IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v322y2025ics0378377425007231.html

Evaluating the potential of desalinated irrigation in water-stressed regions through optimized planting dates and irrigation strategies

Author

Listed:
  • Zolghadr-Asli, Babak
  • McIntyre, Neil
  • Djordjevic, Slobodan
  • Farmani, Raziyeh
  • Pagliero, Liliana
  • Pérez-Murillo, Gabriel

Abstract

With the looming water crisis and its adverse impacts on the food and agriculture industry, exploring the potential of unconventional resources like desalinated water with a fresh perspective is essential. The idea of irrigation using desalinated water has gained increasing traction recently. To maximize the potential of this idea, is essential to appreciate the nuances of using desalinated water for irrigation. In particular, using desalinated water can help avoid dependency on the hydrological cycle, for instance, it may be possible to optimize planting dates and irrigation scheduling to increase agriculture production beyond what would otherwise be possible. As a proof-of-concept, this paper showcases that idea using a case study of tomato production in the Atacama region. A python-based crop growth model, AquaCrop-OSPy, represents the crop responses to irrigation strategies under local hydro-climatic conditions. The self-tuning multi-layer (STML) algorithm was linked to this model to identify the optimal deficit irrigation scheme. This was repeated for different initial planting dates. The impact of soil property uncertainties on the results was analyzed using a Monte Carlo simulation. The results highlight that adjusting the planting dates along with optimal deficit irrigation could indeed improve water productivity, which could, in turn, help offset the costs of using desalinated water. Leveraging economies of scale, both in agriculture and in desalinated water production, could further offset some of the costs.

