Fuzzy intelligence approach for modeling the migration of contaminants ina reservoir affected by AMD pollution

• Autor(a) principal: Santistebán, M.
• Data de Publicação: 2015
• Outros Autores: Grande, J. A., De la Torre, M. L., Valente, Teresa Maria Fernandes, Pérez-Ostalé, E., Cerón, J. C., Aroba, Javier
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/34084
• topic: Fuzzy logic; Iberian pyrite belt; Acid mine drainage; Meca river; Science & Technology

The Sancho Reservoir, located in the Huelva province (SW Spain), is supplied by the Meca River, which receives water contaminated by mining activities in Tharsis. This study focused on determining the relationship that temperature, pH, and electrical conductivity (EC) had with rainfall. The temperature, pH, and EC were simultaneously measured every 30 min by two probes suspended in the Sancho Reservoir. It was anticipated that the use of fuzzy logic and data mining would lead to a model that would show how the contaminant load evolved over space and time. Similar results were obtained for the two locations, except that the parameters had more outliers near the dam due to the greater distance from the contamination source. As expected, higher pH corresponded with lower EC, since, in the absence of chloride, sulphate was the principal anion. The dependency relationship of the variables as well as the cause–effect relationship with the rate of rainfall was more evident in the up-gradient sampling location than near the dam due to the different residence time and the transit time between the two points.