A Monitoring Method for Agricultural Soil Moisture Using Wireless Sensors and the Biswas Model

Yuanzhen Zhang, Guofang Wang, Lingzhi Li () and Mingjing Huang ()
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Yuanzhen Zhang: College of Software, Shanxi Agricultural University, Jinzhong 030801, China
Guofang Wang: College of Resources and Environmental Science, Shanxi Agricultural University, Jinzhong 030801, China
Lingzhi Li: College of Horticulture, Shanxi Agricultural University, Jinzhong 030801, China
Mingjing Huang: Shanxi Institute of Organic Dryland Agriculture, Shanxi Agricultural University, Taiyuan 030000, China

Agriculture, 2025, vol. 15, issue 3, 1-18

Abstract: Efficient monitoring of soil moisture is crucial for optimizing water usage and ensuring crop health in agricultural fields, especially under rainfed conditions. This study proposes a high-throughput soil moisture monitoring method that integrates LoRa-based wireless sensor networks with region-specific statistical models. Wireless sensors were deployed in the top 0–0.2 m soil layer to gather real-time moisture data, which were then combined with the Biswas model to estimate soil moisture distribution down to a depth of 2.0 m. The model was calibrated using field capacity and crop wilting coefficients. Results demonstrated a strong correlation between model predictions and actual measured soil moisture storage, with a coefficient of determination (R 2 ) exceeding 0.94. Additionally, 83% of sample points had relative errors below 18.5%, and for depths of 0–1.2 m, 90% of sample points had relative errors under 15%. The system effectively tracked daily soil moisture dynamics during maize growth, with predicted evapotranspiration relative errors under 10.25%. This method provides a cost-effective and scalable tool for soil moisture monitoring, supporting irrigation optimization and improving water use efficiency in dryland agriculture.

Keywords: soil moisture monitoring; wireless sensor networks; Biswas model; soil water storage (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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