Suggested Citation

  • Zolghadr-Asli, Babak & McIntyre, Neil & Djordjevic, Slobodan & Farmani, Raziyeh & Pagliero, Liliana & Pérez-Murillo, Gabriel, 2025. "Evaluating the potential of desalinated irrigation in water-stressed regions through optimized planting dates and irrigation strategies," Agricultural Water Management, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:agiwat:v:322:y:2025:i:c:s0378377425007231
    DOI: 10.1016/j.agwat.2025.110009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377425007231
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2025.110009?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Zolghadr-Asli, Babak & McIntyre, Neil & Djordjevic, Slobodan & Farmani, Raziyeh & Pagliero, Liliana, 2023. "The sustainability of desalination as a remedy to the water crisis in the agriculture sector: An analysis from the climate-water-energy-food nexus perspective," Agricultural Water Management, Elsevier, vol. 286(C).
    2. Peder Hjorth & Kaveh Madani, 2023. "Adaptive Water Management: On the Need for Using the Post-WWII Science in Water Governance," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2247-2270, May.
    3. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    4. Tenreiro, Tomás R. & García-Vila, Margarita & Gómez, José A. & Jimenez-Berni, José A. & Fereres, Elías, 2020. "Water modelling approaches and opportunities to simulate spatial water variations at crop field level," Agricultural Water Management, Elsevier, vol. 240(C).
    5. 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).
    6. Li, Jiang & Song, Jian & Li, Mo & Shang, Songhao & Mao, Xiaomin & Yang, Jian & Adeloye, Adebayo J., 2018. "Optimization of irrigation scheduling for spring wheat based on simulation-optimization model under uncertainty," Agricultural Water Management, Elsevier, vol. 208(C), pages 245-260.
    7. Manish Yadav & B. B. Vashisht & S. K. Jalota & T. Jyolsna & Samar Pal Singh & Arun Kumar & Amit Kumar & Gurjeet Singh, 2024. "Improving Water Efficiencies in Rural Agriculture for Sustainability of Water Resources: A Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(10), pages 3505-3526, August.
    8. Sharafkhane, Mahdi Gholami & Ziaei, Ali Naghi & Naghedifar, Seyed Mohammadreza & Akbari, Amir & Verdi, Amir, 2024. "AquaCrop Plug-in-PSO: A novel irrigation scheduling optimization framework for maize to maximize crop water productivity using in-season weather forecast and crop yield estimation," Agricultural Water Management, Elsevier, vol. 306(C).
    9. Kelly, T.D. & Foster, T., 2021. "AquaCrop-OSPy: Bridging the gap between research and practice in crop-water modeling," Agricultural Water Management, Elsevier, vol. 254(C).
    10. Kelly, T.D. & Foster, T. & Schultz, David M., 2023. "Assessing the value of adapting irrigation strategies within the season," Agricultural Water Management, Elsevier, vol. 275(C).
    11. Serra, J. & Paredes, P. & Cordovil, CMdS & Cruz, S. & Hutchings, NJ & Cameira, MR, 2023. "Is irrigation water an overlooked source of nitrogen in agriculture?," Agricultural Water Management, Elsevier, vol. 278(C).
    12. Katerji, Nader & Campi, Pasquale & Mastrorilli, Marcello, 2013. "Productivity, evapotranspiration, and water use efficiency of corn and tomato crops simulated by AquaCrop under contrasting water stress conditions in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 130(C), pages 14-26.
    13. Luis Santos Pereira, 2017. "Water, Agriculture and Food: Challenges and Issues," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2985-2999, August.
    14. França, Ana Carolina Ferreira & Coelho, Rubens Duarte & da Silva Gundim, Alice & de Oliveira Costa, Jéfferson & Quiloango-Chimarro, Carlos Alberto, 2024. "Effects of different irrigation scheduling methods on physiology, yield, and irrigation water productivity of soybean varieties," Agricultural Water Management, Elsevier, vol. 293(C).
    15. Wang, Naijiang & Chen, Haixin & Ding, Dianyuan & Zhang, Tibin & Li, Cheng & Luo, Xiaoqi & Chu, Xiaosheng & Feng, Hao & Wei, Yongsheng & Siddique, Kadambot H.M., 2022. "Plastic film mulching affects field water balance components, grain yield, and water productivity of rainfed maize in the Loess Plateau, China: A synthetic analysis of multi-site observations," Agricultural Water Management, Elsevier, vol. 266(C).
    16. Medellín-Azuara, J. & Howitt, R.E. & Harou, J.J., 2012. "Predicting farmer responses to water pricing, rationing and subsidies assuming profit maximizing investment in irrigation technology," Agricultural Water Management, Elsevier, vol. 108(C), pages 73-82.
    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, Kexin & Jiang, Yanan & Li, Ang & Tian, Xiangzhe & Lu, Jiatong & Wei, Tingting & Xiangli, Jiangfeng & Huang, Xifeng & Li, Yongmin & Sun, Shikun, 2026. "An integrated meteorological adaptive simulation-optimization framework for real-time irrigation scheduling considering perfect weather forecasts," Agricultural Systems, Elsevier, vol. 232(C).
