planting data and density.‌ 1(37): 89-102.
Rahnema, M. R., Aghajani, H., Fattahi, M. 2013. Zoning of landfill by combining the weighted averaging method of OWA and GIS in Mashhad. (3): 87-105.
Rossiter, D. G., and Loza, A., 2004. Analyzing land cover change with R. In International Institute for Geo-information Science. Earth Observation (ITC), Enschede (NL). 1.3 edition.
Sarmadian, F., and Taati, A., 2015. Agro-ecological zoning of the Qazvin area for wheat (Triticum aestivum L.) using RS and GIS. Journal of Agroecology 7(3): 368-380. (In Persian)
Satty, T. 1980. The analytical hierarchical process: planning, priority setting, resource allocation. New York: Mc Graw-Hill. 11-21.
Sezavar, S., Safarzadeh, M. N., and Hosseini, A., 2013. Estimation of the highest correlation region. The fifth national conference of Iran. Third part. 705 p.
Simpson, J., and Stitt, J. A., 1998. Procedure for the detection and removal of clouds shadow from AVHRR data over land. IEEE Transactions on Geoscience and Remote Sensing 36(3): 880-897.
Taleai, M., Safarpour, M., and Javadi, Gh. 2018. Potential Evaluation for Establishment of Solar Power Plants Using Multi-Criteria Decision Making OWA and TOPSIS Methods (Case Study: Qazvin-Iran). The Journal of Spatial Planning 22 (4): 1-27.
Yousefi, H., Hafeznia, F., and Razi Astaraee, F. 2017. Identifying optimal sites for grid-connected photovoltaic power plants in Birjand County. The Journal of Spatial Planning 21 (2): 219-242.
Zhang, J., su, Y., wu, J., and Liang, H., 2015. GIS based land suitability assessment for tobacco production using AHP and fuzzy set in Shandong province of china. Computers and Electronica Agricultural 114, 202-211.
The Journal of Spatial Planning and Geomatics
Volume 24, Issue 1
March 2020
Pages 1-19