Dergiler / Verimlilik Dergisi / 2026 / Cilt: 60 Sayı: 1

Aralık Tip-2 Bulanık TOPSIS Yaklaşımı ile Tarımda Sulama Sistemleri Verimlilik Analizi

Efficiency Analysis of Agricultural Irrigation Systems Using the Interval Type-2 Fuzzy TOPSIS Approach

Müslüm Öztürk(KİLİS 7 ARALIK ÜNİVERSİTESİ)0000-0003-1941-3115
Sayfa
39–60
Yayın Tarihi
2026-01-28
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Bulgular: Elde edilen sonuçlara göre, ideal çözüme olan göreli yakınlık açısından en yüksek performansı güneş enerjili otomatik sulama sistemi göstermiştir; onu damla sulama sistemleri takip etmiştir.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Amaç: Yarı kurak bir tarım bölgesi olan Türkiye'nin Şanlıurfa ilinde, su kaynaklarının sınırlı olması ve tarımsal verimliliğin uygun sulama yöntemlerine yüksek oranda bağlı olması nedeniyle, etkili ve sürdürülebilir sulama sistemi seçimi büyük önem taşımaktadır.
📊
Temel Bulgular & Veri:Bu çalışma, belirsizlik altında alternatif sulama sistemlerini değerlendirmek ve sıralamak amacıyla çok kriterli bir karar verme yaklaşımı kullanmayı hedeflemektedir.
💡
Sonuç & Katkı:Bulgular: Elde edilen sonuçlara göre, ideal çözüme olan göreli yakınlık açısından en yüksek performansı güneş enerjili otomatik sulama sistemi göstermiştir; onu damla sulama sistemleri takip etmiştir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Aralık Tip-2 Bulanık TOPSIS · Sulama Sistemleri · Çok Kriterli Karar Verme

Özet

Amaç: Yarı kurak bir tarım bölgesi olan Türkiye'nin Şanlıurfa ilinde, su kaynaklarının sınırlı olması ve tarımsal verimliliğin uygun sulama yöntemlerine yüksek oranda bağlı olması nedeniyle, etkili ve sürdürülebilir sulama sistemi seçimi büyük önem taşımaktadır. Bu çalışma, belirsizlik altında alternatif sulama sistemlerini değerlendirmek ve sıralamak amacıyla çok kriterli bir karar verme yaklaşımı kullanmayı hedeflemektedir. Yöntem: Çalışmada, yüzey sulama, yağmurlama sulama, damla sulama, mikro yağmurlama sulama ve güneş enerjili otomatik sulama sistemleri olmak üzere beş alternatif, Aralık Tip-2 Bulanık TOPSIS yöntemi temelinde entegre bir karar modeliyle değerlendirilmiştir. Değerlendirme altı kritere dayandırılmıştır: su kullanım verimliliği, enerji tüketimi, ilk yatırım maliyeti, çevresel etki, ürün verimine etkisi ve bakım kolaylığı. Uzman görüşlerine dayalı dilsel değerlendirmeler, insan yargısındaki belirsizliği yakalamak amacıyla üçgensel aralık tip-2 bulanık sayılara dönüştürülmüştür. Bulgular: Elde edilen sonuçlara göre, ideal çözüme olan göreli yakınlık açısından en yüksek performansı güneş enerjili otomatik sulama sistemi göstermiştir; onu damla sulama sistemleri takip etmiştir. Yüzey sulama yöntemi ise en düşük performansı göstermiştir. Bu bulgular, Şanlıurfa gibi su stresi yaşayan bölgelerde sürdürülebilirliği artırmak için etkin sulama stratejilerinin benimsenmesinin önemini vurgulamaktadır. Özgünlük: Bu çalışma, yarı kurak bir bölgede gerçek dünya koşullarında uygulanan sulama sistemlerinin değerlendirilmesinde Aralık Tip-2 Bulanık TOPSIS yönteminin yenilikçi bir uygulamasını sunmaktadır. Metodolojik katkısı, belirsizlik modellemesini pratik tarımsal karar verme süreciyle entegre etmesinde yatmakta olup, politika yapıcılar ve çiftçiler için sürdürülebilir su yönetimine yönelik güvenilir bir çerçeve sunmaktadır.

