IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v31y2017i4d10.1007_s11269-016-1567-4.html
   My bibliography  Save this article

A Hybrid Fuzzy-Based Multi-Objective PSO Algorithm for Conjunctive Water Use and Optimal Multi-Crop Pattern Planning

Author

Listed:
  • Farshad Rezaei

    (Isfahan University of Technology)

  • Hamid R. Safavi

    (Isfahan University of Technology)

  • Maryam Zekri

    (Isfahan University of Technology)

Abstract

This paper focuses on extracting an optimal multi-crop pattern plan through multi-objective conjunctive surface-ground water use management. Minimizing shortages in meeting irrigation demands, maximizing groundwater resources sustainability and maximizing agricultural net benefits are the three main goals of the multi-objective optimization problem solved in this paper. A new robust fuzzy-based multi-objective PSO algorithm called f-MOPSO is adopted and modified to solve a three-objective real-world conjunctive use management problem presented in this paper after testing on standard test problems revealed f-MOPSO superiority as compared to the well-known multi-swarm vector evaluated PSO (VEPSO) algorithm. The f-MOPSO benefits from a well-organized Sugeno fuzzy inference system (SFIS) designed for handling multi-objective nature of the optimization problems. The unique performance of f-MOPSO is not only presenting the better final solutions, but also aggregating the capabilities for measurement of dominance and diversity of the solutions in one stage by one index named comprehensive dominance index, in contrast to a wide range of multi-objective algorithms that evaluate dominance and diversity in two separate stages resulting in excessive computational burden. The optimization model is carried out on a 10-year long-term simulation period, resulting in increasing irrigation efficiency i.e. decreasing water losses, decreasing water consumption per unit cultivated area and increasing water productivity compared to those similar criteria observed in actual operation in the study area. The wheat and rice crops were identified as the dominant crops, while the optimization model was the least interested to onion cultivation, assigning the least average cultivation area to this crop over the whole planning period.

