BRIDGE BLACK SEA

One of the First Examples of Digital Twin Ocean Demonstrators

DIGITAL TWIN OCEAN DEMONSTRATOR

What is it?

BRIDGE Black Sea DTO stands out as one of the pioneering digital twin ocean demonstrators, integrating real-time data from database systems and smart observation setups. It incorporates high-resolution, fully coupled sophisticated models of both the sea and the watershed, enhanced by artificial intelligence tools and socio-economic models.

What does it aim?

It aims to enhance our comprehension of regional sea ecosystems, enabling us to predict their conditions under changing climate and environmental stressors. Moreover, it facilitates the testing of alternative socio-economic scenarios, contributing valuable insights to decision-making processes.

How does it work?

Digital twin utilizes integrated simulations and resilience assessments to define the ecosystem's state and associated risks. Decision support tools, employing machine learning and cumulative assessments, are then applied. These tools test various socio-economic and blue economy scenarios, with sector analyses and stakeholder input from living labs across the basin.

BRIDGE Black Sea DTO with Visuals

Visuals were specifically designed to illustrate the BRIDGE Black Sea Digital Twin Ocean Demonstrator.
A proper credit to the METU Institute of Marine Sciences is required.

Innovative Aspects of BRIDGE Black Sea DTO

Decision Support Tools

DSTs are founded on the Tools4MSP modeling framework, enabling a groundbreaking ad-hoc assessment of cumulative stressor effects on Black Sea ecosystem services for the first time.

Cumulative Effects Assesment

CEA employs a distinctive ensemble modeling approach, drawing upon novel insights garnered through a diverse array of modeling techniques.

Adaptive Management Approach

Actual feedback from customers and users across the Black Sea will help you to understand market needs, refining your product or service, and making informed decisions to enhance its value and appeal.

Spatial Identification

Through CEA, BRIDGE Black Sea DTO qualifies the spatial distribution of natural and anthropogenic risks, both individually and in combination, identifying critical marine areas that are affected.

Marine Strategy Framework Directive

Establishing crucial linkages to core Black Sea ecosystem services, a significant contribution to the MSFD is achieved by systematically considering the 15 MSFD pressures along with GES/Target indicators.

Ecosystem-based Management

EBM for marine space and ecosystem services involves spatial identification, understanding cause-effect relationships, and facilitating the comparison of pertinent information and products among stakeholders.

The Black Sea DTO demonstrator will identify the conditions ensuring safe operating space for the services generated by Black Sea ecosystems through the implementation of accurate predictive modeling tools and the capabilities necessary to tackle the increasingly complex array of multistressors. It will extend existing mechanistic modeling tools to assess and predict the marine ecosystem state, which is crucial for the provision of services and selected sectors in the Black Sea. Furthermore, time series and maps of indicators of good environmental status and key habitats will be generated, including their spatial and temporal dynamics, to support the implementation of MFSD, the Bucharest Convention, and the UN SDGs, as well as resilience assessment and adaptive management.

The DTO will provide a holistic resilience assessment of ecosystem services to support the sustainable production of key ecosystem services. It applies a hierarchical analysis framework where the ecosystem processes supporting the ecosystem services are first conceptualized and linked to relevant pressure-state-indicators.

The Digital Twin of the Black Sea will provide '‘what-if’’ scenarios to policymakers for adaptive management recommendations, planning, policy, and knowledge implementation to tackle main risks and ensure the sustainable exploitation of resources. The demonstrator has capacities for decade-long to longer-term predictions of ecosystem states. Machine learning and DST, together with enabling policymakers to understand the links between stressors, state, and services. The benefits and tradeoffs of competing or complementary service utilization will be presented to stakeholders. Adaptive management recommendations will be: i) area-based (i.e., Black Sea and selected Pilot Sites of BRIDGE-BS); ii) core ES-based; iii) based on different Blue Economy opportunities and scenarios for riparian countries and main blue economy sectors. Management recommendations will be proposed, targeting the above areas/frameworks, with both national and transboundary dimensions and relevance and impact on policy implementation and planning (e.g., MSFD, MSP, CFP, SDG14, Bucharest Convention).

The marine boundaries of the safe operating space are defined with an ensemble of models, resilience assessment, and DSTs. This will provide solutions towards the ecosystem-based functioning of sectors.

BRIDGE-BS is targeting local (6 identified Pilot Sites in the Black Sea), national, regional, and international stakeholders through DST activities. A Geospatial Cumulative Effects Assessment (CEA) tool, based on the open-source Tools4MSP modeling framework, is employed to define hotspots of cumulative stressor impacts on core ES in the Black Sea in order to generate adaptive management strategies. CEA-based scenario analysis is developed with feedback from stakeholders, including academics, representatives from the blue economy sector (fisheries and aquaculture, tourism, offshore wind energy, etc.), local authorities, and public administrations through living labs, incubator activities, and policymakers at different levels.

The Black Sea DTO will support the wealth and well-being of society by sustaining ecosystem services, including recreation, tourism, and food provisioning. It will also contribute to the socio-economic aspect by demonstrating stressors and risks on blue economy sectors such as fisheries and aquaculture, renewable energy, thereby enhancing the resilience of these services. Similarly, it will aid in job creation. With adaptive management recommendations based on the outputs, the DTO will contribute to policymaking in research, innovation, and technology, enhance science-policy dialogue, and inform ongoing and future MSP processes. It will also pave the way for zero-carbon practices and innovative methodologies.

Finally, with decade-long predictions, the DTO will enable early detection of environmental hazards, promoting a one-health approach for coastal communities and better disaster preparedness.

The DTO develops an incubator platform supporting the transition needed to secure a sustainable future for the empowered citizens of the Black Sea within a preserved marine environment. This future will be generated by stakeholders themselves in a co-design process of sustainable scenarios and transition pathways for the Black Sea.

The DTO aims to comprehensively investigate the impact of multistressors on local economies, society, and ecosystem services. A stakeholder mapping and engagement strategy will be meticulously crafted and executed across Black Sea countries, laying the foundation for the creation of Living Labs. These Labs will play a pivotal role in formulating strategies to equip society with social innovation solutions and uncover Blue Growth opportunities. Through focused stakeholder engagement mapping in the 7 Pilot Sites, the Living Labs will serve as the cornerstone for ecosystem services valuation.

The DTO will leverage the advancements generated in BRIDGE-BS, transforming them into innovation opportunities for Industry 4.0 to support the Black Sea Blue Economy Sectors, including fisheries and aquaculture, tourism, blue biotech, and renewable energy. The tools and solutions provided by BRIDGE-BS, such as those for mapping habitat changes, predicting ecosystem responses to multistressors, forecasting fish species distribution and habitat quality, deploying smart sensors for environmental monitoring, and managing big environmental data, will contribute significantly. These contributions include the development of (i) innovative nature-based solutions for habitat restoration and climate mitigation; (ii) creative utilization of marine resources, including as a food source; (iii) pioneering methods for data collection using internet-of-things platforms; and other products and services that could generate business opportunities for regional, national, and local industrial sectors, both existing and emerging.

The DTO will capitalize on the tailor-made science generated in BRIDGE-BS to address policy needs and invest in a science-policy stream, aiming to strengthen the science-policy interface beyond the project's duration. The work packages of the BRIDGE-BS will: i) foster an enriched science-policy dialogue, ii) facilitate the transfer of knowledge between science and policy, and contribute to the development of science-based policies, and iii) provide training for policymakers to enable science-based policy-making.