Evaluation of land suitability for irrigation using fuzzy analytic hierarchy process

Document Type : Research Paper


Moghan College of Agriculture and Natural Resources - Mohaghegh Ardabili University, Ardabil, I. R. Iran


Use of new techniques to evaluate irrigation areas can enhance water use efficiency in agriculture. In this study, the fuzzy analytic hierarchy Process (FAHP) was used to qualitative land suitability for sprinkler irrigation and was compared with the parametric method. Evaluation based on parametric method showed that an area of about 1597.83 hectares (31%) of the lands was highly suitable (S1) and an area of about 787.3 hectares (15%) was “moderately suitable” (S2). About 2242.9 hectares (43%) were marginally suitable (S3). Permanently inappropriate suitability included about 546.91 hectares (11%). Inappropriate in present condition suitability matched no land in the study zone. Based on the Fuzzy Analytic Hierarchical Process, there was not highly suitable (S1) area in the plain. The parts with S2 suitability also included an area of about 432.96 hectares (8.3%). Moreover, areas of about 3100.98 hectares (59.9%) were marginally suitable (S3). Some southwest and eastern parts of the plain were not currently suitable (N1) that included an area of about 1277.68 hectares (24.6%). N2 suitability was also observed in some southern in two parts including an area of about 363.38 hectares (7%). Since about 31% of the lands were included as "highly suitable" areas based on the parametric method, and in contrast, there was no "highly suitable" areas in FAHP method, so considering the area of "highly suitable" shown that there was a significant difference between the two methods in terms of "highly suitable" land evaluation. Considering the gradual changes in soil properties, FAHP evaluation has higher accuracy than the ordinary parametric method in evaluating land suitability.


Article Title [Persian]

ارزیابی تناسب اراضی برای آبیاری با استفاده از فرآیند تحلیل سلسله مراتبی فازی

Author [Persian]

  • یاسر حسینی
دانشکده کشاورزی و منابع طبیعی مغان- دانشگاه محقق اردبیلی، اردبیل، ج. ا. ایران
Abstract [Persian]

- استفاده از روش‌های جدید برای تعیین ارزیابی اراضی می تواند باعث افزایش بهره وری آب در کشاورزی شود.  در این تحقیق از فرآیند تحلیل سلسله مراتبی فازی (FAHP[1]) برای بهینه‌سازی ارزیابی پارامتریک تناسب اراضی، در روش آبیاری بارانی استفاده شد و نتایج با روش پارامتریک مقایسه گردید، نتایج روش معمول پارامتریک مشخص نمود که مساحتی حدود 83/1597هکتار (31 درصد) از اراضی دارای تناسب 1S (کاملاً مناسب) بوده و مساحتی حدود3/787 هکتار(15 درصد) دارای تناسب 2S (نسبتاً مناسب) بود و تناسب 3S (تاحدودی مناسب) مساحتی حدود 9/2242هکتار (43درصد) را شامل می‌شد. همچنین تناسب 2N (نامناسب دائمی) مساحتی حدود 91/546 هکتار (11 درصد) را در بر‌گرفته و تناسب 1N (نامناسب در شرایط فعلی)،  در منطقه مورد مطالعه وجود نداشت.. ارزیابی براساس سیستم سلسله مراتب فازی،  نشان داد که در منطقه تناسب 1S  وجود نداشته و مناطقی که دارای تناسب 2S بودند، مساحتی حدود 96/432 هکتار(3/8 درصد) را شامل می‌شد. همچنین حدود 98/3100 هکتار (9/59 درصد) دارای تناسب 3S بوده و اراضی با تناسب 1N مساحتی حدود 68/1277هکتار (6/24 درصد) را در قسمت جنوب غربی و شرق دشت، شامل شد و تناسب 2N  نیز، مساحتی حدود 38/363 هکتار ( 7 درصد) را  در قسمت جنوبی و در دو ناحیه دشت، شامل شد. از آنجاکه حدود 31 درصد از اراضی براساس روش پارامتریک جزو مناطق "کاملا مناسب" قرار گرفتند و در مقابل در روش ارزیابی سلسله مرتب فازی مناطق "کاملا مناسب" وجود نداشت، در نظر گرفتن مساحت اراضی "کاملا مناسب" نشان داد که تفاوت عمده‌ای بین دو روش از لحاظ ارزیابی اراضی "کاملا مناسب" وجود دارد که این موضوع اختلافی معنی‌دار دو روش را نشان می‌دهد. در نظر گرفتن تغییرات تدریجی در ارزیابی در روش سلسله مراتبی فازی، دقت بیش‌تر این روش را نسبت به روش معمول پارامتریک سبب می‌گردد.

