FORWARD -Operational monitoring and FOrecasting system for Resilience of agriculture and forestry under intensification of the WAteR cycle: a big Data approach

The main objective of FORWARD is to understand and increase the resilience of water resources of agricultural systems and forestry through data mining and modelling in a Big Data setting. Hereto, the project has the following three specific objectives: 1. To develop and implement an extensible and tailorable Big Data approach and framework able to manage and process multivariable information sources (see the Methodology section for a short and preliminary list of sources and variables), data-mining techniques and models at several scales (local, regional, nation and continental). 2. To provide improved model forecasting (daily-monthly-seasonal-long term; and at different spatial scales) and monitoring capabilities of eco-hydrological variables and indicators (see the Methodology section for a preliminary list of indicators) relevant to forestry and agricultural applications by combining different modeling types (data-driven, process based and statistical time series analysis) in a Big Data framework 3. To understand the resilience of forest and agricultural ecosystems in water-limited regions to extreme events, in particular drought, and in the context of climate change. Provide maps of most vulnerable sites to those through combining all available data sources and advanced data mining techniques.More

Data and Resources

Additional Info

Field Value
Project coordinator Fernández Villán, A. (Alberto)
Last Updated November 19, 2021, 17:18 (UTC)
Created November 21, 2018, 10:00 (UTC)
Contact partner Monica Garcia
Contact personsfor Dissemination activities - Open Data&Open Acces activities Alberto Fernández Villán
Funders European Commission, H2020, Water JPI, WaterWorks2015
Project partners Technical University of Denmark, Sumaqua
Access level info:eu-repo/semantics/closedAccess
Project identifier grantAgreement/EC/
Start date June 1, 2017, 00:00 (UTC)
End date November 30, 2019, 00:00 (UTC)