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Optimizing agricultural irrigation as virtual energy storage to match renewable power profiles unlocks climate benefits during the energy transition

Nature Food volume 7, pages 27–37 (2026)Cite this article

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Abstract

Agricultural irrigation sustains food production and climate adaptation but intensifies energy use and greenhouse gas emissions. Incorporating irrigation into the power grid’s demand-side response presents a promising yet underexplored opportunity for achieving energy and carbon co-benefits during the global energy transition. We develop the Irrigation Scheduling Optimization Model within the grain–water–energy–carbon nexus to align irrigation schedules with renewable-energy intermittency. Using China as a case study, we demonstrate that fine-tuning irrigation schedules reduces emissions by 11.1%–25.8% under current low-renewable penetrated grids and by 16.5%–56.9% as renewables penetration increases, by using up to 92.3% of otherwise curtailed renewable power. A combined strategy of energy transition, irrigation optimization and diesel-to-electricity electrification could achieve ~42.1 MtCO2e (92.2%) of greenhouse gas savings by the 2050s, approaching net zero emissions. Efficacy peaks when local renewable shares reach 65%–70%, highlighting crucial spatiotemporal windows. Our study positions agricultural irrigation as a nature-integrated form of virtual energy storage, offering a pathway to enhance grid resilience and support low-carbon climate adaptation.

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Fig. 1: Model complex of grain–water–energy–carbon nexus that enables the irrigation rescheduling as a virtual energy storage for decarbonization in agricultural sector during the progress of energy transition and global climate change.
Fig. 2: Grain–water–energy–carbon nexus in China in the 2010s.
Fig. 3: Potential benefits of GHG reduction under different scenarios and irrigation fine-tuning clocks.
Fig. 4: ISOM-induced reuse of curtailed renewable energy for irrigation.
Fig. 5: Carbon reduction benefits from fine-tuning irrigation schedule and the associated mechanisms.

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Data availability

All the data supporting this research were obtained from public sources which have been clearly referenced in the manuscript, Supplementary Methods and Supplementary Tables. Key outcome data can be found in the Supplementary Tables and Zenodo via https://doi.org/10.5281/zenodo.15754319 (ref. 50). Source data are provided with this paper.

Code availability

The codes used for data processing and analysis are available via Zenodo at https://doi.org/10.5281/zenodo.15754319 (ref. 50) to facilitate replication.

References

  1. Wang, X. H. et al. Global irrigation contribution to wheat and maize yield. Nat. Commun. 12, 1235 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. Siebert, S. et al. A global data set of the extent of irrigated land from 1900 to 2005. Hydrol. Earth Syst. Sci. 19, 1521–1545 (2015).

    Article  ADS  Google Scholar 

  3. Okada, M. et al. Varying benefits of irrigation expansion for crop production under a changing climate and competitive water use among crops. Earths Future 6, 1207–1220 (2018).

    Article  ADS  Google Scholar 

  4. Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Qin, J. et al. Global energy use and carbon emissions from irrigated agriculture. Nat. Commun. 15, 3084 (2024).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  6. McCarthy, B. et al. Trends in water use, energy consumption, and carbon emissions from irrigation: role of shifting technologies and energy sources. Environ. Sci. Technol. 54, 15329–15337 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  7. Driscoll, A. W., Conant, R. T., Marston, L. T., Choi, E. & Mueller, N. D. Greenhouse gas emissions from US irrigation pumping and implications for climate-smart irrigation policy. Nat. Commun. 15, 675 (2024).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  8. Siyal, A. W., Gerbens-Leenes, P. W. & Nonhebel, S. Energy and carbon footprints for irrigation water in the lower Indus basin in Pakistan, comparing water supply by gravity fed canal networks and groundwater pumping. J. Clean. Prod. 286, 125489 (2021).

    Article  CAS  Google Scholar 

  9. Karimi, P., Qureshi, A. S., Bahramloo, R. & Molden, D. Reducing carbon emissions through improved irrigation and groundwater management: a case study from Iran. Agric. Water Manage. 108, 52–60 (2012).

    Article  Google Scholar 

  10. Ren, C. & Rosa, L. Global energy and carbon emissions of irrigation and fertilizers management for closing crop yield gaps. Environ. Res. Lett. 20, 104026 (2025).

    Article  ADS  Google Scholar 

  11. Haddeland, I. et al. Global water resources affected by human interventions and climate change. Proc. Natl Acad. Sci. USA 111, 3251–3256 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Lu, S., Bai, X., Li, W. & Wang, N. Impacts of climate change on water resources and grain production. Technol. Forecast. Soc. Change 143, 76–84 (2019).

    Article  Google Scholar 

  13. Lobell, D. B. et al. Prioritizing climate change adaptation needs for food security in 2030. Science 319, 607–610 (2008).

