The Correlation between Proximal and Remote Sensing Methods for Monitoring Soil Water Content in Agricultural Applications

Abstract

Water shortages have increasingly become a global issue due to the acceleration of climate change. The consumption of freshwater can be reduced to a minimum using water irrigation techniques that are based on conservative methods. For example, one of these is precision irrigation, or PI, which uses advanced digital technology to regulate the amount of water used. The aim is to use the least amount of water necessary for a given purpose. This approach keeps consumption to a minimum while the amount remains effective for its purpose. It is also important to note that the variability which occurs in soil and crops will create different types of conditions. These different conditions will need to be studied so as to determine the correct and adequate dynamics for a water management approach that is efficient. In this study, three investigation methods were developed and compared. The first evaluation was performed on outputs from the geoelectric reading of Automatic Resistivity Profiling (ARP). A second evaluation was performed in real time via a sensor network placed in the soil for the duration of two growing seasons of two different crops. The last evaluation was carried out by using maps of spectral indices obtained by the Sentinel 2 satellites. The correlations between the three methods were evaluated to verify if satellite information may have significant potential in the use of water management in varying conditions. From the results obtained, some correlations have been found from the observations of the three systems under study. This has given a positive input towards using satellite maps which are integrated with simplified proximal sensor networks. The outcome of this technique can improve the efficiency of how to manage water distribution on cultivated land.