Advanced Local Digital Twins using AI for Early Warning and Preparedness (IA)

Overview

The EU funding opportunity titled HORIZON-CL4 focuses on "Advanced Local Digital Twins using AI for Early Warning and Preparedness." This initiative falls under the Horizon Europe program, specifically the Digital, Industry, and Space cluster. It aims to leverage AI technologies and digital twins to enhance flood preparedness and disaster management. Eligibility is open to various legal entities established in EU Member States, EEA countries, and Switzerland. Categories include research institutions, universities, private companies (including SMEs and large enterprises), technology providers, innovation centers, non-profit organizations, and international organizations with headquarters in eligible countries. However, entities from China are excluded from participating in this call. The funding type is a lump sum grant model with a total budget of €6 million allocated for this topic in 2026, and it is anticipated that one grant will be awarded. The application process is set as a single-stage submission from January 15 to April 15, 2026. Proposals must include multi-partner collaborations, as a consortium of multiple applicants is required to combine expertise and resources. The focus of projects includes the development and implementation of innovative AI algorithms. Specifically, participants are expected to create local digital twins designed to simulate flood scenarios, identify risk areas, and assess damages. Successful projects will enhance capabilities in urban resilience planning, improve predictions of flooding, and integrate diverse datasets, including real-time meteorological information and hydrological models. Open-source solutions with modular designs for reuse in various contexts, particularly in low- and middle-income countries, are emphasized. Additionally, funded projects should align with EU initiatives such as the Copernicus Emergency Management Service, focusing on proactive decision-making and improving disaster response strategies through better risk analysis and urban planning techniques. The grant will cover 100% of eligible project costs and does not require co-funding, although leveraging additional financial resources from other partners is encouraged. The expected outcomes include advancements in AI for urban management, improved model validation processes, and the development of tools facilitating better disaster preparedness across Europe. Overall, this funding opportunity emphasizes a strategic approach in harnessing AI and digital technologies to improve community resilience against climate-related disasters, ensuring that the solutions developed are both innovative and widely applicable across multiple settings.

