Temporal and spatial variability of soil moisture based on WSN

In order to accurately understand soil water deficit and therefore execute effective and water-saving irrigation, the distribution map of soil moisture was obtained by the integration of wireless sensor networks (WSN) with spatial analysis software. The wireless nodes with moisture sensors were located at predetermined locations, and the geographical coordinates of these points were measured with a GPS receiver. The system sent data of soil moisture every 30 min to the remote management platform using the TCP–IP standard protocol. During the experimental period, the data of soil moisture were dynamically recorded, and the temporal and spatial variability were analyzed to decide whether irrigation was needed. Furthermore, in order to draw the distribution map of soil moisture with the Kriging interpolation method, a P−PP−P normal probability plot was created to test normality of the data, and the variogram model was built to check the spatial continuity of data. Then the distribution map of soil moisture was created with the Kriging interpolation method. Through a long-term testing in the field and data analyzing, it was proved that the whole system worked stably and reliably. The temporal curve could reflect the soil moisture changing trend during the experimental period, and the distribution map could be used to guide precision irrigation management.