Atribución-NoComercial 4.0 InternacionalTaboada, JavierSaavedra, AngelesPaz, MaríaBastante, Fernando GAlejano, Leandro R.2019-07-022019-07-022015-01-01ISSN: 2346-2183https://repositorio.unal.edu.co/handle/unal/60766We statistically analysed the chemical components present in waste water from mines in Galicia (NW Spain). These elements pose a risk to public health and the environment, most particularly in the event of a failure in the containment structure of a pond or dam. The statistical processing of the data, which started with an analysis of the typical contaminants present in mining ponds and dams, pointed to the potential limitations of using non-spatial models for spatially structured data. Our results indicate the greater potential of the generalized linear spatial model over the generalized linear model for analysis of spatially structured data. We also show how a misspecification of the model for analysing spatial data can lead to misleading conclusions, which might lead, in turn, to poorly designed protective or corrective measures.application/pdfspaDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/62 Ingeniería y operaciones afines / EngineeringArtículo de revistahttp://bdigital.unal.edu.co/59098/info:eu-repo/semantics/openAccesstailings pondenvironmental riskgeneralized linear spatial modelMarkov-chain Monte Carlospatial statistics.