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Agricultural Water Allocation by Integration of Hydro-Economic Modeling with Bayesian Networks and Random Forest Approaches

Author

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  • Zohreh Sherafatpour

    (University of Tehran)

  • Abbas Roozbahani

    (University of Tehran)

  • Yousef Hasani

    (Ministry of Energy)

Abstract

Sustainable utilization of water resources requires preventive measures that must be taken to promote optimal use of water resources together with consideration of stakeholder interests and the economic value of water. The main objective of this study is to present an integrated hydro-economic model for allocating agricultural water based on its economic value. The study region covered six irrigation networks downstream of the Zayandeh Rood Dam in Iran. In fact, this study addresses questions of how to allocate scarce water to different consumers, in order to achieve the highest efficiency and economic benefits. To gain this goal, the existing agricultural activities in each irrigation network were simulated by applying the Positive Mathematical Programming (PMP) economic model and then by coupling the economic model with a water allocation planning model of the basin (MODSIM), the hydro-economic framework was generated. These tools helped to allocate water based on its economic value, maximize net profit by determining the optimal cultivating area and analyze the effects of various allocation scenarios on employment, economic productivity, and reliability indicators. Moreover, Bayesian Networks and Random Forest algorithms were developed as an automated substitute to simplify the process and reduce computational complexity. The results showed that the Nekoabad Network enjoys top priority followed by the Barkhar, Mahyar, Sonati, Abshar, and Rodasht Networks. After implementing the Bayesian Network, the four criteria of MAE, MAPE, R2, and the Nash-Sutcliffe index for the irrigation networks were 9 MCM, 24%, 0.738, and 0.644 respectively, which indicated the model has good accuracy. Random Forest method was also employed as a novel technique in automated allocation, and the values obtained for the four mentioned criteria were 7 MCM, 15%, 0.861, and 0.80, which showed it is more accurate. The results indicated the capability of the presented hydro-economic model as well as the intelligent models substituting it in allocating agricultural water.

Suggested Citation

  • Zohreh Sherafatpour & Abbas Roozbahani & Yousef Hasani, 2019. "Agricultural Water Allocation by Integration of Hydro-Economic Modeling with Bayesian Networks and Random Forest Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(7), pages 2277-2299, May.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:7:d:10.1007_s11269-019-02240-9
    DOI: 10.1007/s11269-019-02240-9
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    1. Gomez-Limon, Jose A. & Riesgo, Laura, 2004. "Irrigation water pricing: differential impacts on irrigated farms," Agricultural Economics, Blackwell, vol. 31(1), pages 47-66, July.
    2. Abdoulkarim Esmaeili & Solmaz Vazirzadeh, 2009. "Water Pricing for Agricultural Production in the South of Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(5), pages 957-964, March.
    3. M. Shourian & S. Mousavi & A. Tahershamsi, 2008. "Basin-wide Water Resources Planning by Integrating PSO Algorithm and MODSIM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1347-1366, October.
    4. Quirino Paris & Richard E. Howitt, 1998. "An Analysis of Ill-Posed Production Problems Using Maximum Entropy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 124-138.
    5. Seyed Amir Naghibi & Kourosh Ahmadi & Alireza Daneshi, 2017. "Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2761-2775, July.
    6. Kong Chhuon & Eugene Herrera & Kazuo Nadaoka, 2016. "Application of Integrated Hydrologic and River Basin Management Modeling for the Optimal Development of a Multi-Purpose Reservoir Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 3143-3157, July.
    7. Massoud Tabesh & Abbas Roozbahani & Bardia Roghani & Niousha Rasi Faghihi & Reza Heydarzadeh, 2018. "Risk Assessment of Factors Influencing Non-Revenue Water Using Bayesian Networks and Fuzzy Logic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(11), pages 3647-3670, September.
    8. Bithas, Kostas, 2008. "The sustainable residential water use: Sustainability, efficiency and social equity. The European experience," Ecological Economics, Elsevier, vol. 68(1-2), pages 221-229, December.
    9. Maksud Bekchanov, 2015. "Review of hydro-economic models to address river basin management problems: structure, applications and research gaps," IWMI Working Papers H047337, International Water Management Institute.
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    7. Sadaf-Sadat Mortezaeipooya & Parisa-Sadat Ashofteh & Parvin Golfam, 2022. "Selecting the Best Approach to Modeling the Performance of Water Supply System Using the Combination of Rough Set Theory with Multi-Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3129-3152, July.
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    11. Javier Martínez-Dalmau & Carlos Gutiérrez-Martín & Alfonso Expósito & Julio Berbel, 2023. "Analysis of Water Pricing Policy Effects in a Mediterranean Basin Through a Hydroeconomic Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1599-1618, March.
    12. Seyed Mehdi Seyed Hoshiyar & Nader Pirmoradian & Afshin Ashrafzadeh & Atefeh Parvaresh Rizi, 2021. "Performance Assessment of a Water Delivery Canal to Improve Agricultural Water Distribution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2487-2501, June.
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