Scale-adaptive expected mass fraction framework for contaminant dilution mapping in coastal waters

Coastal waters face continuous threats from inland pollution sources, such as rivers, torrents, and wastewater discharges. These sources pose significant challenges to water quality management. To address the complex dynamics of pollutant transport and dilution in these environments, we introduce a scale-adaptive Expected Mass Fraction (EMF) framework. This framework enables the quantification and mapping of contaminant dilution through a flexible spatial representation, adaptable to arbitrary scales and tailored to specific water quality assessment needs. By combining Lagrangian particle tracking, stochastic ensemble analysis, and spatially integrated concentration statistics, the framework offers a comprehensive tool for evaluating the auto-purification potential of coastal waters. Applied to the Kaštela Bay and Brač Channel in the Eastern Adriatic Sea, the methodology captures the effects of distinct hydrodynamic events – Bora and Sirocco – on pollutant dispersion. Results reveal significant variations in contaminant transport patterns. Bora events exhibit localized surface spreading, while Sirocco events drive extensive horizontal and vertical dispersion. The proposed Auto-Purification Potential (APP) index consolidates these complex dynamics into a region-oriented map, providing a compact and accessible visualization of auto-purification potential. Such a visualization can support public awareness and informed decision-making in coastal water quality management. This study advances the application of EMF concepts to complex hydrodynamic environments, demonstrating its adaptability to diverse spatial scales. The findings provide a foundation for effective pollution monitoring and management strategies in coastal water ecosystems and offer the potential for broader applications in other environmental systems.