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Minimising water inputs and increasing productivity in agricultural plots

The Digital Twins (DT) innovation enables farmers to optimise irrigation through real-time data. With soil moisture sensors, weather forecasts and crop analysis, DT improves water efficiency, increases yields and promotes sustainable agriculture. Learn how this technology facilitates smart decisions and conserves essential resources.

Digital Twins (DT) technology is increasingly recognised for its ability to enable real-time interactions and modifications between an irrigation system and its digital representation. This capability facilitates accurate and less labour-intensive irrigation management.

One way to address inefficiencies in irrigation management and reduce water wastage is through smart technologies related to decision support systems (DSS), such as Digital Twins. This solution involves creating a virtual replica of physical irrigation systems, providing a dynamic, data-driven platform to monitor, predict, and improve irrigation practices.

The main advantage of DT technology lies in its ability to provide accurate, real-time information about the irrigation process. By harnessing data from various sources, such as soil moisture sensors, weather forecasts, and crop growth models, DT is continuously updated to reflect current conditions. This continuous feedback loop enables precise water application, ensuring crops receive the optimum amount of water at the right time. The main outcomes are improved water use efficiency, better crop yields, and sustainable water resource management.

Farmers can integrate DT technologies into their existing irrigation infrastructure. This can be achieved by installing Internet of Things (IoT) sensors and connectivity tools that feed data into the DT model. By doing so, farmers gain a holistic understanding of their irrigation systems, identifying inefficiencies and areas for improvement. For instance, the DT can simulate different irrigation scenarios, helping farmers make informed decisions about scheduling and the quantity of water to apply. This proactive approach ensures judicious water use, conserving resources while maintaining crop health.

Figure 1: Conceptual architecture of an irrigation determination framework.
Source: Manocha, A., Sood, S. K., & Bhatia, M. (2024) https://doi.org/10.1016/j.suscom.2023.100947.

Digital Twins technology involves the creation of a virtual model that accurately reproduces a physical irrigation system. This model is continuously fed with real-time data from a variety of sources:

  • Weather forecasts: Data on temperature, relative humidity, and solar radiation.
  • Soil or plant sensors: Devices that measure soil moisture and other relevant parameters.
  • Remote sensing: Techniques that provide insights into crop vigour and evapotranspiration.
  • Farmer-provided information: Practical insights and historical data contributed by the farmer.

The DT uses this data to simulate different irrigation scenarios, enabling farmers to make informed decisions on water application. DTs continuously learn and adapt, improving their accuracy and efficiency over time. Depending on their complexity and scope, the architecture of a DT can vary significantly. Typically, the creation and maintenance of a DT involve combining various technologies that collaborate to replicate, monitor, and analyse physical systems in a digital environment. Basic guidelines include:

  • Soil moisture sensors: Devices that measure moisture content at different depths and locations across the farm.
  • Weather stations: Comprehensive stations that monitor temperature, humidity, wind speed, solar radiation, and rainfall. These can be installed on-site (most expensive), sourced from public grids (availability dependent), or virtual (if public grid data is unavailable).
  • IoT connectivity tools: Devices connected to a sensing company’s cloud, with access via their server API.
  • Central data collection system: Often cloud-based, this system collects, stores, and processes data from all sensors and external sources.
  • DT modelling software: Specialised software to create and manage the digital twin model.
  • Irrigation control systems: Automated systems that adjust irrigation schedules and amounts based on the DT’s insights.

An example of a demonstration approach to implementing DT technologies in commercial agricultural systems is the DIGIREG project. This initiative integrates sensor installation, remote sensing, and data interpretation to optimise and accurately control irrigation. It also automates schedule adjustments in irrigation controllers, including case studies in commercial vineyards, as well as pistachio, almond, peach, and vegetable orchards.

By adopting DT technologies, farmers can revolutionise irrigation practices, ensuring sustainable water management while boosting productivity and maintaining healthy crops.

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This article was originally written by:
Armand Casadó Tortosa – Institute of Agrifood Research and Technology (IRTA, Spain)

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