Abstract
The purposes and intent of the authorities in establishing water quality standards are to provide enhancement of water quality and prevention of pollution to protect the public health or welfare in accordance with the public interest for drinking water supplies, conservation of fish, wildlife and other beneficial aquatic life, and agricultural, industrial, recreational, and other reasonable and necessary uses as well as to maintain and improve the biological integrity of the waters. In this way, water quality controls involve a large number of variables and observations, often subject to some outliers. An outlier is an observation that is numerically distant from the rest of the data or that appears to deviate markedly from other members of the sample in which it occurs. An interesting analysis is to find those observations that produce measurements that are different from the pattern established in the sample. Therefore, identification of atypical observations is an important concern in water quality monitoring and a difficult task because of the multivariate nature of water quality data. Our study provides a new method for detecting outliers in water quality monitoring parameters, using turbidity, conductivity and ammonium ion as indicator variables. Until now, methods were based on considering the different parameters as a vector whose components were their concentration values. This innovative approach lies in considering water quality monitoring over time as continuous curves instead of discrete points, that is to say, the dataset of the problem are considered as a time-dependent function and not as a set of discrete values in different time instants. This new methodology, which is based on the concept of functional depth, was applied to the detection of outliers in water quality monitoring samples in the Nalón river basin with success. Results of this study were discussed here in terms of origin, causes, etc. Finally, the conclusions as well as advantages of the functional method are exposed.
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Acknowledgements
This study was possible thanks to the experimental dataset from the Automated Water Quality Information System (AWQIS) located in the basin of the Nalón river collected by the Cantabrian Basin Authority (Ministry of Agriculture, Food and Environment of the Government of Spain). At the same time, the authors wish to acknowledge the computational support by the Departament of Mathematics at University of Oviedo and “Centro Universitario de la Defensa” at University of Zaragoza. Furthermore, this paper has been funded by the Government of the Principality of Asturias through funds from the Programme of Science, Technology and Innovation (PCTI) of Asturias 2006–2009, co-financed by 80 % within the priority Focus 1 of the Operational Programme FEDER of the Principality of Asturias 2007–2013 (Research project FC-11-PC10-19) and by the Spanish Ministry ofScience and Technology (research project ECO2011-22650) . Finally, we would like to thank Anthony Ashworth for his revision of English grammar and spelling of the manuscript.
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Piñeiro Di Blasi, J.I., Martínez Torres, J., García Nieto, P.J. et al. Analysis and detection of functional outliers in water quality parameters from different automated monitoring stations in the Nalón River Basin (Northern Spain). Environ Sci Pollut Res 22, 387–396 (2015). https://doi.org/10.1007/s11356-014-3318-5
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DOI: https://doi.org/10.1007/s11356-014-3318-5