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Soil moisture forecasting for precision irrigation management using real-time electricity consumption records

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  • Feng, Xudong
  • Bi, Shaojie
  • Li, Hongjun
  • Qi, Yongqing
  • Chen, Suying
  • Shao, Liwei

Abstract

The installation of the smart electricity meters (SEMs) to the high-density pumping wells in the North China Plain (NCP) provided a method to control the groundwater withdraw. The record in real-time electricity consumption from SEMs also provided an alternative method to forecast soil moisture to make irrigation decisions to improve irrigation efficiency. The irrigation timing and the irrigation amount could be obtained on-line from the SEMs based on the coefficients obtained for electricity-to-water conversion (E-Wc). The real-time recordings in the irrigation timing and amounts were further used to forecast the next irrigation timing and amount based on the water rights per area of land, the lower limit of soil water contents for different crops at their different growing stages and online meteorological data. A smartphone app was developed based on this framework. The running of the app to simulate soil water contents based on the soil water balance equation was supported by databases on soil texture, crop coefficients, water rights, E-Wc and threshold soil water content values as well as the real-time collection of electricity consumption and meteorological data. The simulated real-time soil water contents were shown on the mobile phone screen and could be compared with the threshold values for making irrigation decisions for users. The accuracy in forecasting the soil water contents using the methods developed in this framework was tested under different irrigation schedules for winter wheat and summer maize during 2018–2019 and 2021–2022, and the app was tested for three locations starting from sowing winter wheat in October 2022 to April in 2023. The results showed that the app could be easily run, and precise real-time soil water contents were simulated. With the application of the pumping well renovation project in the NCP, most of the pumping wells were installed with the SEMs, and using SEMs for groundwater pumping control and irrigation decisions should be possible.

Suggested Citation

  • Feng, Xudong & Bi, Shaojie & Li, Hongjun & Qi, Yongqing & Chen, Suying & Shao, Liwei, 2024. "Soil moisture forecasting for precision irrigation management using real-time electricity consumption records," Agricultural Water Management, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:agiwat:v:291:y:2024:i:c:s0378377423005218
    DOI: 10.1016/j.agwat.2023.108656
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    References listed on IDEAS

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    1. Sun, Xuguang & Zhang, Baoyuan & Dai, Menglei & Jing, Cuijiao & Ma, Kai & Tang, Boyi & Li, Kejiang & Dang, Hongkai & Gu, Limin & Zhen, Wenchao & Gu, Xiaohe, 2024. "Accurate irrigation decision-making of winter wheat at the filling stage based on UAV hyperspectral inversion of leaf water content," Agricultural Water Management, Elsevier, vol. 306(C).
    2. Xuan Fang & Jie Yang, 2025. "Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback," Sustainability, MDPI, vol. 17(12), pages 1-20, June.

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