A real-time alert system for predicting and managing short-term pollution and bathing water quality at Enniscrone beach /

Abstract

Under the Bathing Water Directive [2006/7/EC] there is a new highest microbiological quality classification of “Excellent” that is much more stringent than the highest standard of the old directive. This has serious implications for some beach resorts in Ireland as they may now struggle to meet this classification which is also required to qualify for a Blue Flag eco label. Enniscrone, a major sea-side resort in Co. Sligo has failed to attain this highest classification and has also lost its Blue Flag. The cause was a large flux of faecal indictor organisms (E. coli) from an inputting river which grossly affected a compliance sample in 2014, and consequently the current overall classification. These events are defined in the directive as predictable “shortterm pollution” (STP). The directive with its stronger focus on protecting public health encourages beach managers to be much more pro-active in managing bathing water quality. In Enniscrone’s case, to attain “Excellent” status appropriate early-warning systems to predict and manage health hazards like STP must be established. The incentive for managers if such systems exist, are permitted deviations in compliance monitoring which will shield the water’s classification from the impact of the STP. This study utilised innovative new techniques to create maps to identify the critical source areas for E. coli in the contributing local river catchment. These were then used to identify the key locations for monitoring fluxes of E. coli generated in the catchment. Automatic hydrometric monitoring stations were installed at these locations in the river catchment to measure the related flux in river flow and level. Using the conceptual model, hydrometric instrumentation was configured to predict STP events and automatically communicated real-time alerts to the author. These measured hydrographs were compared to E. coli levels analysed in the river and bathing water to develop and confirm the operational model. This study developed and ran real-time bathing water predictions for Enniscrone Beach for the 2016 and 2017 bathing seasons. The E. coli results confirmed a 100% prediction rate for STP with no false positives or missed events. From the summer of 2018 this system has used Twitter® to disseminate bathing water predictions to the public. This is the first operational automatic real-time bathing water prediction system in Ireland. This risk management method will help ensure that bathers’ health at this beach will be protected and that Enniscrone regains and retains a Blue Flag. The approach adopted in this study of using a localised conceptional and operational model could act as a template for environmental management solutions at the many other beaches in Ireland whose bathing waters are affected by diffuse STP.