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Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios

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  • Guo, Daxin
  • Olesen, Jørgen Eivind
  • Manevski, Kiril
  • Ma, Xiaoyi

Abstract

Irrigation schedule is essential for improving crop production and allocating water resources in agricultural regions that heavily rely on irrigation. This study designs a framework based on the AquaCrop model to optimize the irrigation schedule of winter wheat under dry, normal and wet hydrologic scenarios over a large region in China. The model parameters were calibrated for one cultivar using observed data from three locations in the Fenwei Plain, northern China, and were shown to slightly vary spatially across this region. Regional weather data at high spatio-temporal resolution were generated by interpolation and were combined with regional soil data on a 2 × 2 km grid to drive the model. The irrigation schedule for the study area was optimized by combining a multi-objective algorithm with the exponential efficacy coefficient method. The optimization objectives included crop yield, water use efficiency (WUE), irrigation WUE and economic irrigation benefit. The results showed that the optimized irrigation schedule performed better than the current irrigation schedule applied by the farmers under studied hydrologic scenarios, resulting in increased crop yield, WUE, irrigation WUE and irrigation economic benefit by 1.1–9.7% and decreased irrigation amount by 4.2–5.7%, depending on regions within the study area. The framework developed in this study reallocated irrigation water amounts between regions, thereby improving water allocation to achieve optimal crop yield, water use and economic benefit for the Fenwei Plain. The results can also serve as a guide for local farmers and irrigation district managers.

Suggested Citation

  • Guo, Daxin & Olesen, Jørgen Eivind & Manevski, Kiril & Ma, Xiaoyi, 2021. "Optimizing irrigation schedule in a large agricultural region under different hydrologic scenarios," Agricultural Water Management, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:agiwat:v:245:y:2021:i:c:s0378377420321223
    DOI: 10.1016/j.agwat.2020.106575
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    References listed on IDEAS

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    3. Zhu, Hongyan & Zheng, Bingyan & Nie, Weibo & Fei, Liangjun & Shan, Yuyang & Li, Ge & Liang, Fei, 2024. "Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study," Agricultural Water Management, Elsevier, vol. 297(C).
    4. Li, Mo & Li, Haiyan & Fu, Qiang & Liu, Dong & Yu, Lei & Li, Tianxiao, 2021. "Approach for optimizing the water-land-food-energy nexus in agroforestry systems under climate change," Agricultural Systems, Elsevier, vol. 192(C).
    5. Wang, Yongqiang & Huang, Donghua & Sun, Kexin & Shen, Hongzheng & Xing, Xuguang & Liu, Xiao & Ma, Xiaoyi, 2023. "Multiobjective optimization of regional irrigation and nitrogen schedules by using the CERES-Maize model with crop parameters determined from the remotely sensed leaf area index," Agricultural Water Management, Elsevier, vol. 286(C).
    6. 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).

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