IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i12d10.1007_s11269-023-03557-2.html
   My bibliography  Save this article

An Uncertainty-Based Random Boundary Interval Multi-Stage Stochastic Programming for Water Resources Planning

Author

Listed:
  • Mehri Raei

    (University of Tabriz)

  • Javad Hossienzad

    (University of Tabriz)

  • Mohammad Ali Ghorbani

    (University of Tabriz)

Abstract

Given the increasing population growth and rapid global economic development, the conflict between reduced available water resources and increased water demand in many countries has become a challenging issue; confirming the necessity of allocating optimal water resources to equate water conservation and environmental sustainability. Uncertainties and climate change together deteriorate the complexity of optimal allocation related to water resources used for the agricultural sector. The present study sought to design an uncertainty-based random boundary interval multi-stage stochastic programming (URBIMSP) model by integrating the Kataoka’s criterion method and chance-constrained programming within a general optimization framework to control the uncertain information which exists in both constraints and goal functions. The developed model was applied to a case study of water resources allocation in the Marand basin, Iran. Then, a conjunctive water allocation system was arranged to identify the introduced model in two planning periods which were 2023 to 2025 and 2026 to 2028. The results indicated that different water allocation schemes and water shortages with varying net system benefits would be achieved under different stream flow levels and different risk scenarios. The result was significant for carrying out a comprehensive analysis of the tradeoffs between total net benefits and related risks. Finally, the findings demonstrated that improving irrigation efficiency and upgrading irrigation systems are the key strategies for farmers to achieve economic benefits while also help to mitigate environmental impacts.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:12:d:10.1007_s11269-023-03557-2
    DOI: 10.1007/s11269-023-03557-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-023-03557-2
    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/s11269-023-03557-2?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. Xiaona Li & Xiaosheng Wang & Haiying Guo & Weimin Ma, 2020. "Multi-Water Resources Optimal Allocation Based on Multi-Objective Uncertain Chance-Constrained Programming Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4881-4899, December.
    2. Li, Y.P. & Liu, J. & Huang, G.H., 2014. "A hybrid fuzzy-stochastic programming method for water trading within an agricultural system," Agricultural Systems, Elsevier, vol. 123(C), pages 71-83.
    3. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    4. Abbas Amini Fasakhodi & Seyed Nouri & Manouchehr Amini, 2010. "Water Resources Sustainability and Optimal Cropping Pattern in Farming Systems; A Multi-Objective Fractional Goal Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4639-4657, December.
    5. C. Dai & Y. P. Cai & W. T. Lu & H. Liu & H. C. Guo, 2016. "Conjunctive Water Use Optimization for Watershed-Lake Water Distribution System under Uncertainty: a Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4429-4449, September.
    6. 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.
    7. Muñoz, Maria M. & Ruiz, Francisco, 2009. "ISTMO: An interval reference point-based method for stochastic multiobjective programming problems," European Journal of Operational Research, Elsevier, vol. 197(1), pages 25-35, August.
    Full references (including those not matched with items on IDEAS)

