Optimum soil water content sensors placement for surface drip irrigation scheduling in layered soils

Efficient irrigation management requires a sound information basis; therefore, various environmental measurements are currently used in irrigation scheduling. Among other technics, the recent progress in electromagnetic sensors technologies promoted the development of automated irrigation scheduling systems based on soil water content sensors with very promising results in terms of water savings. However, a key factor for the adequate performance of such systems is proper placement of soil moisture sensors. Up to now, sensor placement guidelines are fragmentary or empirically determined from site and crop specific experiments. This study aims to extend the findings of previous studies investigating the issue of proper positioning of water content sensors in drip irrigation scheduling systems in uniform soils for the case of layered soils. In this context the representativeness of soil water content sensors' readings and the existence of Time Stable Representative Positions (TSRP) are investigated using a specially developed mathematical model. The use of soil water content probes that are able to monitor soil water content at various depths is also evaluated. It was found that in contrast to the previous findings concerning uniform soils, in the case of layered soils it is not possible to precisely monitor the average soil water content temporal variation in the root zone using a single sensor; however, it is feasible to achieve this using a pair of sensors. Furthermore, common optimum positions for a pair of sensors providing representative soil water content readings independently from the prevailing conditions and the irrigation system configuration can be identified. It was also found that soil water content probes covering the average rooting depth and penetrating both soil layers are also able to provide representative soil water content readings during the whole duration of the irrigation cycle. The above results represent a further step towards the development of general guidelines for sensor placement in soil water content based surface drip irrigation scheduling systems.