Abstract

Purpose: Efficient and sustainable irrigation system selection is vital in semi-arid agricultural regions such as Şanlıurfa, Türkiye, where water resources are limited and agricultural productivity is highly dependent on appropriate irrigation methods. This study aims to evaluate and rank alternative irrigation systems using a multi-criteria decision-making approach under uncertainty. Methodology: An integrated decision model based on the Interval Type-2 Fuzzy TOPSIS method was employed to assess five irrigation alternatives: surface irrigation, sprinkler irrigation, drip irrigation, micro-sprinkler irrigation, and solar-powered automatic irrigation systems. Six evaluation criteria were considered: water use efficiency, energy consumption, initial investment cost, environmental impact, impact on crop yield, and ease of maintenance. Linguistic evaluations from experts were converted into interval type-2 fuzzy triangular numbers to capture uncertainty in human judgment. Findings: According to the obtained results, the solar-powered automatic irrigation system demonstrated the highest performance in terms of relative closeness to the ideal solution, followed by the drip irrigation systems. The surface irrigation method exhibited the lowest performance. These findings underscore the importance of adopting efficient irrigation strategies to enhance sustainability in water-stressed regions such as Şanlıurfa. Originality: This study presents a novel application of Interval Type-2 Fuzzy TOPSIS in evaluating irrigation systems in a real-world semi-arid context. The methodological contribution lies in integrating uncertainty modeling with practical agricultural decision-making, providing a reliable framework for policymakers and farmers to support sustainable water management.

🔖

Bu Makaleye Atıf Yap

Öztürk, M. (2026). Aralık Tip-2 Bulanık TOPSIS Yaklaşımı ile Tarımda Sulama Sistemleri Verimlilik Analizi. Verimlilik Dergisi, Cilt: 60 Sayı: 1, 39–60. https://doi.org/10.51551/verimlilik.1716178

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (54)