Suggested Citation

  • Farshad Rezaei & Hamid R. Safavi & Maryam Zekri, 2017. "A Hybrid Fuzzy-Based Multi-Objective PSO Algorithm for Conjunctive Water Use and Optimal Multi-Crop Pattern Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1139-1155, March.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:4:d:10.1007_s11269-016-1567-4
    DOI: 10.1007/s11269-016-1567-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-016-1567-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-016-1567-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fateme Heydari & Bahram Saghafian & Majid Delavar, 2016. "Coupled Quantity-Quality Simulation-Optimization Model for Conjunctive Surface-Groundwater Use," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4381-4397, September.
    2. Dattatray Regulwar & Jyotiba Gurav, 2011. "Irrigation Planning Under Uncertainty—A Multi Objective Fuzzy Linear Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1387-1416, March.
    3. Lin, Qiuzhen & Li, Jianqiang & Du, Zhihua & Chen, Jianyong & Ming, Zhong, 2015. "A novel multi-objective particle swarm optimization with multiple search strategies," European Journal of Operational Research, Elsevier, vol. 247(3), pages 732-744.
    4. Farhang Daneshmand & Akbar Karimi & Mohammad Nikoo & Mohammad Bazargan-Lari & Jan Adamowski, 2014. "Mitigating Socio-Economic-Environmental Impacts During Drought Periods by Optimizing the Conjunctive Management of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1517-1529, April.
    5. Hamid Safavi & Mahdieh Esmikhani, 2013. "Conjunctive Use of Surface Water and Groundwater: Application of Support Vector Machines (SVMs) and Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2623-2644, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mirzaie, Nargis & Banihabib, Mohammad Ebrahim & shahdany, S. Mehdy hashemy & Randhir, Timothy O., 2021. "Fuzzy particle swarm optimization for conjunctive use of groundwater and reclaimed wastewater under uncertainty," Agricultural Water Management, Elsevier, vol. 256(C).
    2. Zamani, Omid & Grundmann, Philipp & Libra, Judy A. & Nikouei, Alireza, 2019. "Limiting and timing water supply for agricultural production – The case of the Zayandeh-Rud River Basin, Iran," Agricultural Water Management, Elsevier, vol. 222(C), pages 322-335.
    3. González Perea, R. & Camacho Poyato, E. & Rodríguez Díaz, J.A., 2021. "Forecasting of applied irrigation depths at farm level for energy tariff periods using Coactive neuro-genetic fuzzy system," Agricultural Water Management, Elsevier, vol. 256(C).
    4. Liang Yuan & Xia Wu & Weijun He & Yang Kong & Thomas Stephen Ramsey & Dagmawi Mulugeta Degefu, 2022. "A multi-weight fuzzy Methodological Framework for Allocating Coalition Payoffs of Joint Water Environment Governance in Transboundary River Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3367-3384, July.
    5. Jain, Sonal & Ramesh, Dharavath & Trivedi, Munesh C. & Edla, Damodar Reddy, 2023. "Evaluation of metaheuristic optimization algorithms for optimal allocation of surface water and groundwater resources for crop production," Agricultural Water Management, Elsevier, vol. 279(C).
    6. Mehri Raei & Javad Hossienzad & Mohammad Ali Ghorbani, 2023. "An Uncertainty-Based Random Boundary Interval Multi-Stage Stochastic Programming for Water Resources Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(12), pages 4571-4587, September.
    7. Mehrabi, Ahmad & Heidarpour, Manouchehr & Safavi, Hamid R. & Rezaei, Farshad, 2021. "Assessment of the optimized scenarios for economic-environmental conjunctive water use utilizing gravitational search algorithm," Agricultural Water Management, Elsevier, vol. 246(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mehrabi, Ahmad & Heidarpour, Manouchehr & Safavi, Hamid R. & Rezaei, Farshad, 2021. "Assessment of the optimized scenarios for economic-environmental conjunctive water use utilizing gravitational search algorithm," Agricultural Water Management, Elsevier, vol. 246(C).
    2. Madan K. Jha & Richard C. Peralta & Sasmita Sahoo, 2020. "Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India," IJERPH, MDPI, vol. 17(10), pages 1-20, May.
    3. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    4. Basem Shomar & Mohamed Darwish & Candace Rowell, 2014. "What does Integrated Water Resources Management from Local to Global Perspective Mean? Qatar as a Case Study, the Very Rich Country with No Water," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2781-2791, August.
    5. Alfredo Alcayde & Raul Baños & Francisco M. Arrabal-Campos & Francisco G. Montoya, 2019. "Optimization of the Contracted Electric Power by Means of Genetic Algorithms," Energies, MDPI, vol. 12(7), pages 1-13, April.
    6. Mohd Fahmi Bin Mad Ali & Mohd Khairol Anuar Bin Mohd Ariffin & Aidin Delgoshaei & Faizal Bin Mustapha & Eris Elianddy Bin Supeni, 2023. "A Comprehensive 3-Phase Framework for Determining the Customer’s Product Usage in a Food Supply Chain," Mathematics, MDPI, vol. 11(5), pages 1-20, February.
    7. Karner, Katrin & Schmid, Erwin & Schneider, Uwe A. & Mitter, Hermine, 2021. "Computing stochastic Pareto frontiers between economic and environmental goals for a semi-arid agricultural production region in Austria," Ecological Economics, Elsevier, vol. 185(C).
    8. J. Maestre-Valero & D. Martínez-Granados & V. Martínez-Alvarez & J. Calatrava, 2013. "Socio-Economic Impact of Evaporation Losses from Reservoirs Under Past, Current and Future Water Availability Scenarios in the Semi-Arid Segura Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1411-1426, March.
    9. Qian Zhang & Xiujuan Liang & Zhang Fang & Tao Jiang & Yubo Wang & Lei Wang, 2016. "Urban water resources allocation and shortage risk mapping with support vector machine method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 1209-1228, March.
    10. Qian Zhang & Xiujuan Liang & Zhang Fang & Tao Jiang & Yubo Wang & Lei Wang, 2016. "Urban water resources allocation and shortage risk mapping with support vector machine method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 1209-1228, March.
    11. Iraj Saeedpanah & Ramin Golmohamadi Azar, 2017. "New Analytical Expressions for Two-Dimensional Aquifer Adjoining with Streams of Varying Water Level," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 403-424, January.
    12. Jiyang Tian & Chuanzhe Li & Jia Liu & Fuliang Yu & Shuanghu Cheng & Nana Zhao & Wan Zurina Wan Jaafar, 2016. "Groundwater Depth Prediction Using Data-Driven Models with the Assistance of Gamma Test," Sustainability, MDPI, vol. 8(11), pages 1-17, October.
    13. Singh, Ajay, 2014. "Simulation–optimization modeling for conjunctive water use management," Agricultural Water Management, Elsevier, vol. 141(C), pages 23-29.
    14. Zhang, Chenglong & Engel, Bernard A. & Guo, Ping, 2018. "An Interval-based Fuzzy Chance-constrained Irrigation Water Allocation model with double-sided fuzziness," Agricultural Water Management, Elsevier, vol. 210(C), pages 22-31.
    15. Huang, Jiaoyuan & Shah, Farhed A., 2017. "Climate Change, Agriculture, and Sustainable Management of Water Resources in the Sacramento River Basin," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258349, Agricultural and Applied Economics Association.
    16. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    17. Chenglong Zhang & Qiong Yue & Ping Guo, 2019. "A Nonlinear Inexact Two-Stage Management Model for Agricultural Water Allocation under Uncertainty Based on the Heihe River Water Diversion Plan," IJERPH, MDPI, vol. 16(11), pages 1-18, May.
    18. M. Mohammad Rezapour Tabari, 2015. "Conjunctive Use Management under Uncertainty Conditions in Aquifer Parameters," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2967-2986, June.
    19. Li, Mo & Guo, Ping, 2015. "A coupled random fuzzy two-stage programming model for crop area optimization—A case study of the middle Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 155(C), pages 53-66.
    20. Dehghanipour, Amir Hossein & Zahabiyoun, Bagher & Schoups, Gerrit & Babazadeh, Hossein, 2019. "A WEAP-MODFLOW surface water-groundwater model for the irrigated Miyandoab plain, Urmia lake basin, Iran: Multi-objective calibration and quantification of historical drought impacts," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:31:y:2017:i:4:d:10.1007_s11269-016-1567-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.