DriftGuard — Predicting Marine Pollution Spread

💎 Idea  

DriftGuard is an early-stage project focused on forecasting how marine pollution spreads in coastal waters, with an initial focus on Italian seas. The goal is challenging but impactful: help authorities and environmental stakeholders anticipate where pollution will move before it reaches vulnerable coastlines.

Marine pollution events - whether caused by industrial discharge, shipping incidents or extreme weather - often evolve quickly and unpredictably. Today response actions are largely reactive. DriftGuard aims to build proactivity by using Earth observation data to provide forward-looking insights and support faster, more informed decision-making.

At its core the project is based on a drift simulation model that represents pollution as particles transported by ocean surface currents. By leveraging data from the Copernicus Marine Service, combined with geospatial inputs and physical assumptions, DriftGuard estimates how pollution plumes evolve over time and identifies areas at risk.

The vision is to develop a lightweight and user-friendly decision-support tool capable of:

• forecasting pollution spread over 24–72 hours
• highlighting potential coastal impact zones
• supporting early intervention strategies
• visualizing scenarios in an intuitive and map-based interface.

The project sits at the intersection of environmental protection, geospatial analytics and space data applications. It is designed as a pragmatic and scalable concept that can evolve from a hackathon prototype into a real-world solution for coastal monitoring and emergency response.

🛰️ EU Space Technologies

DriftGuard leverages Earth observation and oceanographic data to transform raw environmental signals into actionable forecasts. The initial location of polluting particles is provided as a geolocated input, typically defined by the coordinates of a reported incident (e.g. spill, discharge or observed contamination). This input serves as the starting point of the simulation, from which the model propagates the particles using ocean current data. The core inputs come from the Copernicus Marine Service, particularly surface current velocity fields (u/v), which drive the simulation of how pollution moves across the sea. These are complemented by satellite-derived indicators such as sea surface temperature and chlorophyll concentration, which help contextualize anomalies and identify potentially affected areas. Where available, wind data (e.g. from ECMWF models) can be incorporated to refine surface drift dynamics. By combining these datasets within a particle-based modelling approach, DriftGuard converts complex geophysical data into intuitive forecasts, highlighting where pollution is likely to spread and when it may reach the coast. This adds value by turning high-volume, underutilized space data into clear, decision-ready insights that can support faster and more targeted environmental response.

  EU Space for Water 

DriftGuard addresses Challenge #2: tracking and preventing water pollution by providing a predictive approach to understanding how contaminants move in marine environments. Instead of relying solely on detection after pollution has occurred, the project focuses on forecasting the spread of pollutants using satellite-derived ocean data. By anticipating where and when contamination is likely to reach coastal areas, DriftGuard enables earlier and more targeted interventions—such as deploying containment measures, prioritizing inspections, or issuing warnings. This contributes to protecting and managing water resources by reducing environmental impact, improving response efficiency, and supporting data-driven decision-making for coastal authorities and environmental agencies.

🤼 Team

Tatiana Quercia, Project Manager

Space engineer and PMP®-certified Project Manager with a background in ESA and Airbus programmes, bringing structured execution and hackathon-winning experience to lead the team from concept to delivery.