FAIR-compliant infrastructure based on istSOS for high-resolution rainfall monitoring and alerting

In Switzerland, short-duration and spatially concentrated rainfall events increasingly affect small catchments, where limited response times can lead to flash floods and debris flows with significant impacts on local infrastructure. These phenomena typically develop at spatial and temporal scales that are not fully captured by conventional meteorological monitoring networks.

Recent events in Southern Switzerland, including in the municipality of Lumino, have shown how localized precipitation can rapidly overload drainage systems and watercourses. Such situations highlight the need for rainfall observations with higher spatial density and minute-scale temporal resolution, able to complement regional forecasting and warning services.

National early warning systems, including those provided by MeteoSwiss, form a key component of flood risk management but may not resolve precipitation variability at local scales. To complement these systems, SUPSI and the Canton Ticino’s Ufficio dei corsi d’acqua (UCA) are testing a denser rainfall monitoring network based on rain gauges delivering one-minute data streams in near real time.

The monitoring infrastructure is designed according to FAIR data principles, ensuring that observations are findable, accessible, interoperable, and reusable. Data are managed through a cloud-based, event-driven architecture built on open geospatial standards, notably the OGC SensorThings API, implemented using the istSOS framework. Incoming data streams are processed on a computing cluster to derive cumulative rainfall indicators at multiple temporal scales (10-minute, hourly, and three-hourly), which are used to support threshold-based alerting mechanisms.

By combining high-resolution observations with open, standards-based data services, the system enables real-time visualization, automated notifications, and seamless integration with existing hydrological and risk management workflows. This approach demonstrates how FAIR-by-design monitoring infrastructures can bridge the gap between regional forecasts and local-scale observations, strengthening early warning capabilities and supporting more resilient flood risk management in a changing climate.