Project description
A systems-based early warning framework for drought forecasting
With climate change increasing the intensity of heatwaves and changing rainfall patterns, droughts are increasing in frequency and duration around the world, posing threats to water security, ecosystem, agriculture and infrastructure. Supported by the Marie Skłodowska-Curie Actions programme, the SyndroDry project is creating a new paradigm for drought monitoring and forecasting. Considering drought as a multifaceted phenomenon, it will design a comprehensive system considering all aspects of the hydrological cycle in a multivariate system, with threshold levels defined based on stakeholder consultation and scientific knowledge. The project’s goal is to deliver an operational early-warning system that enhances decision-making and helps reduce economic and environmental losses from drought.
Objective
Drought is a complex and globally significant hazard that generates cascading impacts across ecosystems, infrastructure, and society. Early-warning forecasting systems can substantially mitigate these impacts. However, most research conceptualizes drought as a set of isolated events, without considering its interconnectedness within the water cycle or its associated impacts. Advancing monitoring and forecasting requires a systems-based framework that quantifies and visualizes all water-cycle components using a unified indicator set. The SyndroDry project addresses this need by developing a synoptic drought monitoring and forecasting framework based on systems theory, establishing a new theoretical model for drought assessment. The primary objective is to provide a visualized, multivariate framework for operational monitoring and forecasting that improves early warning capabilities. The SyndroDry approach incorporates stakeholder knowledge and scientific evidence to define impact-based thresholds, embedding these thresholds within a multivariate representation of the water cycle. The project will evaluate advanced predictive methods, including Long Short-Term Memory (LSTM), GLM-Boost, Tree-based, and hybrid machine-learning models, to identify the most robust strategies for synoptic drought forecasting. Ultimately, the project will deliver an operational tool that provides actionable early warnings to water-resource managers, supporting timely decision-making and reducing economic and ecosystem losses from drought.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2025-PF
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1180 Wien
Austria
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