Abstract
Despite the efforts to control, protect and improve freshwater resources, eutrophication is still one of the main causes for reservoir water quality deterioration. Low-quality raw water reaching water supply treatment plants (WTP) implies an increment of chemical reagents to meet safety requirements, which may also increase the potential of disinfection by-products formation. The objective of this paper was to study the relationship between raw water quality coming from a water supply reservoir and the use of reagents in the associated WTP, through a series of stepwise regression models, in order to develop a simple statistical tool to select the most adequate withdrawal depth for optimizing the treatment processes. The results showed that chlorides, ammonia and water color were the main subrogate parameters in the reservoir explaining the need of chlorine and ozone in the pre-treatment and alum sulphate consumption in the WTP. Therefore, by controlling the variation of these parameters in the water column it would be possible to select the most appropriate reservoir withdrawal depth for reducing costs and risk of by-products formation during treatment, making the most of the water purification service offered by the ecosystem.
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Acknowledgements
We would like to thank Mr. Eduardo Arozamena for providing WTP data, knowledge about treatment, and article revision. Appreciations also to Dr. J. Iñaki Urrutia for his continuous support, guidance and revision efforts. Special mention is also made to the laboratory technicians of Natural Waters Department, for the data acquisition.
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Highlights
• A simple model is presented for evaluating the effects of reservoir water quality on its treatment
• Significant reagent savings can be achieved with selective withdrawal
• Organic matter and reduction potential in the reservoir seem to be the key factors
• Enhancing reservoir water quality will improve and ease water treatment
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Cáceres, L., Méndez, D., Fernández, J. et al. From End-of-Pipe to Nature Based Solutions: a Simple Statistical Tool for Maximizing the Ecosystem Services Provided by Reservoirs for Drinking Water Treatment. Water Resour Manage 32, 1307–1323 (2018). https://doi.org/10.1007/s11269-017-1871-7
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DOI: https://doi.org/10.1007/s11269-017-1871-7