[1]- Fuzzy Analytic Hierarchical Process

[1]- Fuzzy Analytic Hierarchical Process


[1]- Fuzzy Analytic Hierarchical Process

Keywords [Persian]

  • روش تحلیل سلسله مراتب فازی*
  • سیستم اطلاعات جغرافیائی (GIS)
  • ارزیابی اراضی
  • پارامتریک
  • آبیاری بارانی
Akbarzadeh, A., Mehrjardi, R. T., Rouhipour, H., Gorji, M., & Rahimi. H. G. (2009). Estimating of soil erosion covered with rolled erosion control systems using rainfall simulator (neuro-fuzzy and artificial neural network approaches). Journal of Applied Science Research, 5 (5), 505-514.
Albaji, M., Golabi, M., Boroomand Nasab, S., & Nazari Zadeh, F. (2015). Investigation of Surface, Sprinkler and Drip Irrigation methods based on the parametric evaluation approach in Jaizan Plain. Journal of the Saudi Society of Agricultural Sciences, 14(1), 1-10.
Albaji, M., Landi, A., Mravvej, K., & Broomand Nasab, S., )2006(. Land evaluation for irrigated agriculture for drip & Sprinkle irrigation methods for the Base production of Shavoor plain of khuzestan. )M.Sc. Thesis. Chamran University(. (In persian)
Bagherzadeh, A., Ghadiri, E., Souhani Darban, A., & Gholizadeh,  A. (2016). Land suitability modeling by parametric-based neural networks and fuzzy methods for soybean production in a semi-arid region. Modeling Earth Systems and Enviroment 2, 93-104.
Bagherzadeh, A., & Mansouri Daneshvar, M. R. M. (2011). Physical land suitability evaluation for specific cereal crops using GIS at Mashhad Plain, Northeast of Iran. Frontiers of Agriculture in China, 5(4), 90-100.
Bagherzadeh A., & Paymard P. (2015). Assessment of land capability for different irrigation systems by parametric and fuzzy approaches in the Mashhad Plain, northeast Iran. Soil & Water Research, 10, 90-98.
Bagherzadeh, A., & Gholizadeh, A. (2016). Modeling land suitability evaluation for wheat production by parametric and TOPSIS approaches using GIS, northeast of Iran. Modeling Earth Systems and Environment. 2, 126-137.
Burrough, P. A., & McDonnell, R. (1998). “Principles of geographical information systems”. New York: Oxford University Press.
Calderon, F., Fiorillo, E., Yan, N., Barberis, A., & minelli, S. (2005). Land evaluation in the Shouyang county, Shanxi province, china. 25th course professional Master. 8 Nov 2004 - 23 Jun 2005. IAO. Florence. Italy.
Dengiz, O. (2006). Comparison of different irrigation methods based on the parametric evaluation approach. Turkish Journal of Agriculture and Forestry. 30, 21-29.
Elaalem, M. (2013). A comparison of parametric and fuzzy multi- criteria methods for evaluating land suitability for olive in Jeffara plain of Libya, APCBEE Procedia. 5, 405-409.
Feizizadeh, B., & Blaschke, T. (2013). Land suitability analysis for Tabriz county, Iran: a multi-criteria evaluation approach using GIS, Journal of Environmental Planning and Management, 56(1), 1-23.
Hamzeh, S., Mokarramb, M., & Alavipanaha, S. K. (2014). Combination of fuzzy and AHP methods to assess land suitability for barley: Case study of semi-arid lands in the southwest of Iran. Desert. 19(2), 173-181.
Houshyar, E., Smith, P., Mahmoodi-Eshkaftaki, M., & Azadi, H. (2017). Sustainability of wheat production in Southwest Iran: A fuzzy-GIS based evaluation by ANFIS. Cogent Food & Agriculture, 3(1), 2-18.
Hoseini, Y., & Kamrani, M. (2018). Using a fuzzy logic decision system to optimize the land suitability evaluation for a sprinkler irrigation method. Outlook on Agriculture, 47(4), 298-307.
Hoseini, Y. (2019). Use fuzzy interface systems to optimize land suitability evaluation for surface and trickle irrigation, Information Processing in Agriculture. 6(1), 11-19.
Karatalopoulos, S. V. (2000). Understanding neural networks and fuzzy logic- basic concepts and applications. New-Delhi, India: Prentice Hall.
Karimi, F., Sultana, S., Shirzadi Babakan, A., Royall, D. (2018). Land suitability evaluationfor organic agriculture of wheat using GIS and multicriteria analysis. Pappers in Applied Geography 4 (3), 326-342.
