Dynamic Monitoring of Water Quality in Constructed Wetlands Using Bayesian Data Assimilation and Geospatial Intelligence

Preprint of an extended abstract accepted for presentation at the IWA 19th International Conference on Wetland Systems for Water Pollution Control, Chania, Greece, September 13–17, 2026. The final version will be published in the conference proceedings. This work proposes an intelligent monitoring framework for constructed wetlands that integrates remote sensing and in situ sensor networks within the Adaptive Environmental Remediation Systems (AERS) architecture. A composite Water Quality and Potability Index, based on key physicochemical parameters such as dissolved oxygen, turbidity, and nutrients, is dynamically updated using Bayesian data assimilation to incorporate uncertainty and temporal variability. The approach enables continuous system state estimation and spatiotemporal analysis of pollutant removal efficiency. Simulation results indicate improved predictive consistency and reduced uncertainty compared to conventional monitoring approaches. This work represents a conceptual and methodological contribution, with future work focusing on full-scale experimental validation. This preprint corresponds to the accepted extended abstract version.