{"id":4310,"date":"2026-07-21T09:29:34","date_gmt":"2026-07-21T09:29:34","guid":{"rendered":"https:\/\/www.eoliann.com\/?p=4310"},"modified":"2026-07-21T09:29:34","modified_gmt":"2026-07-21T09:29:34","slug":"terna-proof-of-concept-for-mapping-flood-hazard-across-the-italian-national-transmission-grid","status":"publish","type":"post","link":"https:\/\/www.eoliann.com\/en\/terna-proof-of-concept-for-mapping-flood-hazard-across-the-italian-national-transmission-grid\/","title":{"rendered":"Terna \u2013 Proof of Concept for Mapping Flood Hazard across the Italian National Transmission Grid"},"content":{"rendered":"

\"\"<\/h2>\n

The context<\/h2>\n

Terna<\/a> is the operator of the Italian National Transmission Grid, one of the largest in Europe. Listed on the FTSE MIB index, it manages approximately 76,000 km of high- and extra-high-voltage power lines and hundreds of substations,<\/strong> ensuring the security, continuity and quality of the country\u2019s electricity service.<\/p>\n

In 2024, Terna tested Eoliann\u2019s predictive models, based on artificial intelligence and satellite data, with the aim of creating a more comprehensive and consistent flood hazard map.<\/strong> This was an essential step in identifying the areas of the grid most exposed to risk and targeting resilience measures more effectively.<\/p>\n

Although the maps produced by Italy\u2019s River Basin Authorities remain the official reference, they cover only 39% of the country in terms of water-depth data,<\/strong> with information that is often inconsistent across districts. The maps produced by the European Commission\u2019s Joint Research Centre offer broader coverage, but exclude smaller catchments and lack the resolution required to accurately capture local features such as flood defence structures.<\/p>\n

Against this backdrop, Terna launched a Proof of Concept with Eoliann as part of the \u201cData Science for Resilience\u201d Innovation Bootcamp, to develop an approach capable of overcoming the limitations of existing sources.<\/strong><\/p>\n

The project<\/h2>\n

The project, completed in March 2024, was jointly developed by Terna and Eoliann using a twofold approach: two-dimensional numerical hydraulic simulations,<\/strong> designed to generate physically accurate maps, and the application of the Airis Flood machine-learning model,<\/strong> to assess whether the analysis could be extended to a national scale.<\/p>\n

Terna selected three pilot areas in Piedmont,<\/strong> each centred around a substation affected by documented flood events in previous years. This made it possible to compare the project\u2019s results with high-quality observational data provided by ARPA Piemonte.<\/p>\n

1. Two-dimensional numerical hydraulic simulations<\/h3>\n

For each area, Eoliann developed two-dimensional hydrological and hydraulic simulations<\/strong> using only Earth observation data, including a digital terrain model, precipitation, land cover and the hydrographic network.<\/p>\n

The simulations produced water-depth and water-velocity maps at a spatial resolution of 30 metres for three return periods<\/strong> – 20, 100 and 200 years – in line with the relevant regulatory framework.<\/p>\n

2. Validation against observed events and official sources<\/h3>\n

The results were systematically assessed against three independent sources:<\/strong><\/p>\n