SWIM (Surface Water Information Management) developed, integrated and validated a Copernicus-based decision-support platform for continuous, AI-informed monitoring of surface water. The result is an operational TRL 4 prototype that combines satellite Earth Observation (EO), real-time in-situ IoT sensing and machine learning to support decisions on water quality, water balance and natural-disaster risk.
EO and in-situ data ingestion (WP2). An automated, multi-source pipeline acquires, harmonises and pre-processes Copernicus Sentinel-1/2/3 data (through the Copernicus Data Space Ecosystem, atmospherically corrected with ACOLITE), the in-situ WAMO sensor network, and auxiliary datasets (ERA5-Land, MERIT Hydro DEM, GloFAS, HydroSHEDS, SMAP and GPM). It standardises the heterogeneous streams into unified spatial-temporal data cubes, processing roughly 5 to 10 GB of EO data per day.
WOLF calibration engine (WP2). The WAMO-OPIE Learning Framework dynamically matches satellite pixels with WAMO readings to correct atmospheric noise and mixed pixels. This reduces the uncertainty of Copernicus products and assigns a confidence flag to each value. A priority patent was filed for the dynamic water-quality calibration logic.
Three modules at TRL 4. A Water Quality Module (chlorophyll-a/NDCI, turbidity, total suspended matter, Secchi depth and algal-bloom indices) was deployed at La Fe Reservoir. A Water Balance Module predicts discharge in poorly gauged and ungauged basins from global data (SVR R²=0.92 NSE=0.91). A Natural Disaster Module provides flood and drought early warning, piloted at Las Palmas. WAMO was installed at La Fe on 12 June 2025 and transmits 19 parameters hourly via LTE.
AI-DSS, software architecture and user interface (WP3 and WP4). The system runs on a scalable OPIE REST backend (PostgreSQL/PostGIS, dual-server, HTTPS/SSL) with an ML pipeline (SVR, Random Forest, XGBoost), a multilingual LLM-based chatbot in Spanish, German and English for data retrieval, statistics and anomaly detection, and an interactive TypeScript/MapLibre/Three.js dashboard with role-based views and automated alerts. End-to-end integration across five layers was tested in April 2026 (D4.3).
Requirements and end-user engagement (WP4). More than 30 prioritised functional and non-functional requirements were gathered through fieldwork, interviews and workshops with EPM, the Municipality of Envigado and the University of Envigado, and were formalised through MoUs (D4.1 D4.2).
Dissemination, exploitation and communication (WP5). The consortium delivered the brand identity and website (theswimapp.com) social media activity, a concept demonstration video, webinars, FAIR-compliant open-data practices, an IPR assessment, a preliminary Business Innovation and Commercialisation Plan with six exploitable results and routes to market, and a future-evolution roadmap from TRL 4 toward operational deployment. Management (WP1) covered data security, GDPR compliance, the Data Management Plan and timely reporting.