Khashei Sivaki, A., GHahreman, B., & Koochakzadeh, M. (2012). Fuzzy-analytic hierarchy process method for evaluating groundwater potentials of aquifers (Case study: Nayshabur Plain). Iranian Water Researches Journal. 5(9), 171-180. (in Persian)
Keshavarzi, A., & Sarmadian, F. (2009). Investigation of fuzzy set theory’s efficiency in land suitability assessment for irrigated wheat in Qazvin province using Analytic hierarchy process (AHP) and multivariate regression methods. In: Proceedings of ‘Pedometrics, 2009’ conference, August 26-28, Beijing, China
Koorehpazan, A. (2008). Principles of fuzzy set theory and its applications in modeling water engineering issues. First edition, Tehran: Amirkabir University. (In persian)
Klein, L. (1999). Sensor and data fusion concepts and applications. Bellingham: SPIE optical engineering Press.
Laffan, M., & Rees, S. (2004). Site suitability for spray irrigation of stormwater and log sprinkler wastewater in stage 1 and 2 at the soutwood processing complex, southern Tasmania. Technical Report, division of forest research and development, forestry Tasmania: Camdale.
Lu, l., Shi, Zh., Yin, W., Zhu, D., Sai, N., Leung, Cai., Chong, Fa., & Leia, l. (2009). A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the Danjiangkou reservoir area, China. Ecological Modeling, 220. 3439-3447.
Miháliková, M., & Dengiz, O. (2019). Towards more effective irrigation water usage by employing land suitability assessment for various irrigation techniques. Irrigation and Drainage, 68, 617-628.
Mirzaiie Takhtgahi, H., Broomand Nasab, S., Behzad, M., & Ghamarnia, H. (2005). Land evaluation for pressurized irrigation systems in the center areas of Kermanshah. National Conference on Management of Irrigation and Drainage Network, Khuzestan Province, Ahvaz. (In persian)
Mottakan, A., Shakiba, A., Hoseinpur, A., & Ebadi, A. (2009). Crisp and fuzzy decision making in multistore public parking lots. Journal of Environmental Sciences, 6(3), 207-222. (In persian)
Naseri, A. A., Rezania, A. R., & Albaji, M. (2009). Investigation of soil quality for different irrigation systems in Lali Plain, Iran. Journal of Food, Agriculture & Environment, 7(3&4), 955-960.
Qureshi, M. R. N., Singh, R. K., & Hasan, M. A. (2018). Decision support model to select crop pattern for sustainable agricultural practices using fuzzy MCDM. Environment, Development and Sustainability, 20(2), 641-659.
Ramzi, R., Shahidi, A., & Khashei, A. (2014). Finding the potentials of sprinkler irrigation using fuzzy analytical hierarchy process method in South Khorasan province. Iranian Society of Irrigation & Water Engineering. 16, 1-11. (in Persian)
Roy, J., Saha, S. (2018). Assessment of land suitability for the paddy cultivation using analytical hierarchical process (AHP): A study on Hinglo river basin, Eastern India. Modeling Earth Systems and Enviroment, 4(2), 601-618.
Singha, C., & Chandra Swain, K. (2016). Land suitability evaluation criteria for agricultural crop selection: A review. Agricultural Reviews, 37 (2), 125-132.
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.
Sys, C., Vanranst E., & Debaveye, J. (1991). Land evaluation. Part I. Principles in land evaluation and crop production calculations. International training center for post-graduate soil scientists, University Ghent. Retrieved from: https://biblio.ugent.be/publication/223207
Turkish statistical institute, agricultural statistics summary (2018).  Retrieved from: https://www.library.illinois.edu/ias/iri/turkish/turk_stat_inst /
Torrieri, F., & Batà, A. (2017). Spatial multi-criteria decision support system and strategic environmental assessment: A case study. Buildings, 7(4), 96-99.
Uyan, M. (2013). GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region Konya. Turkey. Renewable and Sustainable Energy Reviews, 28, 11-17.
Zadeh, L. (1965). Fuzzy sets. Information Control. 8, 338-353.