RIVERCAST

AI-supported flood forecasting via hybrid satellite communication. ERDF/JTF-funded collaborative project (GreenEconomy.IN.NRW programme), October 2025 – September 2028, led by TerraTransfer.

ERDF / JTF NRW · 2025–2028

RIVERCAST

AI-supported flood forecasting via hybrid satellite communication.

The RIVERCAST project is developing an intelligent early-warning and information system that predicts flood events earlier and more precisely. It combines AI models, modern IoT measurement systems and a hybrid data link that uses both cellular networks and LEO satellites — so measurement data remains available even when cellular networks fail during a disaster.

The goal is to forecast water levels, discharge and the filling levels of flood retention basins reliably, significantly increasing resilience and planning certainty in flood protection.

Erft catchment, test region for RIVERCAST

Erft catchment, test region for the RIVERCAST observation areas.

DurationOctober 2025 – September 2028

FundingERDF programme GreenEconomy.IN.NRW

Project leadTerraTransfer GmbH

RegionErft catchment, North Rhine-Westphalia

Project partners

TerraTransfer GmbH Project lead, development of hybrid IoT data loggers, backend and frontend systems, overall coordination
Erftverband Provision of the test region, hydrological analyses and integration into existing flood-protection structures
BO-I-T gGmbH Development of AI and machine-learning algorithms and the data pipeline
FAU Erlangen-Nürnberg Prof. Dr. Gabriele Chiogna (Professor of Applied Geology and Environmental Systems Modelling), scientific modelling and validation

Friedrich-Alexander-Universität Erlangen-Nürnberg

Project timeline

2025 / 2026Selection and set-up of the test areas in the Erft catchment, definition of sensor requirements.
2026 / 2027Installation of the extended IoT measurement network, development and training of the first AI models.
2027 / 2028Construction and testing of hybrid data loggers (cellular / satellite), integration of the models into a real-time monitoring platform.

Results and benefits

Hybrid data logger with automatic switchover between cellular and satellite when the network fails
AI-supported forecasting models for water levels and retention-basin filling levels
Extended IoT network for real-time water level, rainfall and discharge (via stage–discharge relations), plus water temperature and electrical conductivity as a major-ion proxy
Monitoring platform for authorities and emergency services with forecasting and visualisation functions
Transferable concept that scales to other river catchments in NRW and across Europe

RIVERCAST strengthens resilience against hydrological extremes and lays the foundation for modern, digitally networked flood management in North Rhine-Westphalia.

Funded by the European Union and the State of North Rhine-Westphalia under the ERDF/JTF programme NRW 2021–2027 (GreenEconomy.IN.NRW).

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