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Highlights

This EU funding opportunity, HORIZON-CL4, focuses on "Advanced Local Digital Twins using AI for Early Warning and Preparedness (IA)". It falls under the Horizon Europe (HORIZON) program, specifically the DIGITAL (HORIZON-CL4-2026-04) call. The action type is a HORIZON Innovation Action (HORIZON-IA), utilizing a HORIZON Lump Sum Grant [HORIZON-AG-LS] Model Grant Agreement (MGA). The funding opportunity employs a single-stage deadline model, with a planned opening date of January 15, 2026, and a deadline of April 15, 2026, at 17:00:00 Brussels time. The total budget allocated to this topic is €6,000,000 for the year 2026, and it is anticipated that approximately 1 grant will be awarded. The expected outcome of projects funded under this topic is the development of open AI models that can effectively predict, respond to, and mitigate the impacts of disasters. This includes enabling proactive decision-making and effective disaster management, as well as protecting citizens from natural hazards through preparedness strategies and urban resilience planning. Specifically, project results should contribute to: Enhanced protection of citizens from flooding through AI-driven models for urban resilience. Improved modeling and prediction of urban and riverine flooding using Local Digital Twins and sophisticated AI algorithms. Strengthened integration of diverse datasets (terrain, land cover, urban features, soil data, real-time meteorological information, river geometry, flow) to enhance flood analysis and preparedness, especially in response to climate change. The scope of the projects should include: Development and implementation of innovative AI algorithms and models, advancing them from concept to large-scale testing and validation. Application of these AI solutions to create Local Digital Twins for flood preparedness, enabling flood scenario simulation, risk area identification, and damage estimation. Focus on AI algorithms that use dynamic descriptive building features derived from digital models (geometrical parameters, urban morphology, socio-economic indicators) integrated with high-resolution hazard models. Development of Local Digital Twins that enable: Flood damage models for building-scale impact calculation and damage hotspot maps. Interactive user interfaces for modifying components and estimating flood damage under various scenarios, including assessing construction feasibility in flood-prone zones and recommending mitigation strategies. Prototyping, testing, and large-scale validation of AI algorithms for modeling multiple disaster types, with a focus on operational deployment. Prioritization of frugal (and local) AI to reduce greenhouse emissions and ensure functionality in environments with limited connectivity. Consideration of the expertise of the European Commission's Joint Research Centre (JRC) and potential uptake by the Copernicus Emergency Management Service. Alignment with the 2025 Mission call on Local Digital Twin for urban planning. Modular project results for reuse in locations outside Europe, especially in low- and middle-income countries. Open-source project results transferable through open platforms. Support for open-source software and open hardware design. Open access to data, testing, and operational infrastructures, with an IPR regime ensuring lasting impact and reusability. Beneficiaries intending to transfer ownership or grant exclusive licenses must notify the granting authority (DG-CNECT and HaDEA). The granting authority may object to such transfers or licensing for up to four years after the project's end. This funding opportunity aims to achieve open strategic autonomy in digital and emerging enabling technologies, aligning with the EU's ambition to become an "AI Continent" and the concrete actions in the Apply AI Strategy. It emphasizes leadership in Artificial Intelligence, Quantum, Photonics, and Semiconductors to enhance Europe’s economic security and global competitiveness. Legal entities established in China are not eligible to participate in Research and Innovation Actions (RIAs) and Innovation Actions (IAs) falling under this destination. General conditions for participation include: Admissibility Conditions: Proposal page limit and layout as described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes and Part B of the Application Form. Eligible Countries: As described in Annex B of the Work Programme General Annexes, with specific provisions for non-EU/non-Associated Countries as detailed in the Horizon Europe Programme Guide. Other Eligible Conditions: International organizations with headquarters in a Member State or Horizon Europe Associated Country are exceptionally eligible. The Joint Research Centre (JRC) may participate as a beneficiary with zero funding or as an associated partner. Projects using satellite data must use Copernicus and/or Galileo/EGNOS. Financial and operational capacity and exclusion: As described in Annex C of the Work Programme General Annexes. Evaluation and award: Award criteria, scoring, and thresholds are described in Annex D of the Work Programme General Annexes. Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual. The indicative timeline for evaluation and grant agreement is described in Annex F of the Work Programme General Annexes. Legal and financial set-up of the grants: As per Annex 5, the granting authority may object to ownership transfer or exclusive licensing for up to four years after the action's end. Eligible costs will be in the form of a lump sum, as defined in the Decision of 7 July 2021. Specific conditions are described in the specific topic of the Work Programme and Annex G of the Work Programme General Annexes. Application and evaluation forms and model grant agreement (MGA): Application form templates are available in the Submission System (Standard application form HE RIA, IA). Evaluation form templates will be used with necessary adaptations (Standard evaluation form HE RIA, IA). Guidance is provided in the HE Programme Guide. The Model Grant Agreement (MGA) is a Lump Sum MGA. Call-specific instructions and a detailed budget table (HE LS) are available, along with guidance on lump sums. Additional documents include: HE Main Work Programme 2026-2027 – 1. General Introduction HE Main Work Programme 2026-2027 – 7. Digital, Industry and Space HE Main Work Programme 2026-2027 – 15. General Annexes HE Programme Guide HE Framework Programme 2021/695 HE Specific Programme Decision 2021/764 EU Financial Regulation 2024/2509 Decision authorising the use of lump sum contributions under the Horizon Europe Programme Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment EU Grants AGA — Annotated Model Grant Agreement Funding & Tenders Portal Online Manual Funding & Tenders Portal Terms and Conditions Funding & Tenders Portal Privacy Statement Partner search announcements can be viewed and edited by LEARs, Account Administrators, or self-registrants. The submission system is planned to open on the date stated in the topic header. This opportunity seeks to harness the power of AI and digital twins to enhance flood preparedness and disaster management in urban areas. It encourages the development of open-source, modular solutions that can be widely adopted, particularly in resource-constrained environments. By integrating diverse data sources and advanced modeling techniques, the funded projects are expected to contribute to more effective urban planning, increased resilience to climate change, and enhanced protection for citizens against the devastating impacts of flooding. The emphasis on frugal AI and open-source solutions ensures sustainability and broad accessibility of the project outcomes.

