IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v29y2015i7p2153-2170.html
   My bibliography  Save this article

Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production

Author

Listed:
  • D.-A. An-Vo
  • S. Mushtaq
  • T. Nguyen-Ky
  • J. Bundschuh
  • T. Tran-Cong
  • T. Maraseni
  • K. Reardon-Smith

Abstract

Uncertainty and shortages of surface water supplies, as a result of global climate change, necessitate development of groundwater in many canal commands. Groundwater can be expensive to pump, but provides a reliable supply if managed sustainably. Groundwater can be used optimally in conjunction with surface water supplies. The use of such conjunctive systems can significantly decrease the risk associated with a stochastic availability of surface water supply. However, increasing pumping cost due to groundwater drawdown and energy prices are key concerns. We propose an innovative nonlinear programing model for the optimisation of profitability and productivity in an irrigation command area, with conjunctive water use options. The model, rather than using exogenous yields and gross margins, uses crop water production and profit functions to endogenously determine yields and water uses, and associated gross margins, respectively, for various conjunctive water use options. The model allows the estimation of the potential economic benefits of conjunctive water use and derives an optimal use of regional level land and water resources by maximising the net benefits and water productivity under various physical and economic constraints, including escalating energy prices. The proposed model is applied to the Coleambally Irrigation Area (CIA) in southeastern Australia to explore potential of conjunctive water use and evaluate economic implication of increasing energy prices. The results show that optimal conjunctive water use can offer significant economic benefit especially at low levels of surface water allocation and pumping cost. The results show that conjunctive water use potentially generates additional AUD 57.3 million if groundwater price is the same as surface water price. The benefit decreases significantly with increasing pumping cost. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • D.-A. An-Vo & S. Mushtaq & T. Nguyen-Ky & J. Bundschuh & T. Tran-Cong & T. Maraseni & K. Reardon-Smith, 2015. "Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2153-2170, May.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:7:p:2153-2170
    DOI: 10.1007/s11269-015-0933-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-015-0933-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-015-0933-y?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. Sanjay Raul & Sudhindra Panda, 2013. "Simulation-Optimization Modeling for Conjunctive Use Management under Hydrological Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1323-1350, March.
    2. Ching-Wen Chen & Chih-Chiang Wei & Hung-Jen Liu & Nien-Sheng Hsu, 2014. "Application of Neural Networks and Optimization Model in Conjunctive Use of Surface Water and Groundwater," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2813-2832, August.
    3. M. Tabari & Jaber Soltani, 2013. "Multi-Objective Optimal Model for Conjunctive Use Management Using SGAs and NSGA-II Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 37-53, January.
    4. Chao-Chung Yang & Liang-Cheng Chang & Chang-Shian Chen & Ming-Sheng Yeh, 2009. "Multi-objective Planning for Conjunctive Use of Surface and Subsurface Water Using Genetic Algorithm and Dynamics Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(3), pages 417-437, February.
    5. Khan, Shahbaz & Tariq, Rana & Yuanlai, Cui & Blackwell, J., 2006. "Can irrigation be sustainable?," Agricultural Water Management, Elsevier, vol. 80(1-3), pages 87-99, February.
    6. Ajay Singh, 2014. "Irrigation Planning and Management Through Optimization Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 1-14, January.
    7. Aliasghar Montazar & H. Riazi & S. Behbahani, 2010. "Conjunctive Water Use Planning in an Irrigation Command Area," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 577-596, February.
    8. Dwyer, Gavan & Loke, Paul & Appels, David & Stone, Susan F. & Peterson, Deborah C., 2005. "Integrating rural and urban water markets in south east Australia: Preliminary analysis," Conference Workshop Proceedings 31909, Productivity Commission.
    9. Cortignani, Raffaele & Severini, Simone, 2009. "Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming," Agricultural Water Management, Elsevier, vol. 96(12), pages 1785-1791, December.
    10. Khan, Shahbaz & Rana, Tariq & Hanjra, Munir A. & Zirilli, John, 2009. "Water markets and soil salinity nexus: Can minimum irrigation intensities address the issue?," Agricultural Water Management, Elsevier, vol. 96(3), pages 493-503, March.
    11. Yu Chen & Liang Chang & Chun Huang & Hone Chu, 2013. "Applying Genetic Algorithm and Neural Network to the Conjunctive Use of Surface and Subsurface Water," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4731-4757, November.
    12. Wichelns, Dennis & Oster, J.D., 2006. "Sustainable irrigation is necessary and achievable, but direct costs and environmental impacts can be substantial," Agricultural Water Management, Elsevier, vol. 86(1-2), pages 114-127, November.
    13. Hamid Safavi & Iman Chakraei & Abdolreza Kabiri-Samani & Mohammad Golmohammadi, 2013. "Optimal Reservoir Operation Based on Conjunctive Use of Surface Water and Groundwater Using Neuro-Fuzzy Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4259-4275, September.
    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. Nguyen-Huy, Thong & Deo, Ravinesh C. & An-Vo, Duc-Anh & Mushtaq, Shahbaz & Khan, Shahjahan, 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones," Agricultural Water Management, Elsevier, vol. 191(C), pages 153-172.
    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. Monjardino, Marta & Harrison, Matthew T. & DeVoil, Peter & Rodriguez, Daniel & Sadras, Victor O., 2022. "Agronomic and on-farm infrastructure adaptations to manage economic risk in Australian irrigated broadacre systems: A case study," Agricultural Water Management, Elsevier, vol. 269(C).
    4. Mahdieh Kalhori & Parisa-Sadat Ashofteh & Seyedeh Hadis Moghadam, 2023. "Development of the Multi-Objective Invasive Weed Optimization Algorithm in the Integrated Water Resources Allocation Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4433-4458, September.
    5. Mai, Thanh & Mushtaq, Shahbaz & Loch, Adam & Reardon-Smith, K. & An-Vo, Duc-Anh, 2019. "A systems thinking approach to water trade: Finding leverage for sustainable development," Land Use Policy, Elsevier, vol. 82(C), pages 595-608.
    6. An-Vo, Duc-Anh & Mushtaq, Shahbaz & Zheng, Bangyou & Christopher, Jack T. & Chapman, Scott C. & Chenu, Karine, 2018. "Direct and Indirect Costs of Frost in the Australian Wheatbelt," Ecological Economics, Elsevier, vol. 150(C), pages 122-136.
    7. Zahra Kayhomayoon & Sami Ghordoyee Milan & Naser Arya Azar & Pete Bettinger & Faezeh Babaian & Abolfazl Jaafari, 2022. "A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    8. Shu Chen & Dongguo Shao & Xudong Li & Caixiu Lei, 2016. "Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 2887-2905, July.
    9. Chen, Shu & Shao, Dongguo & Gu, Wenquan & Xu, Baoli & Li, Haoxin & Fang, Longzhang, 2017. "An interval multistage water allocation model for crop different growth stages under inputs uncertainty," Agricultural Water Management, Elsevier, vol. 186(C), pages 86-97.