    Article  CAS  PubMed  Google Scholar 

  14. Cremades, R. et al. Co-benefits and trade-offs in the water-energy nexus of irrigation modernization in China. Environ. Res. Lett. 11, 054007 (2016).

    Article  ADS  Google Scholar 

  15. Rajan, A., Ghosh, K. & Shah, A. N. Carbon footprint of India’s groundwater irrigation. Carbon Manag. 11, 265–280 (2020).

    CAS  Google Scholar 

  16. World Energy Statistics and Balances (International Energy Agency, accessed 30 April 2024); https://www.iea.org/data-and-statistics/data-product/world-energy-statistics-and-balances

  17. Bai, B., Lee, H., Shi, Y. & Wang, Z. Integrating solar electricity into a fossil fueled system. Energy 304, 132000 (2024).

    Article  Google Scholar 

  18. Wang, Y. Z. et al. Matching characteristic research of building renewable energy system based on virtual energy storage of air conditioning load. Energies 13, 1269 (2020).

    Article  Google Scholar 

  19. Zhang, Z., Hui, H. & Song, Y. Mitigating the vicious cycle between urban heatwaves and building energy systems in Guangdong–Hong Kong–Macao Greater Bay Area. Innov. Energy 2, 100080 (2025).

    Article  Google Scholar 

  20. Zhang, J., Che, Y., Teodorescu, R., Song, Z. & Hu, X. Energy storage management in electric vehicles. Nat. Rev. Clean Technol. 1, 161–175 (2025).

    Article  Google Scholar 

  21. Liu, X. et al. Transforming public transport depots into profitable energy hubs. Nat. Energy 9, 1206–1219 (2024).

    Article  ADS  Google Scholar 

  22. Li, Y. C. & Hong, S. H. Real-time demand bidding for energy management in discrete manufacturing facilities. IEEE Trans. Ind. Electron. 64, 739–749 (2017).

    Article  Google Scholar 

  23. Luo, Z., Hong, S.-H. & Kim, J.-B. A price-based demand response scheme for discrete manufacturing in smart grids. Energies 9, 650 (2016).

    Article  Google Scholar 

  24. Mohammad, N. & Mishra, Y. in Smart Grids and Their Communication Systems (eds Kabalci, E. & Kabalci, Y.) 197–231 (Springer, 2019).

  25. Tang, H., Wang, S. & Li, H. Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: state-of-the-art and future perspective. Energy 219, 119598 (2021).

    Article  Google Scholar 

  26. Sudhir, Y., Gill, G., Humphreys, E., Kukal, S. S. & Walia, U. S. Effect of water management on dry seeded and puddled transplanted rice. Part 1: crop performance. Field Crop. Res. 120, 112–122 (2011).

    Article  Google Scholar 

  27. Ji, J. et al. Effects of irrigation amount and frequency on water consumption and yield of field cucumber. J. Irrig. Drain. 40, 63–69 (2021).

    Google Scholar 

  28. Zai, S., Feng, X., Wu, F. & Li, L. Effect of time scales on probability of irrigation water requirement of farmland. Trans. Chin. Soc. Agric. Eng 34, 96–102 (2018).

    Google Scholar 

  29. Heptonstall, P. J. & Gross, R. J. K. A systematic review of the costs and impacts of integrating variable renewables into power grids. Nat. Energy 6, 72–83 (2021).

    Article  ADS  Google Scholar 

  30. Jabir, H. J., Teh, J., Ishak, D. & Abunima, H. Impacts of demand-side management on electrical power systems: a review. Energies 11, 1050 (2018).

    Article  Google Scholar 

  31. Cao, X. C., Wang, Y. B., Wu, P., Zhao, X. N. & Wang, J. An evaluation of the water utilization and grain production of irrigated and rain-fed croplands in China. Sci. Total Environ. 529, 10–20 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  32. National Grid Energy Research Institute Corporation. China’s Energy and Electricity Outlook (in Chinese) (China Electric Power, 2018); http://www.sgeri.sgcc.com.cn/u/cms/sgeri/other/201902/20190219111915944695018.pdf

  33. Yang, Y. et al. Sustainable irrigation and climate feedbacks. Nat. Food 4, 654–663 (2023).

    Article  PubMed  Google Scholar 

  34. Rosa, L. Adapting agriculture to climate change via sustainable irrigation: biophysical potentials and feedbacks. Environ. Res. Lett. 17, 063008 (2022).

    Article  ADS  Google Scholar 

  35. Benartzi, S. et al. Should governments invest more in nudging? Psychol. Sci. 28, 1041–1055 (2017).

    Article  PubMed  Google Scholar 

  36. Lehner, M., Mont, O. & Heiskanen, E. Lehner, M., Mont, O. & Heiskanen, E. Nudging – a promising tool for sustainable consumption behaviour? J. Clean. Prod. 134, 166–177 (2016).

    Article  Google Scholar 

  37. Abioye, A. E. et al. Model based predictive control strategy for water saving drip irrigation. Smart Agr. Technol. 4, 100179 (2023).

