How digital twins are being used in MARCLAIMED to monitor and optimise water management strategies
The MARCLAIMED project creates an integrated decision‑support environment built around a high‑fidelity digital twin of river‑basin and aquifer systems. Real‑time sensor feeds, including hydrological, meteorological, water‑quality and infrastructure data, are exchanged using the NGSI‑LD standard and are coupled with physics‑based hydraulic models, producing a continuously updated virtual replica of the water network across the three demonstration sites in Portugal, Spain and the Netherlands. This virtual replica serves as the foundation for three AI‑driven tools that work on a shared, coherent representation of the system.
The twin monitors the quality of alternative water resources (AWR) such as reclaimed wastewater, storm‑water capture and rain‑water harvesting. Sensors measuring turbidity, temperature, dissolved‑oxygen and contaminant concentrations stream into the twin, where data‑assimilation algorithms reconcile measurements with model predictions, flag anomalies and trigger alerts when thresholds are exceeded.
It also forecasts water availability under varying climate scenarios. By integrating short‑term weather forecasts, long‑term climate projections and groundwater‑recharge models, the twin generates probabilistic estimates of surface‑water inflow, aquifer storage and demand‑supply balances. These forecasts feed directly into the MAR optimization module, which evaluates trade‑offs between managed aquifer recharge (MAR) volumes and the use of AWR, identifying the most resilient allocation of water resources for each basin.
The twin further supplies the economic‑sustainability layer with a municipal‑scale water‑scarcity index and a cost‑recovery model. Because the twin quantifies the volume of water stored, released or diverted in near‑real time, it can calculate the marginal value of each cubic meter of water and the associated operational costs. Decision‑makers can therefore test “what‑if” scenarios, such as increasing MAR capacity, altering pumping schedules or expanding AWR treatment, and instantly see the impact on both water security and the economic bottom line.
Finally, the twin supports stakeholder engagement through a visual dashboard that displays the evolving state of the basin, the status of MAR facilities and the performance of AWR assets. By presenting complex hydrological dynamics in an intuitive, interactive format, the digital twin helps policy‑makers, water utilities and local communities co‑design adaptive management strategies, fostering transparency, trust and rapid response to emerging drought or flood risks. In sum, MARCLAIMED’s digital twin acts as the nervous system of the water‑management ecosystem, turning raw sensor data, standardized via NGSI‑LD, into actionable intelligence that optimizes both the physical operation of MAR schemes and the socioeconomic outcomes of water‑resource planning.
