DEVELOPMENT OF A DIGITAL TWIN-BASED DECISION SUPPORT PLATFORM FOR DRINKING WATER QUALITY MONITORING AND MANAGEMENT

Climate change, ageing infrastructure, and the revised EU Drinking Water Directive highlight the need for proactive, risk-based approaches to drinking water management. This study presents the development and deployment of a modular, FIWARE-compliant decision-support platform aimed at enabling real-time risk assessment and operational decision-making in drinking water treatment. Implemented at Waternet’s Leiduin Drinking Water Treatment Plant, the platform integrates real-time data from SCADA and machine-learning-based soft sensors to monitor key treatment processes. It quantifies the likelihood and severity of short-term hazards—such as high turbidity and insufficient ozone exposure during ozonation (low contact time, CT)—as well as long-term risks, including saturation of granular activated carbon (GAC), and elevated assimilable organic carbon (AOC) levels, which can promote microbial growth in the non-chlorinated distribution network. By generating timely alerts and supporting risk-informed decisions, the platform helps operators and water
technologists take preventive actions to maintain providing high quality drinking water.