Land Evaluation System for Trickle and Sprinkle Irrigation Methods Using Fuzzy Logic System

Document Type : Research Paper

Author

College of Agriculture and Natural Resources - University of Mohaghegh Ardabili - Ardabil – IRAN

Abstract

Limited water and soil resources and growing population have led countries around the world towards raising agricultural production per unit area and optimal utilization of these resources. Due to the population growth and rising living standards, the demand for food has increased. In this regard, identification and knowledge of the parameters that somehow affect food production is essential. Using new techniques for selecting  appropriate land irrigation methods can enhance water use efficiency in farm lands. Selecting a proper irrigation method in irrigated agriculture in order to achieve a high efficiency and maximum water use. Nowadays Fuzzy systems are one of the most efficient methods in the field of forecasting and modeling (Akbarzadeh et al, 2009). Fuzzy system is able to use human language and human experiences and experts and connoisseurs (Karatalopoulos, 2000). Sys, Vanranst and Debaveye (1991) proposed parametric evaluation system to select irrigation methods based on physical and chemical properties of soil. Using fuzzy logic capabilities which stem from the ability of continuous membership function of input variables and by combination of parameters affecting irrigation methods evaluation in parametric system with fuzzy logic membership functions, it is possible to  assess farm lands for choosing the right irrigation method more accurately. Therefore, this study aims to utilize the functionalities of fuzzy logic method to evaluate land suitability of the area studied based on parametric system for two drip and sprinkler irrigation methods.

Keywords

Main Subjects

References

1-    Albaji, M., Landi, A., Mravvej, K. and Broomand Nasab, S., 2006. Land evaluation for irrigated agriculture for drip& Sprinkle irrigation methods for the Base production of Shavoor plain of khuzestan. MS Thesis. Chamran university. (In persian).
 
2-    Al-Jarrah, O. and fic cereal crops using GIS at Mashhad Plain, Northeast of Iran. Front Agric Abu-Qdais, H., 2006. Municipal soil waste landfill siting using intelligent system. Waste Management. 26, PP. 299–306.
 
3-    Akbarzadeh, A., Mehrjardi, R.T., Rouhipour, H., Gorji, M. and 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), PP. 505–514.
 
4-    Bagherzadeh, A. and Mansourie Daneshvar, M.R.M., 2011. Physical land suitability evaluation for speci China .5(4), PP. 90–100.
 
5-    Bagherzadeh, A. and Paymar, P., 2015. Assessment of Land Capability for Different Irrigation Systems by Parametric and Fuzzy Approaches in the Mashhad Plain, Northeast Iran. Soil & Water Res. 10 (2), PP. 90–98.
 
6-    Bagherzadeh, A. and Gholizadeh, A., 2016. Modeling land suitability evaluation for wheat production by parametric and TOPSIS approaches using GIS, northeast of Iran. Model Earth Syst Environ. 2, PP.126-137.
 
7-    Baja, S., Chapman, D.M. and Dragovich, D. 2002., A conceptual model for defining and assessing land management units using a fuzzy modeling approach in GIS environment. Environmental Management. 29 (5), PP. 647–661.
 
8-    Burrough, P.A. and McDonnell, R., 1998. Principles of Geographical Information Systems. Oxford University Press: 333p.
 
9-      Calderon, F., Fiorillo, E., Yan, N., Barberis, A. and minelli, S., 2005. Land Evaluation in the shouyang county, shanxi province, china. 25th Course professional Master. IAO. Florence. Italy.
 
10-   Dengiz, O., Gol, C., Karaca, S. and Yuksel, M., 2006. Effects of Different Landscape Position and Parent Material on Soil Variability and Land Use in both Sides of Acicay River Cankiri, International Soil Meeting on Soil Sustaining Life on Earth, Managing Soil and Technology Proceedings, Sanliurfa. 2, pp. 745-751.
 
11-   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, pp. 405 – 409.
 
12-   Hamzeha, S. Mokarramb, M. and 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), pp. 173-181.
 
13-   Joss, B.N., Hall, R.J., Sidders, D.M. and Keddy, T.J., 2008. Fuzzy-logic modeling of land suitability for hybrid poplar across the Prairie Provinces of Canada. Earth Environ Sci. 141, pp.79–96.
 
14-   Karatalopoulos, S. V., 2000. Understanding Neural Networks and Fuzzy Logic- Basic Concepts and Applications; Prentice Hall, New-Delhi, India.
 
