Open-source electronics Arduino platform for soil water measurement with the dual-probe heat-pulse (DPHP) method

Soil moisture content, which is important in agriculture, has large spatiotemporal variability, making inexpensive multi-site monitoring ideal. The dual-probe heat-pulse (DPHP) method is attractive for estimating soil volumetric water content from soil thermal properties, as the method is physically based and relatively straightforward. In this manuscript, we report on implementation of this method using a custom-made inexpensive open-source electronic hardware measurement system, based on the Arduino Uno platform. We compare the measurement and control performance of the Arduino system to those of a high-end commercial data acquisition system. By conducting the measurements with both systems, sequentially, with the sensors remaining in place, variations that may arise from the sensor installation and sample preparation are minimal, thereby allowing for a direct comparison between the data acquisition systems. The measurements are conducted with four rigid-DPHP (RDPHP) sensors in three media: immobilized water, dry quartz sand, and saturated quartz sand. The identical cylindrical perfect conductors (ICPC) model is fit to the data through parameter optimization, for estimating the unknown properties: effective probe spacing and thermal properties. The volumetric water content is calculated from the volumetric heat capacity through a linear relationship. The measurement results indicate that the open hardware Arduino system has similar accuracy to that of the commercial acquisition system. The results show that the proposed Arduino system can be successfully implemented for the DPHP method, making it an attractive option for a low-cost system, alternative to the available high-end commercial system. • Open-source electronic hardware system based on Arduino Uno is developed for controlling and measuring the dual-probe heat-pulse (DPHP) sensor. • In-situ volumetric water content measurements are conducted under different saturation levels and media conditions, and with different data acquisition systems. • Water content estimations from the different systems are compared and validated with reference methods. • Statistical measures of the measurements and its signal-to-noise ratio are presented for evaluating the systems’ performance.