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Breakdown

Eligible Applicant Types: The eligible applicant types include international organizations with headquarters in a Member State or Horizon Europe Associated Country, legal entities established in EU member states, legal entities from Horizon Europe associated countries, and legal entities from non-EU/non-associated countries that have specific provisions for funding participants in Horizon Europe projects. The Joint Research Centre (JRC) may participate as a member of the consortium selected for funding as a beneficiary with zero funding, or as an associated partner. However, legal entities established in China are not eligible to participate in both Research and Innovation Actions (RIAs) and Innovation Actions (IAs) falling under this destination. Funding Type: The funding type is a grant, specifically a HORIZON Innovation Action (HORIZON-IA) with a HORIZON Lump Sum Grant [HORIZON-AG-LS] model grant agreement. Consortium Requirement: A consortium is required, as the Joint Research Centre (JRC) may participate as a member of the consortium. Beneficiary Scope (Geographic Eligibility): The geographic eligibility includes EU Member States, Horizon Europe Associated Countries, and potentially other non-EU/non-Associated Countries with specific funding provisions. International organizations with headquarters in a Member State or Horizon Europe Associated Country are also eligible. Target Sector: The target sectors are digital, industry, space, artificial intelligence, urban planning, climate, and security/cybersecurity, with a focus on disaster risk management and flood preparedness. Mentioned Countries: China is explicitly mentioned as ineligible. The opportunity is primarily focused on EU Member States and Horizon Europe Associated Countries, but also open to non-EU/non-Associated Countries with specific funding provisions. Project Stage: The project stage is focused on innovation actions, which implies a maturity level of development, validation, demonstration, and potentially commercialization or scale-up, with a strong emphasis on prototyping, testing, and large-scale validation of AI algorithms. Funding Amount: The funding amount for the HORIZON-CL4 topic is approximately €6,000,000. Other related topics under the same call (DIGITAL (HORIZON-CL4-2026-04)) have varying budgets, ranging from €1,000,000 to €46,500,000, with individual grant contributions varying from around €500,000 to between €7,000,000 and €23,500,000, depending on the specific action type (RIA, CSA, IA). Application Type: The application type is a single-stage call. Nature of Support: Beneficiaries will receive money in the form of a lump sum grant. Application Stages: The application process is a single-stage process. Success Rates: The success rates are not explicitly mentioned, but the indicative number of grants is provided for each topic, which can give an idea of the competition level. For the HORIZON-CL4 topic, the indicative number of grants is 1. Co-funding Requirement: The need for co-funding is not explicitly stated, but Horizon Europe projects often require some level of co-funding, which can be determined from the program guide and call-specific instructions. This opportunity focuses on developing and implementing innovative AI algorithms and models for flood preparedness using Local Digital Twins. The goal is to enhance the protection of citizens from flooding by improving the prediction and management of flood events. The projects should leverage high-resolution climatic and meteorological models, integrate diverse datasets, and align with the EU's Apply AI Strategy and other relevant initiatives like the Copernicus Emergency Management Service. The emphasis is on open-source solutions and modular designs that can be reused in various locations, including low- and middle-income countries. Legal entities from China are not eligible, and international organizations with headquarters in a Member State or Horizon Europe Associated Country are exceptionally eligible. The funding is provided as a lump sum grant, and the application process is a single-stage call.

Short Summary

Impact

The funding aims to enhance flood preparedness and disaster management by developing advanced AI algorithms integrated with Local Digital Twin technology to protect citizens from natural hazards.

Applicant

Applicants should possess expertise in artificial intelligence, disaster management, urban planning, and data science to effectively develop and validate innovative AI solutions.

Developments

The funding will support projects focused on creating AI-driven models for flood prediction and management, utilizing Local Digital Twins and diverse datasets for urban resilience.

Applicant Type

This funding is designed for legal entities including research institutions, private sector companies, technology providers, and non-profit organizations established in eligible countries.

Consortium

A consortium of multiple applicants is required to ensure diverse expertise and collaborative development of project solutions.

Funding Amount

The funding amount per project is €6,000,000, with only one grant expected to be awarded.

Countries

Relevant countries include EU Member States, EEA countries, and Switzerland, as they are eligible to participate in this funding opportunity.

Industry

This funding targets the digital, industry, and space sectors, specifically focusing on artificial intelligence and disaster risk management.

Update Log

Showing 2 updates

Update on March 16th, 2026
16 days ago
1 field changed
Description II
Expected Outcome:Open AI models that can help predict, respond to, and mitigate impacts before a disaster occurs, enabling proactive decision-making and effective disaster management effectively. Protection of citizens from natural hazards through proactive measures, preparedness strategies, and urban resilience, planningProject results are expected to contribute to one of the following outcomes:Enhanced protection of citizens from the natural hazard of flooding by facilitating proactive decision-making and effective disaster management through open AI-driven models for urban resilience strategies and planning that can help predict, respond to, and mitigate impacts before a disaster occurs.Improved modelling and prediction of urban and riverine flooding by expanding the capabilities of Local Digital Twins with sophisticated AI algorithms and relevant data detailing hydrological and hydraulic processes.Strengthened integration of diverse and essential datasets including detailed terrain...
Update on January 16th, 2026
2 months ago
1 field changed
Status
Old:Forthcoming
New:Open

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