NDLI: A global stochastic index for water quality: The case of the river Turia in Spain

Content Provider	Springer Nature Link
Author	Beamonte, Eduardo Bermúdez, José D. Casino, Alejandro Veres, Ernesto
Copyright Year	2005
Abstract	Which are applicable in all Member States. Those directives specify a set of physical and chemical characteristics, which depend on the use the water is intended for, the parameters to be regularly controlled in a network of sampling points, and the limiting values of those parameters for each quality level. Hence, an administrative quality classification for each sampling point is obtained. This article proposes a stochastic quality index that takes into account the uncertainty surrounding the quality classification still remaining after the data have been observed. This stochastic index is built with the probability classification vector of each parameter. In order to obtain those vectors, a mixed-lognormal model is introduced and its statistical analysis developed. The methodology proposed here is then applied to the data observed in the La Presa station, one of the sampling points of the Spanish surface water quality network. Located on the river Turia, near the city of Valencia, its aim is to control the quality of water intended for the abstraction of drinking water. Its stochastic quality classification is obtained and compared with the legally applicable administrative one.
Starting Page	424
Ending Page	439
Page Count	16
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	10
Issue Number	4
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2005-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bayesian analysis Estimation of percentiles Monte Carlo methods Mixed models Water intended for the abstraction of drinking water Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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