IDEAS home Printed from https://ideas.repec.org/a/ags/agreko/347968.html
   My bibliography  Save this article

Risk efficiency of optimal water allocation within a single- and multi-stage decision-making framework

Author

Listed:
  • Madende, Primrose
  • Grové, Bennie

Abstract

The South African government has put legislation in place to exercise better control over irrigation water usage. Thus, proper planning of irrigation areas and scheduling of irrigation events in order to stay within water quotas has become more important. Currently, the available methodologies to assist irrigation farmers overlook the complexities and interrelated relationships between crop-area planning and the multi-stage nature of irrigation-scheduling decisions within a stochastic dynamic environment. This paper contributes to knowledge through the development of a bio-economic model that uses evolutionary algorithms to optimise water use, taking cognisance of the complex interrelationships between crop-area planning, the multistage decision-making nature of irrigation-scheduling decisions, and the stochastic dynamic environment under conditions of limited water supply. The results show that gross margin variability is reduced and the expected outcomes are improved due to improved irrigation-scheduling decisions made sequentially in multiple stages. Multi-stage decisions tend to make the impact of risk aversion less profound because taking account of unfolding weather information is risk reducing. Ignoring the risk-reducing impact of sequential decision-making will over-estimate the cost of water restrictions. Caution is hence necessary when formulating agricultural water-allocation policies based on crop water optimisation models that overlook the complex nature of irrigation decisions.

Suggested Citation

  • Madende, Primrose & Grové, Bennie, 2019. "Risk efficiency of optimal water allocation within a single- and multi-stage decision-making framework," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 59(01), August.
    • Handle: RePEc:ags:agreko:347968
    DOI: 10.22004/ag.econ.347968
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/347968/files/Risk%20efficiency%20of%20optimal%20water%20allocation%20within%20a%20single-%20and%20multi-stage%20decision-making%20framework.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.347968?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
    ---><---

