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The primary aim of a catchment water safety plan is to reduce risks within the catchment to protect the quality of drinking water sources at the point of abstraction. Even where effective arrangements for catchment management and control have been implemented, unexpected deterioration in raw water quality can pose a risk to treated drinking water quality. Thus potential sources of pollution impacting the abstraction point should be identified and monitored. An important part of any catchment management strategy includes implementation of raw water monitoring programmes, targeted at the most likely microbiological challenges to water treatment. When combined with good monitoring datasets, properly calibrated, tested and verified surface water models can be used to forecast or estimate risks under various scenarios. This allows a good insight into impacts associated with known and anticipated land use activities within the catchment. In this work a hybrid methodology based on river water quality data analysis and hydrodynamic and water quality modelling was developed to assess the surface water quality in the Portuguese river Cávado and the technical performance of waste water treatment plants sited in the river basin. Time series of water quality data (dissolved oxygen, biochemical oxygen demand, coliform bacteria, faecal streptococci and faecal coliforms) have been collected for twelve monitoring stations. The river model was implemented applying the Sobek software and includes reservoirs, hydraulic structures and main tributaries, as well as the most significant point sources pollutant loads discharged by waste water treatment plants, industrial and livestock within the river basin. The obtained results reveal to be very sensitive to the seasonal river flow regime variation and to the adopted hydropower generation operational schemes. They also show a great sensitivity of the receiving water quality status to wastewater discharges in the dry season, for all simulated parameters.


Session R25, Eco-Hydraulic Modeling: Water Quality Aspects



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