    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. 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.
    2. 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.
    3. Singh, Ajay, 2014. "Simulation–optimization modeling for conjunctive water use management," Agricultural Water Management, Elsevier, vol. 141(C), pages 23-29.
    4. Shu Chen & Dongguo Shao & Xudong Li & Caixiu Lei, 2016. "Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 2887-2905, July.
    5. Chen, Shu & Shao, Dongguo & Gu, Wenquan & Xu, Baoli & Li, Haoxin & Fang, Longzhang, 2017. "An interval multistage water allocation model for crop different growth stages under inputs uncertainty," Agricultural Water Management, Elsevier, vol. 186(C), pages 86-97.
    6. 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.
    7. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.
    8. 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.
    9. Tsai, Wen-Ping & Cheng, Chung-Lien & Uen, Tinn-Shuan & Zhou, Yanlai & Chang, Fi-John, 2019. "Drought mitigation under urbanization through an intelligent water allocation system," Agricultural Water Management, Elsevier, vol. 213(C), pages 87-96.
    10. Singh, Ajay & Panda, Sudhindra Nath, 2012. "Development and application of an optimization model for the maximization of net agricultural return," Agricultural Water Management, Elsevier, vol. 115(C), pages 267-275.
    11. 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.
    12. Khan, S. & Khan, M.A. & Hanjra, M.A. & Mu, J., 2009. "Pathways to reduce the environmental footprints of water and energy inputs in food production," Food Policy, Elsevier, vol. 34(2), pages 141-149, April.
    13. Zhou, Huiping & Chen, Jinliang & Wang, Feng & Li, Xiaojuan & Génard, Michel & Kang, Shaozhong, 2020. "An integrated irrigation strategy for water-saving and quality-improving of cash crops: Theory and practice in China," Agricultural Water Management, Elsevier, vol. 241(C).
    14. Mandal, Uday & Dhar, Anirban & Panda, Sudhindra N., 2021. "Enhancement of sustainable agricultural production system by integrated natural resources management framework under climatic and operational uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    15. Elahe Fallah-Mehdipour & Omid Bozorg Haddad & Saeed Alimohammadi & Hugo Loáiciga, 2015. "Development of Real-Time Conjunctive Use Operation Rules for Aquifer-Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1887-1906, April.
    16. Khan, Shahbaz & Hanjra, Munir A., 2009. "Footprints of water and energy inputs in food production - Global perspectives," Food Policy, Elsevier, vol. 34(2), pages 130-140, April.
    17. Sanjay Raul & Sudhindra Panda, 2013. "Simulation-Optimization Modeling for Conjunctive Use Management under Hydrological Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1323-1350, March.
    18. Ajay Singh, 2014. "Irrigation Planning and Management Through Optimization Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 1-14, January.
    19. Bennie Grové, 2019. "Improved Water Allocation under Limited Water Supplies Using Integrated Soil-Moisture Balance Calculations and Nonlinear Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 423-437, January.
    20. M. Rezapour Tabari & Abdollah Yazdi, 2014. "Conjunctive Use of Surface and Groundwater with Inter-Basin Transfer Approach: Case Study Piranshahr," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1887-1906, May.

    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:29:y:2015:i:7:p:2153-2170. 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.