    References listed on IDEAS

    as
    1. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    2. Dai, Z.Y. & Li, Y.P., 2013. "A multistage irrigation water allocation model for agricultural land-use planning under uncertainty," Agricultural Water Management, Elsevier, vol. 129(C), pages 69-79.
    3. Robert, Marion & Dury, Jérôme & Thomas, Alban & Therond, Olivier & Sekhar, Muddu & Badiger, Shrini & Ruiz, Laurent & Bergez, Jacques-Eric, 2016. "CMFDM: A methodology to guide the design of a conceptual model of farmers' decision-making processes," Agricultural Systems, Elsevier, vol. 148(C), pages 86-94.
    4. Robert, Marion & Thomas, Alban & Sekhar, Muddu & Badiger, Shrinivas & Ruiz, Laurent & Raynal, Hélène & Bergez, Jacques-Eric, 2017. "Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms," Agricultural Systems, Elsevier, vol. 157(C), pages 279-291.
    5. Rao, N. H. & Sarma, P. B. S. & Chander, Subhash, 1988. "A simple dated water-production function for use in irrigated agriculture," Agricultural Water Management, Elsevier, vol. 13(1), pages 25-32, April.
    6. Kusunose, Yoko & Mahmood, Rezaul, 2016. "Imperfect forecasts and decision making in agriculture," Agricultural Systems, Elsevier, vol. 146(C), pages 103-110.
    7. Botes, J. H. F. & Bosch, D. J. & Oosthuizen, L. K., 1996. "A simulation and optimization approach for evaluating irrigation information," Agricultural Systems, Elsevier, vol. 51(2), pages 165-183, June.
    8. Kelly J. Bryant & James W. Mjelde & Ronald D. Lacewell, 1993. "An Intraseasonal Dynamic Optimization Model to Allocate Irrigation Water between Crops," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1021-1029.
    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. Baccar, Mariem & Raynal, Hélène & Sekhar, Muddu & Bergez, Jacques-Eric & Willaume, Magali & Casel, Pierre & Giriraj, P. & Murthy, Sanjeeva & Ruiz, Laurent, 2023. "Dynamics of crop category choices reveal strategies and tactics used by smallholder farmers in India to cope with unreliable water availability," Agricultural Systems, Elsevier, vol. 211(C).
    2. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    3. 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.
    4. Amin Daghighi & Ali Nahvi & Ungtae Kim, 2017. "Optimal Cultivation Pattern to Increase Revenue and Reduce Water Use: Application of Linear Programming to Arjan Plain in Fars Province," Agriculture, MDPI, vol. 7(9), pages 1-11, September.
    5. 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.
    6. 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).
    7. Jahel, C. & Augusseau, X. & Lo Seen, D., 2018. "Modelling cropping plan strategies: What decision margin for farmers in Burkina Faso?," Agricultural Systems, Elsevier, vol. 167(C), pages 17-33.
    8. Wang, Yufeng & Kang, Shaozhong & Li, Fusheng & Zhang, Xiaotao, 2021. "Modified water-nitrogen productivity function based on response of water sensitive index to nitrogen for hybrid maize under drip fertigation," Agricultural Water Management, Elsevier, vol. 245(C).
    9. Bergez, J. -E. & Garcia, F. & Lapasse, L., 2004. "A hierarchical partitioning method for optimizing irrigation strategies," Agricultural Systems, Elsevier, vol. 80(3), pages 235-253, June.
    10. Bingkui Qiu & Shasha Lu & Min Zhou & Lu Zhang & Yu Deng & Ci Song & Zuo Zhang, 2015. "A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    11. Novotny, Ivan P. & Boul Lefeuvre, Nastasia & Attiogbé, Koffi S. & Wouyo, Atakpama & Fousseni, Folega & Dray, Anne & Waeber, Patrick O., 2024. "Exploring farmer choices in Southern Togo: Utilizing a strategy game to understand decision-making in agricultural practices," Agricultural Systems, Elsevier, vol. 218(C).
    12. Shang, Songhao & Mao, Xiaomin, 2006. "Application of a simulation based optimization model for winter wheat irrigation scheduling in North China," Agricultural Water Management, Elsevier, vol. 85(3), pages 314-322, October.
    13. Ghazali, Mahboubeh & Honar, Tooraj & Nikoo, Mohammad Reza, 2018. "A hybrid TOPSIS-agent-based framework for reducing the water demand requested by stakeholders with considering the agents’ characteristics and optimization of cropping pattern," Agricultural Water Management, Elsevier, vol. 199(C), pages 71-85.
    14. Domínguez, Alfonso & Schwartz, Robert C. & Pardo, José J. & Guerrero, Bridget & Bell, Jourdan M. & Colaizzi, Paul D. & Louis Baumhardt, R., 2022. "Center pivot irrigation capacity effects on maize yield and profitability in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 261(C).
    15. Wu, Xin & Zheng, Yi & Wu, Bin & Tian, Yong & Han, Feng & Zheng, Chunmiao, 2016. "Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach," Agricultural Water Management, Elsevier, vol. 163(C), pages 380-392.
    16. 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.
    17. Jana, R.K. & Sharma, Dinesh K. & Chakraborty, B., 2016. "A hybrid probabilistic fuzzy goal programming approach for agricultural decision-making," International Journal of Production Economics, Elsevier, vol. 173(C), pages 134-141.
    18. Verena Preusse & Nils Nölke & Meike Wollni, 2024. "Urbanization and adoption of sustainable agricultural practices in the rural‐urban interface of Bangalore, India," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(2), pages 167-198, June.
    19. Ko, Jonghan & Piccinni, Giovanni & Steglich, Evelyn, 2009. "Using EPIC model to manage irrigated cotton and maize," Agricultural Water Management, Elsevier, vol. 96(9), pages 1323-1331, September.
    20. Mandal, Uttam Kumar & Victor, U.S. & Srivastava, N.N. & Sharma, K.L. & Ramesh, V. & Vanaja, M. & Korwar, G.R. & Ramakrishna, Y.S., 2007. "Estimating yield of sorghum using root zone water balance model and spectral characteristics of crop in a dryland Alfisol," Agricultural Water Management, Elsevier, vol. 87(3), pages 315-327, February.

    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:ags:agreko:347968. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aeasaea.html .

    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.