    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. Li, Mo & Guo, Ping & Singh, Vijay P., 2016. "An efficient irrigation water allocation model under uncertainty," Agricultural Systems, Elsevier, vol. 144(C), pages 46-57.
    2. S. Dutta & B.C. Sahoo & Rajashree Mishra & S. Acharya, 2016. "Fuzzy Stochastic Genetic Algorithm for Obtaining Optimum Crops Pattern and Water Balance in a Farm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4097-4123, September.
    3. Li, Mo & Guo, Ping & Singh, Vijay P. & Yang, Gaiqiang, 2016. "An uncertainty-based framework for agricultural water-land resources allocation and risk evaluation," Agricultural Water Management, Elsevier, vol. 177(C), pages 10-23.
    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. Arbizu-Milagro, Julia & Castillo-Ruiz, Francisco J. & Tascón, Alberto & Peña, Jose M., 2023. "Effects of regulated, precision and continuous deficit irrigation on the growth and productivity of a young super high-density olive orchard," Agricultural Water Management, Elsevier, vol. 286(C).
    6. Cameira, Maria do Rosário & Rodrigo, Isabel & Garção, Andreia & Neves, Manuela & Ferreira, Antónia & Paredes, Paula, 2024. "Linking participatory approach and rapid appraisal methods to select potential innovations in collective irrigation systems," Agricultural Water Management, Elsevier, vol. 299(C).
    7. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    8. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    9. Feng, Z.Y. & Qin, T. & Du, X.Z. & Sheng, F. & Li, C.F., 2021. "Effects of irrigation regime and rice variety on greenhouse gas emissions and grain yields from paddy fields in central China," Agricultural Water Management, Elsevier, vol. 250(C).
    10. Bopp, Carlos & Jara-Rojas, Roberto & Bravo-Ureta, Boris & Engler, Alejandra, 2022. "Irrigation water use, shadow values and productivity: Evidence from stochastic production frontiers in vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    11. Feng Guo & Liguo Jiao, 2023. "A new scheme for approximating the weakly efficient solution set of vector rational optimization problems," Journal of Global Optimization, Springer, vol. 86(4), pages 905-930, August.
    12. 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).
    13. Wu, Lihong & Quan, Hao & Wu, Lina & Zhang, Xi & Feng, Hao & Ding, Dianyuan & Siddique, Kadambot H.M., 2023. "Responses of winter wheat yield and water productivity to sowing time and plastic mulching in the Loess Plateau," Agricultural Water Management, Elsevier, vol. 289(C).
    14. Xing, Yingying & Zhang, Teng & Jiang, Wenting & Li, Peng & Shi, Peng & Xu, Guoce & Cheng, Shengdong & Cheng, Yuting & Fan, Zhang & Wang, Xiukang, 2022. "Effects of irrigation and fertilization on different potato varieties growth, yield and resources use efficiency in the Northwest China," Agricultural Water Management, Elsevier, vol. 261(C).
    15. Agüero Alcaras, L. Martín & Rousseaux, M. Cecilia & Searles, Peter S., 2021. "Yield and water productivity responses of olive trees (cv. Manzanilla) to post-harvest deficit irrigation in a non-Mediterranean climate," Agricultural Water Management, Elsevier, vol. 245(C).
    16. Siakou, M. & Bruggeman, A. & Eliades, M. & Zoumides, C. & Djuma, H. & Kyriacou, M.C. & Emmanouilidou, M.G. & Spyros, A. & Manolopoulou, E. & Moriana, A., 2021. "Effects of deficit irrigation on ‘Koroneiki’ olive tree growth, physiology and olive oil quality at different harvest dates," Agricultural Water Management, Elsevier, vol. 258(C).
    17. Wang, Rong & Huang, Guanhua & Xu, Xu & Ren, Dongyang & Gou, Jiachao & Wu, Zhangsheng, 2022. "Significant differences in agro-hydrological processes and water productivity between canal- and well-irrigated areas in an arid region," Agricultural Water Management, Elsevier, vol. 267(C).
    18. Martínez-Gimeno, M.A. & Zahaf, A. & Badal, E. & Paz, S. & Bonet, L. & Pérez-Pérez, J.G., 2022. "Effect of progressive irrigation water reductions on super-high-density olive orchards according to different scarcity scenarios," Agricultural Water Management, Elsevier, vol. 262(C).
    19. Seyedeh Hadis Moghadam & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2022. "Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3181-3205, July.
    20. Mansour, Elsayed & Desoky, El-Sayed M. & Ali, Mohamed M.A. & Abdul-Hamid, Mohamed I. & Ullah, Hayat & Attia, Ahmed & Datta, Avishek, 2021. "Identifying drought-tolerant genotypes of faba bean and their agro-physiological responses to different water regimes in an arid Mediterranean environment," Agricultural Water Management, Elsevier, vol. 247(C).

    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:37:y:2023:i:12:d:10.1007_s11269-023-03557-2. 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.