Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems

Recent advances in electromagnetic sensor technologies have made automated irrigation scheduling a reality using state-of-the-art soil moisture sensing devices. However, many of the available guidelines for sensor placement were empirically determined from site and crop specific experiments. Sensors accuracy could be also an important factor affecting irrigation efficiency. This study investigates how soil moisture sensors positioning and accuracy may affect the performance of soil moisture based surface drip irrigation scheduling systems under various conditions. For this purpose several numerical experiments were carried out using a mathematical model, incorporating a system-dependent boundary condition in order to simulate soil moisture based irrigation scheduling systems. The results of this study provided clear evidence that soil moisture sensors positioning and accuracy may considerably affect irrigation efficiency in soil moisture based drip irrigation scheduling systems. In specific cases the effect of soil moisture sensors positioning was as high as 16%; however, when nearby sensor positions were examined, the observed differences were generally low. The effect of sensors accuracy was even clearer. For the lower sensor's error level studied (±0.01 cm3 cm−3) the effect on irrigation efficiency ranged between 2.5% and 6.4%, while for the higher error level (±0.03 cm3 cm−3) the effect ranged between 10.2% and 18.7%. These results highlight the importance of a detailed study taking into account the characteristics of specific crops, irrigation, and scheduling systems as well as soil moisture sensors in order to provide a sound basis for improved irrigation scheduling. The need for soil specific calibration of the sensors used in such systems is highlighted as well. Lastly, a significant outcome of this study is the ability of computer models to serve as efficient tools for the detailed investigation of sensors positioning and accuracy, or other automated scheduling system characteristics.