A Monitoring Method for Agricultural Soil Moisture Using Wireless Sensors and the Biswas Model
Year: 2025
Type: article
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 (R2) 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.
Source: Agriculture
Authors: Yuanzhen Zhang, Guofang Wang, Lingzhi Li, Mingjing Huang
Institution: Shanxi Agricultural University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDGs: Zero hunger, Life on land
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4407190987