Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-351-2019
https://doi.org/10.5194/hess-23-351-2019
Research article
 | 
21 Jan 2019
Research article |  | 21 Jan 2019

Contaminant source localization via Bayesian global optimization

Guillaume Pirot, Tipaluck Krityakierne, David Ginsbourger, and Philippe Renard

Viewed

Total article views: 4,336 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,585 1,635 116 4,336 173 203
  • HTML: 2,585
  • PDF: 1,635
  • XML: 116
  • Total: 4,336
  • BibTeX: 173
  • EndNote: 203
Views and downloads (calculated since 14 Aug 2017)
Cumulative views and downloads (calculated since 14 Aug 2017)

Viewed (geographical distribution)

Total article views: 4,336 (including HTML, PDF, and XML) Thereof 3,930 with geography defined and 406 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 Feb 2026
Download
Short summary
To localize the source of a contaminant in the subsurface, based on concentration observations at some wells, we propose to test different possible locations and minimize the misfit between observed and simulated concentrations. We use a global optimization technique that relies on an expected improvement criterion, which allows a good exploration of the parameter space, avoids the trapping of local minima and quickly localizes the source of the contaminant on the presented synthetic cases.
Share