Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 23, issue 1
Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-351-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-351-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 1
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

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Cited articles

Ababou, R., Bagtzoglou, A. C., and Mallet, A.: Anti-diffusion and source identification with the 'RAW' scheme: a particle-based censored random walk, Environ. Fluid Mech., 10, 41–76, 2010.
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Alapati, S. and Kabala, Z.: Recovering the release history of a groundwater contaminant using a non-linear least-squares method, Hydrol. Process., 14, 1003–1016, 2000.
Amirabdollahian, M. and Datta, B.: Identification of contaminant source characteristics and monitoring network design in groundwater aquifers: an overview, Journal of Environmental Protection, 4, 23–41, 2013.
Amirabdollahian, M. and Datta, B.: Identification of pollutant source characteristics under uncertainty in contaminated water resources systems using adaptive simulated anealing and fuzzy logic, International Journal of GEOMATE, 6, 757–763, 2014.
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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.
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