  1. Ağızan, S. and Bayramoğlu, Z. (2021). “Comparative Investment Analysis of Agricultural Irrigation Systems”, Tekirdağ Ziraat Fakültesi Dergisi, 18(2), 222-233. https://doi.org/10.33462/jotaf.745548
  2. Aktaş, Ö. (2014). “Impacts of Climate Change on Water Resources in Turkey”, Environmental Engineering & Management Journal (EEMJ), 13(4).
  3. Alaoui, M.E., Yassini, K.E. and Ben-Azza, H. (2019). “Type 2 Fuzzy TOPSIS for Agriculture MCDM Problems”, International Journal of Sustainable Agricultural Management and Informatics, 5(2–3), 112–130. https://doi.org/10.1504/IJSAMI.2019.101672
  4. Aydın, M. and Yıldız, F. (2019). “Sulama Sistemlerinin Performans Değerlendirmesi: GAP Bölgesinden Bir Uygulama”, Tarım Bilimleri Dergisi, 25(4), 520–529.
  5. Balin, A. and Baraçli, H. (2017). “A Fuzzy Multi-Criteria Decision Making Methodology Based upon the Interval Type-2 Fuzzy Sets for Evaluating Renewable Energy Alternatives in Turkey”, Technological and Economic Development of Economy, 23(5), 742–763. https://doi.org/10.3846/20294913.2015.1056276
  6. Baykasoğlu, A. and Gölcük, İ. (2017). “Development of an Interval Type-2 Fuzzy Sets Based Hierarchical MADM Model by Combining DEMATEL and TOPSIS”, Expert Systems with Applications, 70, 37–51. https://doi.org/10.1016/j.eswa.2016.11.001
  7. Bayraktar, T.U., Şengül, Z. and Altın, A. (2024). “Evaluating Sustainability Practices in Viticulture Through a Comprehensive Study of Environmental, Social, and Economic Factors: A Case from Batman Province, Türkiye”, Turkish Journal of Agriculture-Food Science and Technology, 12(10), 1696-1705. https://doi.org/10.24925/turjaf.v12i10.1696-1705.6991
  8. Büyüközkan, G., Parlak, I.B. and Tolga, A.C. (2016). “Evaluation of Knowledge Management Tools by Using an Interval Type-2 Fuzzy TOPSIS Method”, International Journal of Computational Intelligence Systems, 9(5), 812–826. https://doi.org/10.1080/18756891.2016.1237182
  9. Büyüközkan, G. and Çifçi, G. (2012). “A Combined Fuzzy AHP and Fuzzy TOPSIS Based Strategic Analysis of Electronic Service Quality in Healthcare Industry”, Expert Systems with Applications, 39(3), 2341-2354. https://doi.org/10.1016/j.eswa.2011.08.061
  10. Chu, T.C. and Le, T.H.P. (2022). “Evaluating and Selecting Agricultural Insurance Packages through an AHP-Based Fuzzy TOPSIS Method”, Soft computing, 26(15), 7339-7354. https://doi.org/10.1007/s00500-022-06964-6
  11. Çelik, E. and Akyuz, E. (2018). “An Interval Type-2 Fuzzy AHP and TOPSIS Methods for Decision-Making Problems in Maritime Transportation Engineering: The Case of Ship Loader”, Ocean Engineering, 155, 371–381. https://doi.org/10.1016/j.oceaneng.2018.01.039
  12. Deniraraslan, P.Ç. (2023). “Picture Fuzzy Set-Based Multi-Criteria Decision Making Approach and Its Applications”, Doctoral Thesis, Bartin University, Graduate School of Science and Engineering, Türkiye. DSI 15th Regional Directorate. (2025). “Şanlıurfa Province Irrigation Data”, https://bolge15.dsi.gov.tr/Sayfa/Detay/812 (Accessed: 06.06. 2025).
  13. Dikopoulou, Z., Nápoles, G., Papageorgiou, E. and Vanhoof, K. (2017). “A Modified Fuzzy TOPSIS Method Aggregating 8.921 Partial Rankings for Companies’ Attractiveness”, The Application of Fuzzy Logic for Managerial Decision Making Processes: Latest Research and Case Studies, 59–71, Springer International Publishing, Cham.
  14. Elleuch, M.A., Anane, M., Euchi, J. and Frikha, A. (2019). “Hybrid Fuzzy Multi-Criteria Decision Making to Solve the Irrigation Water Allocation Problem in the Tunisian Case”, Agricultural Systems, 176, 102644. https://doi.org/10.1016/j.agsy.2019.102644
  15. Food and Agriculture Organization (FAO). (2021). “The State of the World's Land and Water Resources for Food and Agriculture – Systems at Breaking Point”, https://www.fao.org/publications, (Accessed: 02.06.2025).
  16. Gautam, T.K., Paudel, K.P. and Guidry, K.M. (2020). “An Evaluation of Irrigation Water Use Efficiency in Crop Production Using a Data Envelopment Analysis Approach: A Case of Louisiana, USA”, Water, 12(11), 3193. https://doi.org/10.3390/w12113193
  17. General Directorate of State Hydraulic Works (DSI). (2022). “GAP Irrigation Project Report”, DSİ Publications, Ankara, Türkiye, https://www.dsi.gov.tr, (Accessed: 01.06.2025).
