This research has developed a numerical stochastic methodology for analyzing the uncertainty of groundwater flow and transport parameters and their effects on exposure and risk assessment.
The Monte Carlo method is commonly used to analyze exposure uncertainty based on the uncertainty of each groundwater parameter measured.
If the Monte Carlo method was used for all parameters in this study, it would have required an extremely large number of simulations.
Therefore, a stochastic modeling approach based on Latin Hypercube Sampling was used to reduce the number of simulations required and to make uncertainty analysis feasible.
This technique was adapted to use samples from both the statistical distributions of nonspatial stochastic parameters and spatial and discrete hydraulic conductivity field simultaneously.
The use of Latin Hypercube Sampling proved to be very efficient for modeling uncertainty in exposure and risk assessment related to groundwater contamination.
Mots-clés Pascal : Pollution eau, Eau souterraine, Nappe eau, Devenir polluant, Modélisation, Simulation numérique, Analyse risque, Contamination, Modèle stochastique, Théorie échantillonnage
Mots-clés Pascal anglais : Water pollution, Ground water, Aquifers, Pollutant behavior, Modeling, Numerical simulation, Risk analysis, Contamination, Stochastic model, Sampling theory
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 99-0474494
Code Inist : 001D16A04B. Création : 22/03/2000.