Development of an automated general temperature correction method for dielectric sensors
This study developed an automated general temperature correction method for dielectric sensors which require neither on-site rainfall data nor soil property information. The automated general temperature correction method was developed and tested using 43 soil moisture monitoring stations covering four major climates and six major soil types. The in situ data sets used in this study were observed with four commercially available dielectric sensors. The results indicated that the automated temperature correction developed in this study is capable of eliminating temperature effects from dielectrically measured soil water content data regardless of the differences in sensor type, climatic condition and site or soil conditions. Further, it has been found that due to temperature effects of dielectric sensors, actual daily average of SWC has also changed substantially in comparison to the ±1% specification.