  18. Golfam, P., Ashofteh, P.S. and Loáiciga, H.A. (2019). “Evaluation of the VIKOR and FOWA Multi-Criteria Decision Making Methods for Climate-Change Adaptation of Agricultural Water Supply”, Water Resources Management, 33(8), 2867-2884. https://doi.org/10.1007/s11269-019-02274-z
  19. Gómez-Limón, J.A., Arriaza, M. and Riesgo, L. (2003). “An MCDM Analysis of Agricultural Risk Aversion”, European Journal of Operational Research, 151(3), 569-585. https://doi.org/10.1016/S0377-2217(02)00625-2
  20. Haffaf, A., Lakdja, F., Meziane, R. and Abdeslam, D.O. (2021). “Study of Economic and Sustainable Energy Supply for Water Irrigation System (WIS)”, Sustainable Energy, Grids and Networks, 25, 100412. https://doi.org/10.1016/j.segan.2020.100412
  21. Hezam, I.M., Ali, A.M., Sallam, K., Hameed, I.A. and Abdel-Basset, M. (2024). “An Efficient Decision-Making Model for Evaluating Irrigation Systems Under Uncertainty: Toward Integrated Approaches to Sustainability”, Agricultural Water Management, 303, 109034. https://doi.org/10.1016/j.agwat.2024.109034
  22. Ilieva, G. (2016). “TOPSIS Modification with Interval Type-2 Fuzzy Numbers”, Cybernetics and Information Technologies, 16(2), 60-68. https://doi.org/10.1515/cait-2016-0020
  23. Kartal, S., Değirmenci, H. and Arslan, F. (2020). “Assessment of Irrigation Schemes with Performance Indicators in Southeastern Irrigation District of Turkey”, Journal of Agricultural Sciences, 26(2), 138-146. https://doi.org/10.15832/ankutbd.512677
  24. Kaya, T. and Kahraman, C. (2011). “A Fuzzy Approach to Energy Resource Selection Using Fuzzy TOPSIS and Generalized Fuzzy AHP”, Energy Conversion and Management, 52, 393–402. https://doi.org/10.48145/gopsbad.906183
  25. Kirmikil, M. (2025). “Irrigation Performance Evaluation for Sustainable Water Management: A Study of Karacabey Water Users Association, Türkiye (2006–2023)”, Sustainability, 17(9), 4059. https://doi.org/10.3390/su17094059
  26. Koç, C. and Çakmak, B. (2020). “Şanlıurfa’da Tarımsal Üretimde Su Kaynaklarının Yönetimi”, Sürdürülebilir Tarım ve Su Politikaları Dergisi, 2(1), 15–28.
  27. Kustiyahningsih, Y., Rahmanita, E., Rachmad, A. and Purnama, J. (2021). “Integration Interval Type-2 FAHP-FTOPSIS Group Decision-Making Problems for Salt Farmer Recommendation”, Communications in Mathematical Biology and Neuroscience, 2021, Article-ID 92.
  28. Le, T.H.P. and Chu, T.C. (2023). “A Weighted Centroids Approach Based Trapezoidal Interval Type-2 Fuzzy TOPSIS Method for Evaluating Agricultural Risk Management Tools”, Soft Computing-A Fusion of Foundations, Methodologies & Applications, 27(22). https://doi.org/10.1007/s00500-023-08953-9
  29. Liang, Y., Wang, H. and Wei-Chiang, H. (2022). “Sustainability Evaluation of Modern Photovoltaic Agriculture Based on Interval Type-2 Fuzzy AHP-TOPSIS and Least Squares Support Vector Machine Optimized by Fireworks Algorithm”, Energy Engineering, 119(1), 163. https://doi.org/10.32604/EE.2022.017396
  30. López-Felices, B., Aznar-Sánchez, J.A., Velasco-Muñoz, J.F. and Piquer-Rodríguez, M. (2020). “Contribution of Irrigation Ponds to the Sustainability of Agriculture: A Review of Worldwide Research”, Sustainability, 12(13), 5425. https://doi.org/10.3390/su12135425
  31. Loureiro, D., Beceiro, P., Fernandes, E., Alegre, H. and Covas, D. (2024). “Energy Efficiency Assessment in Collective Irrigation Systems Using Water and Energy Balances: Methodology and Application”, Irrigation Science, 42(4), 745-768. https://doi.org/10.1007/s00271-023-00891-6
  32. Madi, E.N., Zakaria, Z.A., Sambas, A. and Sukono. (2023). “Toward Effective Uncertainty Management in Decision-Making Models Based on Type-2 Fuzzy TOPSIS”, Mathematics, 11(16), 3512. https://doi.org/10.3390/math11163512
  33. Mendel, J.M. (2001). “Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions”, Prentice-Hall, Upper Saddle River, NJ, USA.
  34. Meni̇z, B. (2021). “An Advanced TOPSIS Method with New Fuzzy Metric Based on Interval Type-2 Fuzzy Sets”, Expert Systems with Applications, 186, 115770. https://doi.org/10.1016/j.eswa.2021.115770
  35. Morankar, R.S. (2013). “Performance Evaluation of Irrigation Subsystems Using Interval Valued Fuzzy TOPSIS”, International Journal of Hydrology Science and Technology, 3(1), 75–89. https://doi.org/10.1504/IJHST.2013.055230
