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Combining a crop growth model and a machine learning algorithm to estimate regional water-saving potential for field crops

Author

Listed:
  • Liu, Yuqi
  • Li, Chenghao
  • Wu, Yuzhen
  • Wei, Hangzhi
  • Chen, Yifan
  • Wang, Changxi
  • Wang, Yang
  • Šimůnek, Jirka
  • Liao, Renkuan

Abstract

Global water scarcity challenges sustainable development, particularly in arid and semi-arid regions where agriculture consumes the majority of available freshwater. Accurately evaluating water-saving potential at a regional scale is essential for informed water resource allocation. However, upscaling from the field to the regional level remains a significant challenge due to the spatial complexity of environmental factors.

Suggested Citation

  • Liu, Yuqi & Li, Chenghao & Wu, Yuzhen & Wei, Hangzhi & Chen, Yifan & Wang, Changxi & Wang, Yang & Šimůnek, Jirka & Liao, Renkuan, 2026. "Combining a crop growth model and a machine learning algorithm to estimate regional water-saving potential for field crops," Agricultural Systems, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:agisys:v:235:y:2026:i:c:s0308521x26001058
    DOI: 10.1016/j.agsy.2026.104737
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