Current advances in connected sensor technologies for near real-time environmental monitoring are transforming the quality of information provision to land managers. This “Third Industrial
Revolution” that connects digital sensor data analytics with adaptive services aims to transform data processing for timely decision support. The information is needed to improve irrigation scheduling, because global demand for food relies heavily on irrigation and global freshwater resources are diminishing. Previously, practitioners used visual indicators, infrequent measurements or
predictive water balance models to estimate irrigation schedules. Visual indicators
and infrequent measurements are approximate, and predictive models require many
inputs so that likely cumulative errors cause inaccuracies in scheduling. In
contrast, wireless sensor networks enable near real-time continuousmeasurement of soil
moisture at targeted positions providing the site-specific information required
for precision irrigation scheduling and efficient freshwater management. This
paper describes and compares the structure, build and implementation of
Crossbow, DigiMesh, and LoRa systems to deliver information on spatio-temporal
soil water status and crop stress to practitioners over smart phones and
webpages to improve management of irrigated land. Our study found that the
newer LoRA system has advantages over the other systems, especially on flat
land, with furthest node range of >10 km and advanced communication
protocols that can penetrate dense vegetation. The mesh networking of the
DigiMesh and Crossbow systems was preferred in hilly terrain to communicate
around hills, and allows easy expansion of the network. The Crossbow system is
simpler to install but presents difficulties for third party sensor integration.
All systems allowed a step change in our ability to track dynamic changes in
soil hydraulic properties and crop stress, to improve irrigation water use
efficiency.
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