H2020 STARGATE Project: Resilient Agriculture through Adaptive Microclimate Management

During the 1st and 2nd reporting periods, STARGATE focused and worked on the following objectives: Formation of the STARGATE community through engagement of pilot stakeholders: A strong stakeholder community consisting of farmers, farmers’ associations, agronomists, water managers, public sector agencies, governments, agri-businesses, civil society organizations and experts has been developed across 6 countries and 16 different use cases. Definition of the STARGATE pilot case studies through active engagement of pilot stakeholders/users: 16 use cases have been identified, covering different aspects of crop and livestock production as well as different agro-climatic zones and user segments. Understanding service and user requirements for weather and climate information at the pilot sites, as well as the needs and challenges of adopting climate-smart agriculture technologies at the pilot sites: A detailed database of user requirements for weather and climate information needs at the pilot sites, including their spatiotemporal characteristics, has been developed.

Understanding the pilot's data requirements and defining the STARGATE data collection protocol: A detailed analysis of the use cases from a data management perspective leads to the design of the data collection protocols for the STARGATE data management platform. The atmospheric data assimilation system: A workflow chain for an atmospheric data assimilation system has been developed. Satellite and ground-based observations are preprocessed and input into the assimilation system to produce high-quality atmospheric analysis fields. These are then used as inputs for the prediction model, which subsequently produces high-spatial-resolution weather forecasts. The coupled analysis/forecast system is deployed for two separate domain areas covering all pilot sites in six countries. The multi-model numerical weather prediction system: A system was created from three different operational weather prediction models: METEOBLUE, AUTH, and AGROAPPS, providing weather forecasts up to 7 days in advance.

Subseasonal to Seasonal Climate Prediction System: A system has been developed that provides operational climate predictions spanning from 1 month to 6 months. Climate predictions are presented in a meaningful way, including probabilities and anomalies, which can guide the agricultural sector's decision-making chain. Crop-Specific Risk Analysis/Monitoring/Prediction Method for Pilots Based on Historical Climate Data: Several climate risk scenarios have been developed for each pilot use case based on temperature, precipitation, solar radiation, soil moisture, wind, and crop type. Agroclimatic Indicator Set for Each Pilot Site: 16 different agroclimatic indicators have been developed that attempt to account for all aspects of climate impacts on agricultural production at each pilot site. Evaluating the Impact of Crop Practices on the Local Microclimate: Several numerical experiments were carried out in three pilot areas to quantify the impact of irrigated/non-irrigated and tillage/direct seeding agriculture on the near-surface atmospheric environment, especially on the intensity of extreme weather events. Conducting a climatological analysis of past and future climate conditions for the pilot project: A climatological analysis was performed for each use case to identify climate trends and assess the impact of anthropogenic global warming at the pilot sites. The climate analysis covered temperature, precipitation, relative humidity, evapotranspiration, solar radiation, and wind. Strategic and Tactical Climate-Smart Decision Tools: A suite of tools was designed for STARGATE. These tools will be used to assist policymakers, farmers, and agricultural consultants in using farm inputs and energy more efficiently, while reducing agricultural emissions and preserving the environment.

These tools will be developed using state-of-the-art precision agriculture methodologies using earth observations and meteorological data, along with crop models and machine learning algorithms to support the above farming procedures. The Land and Crop Suitability Methodology: A suitability methodology has been developed that will be used by STARGATE for efficient land-use planning and crop variety selection to enhance the adaptability of the agricultural sector at the pilot sites in a changing climate. The Multi-Stakeholder Validation Framework: STARGATE establishes the fundamental concepts and methods for establishing, implementing, and monitoring the participatory process that will be carried out at all pilot sites throughout the project lifetime. Effective Dissemination and Communication of Project Results: A dissemination package has been developed for the effective dissemination and communication of project results.