  36. Mousakhani, M., Bahrami, M.A. and Esfahani, M.M.N. (2017). “An Integrated Interval Type-2 Fuzzy MCDM Approach for Green Supplier Selection Problem”, Journal of Cleaner Production, 147, 919–936. https://doi.org/10.21203/rs.3.rs-168876/v1
  37. Öztürk, M. (2025). “A Hybrid Approach for Battery Selection Based on Green Criteria in Electric Vehicles: DEMATEL-QFD-Interval Type-2 Fuzzy VIKOR”, Sustainability, 17(14), 6277. https://doi.org/10.3390/su17146277
  38. Petrovic, I. and Kankaras, M. (2020). “A Hybridized IT2FS-DEMATEL-AHP-TOPSIS Multicriteria Decision Making Approach: Case Study of Selection and Evaluation of Criteria for Determination of Air Traffic Control Radar Position”, Decision Making: Applications in Management and Engineering, 3(1), 146–164. https://doi.org/10.31181/dmame2003134p
  39. Polat Solar Energy, (2025). “Güneş Enerjili Sulama Sistemleri Çözümleri”, https://www.polatsolar.com/cozumlerimiz/sulama-sistemleri, (Accessed: 03.06.2025).
  40. Puška, A., Nedeljković, M., Hashemkhani Zolfani, S. and Pamučar, D. (2021). “Application of Interval Fuzzy Logic in Selecting a Sustainable Supplier on the Example of Agricultural Production”, Symmetry, 13, 774. https://doi.org/10.3390/sym13050774
  41. Qin, J. and Liu, X. (2019). “Interval Type-2 Fuzzy Decision Making Based on TOPSIS”, in Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications, Springer, Cham, Switzerland, pp. 85–106. https://doi.org/10.1007/978-981-13-9891-9_5
  42. Rouyendegh, B.D. and Savalan, Ş. (2022). “An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production”, Sustainability, 14(8), 4835. https://doi.org/10.3390/su14084835
  43. Sharaf, I.M. (2020). “An Interval Type-2 Fuzzy TOPSIS Using the Extended Vertex Method for MAGDM”, SN Applied Sciences, 2, 1–15. https://doi.org/10.1007/s42452-019-1825-1
  44. Sodhi, B. and Prabhakar, T.V. (2012). “A Simplified Description of Fuzzy TOPSIS”, arXiv preprint arXiv:1205.5098.
  45. Taguta, C., Dirwai, T.L., Senzanje, A., Sikka, A. and Mabhaudhi, T. (2022). “Sustainable Irrigation Technologies: A Water-Energy-Food (WEF) Nexus Perspective towards Achieving More Crop per Drop per Joule per Hectare”, Environmental Research Letters, 17(7), 073003. https://doi.org/10.1088/1748-9326/ac7b39
  46. Topaloğlu, M., Yarkin, F. and Kaya, T. (2018). “Solid Waste Collection System Selection for Smart Cities Based on a Type-2 Fuzzy Multi-Criteria Decision Technique”, Soft Computing, 22, 4879–4890. https://doi.org/10.1007/s00500-018-3232-8
  47. Torfi, F., Farahani, R.Z. and Rezapour, S. (2010). “Fuzzy AHP to Determine the Relative Weights of Evaluation Criteria and Fuzzy TOPSIS to Rank the Alternatives”, Applied Soft Computing, 10(2), 520–528. https://doi.org/10.1016/j.asoc.2009.08.021
  48. Ünal, S., Kaya, M. and Aksu, M. (2021). “Sulama Sistemleri Seçimi Için Bulanık Çok Kriterli Karar Verme Yöntemlerinin Karşılaştırılması”, Mühendislik Bilimleri ve Tasarım Dergisi, 9(1), 50–63. https://doi.org/10.47495/okufbed.1440315
  49. Üsküdar, A., Özdemir, Y.S., Karabüber, Ö., Yıldırım, E. and Gezer, Ö. (2018). “Fuzzy AHP-TOPSIS Strategic Theme Selection and Application”, Journal of Advanced Management Science, 6(2), 63-68. https://doi.org/10.18178/joams.6.2.63-68
  50. Wang, D. (2017). “Water Use Efficiency and Optimal Supplemental Irrigation in a High Yield Wheat Field”, Field Crops Research, 213, 213-220. https://doi.org/10.1016/j.fcr.2017.08.012
  51. Wikipedia. (2025). “Şanlıurfa Irrigation Tunnels”, https://en.wikipedia.org/wiki/Şanlıurfa_Irrigation_Tunnels, (Accessed: 04.06.2025).
  52. Yetik, A.K. and Ünal, Z. (2024). “Analitik Hiyerarşi Süreci (AHP) ile Sulama Sistemi Seçimi”, Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 7(5), 2190-2204. https://doi.org/10.47495/okufbed.1440315
  53. Zeng, X.J. and Guo, H. (2015). “Type-2 Fuzzy Logic Systems: An Overview”, IEEE Transactions on Fuzzy Systems, 23(6), 1773–1793.
  54. Zhang, X., Jin, L., Fan, Y., Wang, L., Liu, J. and Gao, P. (2025). “Improved Semi-Infinite Interval Type-2 Fuzzy Multi-Objective Programming with Integrated Multi-Criteria Decision Analysis for Sustainable Water Resource Management”, Journal of Water Process Engineering, 73, 107687. https://doi.org/10.1016/j.jwpe.2025.107687