Periodic Reporting for period 2 - MAGDA (METEOROLOGICAL ASSIMILATION FROM GALILEO AND DRONES FOR AGRICULTURE)
Período documentado: 2024-02-01 hasta 2025-04-30
The MAGDA project aims at developing a toolchain for atmosphere monitoring, weather forecasting, and severe weather/irrigation/crop monitoring advisory, with GNSS (including Galileo) at its core, to provide useful information to agricultural operators. Specifically, MAGDA will deal with the assimilation of different satellite-borne, drone-borne, ground-based weather radar, and in-situ weather observations into very high-resolution numerical weather prediction models, and with the delivery of meteorological products for severe weather warnings and advisories to farmers by either a dedicated dashboard or by interfacing with a Farm Management System. The tools developed within MAGDA will represent the technical and methodological components based on which services to support agricultural operations will be defined.
Continuous monitoring, together with cutting-edge prediction models, is the key to a better management of available resources. Extreme weather events connected with climate change are no longer just isolated cases, droughts and heatwaves are every year getting more frequent. In this environment farmers are required to work using everything technology can provide to mitigate disasters, reduce the use of precious resources, and improve their productivity. A system able to collect and process measurements of key parameters automatically can help save millions of Euros. When this data is transformed to be presented in a clear and useful way to the final users, this system may represent an effective method to push agriculture to newer levels of efficiency.
Within a period of 30 months, MAGDA aims to provide valuable weather and irrigation information directly to farmers and agricultural operators, by exploiting the strengths of atmosphere and soil sensing technologies. The MAGDA project brings together 7 partners from 6 European countries (Austria, France, Italy, Romania, Spain, and Switzerland). MAGDA is inherently inter-disciplinary, as it funnels expertise and activities from various sectors into a system that will tackle meteorological as well as hydrological forecasts, specifically tailored for agricultural needs.
Continuous monitoring, together with cutting-edge prediction models, is the key to a better management of available resources. Extreme weather events connected with climate change are no longer just isolated cases, droughts and heatwaves are every year getting more frequent. In this environment farmers are required to work using everything technology can provide to mitigate disasters, reduce the use of precious resources, and improve their productivity. A system able to collect and process measurements of key parameters automatically can help save millions of Euros. When this data is transformed to be presented in a clear and useful way to the final users, this system may represent an effective method to push agriculture to newer levels of efficiency.
Within a period of 30 months, MAGDA aims to provide valuable weather and irrigation information directly to farmers and agricultural operators, by exploiting the strengths of atmosphere and soil sensing technologies. The MAGDA project brings together 7 partners from 6 European countries (Austria, France, Italy, Romania, Spain, and Switzerland). MAGDA is inherently inter-disciplinary, as it funnels expertise and activities from various sectors into a system that will tackle meteorological as well as hydrological forecasts, specifically tailored for agricultural needs.
The project activities started with a thorough analysis of the user requirements and system design. The user requirements were collected both through direct interviews of the users providing their fields for the MAGDA demonstrators and through dedicated surveys. The user requirements analysis included the implications for the MAGDA user interface, based on validated principles for human-computer interaction and interface design guidelines. The system design included various levels: hardware level, data level, data-processing level, and modeling level, as well as the delivery of the results to the end-users by interfacing with a Farm Management System. The system design included the selection of the three demonstrator areas, identified in Italy (Cuneo), France (Burgundy), and Romania (Braila). Site inspections were conducted by the MAGDA partners to select the best solutions for the deployment of the instrumentation, as well as to interact directly with the end-users.
Deployment of nine low-cost, dual-frequency, Galileo-enabled GNSS stations, together with fourteen low-cost in-situ sensor stations was completed. The collection of authorizations needed to fly the meteodrones appropriately to meet the project objectives is being completed.
