Rain2Risk

💎 Idea

Rain2Risk is a geospatial platform for near-real-time monitoring and short-term prediction of runoff and flash flood risk.

Our idea is to combine high-resolution digital elevation models, land use data, rainfall observations, forecasted precipitation, soil moisture, and remote sensing flood-related data into a single predictive system. Based on the terrain conditions of a specific area and the rainfall that has already occurred, together with the rainfall expected in the coming days, Rain2Risk estimates where runoff is most likely to concentrate and where flood risk is likely to increase.

Users can open the viewer, explore the current state of the territory, and understand both present and upcoming flood risk.

To achieve this, we will combine terrain-based hydrological indicators with machine learning models that help identify patterns linking topography, land conditions, antecedent wetness, rainfall, and flood-prone behaviour. The result is a practical decision-support tool for both immediate response and long-term planning.

🛰️ EU space technologies

Rain2Risk relies on EU space technologies as a core part of its value proposition.

We use Copernicus Earth observation data and services to support flood risk monitoring and modelling. This includes elevation products for terrain analysis, land monitoring products for land cover and soil-related conditions, and satellite-based data that help capture hydrological context and flood-related patterns. These datasets are essential for understanding how water moves across the landscape and where flood risk is likely to emerge.

Copernicus brings major value to our idea because it provides consistent, large-scale, openly accessible geospatial information that can be updated and applied across different territories. By combining this with rainfall observations and forecasts, Rain2Risk can turn EO-based environmental intelligence into practical flood risk insights.

In short, EU space technologies allow us to move from static mapping to dynamic, scalable, and predictive flood-risk monitoring.

EU Space for Water

Rain2Risk addresses the challenge of disaster risk monitoring.

The project contributes to protecting and managing water resources by improving our ability to anticipate flood and runoff risk before critical situations escalate. If flood-prone areas can be identified in advance, water managers and public authorities can make better operational decisions, for example by improving preparedness measures or supporting reservoir and dam management strategies when relevant.

Beyond emergency response, Rain2Risk also supports long-term water and land management. If some areas are consistently identified as highly prone to runoff and flooding, this can guide hydrological restoration, land-use changes, and landscape planning measures that improve water regulation and reduce vulnerability over time.

In this way, the project helps shift from reactive flood response to more preventive and strategic water management.

🤼 Team

Mario Peces — Product Design & Spatial Data Mining

Responsible for product design and the spatial data mining workflow. Will focus on shaping the platform, define how users interact with the risk maps, and prepare the geospatial datasets needed for the modelling pipeline.

Joan Medina — Machine Learning

In charge of training the machine learning models used to predict runoff and flood risk. 

Guillermo Pérez — Infrastructure

Responsible for the infrastructure behind the platform. Management of the technical backbone required to process data, run the models, and support a scalable and reliable application.