Groundwater Vulnerability and Risk Mapping Based on Residence Time Distributions: Spatial Analysis for the Estimation of Lumped Parameters - INSU - Institut national des sciences de l'Univers Accéder directement au contenu
Article Dans Une Revue Water Resources Management Année : 2015

Groundwater Vulnerability and Risk Mapping Based on Residence Time Distributions: Spatial Analysis for the Estimation of Lumped Parameters

Résumé

Specific vulnerability estimations for groundwater resources are usually geographic information system-based (GIS) methods that establish spatial qualitative indexes which determine the sensitivity to infiltration of surface contaminants, but with little validation of the working hypothesis. On the other hand, lumped parameter models, such as the Residence Time Distribution (RTD), are used to predict temporal water quality changes in drinking water supply, but the lumped parameters do not incorporate the spatial variability of the land cover and use. At the interface between these two approaches, a GIS tool was developed to estimate the lumped parameters from the vulnerability mapping dataset. In this method the temporal evolution of groundwater quality is linked to the vulnerability concept on the basis of equivalent lumped parameters that account for the spatially distributed hydrodynamic characteristics of the overall unsaturated and saturated flow nets feeding the drinking water supply. This vulnerability mapping method can be validated by field observations of water concentrations. A test for atrazine specific vulnerability of the Val d’Orléans karstic aquifer demonstrates the reliability of this approach for groundwater contamination assessment.
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Dates et versions

insu-01237105 , version 1 (20-01-2016)

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Paternité - Pas d'utilisation commerciale - Pas de modification

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Myriam Dedewanou, Stéphane Binet, Jean-Louis Rouet, Yves Coquet, Ary Bruand, et al.. Groundwater Vulnerability and Risk Mapping Based on Residence Time Distributions: Spatial Analysis for the Estimation of Lumped Parameters. Water Resources Management, 2015, 29 (15), pp.5489-5504. ⟨10.1007/s11269-015-1130-8⟩. ⟨insu-01237105⟩
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