title: A concurrent neuro-fuzzy inference system for screening the ecological risk in rivers.
abstract: OBJECTIVE
  A conceptual model to assess water quality in river basins was developed here. The model was based on ecological risk assessment principles, and incorporated a novel ranking and scoring system, based on self-organizing maps, to account for the likely ecological hazards posed by the presence of chemical substances in freshwater. This approach was used to study the chemical pollution in the Ebro River basin (Spain), whose currently applied environmental indices must be revised in terms of scientific accuracy.
  
  
  METHODS
  Ecological hazard indexes for chemical substances were calculated by pattern recognition of persistence, bioaccumulation, and toxicity properties. A fuzzy inference system was proposed to compute ecological risk points (ERP), which are a combination of the ecological hazard to aquatic sensitive organisms and environmental concentrations. By aggregating ERP, changes in water quality over time were estimated.
  
  
  RESULTS
  The proposed concurrent neuro-fuzzy model was applied to a comprehensive dataset of the network controlling the levels of dangerous substances, such as metals, pesticides, and polycyclic aromatic hydrocarbons, in the Ebro river basin. The approach was verified by comparison versus biological monitoring. The results showed that water quality in the Ebro river basin is affected by presence of micro-pollutants.
  
  
  CONCLUSIONS
  The ERP approach is suitable to analyze overall trends of potential threats to freshwater ecosystems by anticipating the likely impacts from multiple substances, although it does not account for synergies among pollutants. Anyhow, the model produces a convenient indicator to search for pollutant levels of concern.
authors.affiliation: Faculty of Engineering, Pontificia Universidad Javeriana, Cali, Colombia.
authors.forename: William
authors.initials: W
authors.lastname: Ocampo-Duque
authors.forename: Ronnie
authors.initials: R
authors.lastname: Juraske
authors.forename: Vikas
authors.initials: V
authors.lastname: Kumar
authors.forename: Martí
authors.initials: M
authors.lastname: Nadal
authors.forename: José Luis
authors.initials: JL
authors.lastname: Domingo
authors.forename: Marta
authors.initials: M
authors.lastname: Schuhmacher
mesh_terms: D004784:Environmental Monitoring; D005062:European Union; D017143:Fuzzy Logic; D006843:Hydrocarbons, Chlorinated / Q000032:analysis; D008670:Metals / Q000032:analysis; D008956:Models, Chemical; D016571:Neural Networks, Computer; D010575:Pesticides / Q000032:analysis; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis; D018570:Risk Assessment / Q000379:methods*; D045483:Rivers / Q000737:chemistry; D012680:Sensitivity and Specificity; D013030:Spain; D014874:Water Pollutants, Chemical / Q000032:analysis*; D060753:Water Quality
chemical_list: D006843:Hydrocarbons, Chlorinated; D008670:Metals; D010575:Pesticides; D011084:Polycyclic Aromatic Hydrocarbons; D014874:Water Pollutants, Chemical