15-   Keshavarzi, A. and 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 ‘Geometrics 2009’ conference, August 26–28, Beijing, China.
 
16-   Khashei Sivaki, A., Ghahreman, B. and Koochazadeh, M., 2012. Assessing the potential for water extraction from the aquifer using a fuzzy hierarchical process analysis process, case study: Neishabur plain. Iranian Journal of Water Research. 5(9), pp.1-10. (In persian)
 
17-   Klein, L., 1999. Sensor and Data Fusion Concepts and Applications. SPIE Optical Engineering Press, Bellingham, 253p.
 
18-   Koorehpazan, A., 2008. Principles of Fuzzy Set Theory and its Applications in Modeling Water Engineering Issues. First edition, Amirkabir university. (In persian)
 
19-   Lu, L., Shi, Zh., Yin, W., Zhu, D., Sai, N., Leung, C., Chong, f. and Leia, L., 2009. A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the Danjiangkou reservoir area. China. Eco logical modeling. 220, pp. 3439-3447.
 
20-   Mahari, A. and Alebachew, A., 2013. Land suitability evaluation for irrigation in dejen district Ethiopia. International Journal of Scientific and Research Publications. 3(9), pp. 1-3.
 
21-   Mirzaiie Takhtgahi, H., Broomand Nasab, S., Behzad, M. and Ghamarnia, H., 2004. Land evaluation for pressurized irrigation systems in the center areas of Kermanshah. National Conference on Management of Irrigation and Drainage Network, khuzestan Province, Ahvaz. Pp.10. (In persian)
 
22-   Mottakan, A., Shakiba, A., Hoseinpur, A. and Ebadi, A., 2009. Crisp and Fuzzy Decision Making in Multistore Public Parking Lots. Journal of Environmental Sciences, 6(3), pp. 207-222. (In persian)
 
23-   Nasiri, F., Maqsood, I., Huang, G. and Fuller, N., 2007. Water quality index: a fuzzy river pollution decision support expert system. Journal of Water Resources Planning and Management. 133 (2), pp. 95–105.
 
24-   Naseri, A.A., Rezania, A.R. and Albaji, M., 2009. Investigation of soil quality for different systems in Lali Plain, Iran. Journal of Food, Agriculture & Environment, 7(3&4), pp. 955–960.
 
25-   Nikravesh, M., Zadeh, L. and Korotkikh, V., 2004. Fuzzy partial differential equations and rational equations (reservoir characterization and modeling). Springer Verlag Berlin Heidelberg New York. pp. 1-79.
 
26-   Ramzy, R., Shahidi, A. and Khashei, A., 2014. Sprinkler irrigation potential using fuzzy hierarchy process analysis method in South Khorasan province. Scientific Journal of Irrigation and Water Engineering. 16(2), pp.1-11. (In persian)
 
27-   Sanchez, J.F., 2007. Applicability of knowledge-based and fuzzy theory-oriented approaches to land suitability for upland rice and rubber. M.Sc. Thesis ITC, The Netherlands
 
28-   Sys, C., 1985. Land evaluation, part Ι, И, Ш. ITC, University of Ghent, Belgium, 343 pp.
 
29-   Sys, C., Vanranst, E. and 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.
 
30-   Wang, F. and Hall, G.B., 1990. Fuzzy information representation and Processing in conventional GIS software: database design and application. International Journal of Geographic Information Sciences. 4 (3), pp.261–283.
 
31-   Zadeh, L., 1965. Fuzzy sets. Information Control. 8: 338-353.
 
32-   Zali Vargahan, B., Shahbazi, F. and Hajrasouli, M., 2011. Quantitative and qualitative land suitability evaluation for maize cultivation in Ghobadlou region, Iran. Ocean Journal of Applied Sciences. 4, pp. 91-104.
 
33-   Zare Naghadehi, M., Mikaeiland, R. and Ataei, M., 2009. The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm bauxite mine. Iran. Expert systems with applications. 36, pp. 8218-8226.
 
34-     Zaresefat, M., Kalantari, N., Aram, A., Roohi, H.  and Cheraghi, GH., 2011. Potential for natural feeding of groundwater using FAHP method and GIS software. Case study: North of Dezful. Proceedings of the Thirtieth meeting of earth sciences. 21-23.
Irrigation Sciences and Engineering
Volume 41, Issue 2
June 2018
Pages 135-149

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History

  • Receive Date: 13 April 2016
  • Revise Date: 29 January 2017
  • Accept Date: 14 February 2017
  • Publish Date: 22 June 2018

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