CANALBRAIN Operational Group: Project for the modeling and regulation of canals and hydraulic networks using elements managed by artificial intelligence
- Type Operational group
- Status In progress
- Execution 2023 -2027
- Assigned Budget 150.000,00 €
- Scope Autonómico
- Autonomous community Aragón
The project's objectives are: to analyze current and future water demand scenarios in the canals and distribution networks of an irrigated area of the Monegros Canal; to define current management strategies and how they should be modified to adapt to these scenarios; to develop predictive tools (Artificial Intelligence systems) to anticipate management maneuvers; and to implement a control system in a pilot section of the canal network.
To this end, a work plan will be developed that consists of defining simulation models to emulate the channel's operating conditions in different demand scenarios; introducing these models into a predictive control IT service through the development of Artificial Intelligence techniques; implementing pilot field tests to verify the results of the development; analyzing the system's potential; and disseminating and expanding its use to other channels with similar problems.
Obtain an artificial intelligence methodology applied to a case study and applicable to other channels, allowing channel management taking into account: changing supply and demand conditions, physical characteristics of the channel, remote control tools, and automation.
- DESIGN PHASE: Project definition and scope. Study, selection, and documentation of the pilot canal section. Definition of the agronomic influence on canal management. Definition of the functional needs and specific objectives of the pilot canal.
- MODELING PHASE: Definition of necessary simulation models. Definition of intelligent control system specifications. Generation of the digital twin. Simulation and modeling of possible events.
- GENERATION OF CONTROL SERVICES: Design of the intelligent controller system Implementation together with real control software and hardware.
- IMPLEMENTATION OF PILOT TESTS: Design of field tests Adaptation of necessary elements for pilot tests Activation of the intelligent control system on the pilot case Supervision and surveillance Analysis of field information.
- FINAL PHASE: Verification of the prediction accuracy of the models. Analysis of improvements to regulation and control systems. Commissioning, verification and consolidation of the computer system.
- DISSEMINATION: Documentation, publication and dissemination of specific results.
- PROJECT CONCLUSION: Completion of the project and final conclusions.
Precision irrigation agriculture must adjust water application to the times when the plant truly requires it, avoiding periods when application is less efficient due to weather or management. If water use is based on rigid schedules, inefficiencies may arise that are unacceptable in a resource-scarce environment.
For this reason, farms need to be able to access water supplies on demand in order to schedule their irrigation under optimal conditions. When a farm decides to postpone irrigation to a time with more favorable conditions, the demand in the network decreases. This demand across an entire irrigated area is shifted to the main intakes or to the canal itself. Since there is insufficient storage capacity, this decrease in demand translates into a risk of discharge through the canal's spillways.
The rigidity of a canal distribution system in response to such demand variability can lead to losses of up to 10% of the water volume. This also puts the safety of the canal and its surroundings at risk. Moreover, when water application conditions are optimal, the opposite effect occurs, and spot demand increases. If the canal is not prepared to meet this increase, the depth and pressure in the networks decrease, causing increased energy consumption with costs that can rise by up to 15%.
Managing this demand in a rigid canal like the current one would require a significant investment in reservoirs, regulation systems, and management personnel for continuous monitoring (24 hours a day). The goal of this project is to facilitate predictive management of this fluctuating demand from the plots of land to the canal's origin.
The agility and quality of work of distribution infrastructure managers will be improved, thus enabling better use of water by adjusting supply and consumption, freeing up resources, and generating new opportunities. Saving water, energy, and optimizing time are the three key factors that determine not only improved productivity but also the viability of many agricultural and livestock farms in Spain.
Develop and validate a predictive technology for automatic channel control.
Canal operation requires a significant amount of labor to open and close control elements. These are rigid systems that cannot adapt to changing demand conditions and require extensive safeguards to prevent incidents. The project will work to develop self-learning tools to improve this management.
Validate a methodology for predicting water needs at supply points (distributed demand). Develop water flow simulation models in the canal that approximate the reality of the hydraulic behavior of the case study canal and others. Obtain an artificial intelligence tool to automatically control aspects of canal management.
- Coordinator/entity name: RIEGOSALZ SL
- Postal address: Calle La Ontina 3
- Coordinator/entity email: Administracion@riegosalz.com
- Telephone: 652964560
- RIEGOSALZ SL
- Comunidad General de Riesgos del Alto Aragón (Administracion@riegosaltoaragon.es)
- RIEGOSALZ SL
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