Empirical two‐point α‐mixing model for calibrating the ECH2O EC‐5 soil moisture sensor in sands

Recently improved ECH 2 O soil moisture sensors have received significant attention in many field and laboratory applications. Focusing on the EC‐5 sensor, a simple and robust calibration method is proposed. The sensor‐to‐sensor variability in the readings (analog‐to‐digital converter (ADC) counts) among 30 EC‐5 sensors was relatively small but not negligible. A large number of ADC counts were taken under various volumetric water contents (θ) using four test sands. The proposed two‐point α ‐mixing model, as well as linear and quadratic models, was fitted to the ADC – θ data. Unlike for conventional TDR measurements, the effect of sensor characteristics is lumped into the empirical parameter α in the two‐point α ‐mixing model. The value of α was fitted to be 2.5, yielding a nearly identical calibration curve to the quadratic model. Errors in θ associated with the sensor‐to‐sensor variability for the two‐point α ‐mixing model were ±0.005 cm 3 cm −3 for dry sand and ±0.028 cm 3 cm −3 for saturated sand. In the validation experiments, the highest accuracy in water content estimation was achieved when sensor‐specific ADC dry and ADC sat were used in the two‐point α ‐mixing model. Assuming that α = 2.5 is valid for most mineral soils, the two‐point α ‐mixing model only requires the measurement of two extreme ADC counts in dry and saturated soils. Sensor‐specific ADC dry and ADC sat counts are readily measured in most cases. Therefore, the two‐point α ‐mixing model (with α = 2.5) can be considered as a quick, easy, and robust method for calibrating the ECH 2 O EC‐5 sensor. Although further investigation is needed, the two‐point α ‐mixing model may also be applied to calibrating other sensors.