An iterative strategy for contaminant source localisation using GLMA optimization and Data Worth on two synthetic 2D Aquifers

E. Essouayed, E. Verardo, A. Pryet, Romain Chassagne, O. Atteia

Research output: Contribution to journalArticle

Abstract

A contaminant source localisation strategy was developed considering unknown heterogeneous hydraulic conductivity field, unknown dispersivity and unknown location of a continuous contaminant source. The Gauss-Levenberg-Marquardt algorithm is combined with a data worth analysis to estimate the unknown parameters and identify the best locations of additional measurements. The data collection strategy is iterative, based on the ability of the additional dataset to decrease the uncertainties on the contaminant source location. Two 2D synthetic models are considered. The method is first illustrated with a simple model and a more complex model is then considered to evaluate the ability of the approach to locate the contaminant source from hydraulic heads and concentration data. This approach is parsimonious in terms of model runs and applicable to real cases. The results give a good estimate of the source location and the dispersivity, with acceptable NRMSE for each case. New observations introduced at each iteration decrease the standard deviation of the source location and improve the NRMSE. The estimated hydraulic conductivity field presents the same features as the original field.

Original languageEnglish
Article number103554
JournalJournal of Contaminant Hydrology
Volume228
Early online date11 Sep 2019
DOIs
Publication statusPublished - Jan 2020

Keywords

  • Contaminant source localisation
  • Data worth
  • GLMA
  • Heterogeneous synthetic cases
  • Iterative strategy
  • K field estimation

ASJC Scopus subject areas

  • Environmental Chemistry
  • Water Science and Technology

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