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Water Resources Research



Recently improved ECH2O 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 (?) using four test sands. The proposed two-point a-mixing model, as well as linear and quadratic models, was fitted to the ADC – ? data. Unlike for conventional TDR measurements, the effect of sensor characteristics is lumped into the empirical parameter a in the two-point a-mixing model. The value of a was fitted to be 2.5, yielding a nearly identical calibration curve to the quadratic model. Errors in ? associated with the sensor-to-sensor variability for the two-point a-mixing model were ±0.005 cm3 cm-3 for dry sand and ±0.028 cm3 cm-3 for saturated sand. In the validation experiments, the highest accuracy in water content estimation was achieved when sensor-specific ADCdry and ADCsat were used in the two-point a-mixing model. Assuming that a = 2.5 is valid for most mineral soils, the two-point a-mixing model only requires the measurement of two extreme ADC counts in dry and saturated soils. Sensor-specific ADCdry and ADCsat counts are readily measured in most cases. Therefore, the two-point a-mixing model (with a = 2.5) can be considered as a quick, easy, and robust method for calibrating the ECH2O EC-5 sensor. Although further investigation is needed, the two-point a-mixing model may also be applied to calibrating other sensors.


Civil and Environmental Engineering | Civil Engineering | Engineering

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