摘要
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 continuous measurement 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.
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 continuous measurement 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.
