Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots

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dc.contributor.author Rizo-Decelis, L. D.
dc.contributor.author Pardo Iguzquiza, Eulogio
dc.contributor.author Andreo Navarro, Bartolomé
dc.date.accessioned 2020-11-04T05:07:07Z
dc.date.available 2020-11-04T05:07:07Z
dc.date.issued 2017-12-15
dc.identifier.citation Science of the Total Environment, vol. 605–606, 276-290 es_ES
dc.identifier.issn 1879-1026
dc.identifier.uri http://hdl.handle.net/20.500.12468/556
dc.description.abstract In order to treat and evaluate the available data of water quality and fully exploit monitoring results (e.g. characterize regional patterns, optimize monitoring networks, infer conditions at unmonitored locations, etc.), it is crucial to develop improved and efficient methodologies. Accordingly, estimation of water quality along fluvial ecosystems is a frequent task in environment studies. In this work, a particular case of this problem is examined, namely, the estimation of water quality along a main stem of a large basin (where most anthropic activity takes place), from observational data measured along this river channel. We adapted topological kriging to this case, where each watershed contains all the watersheds of the upstream observed data (“nested support effect”). Data analysis was additionally extended by taking into account the upstream distance to the closest contamination hotspot as an external drift. We propose choosing the best estimation method by cross-validation. The methodological approach in spatial variability modeling may be used for optimizing the water quality monitoring of a given watercourse. The methodology presented is applied to 28 water quality variables measured along the Santiago River in Western Mexico. es_ES
dc.description.sponsorship Centro de Hidrogeología, Universidad de Málaga, España es_ES
dc.description.sponsorship Instituto Geológico y Minero de España, España es_ES
dc.language.iso en es_ES
dc.publisher Elsevier es_ES
dc.rights Otro es_ES
dc.subject Geostatistics es_ES
dc.subject river pollution es_ES
dc.subject water quality es_ES
dc.subject interpolation es_ES
dc.subject spatial analysis es_ES
dc.subject Mexico es_ES
dc.title Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots es_ES
dc.type Postprint es_ES
dc.relation.publisherversion https://www.sciencedirect.com/science/article/abs/pii/S0048969717315498?via%3Dihub#! es_ES
dc.identifier.doi https://doi.org/10.1016/j.scitotenv.2017.06.145 es_ES
dc.coverage.spatialStudy Río Santiago, México es_ES


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