Project: Une nouvelle approche pour estimer les besoins en eau d'irrigation des vergers pour une gestion optimale de l'eau (IRRIWELL)

Project Topic Fruit orchards are sensitive crop systems threatened by future scenarios. In the Mediterranean region increase in water scarcity induced by climate is seen as a major threat for many crop productions. As perennials, fruit trees are particularly concerned by this risk since they can be damaged by drought wit long term consequences on fruit production. Therefore farmers need rational strategies to improve the water use efficiency of their orchards. Although a lot of progress has been made in irrigation methods and scheduling, the reality shows that such progress was rarely adopted by farmers. The main goal of IRRIWELL is to test the implementation of a novel approach to estimate water requirements of fruit trees based on stomatal conductance with the aid of plant sensors and mechanistic physiological models, and facilitate the implementation of a decision support system by small farmers. IRRIWELL offers an innovative solution based on the monitoring of physiological processes and their representation in mechanistic models. It is thus possible to understand key processes behind the observed response of plants to water stress. The approach is then generic facilitating its transfer to different species and cultivar and offer the possibility to address trade-off implications by deficit irrigation thanks to the method's ability to evaluate the consequences on the production of a reduction in irrigation. The approach proposed is based on the combination of plant sensors, remote sensing observation and mechanistic models. In this approach, the target is the use of stomatal conductance as the best indicator of water status and stress level in the plant. Stomatal conductance is a key physiological parameter to assess water consumption but also a unique way to bridge the carbon and water cycles and thus link water consumption to production. Stomatal conductance will be estimated automatically from plant sensors in the field, and then the carbon uptake will be calculated by a biochemical model of photosynthesis. The method is in an advanced stage of maturity, although it has been tested and validated only in olive orchards. IRRIWELL will provide a unique opportunity to test its performance in several fruit tree species and under various pedoclimatic conditions. The method represents an innovative solution for the use of plant sensors to schedule irrigation and open also the possibility to researchers working on agriculture to understand the behaviour and mechanisms of woody crop species and their response to environmental factors. The method will take profit of the Sentinel-2 capabilities to characterize orchard heterogeneity and estimate the evolution of plant leaf area which is useful to upscale plant information delivered by plant sensors and determine their installation. All this information will be integrated into a web platform already designed and commercially available at the international level for this purpose by a company, who is a partner of the project, but that will be improved with the algorithms based on mechanistic models obtained in IRRIWELL. The underlying IoT (Internet of Things) technologies make the integration of numerous user as well as the development of tailored services easy. A demonstration experiment of the whole services will be implemented in farms located in the different countries covered by the consortium to demonstrate the benefit, improve the services thanks to user feedback and elaborate a business model. This demonstration will be the cornerstone for the dissemination of IRRIWELL solutions.
Network PRIMA
Call Section 2 Call 2020 - Multi-topic

Project partner

Number Name Role Country
1 CSIC Coordinator Spain
2 VerdeSmart Partner Spain
3 ATB Partner Germany
4 Institut National de Recherche pour l'agriculture, l'alimentation et l'environnement Partner France
5 Centre d'études spatiales de la biosphère Partner France
6 UCAM Partner Morocco
7 OTI Partner Tunisia