    2. Feng, Xudong & Yan, Zongzheng & Liu, Na & Liu, Qingshan & Shao, Liwei & Liu, Xiuwei, 2025. "Optimizing soil water sensor placement and irrigation thresholds for winter wheat: A data-driven approach to efficient water management," Agricultural Water Management, Elsevier, vol. 320(C).
    3. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    4. Nicolette Matthews & Bennie Grové & Johannes Hendrikus Barnard, 2025. "Economic Analysis of Segmented Soil Salinity Management Using Current Irrigation Technology," Agriculture, MDPI, vol. 15(8), pages 1-14, April.
    5. Liu, Yuqi & Wang, Yang & Šimůnek, Jirka & Liao, Renkuan, 2025. "An integrated data assimilation, crop modeling, and multi-objective optimization framework for improving cotton irrigation water use efficiency," Agricultural Water Management, Elsevier, vol. 319(C).
    6. Ivan Portoghese & Raffaella Matarrese & Laura Mirra & Giacomo Giannoccaro, 2025. "Assimilating Farmers’ Behaviour in the Development of an ET-Based Irrigation Water-Accounting Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(14), pages 7749-7774, November.
    7. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
    8. Quiloango-Chimarro, Carlos Alberto & Coelho, Rubens Duarte & Gundim, Alice da Silva & Costa, Jéfferson de Oliveira & da Rocha, Tainá Ferreira & Heinemann, Alexandre Bryan, 2025. "Irrigation strategies for upland rice cultivars in Brazil: Physiological responses and agronomic performance," Agricultural Water Management, Elsevier, vol. 321(C).
    9. Zhang, Ting & Zuo, Qiang & Ma, Ning & Shi, Jianchu & Fan, Yuchuan & Wu, Xun & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2023. "Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop," Agricultural Water Management, Elsevier, vol. 286(C).
    10. Peng, Zhiwen & Guo, Aijun & Chang, Jianxia & Wang, Yimin & Wang, Xuebin & Niu, Chen & Li, Zhehao, 2025. "Developing reservoir operation strategy under the mechanism-data dual-driven framework: Coordinating the water demand characteristics of multi sectors," Agricultural Water Management, Elsevier, vol. 318(C).
    11. Silva, Simão P. & Valín, M. Isabel & Mendes, Susana & Araujo-Paredes, Claúdio & Cancela, Javier J., 2024. "Water productivity in Vitis vinifera L. cv. Alvarinho using dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 303(C).
    12. Teng, Kuixiu & Meng, Shilong & Liu, Yunqi, 2025. "Can alternating irrigation technology drive water saving in agricultural irrigation? Evidence from China," Agricultural Water Management, Elsevier, vol. 320(C).
    13. Muhammad Alkaff & Abdullah Basuhail & Yuslena Sari, 2025. "Optimizing Water Use in Maize Irrigation with Reinforcement Learning," Mathematics, MDPI, vol. 13(4), pages 1-21, February.
    14. Wang, Qunyan & Jia, Yifan & Pang, Zhongjun & Zhou, Jianbin & Scriber, Kevin Emmanuel & Liang, Bin & Chen, Zhujun, 2024. "Intelligent fertigation improves tomato yield and quality and water and nutrient use efficiency in solar greenhouse production," Agricultural Water Management, Elsevier, vol. 298(C).
    15. Dercas, Nicholas & Tziatzios, Georgios A. & Sidiropoulos, Pantelis & Sarchani, Sofia & Faraslis, Ioannis & Belaud, Gilles & Daudin, Kevin & Spiliotopoulos, Marios & Sakellariou, Stavros & Alpanakis, N, 2025. "Monitoring satellite-based crop irrigation water requirements for maize, cotton and hay in distinct Mediterranean regions," Agricultural Water Management, Elsevier, vol. 319(C).
    16. Xue, Run & Jiang, Yue & Li, Hong & Shi, Bin, 2025. "Review of advancements and challenges in delayed irrigation: Enhancing crop water productivity and sustainable crop production," Agricultural Water Management, Elsevier, vol. 318(C).
    17. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Xiang, Youzhen & Liu, Xiaoqiang & Liao, Zhenqi & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun, 2022. "Evaluation of AquaCrop model for greenhouse cherry tomato with plastic film mulch under various water and nitrogen supplies," Agricultural Water Management, Elsevier, vol. 274(C).
    18. Liu, Xiao & Yang, Dawen, 2021. "Irrigation schedule analysis and optimization under the different combination of P and ET0 using a spatially distributed crop model," Agricultural Water Management, Elsevier, vol. 256(C).
    19. Zhang, Xuegui & Li, Yao & Deng, Zengxuan & Zhao, Zhengxin & Gu, Xiaobo & Yu, Lianyu & Xu, Jiatun & Cai, Huanjie, 2025. "Revealing nonlinear thresholds and interactions in maize yield and water productivity responses to straw incorporation via an integrated meta-analysis and explainable machine learning framework," Agricultural Water Management, Elsevier, vol. 322(C).
    20. Parra-López, Carlos & Ben Abdallah, Saker & Garcia-Garcia, Guillermo & Hassoun, Abdo & Trollman, Hana & Jagtap, Sandeep & Gupta, Sumit & Aït-Kaddour, Abderrahmane & Makmuang, Sureerat & Carmona-Torres, 2025. "Digital technologies for water use and management in agriculture: Recent applications and future outlook," Agricultural Water Management, Elsevier, vol. 309(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:agiwat:v:322:y:2025:i:c:s0378377425007231. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.