Modeling the fate of down-the-drain chemicals in whole watersheds: New version of the GREAT-ER software. (February 2015)

• Record Type: Journal Article
• Authors: Kehrein, Nils; Berlekamp, Jürgen; Klasmeier, Jörg
• Is Part Of: Environmental modelling & software. Volume 64(2015:Feb.)
• Page Start: 1
• Page End: 8
• Publication Date: 2015-02
• Subjects: Exposure assessment -- River basin management -- Spatial model -- Surface water model; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.10.018
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The geo-referenced regional exposure assessment tool for European rivers (GREAT-ER) designed for the prediction of spatially explicit exposure concentrations of typical down-the-drain chemicals in whole river basins was improved. New features for scenario creation and analyses were amended for use in river basin management or within the Water Framework Directive implementation process. Improvements of the new model version are exemplary illustrated by means of an extensive case study for the pharmaceutical diclofenac in the German watershed of Ruhr River, a tributary of River Rhine. Comparison with monitoring data corroborates the capability of the probabilistic model to realistically predict spatial surface water concentration ranges for non-persistent chemicals. Based on the evaluation of the actual contamination, two management scenarios are investigated in terms of their reduction potential. The analysis demonstrates how the model allows for a priori evaluation of mitigation strategies. Highlights: New GREAT-ER version combines aquatic exposure assessment and risk reduction management. Graphical features for meaningful evaluation of results were substantially enhanced. Usefulness of a priori evaluation of reduction measures on river-basin scale is demonstrated.