An evaluation methodology and plan for MAGDA was defined. The plan involved defining the goals of the system, identifying key performance indicators (KPIs), developing a data collection plan, establishing a baseline, evaluating the system's performance, identifying areas for improvement, repeating the process regularly, and communicating the results to relevant stakeholders. Relevant and important KPIs to monitor the system's performance were selected.
The MAGDA data environment was carefully analysed and designed to ensure efficient and proper usage of data and exploitation of results.
Severe weather cases were identified and selected to be used to test the performance of the WRF meteorological model. These case studies have been chosen based on their relevance to improving agricultural forecasting, considering the specific interests of crops in different target sites. The selected case studies were six in total, two for each site. Based on the end-user feedback, the two cases for the Italian site targeted rainfall events, while the four remaining cases targeted hail events.
Water balance simulations were run to form the foundation for an Irrigation Advisory Service. Water balance simulations have been conducted for three pilot areas in France, Italy, and Romania utilizing the SPHY simulation model. The spatial results indicate a generally high correlation between the SPHY model's evapotranspiration output and remote sensing data for the pilot areas in France and Italy, although adjustments to certain input parameters are needed for better performance. The Romanian sites show less correlation.
Deployment of nine low-cost, dual-frequency, Galileo-enabled GNSS stations, together with fourteen low-cost in-situ sensor stations was completed. The collection of authorizations needed to fly the meteodrones appropriately to meet the project objectives is being completed.
An evaluation methodology and plan for MAGDA was defined. The plan involved defining the goals of the system, identifying key performance indicators (KPIs), developing a data collection plan, establishing a baseline, evaluating the system's performance, identifying areas for improvement, repeating the process regularly, and communicating the results to relevant stakeholders. Relevant and important KPIs to monitor the system's performance were selected.
The MAGDA data environment was carefully analysed and designed to ensure efficient and proper usage of data and exploitation of results.
Severe weather cases were identified and selected to be used to test the performance of the WRF meteorological model. These case studies have been chosen based on their relevance to improving agricultural forecasting, considering the specific interests of crops in different target sites. The selected case studies were six in total, two for each site. Based on the end-user feedback, the two cases for the Italian site targeted rainfall events, while the four remaining cases targeted hail events.
Water balance simulations were run to form the foundation for an Irrigation Advisory Service. Water balance simulations have been conducted for three pilot areas in France, Italy, and Romania utilizing the SPHY simulation model. The spatial results indicate a generally high correlation between the SPHY model's evapotranspiration output and remote sensing data for the pilot areas in France and Italy, although adjustments to certain input parameters are needed for better performance. The Romanian sites show less correlation.
Given the multifaceted nature of the MAGDA project, its outcomes span scientific advancements, technological innovations, and practical applications in agriculture and environmental management.
Potential Impacts:
- Scientific Impact: Contributions to the fields of meteorology, hydrology, and agricultural sciences through advanced data collection and modeling techniques.
- Economic Impact: Potential for significant cost savings and increased efficiency in agricultural practices, leading to enhanced productivity and sustainability.
- Societal Impact: Support for sustainable agriculture and water management practices can contribute to food security, climate change adaptation, and environmental conservation.
The MAGDA project stands at the confluence of innovation, sustainability, and practicality, aiming to transform agricultural practices through science and technology. Its success hinges not just on the scientific and technical achievements but also on the effective translation of these advancements into tangible benefits for agriculture and society.
Potential Impacts:
- Scientific Impact: Contributions to the fields of meteorology, hydrology, and agricultural sciences through advanced data collection and modeling techniques.
- Economic Impact: Potential for significant cost savings and increased efficiency in agricultural practices, leading to enhanced productivity and sustainability.
- Societal Impact: Support for sustainable agriculture and water management practices can contribute to food security, climate change adaptation, and environmental conservation.
The MAGDA project stands at the confluence of innovation, sustainability, and practicality, aiming to transform agricultural practices through science and technology. Its success hinges not just on the scientific and technical achievements but also on the effective translation of these advancements into tangible benefits for agriculture and society.