The FIGARO platform: how the irrigation decision-support system worked

The platform gives the grower a view of current field conditions, warns of changes ahead (heat, rain, water stress) and recommends how to irrigate in response.

Main features

Model-based recommendations

Advice comes from established crop models such as FAO's AquaCrop or Daisy, not from sensor thresholds alone. The models can be updated during the season, so a schedule can still be corrected mid-season.

Weather and hydrology

Weather forecasts and hydrological models (for example MOHID) can be linked in.

Open to many sensors

Rather than being tied to one brand, the platform accepts a wide range of sensors and remote devices through plug-ins.

Agronomy and hydrology together

Several models can run side by side with measured data, covering both crop and water-system processes.

Optimisation

An optimisation algorithm (developed at the Technion) can aim for yield, water savings or a compromise between the two, so schedules can respect economic constraints and water regulations.

Upgradable and configurable

Local crop models, extra sensors or new technologies can be added without changing the user interface.

Records

Water use and computed performance are logged, which can serve as evidence of compliance.

Two-way information

Researchers' models and farmers' observations both feed the system.

In the field

Inputs typically included weather stations (temperature, humidity, radiation, wind, rain, evapotranspiration), soil moisture probes, water meters, satellite images and, at some sites, canopy sensors. Read more: sensors and satellite images, crop models and real-time data, field data web apps.