    Google Scholar 

  38. Rosa, L. et al. Potential for sustainable irrigation expansion in a 3 °C warmer climate. Proc. Natl Acad. Sci. USA 117, 29526–29534 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. Elliott, J. et al. Constraints and potentials of future irrigation water availability on agricultural production under climate change. Proc. Natl Acad. Sci. USA 111, 3239–3244 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  40. D’Odorico, P. et al. The global food-energy-water nexus. Rev. Geophys. 56, 456–531 (2018).

    Article  ADS  Google Scholar 

  41. Jufri, F. H., Widiputra, V. & Jung, J. State-of-the-art review on power grid resilience to extreme weather events: definitions, frameworks, quantitative assessment methodologies, and enhancement strategies. Appl. Energy 239, 1049–1065 (2019).

    Article  ADS  Google Scholar 

  42. Liu, L. B. et al. Potential contributions of wind and solar power to China’s carbon neutrality. Resourc. Conserv. Recycl 180, 106155 (2022).

    Article  CAS  Google Scholar 

  43. Liu, J. et al. Nexus approaches to global sustainable development. Nat. Sustain. 1, 466–476 (2018).

    Article  Google Scholar 

  44. Siebert, S. & Döll, P. Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation. J. Hydrol. 384, 198–217 (2010).

    Article  ADS  Google Scholar 

  45. Siebert, S. & Doell, P. The Global Crop Water Model (GCWM): Documentation and First Results for Irrigated Crops Frankfurt Hydrology Paper 07 (Institute of Physical Geography, University of Frankfurt, 2008); https://www.researchgate.net/publication/264556342_The_Global_Crop_Water_Model_GCWM_Documentation_and_first_results_for_irrigated_crops#fullTextFileContent

  46. International Food Policy Research Institute. Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 2.0. Harvard Dataverse https://doi.org/10.7910/DVN/PRFF8V (2019).

  47. Fan, X., Zhang, W., Chen, W. & Chen, B. Land-water-energy nexus in agricultural management for greenhouse gas mitigation. Appl. Energy 265, 114796 (2020).

    Article  Google Scholar 

  48. Cremades, R., Wang, J. & Morris, J. Policies, economic incentives and the adoption of modern irrigation technology in China. Earth Syst. Dyn. 6, 399–410 (2015).

    Article  ADS  Google Scholar 

  49. Wang, J. et al. China’s water–energy nexus: greenhouse-gas emissions from groundwater use for agriculture. Environ. Res. Lett. 7, 014035 (2012).

    Article  ADS  Google Scholar 

  50. Wang, R. Fine-tuning-irrigation-matching-renewable-power-profile. Zenodo https://doi.org/10.5281/zenodo.15754319 (2025)

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Acknowledgements

B.L. is funded in part by the National Natural Science Foundation of China (W2412016, 72174085 and 72488101). Y.Y. is funded in part by National Social Science Fund (22&ZD103), Start-UP funding of China University of Petroleum (Beijing) (ZX20250049), and the National Natural Science Foundation of China (72140005). R.W. acknowledges support from the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX25_0353). We also thank Y. Qin from Peking University for her insightful technical guidance on soil water balance modelling.

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Author notes

  1. These authors contributed equally: Rui Wang 汪瑞, Wenfeng He 何汶峰.

Authors and Affiliations

  1. State Key Laboratory of Water Pollution Control & Green Resource Recycling, School of Environment, Nanjing University, Nanjing, People’s Republic of China

    Rui Wang  (汪瑞), Wenfeng He  (何汶峰), Yumiao Xue  (薛玉苗) & Beibei Liu  (刘蓓蓓)

  2. National Engineering Research Center of Eco-Environment in the Yangtze River Economic Belt, Wuhan, People’s Republic of China

    Wenfeng He  (何汶峰)

  3. School of Economics and Management, China University of Petroleum (Beijing), Beijing, People’s Republic of China

    Yang Yu  (于洋)

  4. Basic Science Center for Energy and Climate Change, Beijing, People’s Republic of China

    Beibei Liu  (刘蓓蓓)

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  1. Rui Wang  (汪瑞)
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Contributions

B.L., Y.Y., W.H. and R.W. conceptualized and designed the study. R.W., W.H. and Y.X. performed the analyses. Y.X., R.W. and W.H. produced the figures. R.W. and W.H. wrote the original draft. R.W., Y.Y. and B.L. further revised the paper.

Corresponding authors

Correspondence to Yang Yu  (于洋) or Beibei Liu  (刘蓓蓓).

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Nature Food thanks Weili Duan, Lorenzo Rosa and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Wang, R., He, W., Xue, Y. et al. Optimizing agricultural irrigation as virtual energy storage to match renewable power profiles unlocks climate benefits during the energy transition. Nat Food 7, 27–37 (2026). https://doi.org/10.1038/s43016-025-01285-x

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