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STARS4Water

Supporting STakeholders for Adaptive, Resilient and Sustainable Water Management
Funder: European CommissionProject code: 101059372 Call for proposal: HORIZON-CL6-2021-CLIMATE-01
Funded under: HE | HORIZON-RIA Overall Budget: 4,584,730 EURFunder Contribution: 4,580,980 EUR
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Description

Worldwide freshwater resources are under increasing pressures of rapidly intensifying climate change effects putting the availability and quality of water resources and socio-economic developments at risk. River basin organisations need to be prepared. STARS4Water aims at improving the understanding of climate change impacts on water resources availability and the vulnerabilities for ecosystems, society and economic sectors at river basin scale. STARS4Water will develop and deliver new data services and data-driven models for better supporting the decision making on planning on actions for adaptative, resilient and sustainable management of fresh water resources. The project team will work with seven river basin organisations through a co-creation, living lab approach. The new services and models will be co-designed with stakeholders to meet their needs on data and information, ensuring relevance and uptake for use beyond the lifetime of the project. The STARS4Water project includes two distinctive elements: first, the need for an international stakeholder community to address the stakeholders’ needs and requirements and second, the development and application of innovative data and model concepts. New datasets and models offer possibilities for improved projections on water resources availability, and the new insights on links between water, nature, society ask for a broader set of indicators to be considered in decision-making on water management. These novel datasets, models and indicators are not yet fully matured and integrated in current river basin management information tools and decision-making processes. We acknowledge that these elements are of a different nature, being a stakeholder-driven approach and rather science-(data-)driven in the application of novel data and models, respectively. It is the consortium’s firm conviction that for substantial progress in climate change adaptation the two elements need to be combined.

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