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.
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.
the Creative Commons Attribution 4.0 License.
Contaminant source localization via Bayesian global optimization
Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
Tipaluck Krityakierne
Department of Mathematics, Faculty of Science, Mahidol University, Bangkok, Thailand
Centre of Excellence in Mathematics, CHE, Bangkok, Thailand
Oeschger Center for Climate Change Research,
University of Bern, Bern, Switzerland
David Ginsbourger
Oeschger Center for Climate Change Research,
University of Bern, Bern, Switzerland
Uncertainty Quantification and Optimal Design group, Idiap Research Institute, Martigny, Switzerland
Institute of Mathematical Statistics and Actuarial Science,
University of Bern, Bern, Switzerland
Philippe Renard
Centre for Hydrogeology and Geothermics, University of Neuchâtel, Neuchâtel, Switzerland
Related authors
Léonard Moracchini, Guillaume Pirot, Kerry Bardot, Mark W. Jessell, and James L. McCallum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-154, https://doi.org/10.5194/gmd-2024-154, 2024
Preprint under review for GMD
Short summary
Short summary
To facilitate the exploration of alternative hydrogeological scenarios, we propose to approximate costly physical simulations of contaminant transport by more affordable shortest distances computations. It enables to accept or reject scenarios within a predefined confidence interval. In particular, it can allow to estimate the probability of a fault acting as a preferential path or a barrier.
Alan Robert Alexander Aitken, Ian Delaney, Guillaume Pirot, and Mauro A. Werder
The Cryosphere, 18, 4111–4136, https://doi.org/10.5194/tc-18-4111-2024, https://doi.org/10.5194/tc-18-4111-2024, 2024
Short summary
Short summary
Understanding how glaciers generate sediment and transport it to the ocean is important for understanding ocean ecosystems and developing knowledge of the past cryosphere from marine sediments. This paper presents a new way to simulate sediment transport in rivers below ice sheets and glaciers and quantify volumes and characteristics of sediment that can be used to reveal the hidden record of the subglacial environment for both past and present glacial conditions.
Guillaume Pirot, Ranee Joshi, Jérémie Giraud, Mark Douglas Lindsay, and Mark Walter Jessell
Geosci. Model Dev., 15, 4689–4708, https://doi.org/10.5194/gmd-15-4689-2022, https://doi.org/10.5194/gmd-15-4689-2022, 2022
Short summary
Short summary
Results of a survey launched among practitioners in the mineral industry show that despite recognising the importance of uncertainty quantification it is not very well performed due to lack of data, time requirements, poor tracking of interpretations and relative complexity of uncertainty quantification. To alleviate the latter, we provide an open-source set of local and global indicators to measure geological uncertainty among an ensemble of geological models.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
Short summary
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Mark Jessell, Jiateng Guo, Yunqiang Li, Mark Lindsay, Richard Scalzo, Jérémie Giraud, Guillaume Pirot, Ed Cripps, and Vitaliy Ogarko
Earth Syst. Sci. Data, 14, 381–392, https://doi.org/10.5194/essd-14-381-2022, https://doi.org/10.5194/essd-14-381-2022, 2022
Short summary
Short summary
To robustly train and test automated methods in the geosciences, we need to have access to large numbers of examples where we know
the answer. We present a suite of synthetic 3D geological models with their gravity and magnetic responses that allow researchers to test their methods on a whole range of geologically plausible models, thus overcoming one of the fundamental limitations of automation studies.
Ranee Joshi, Kavitha Madaiah, Mark Jessell, Mark Lindsay, and Guillaume Pirot
Geosci. Model Dev., 14, 6711–6740, https://doi.org/10.5194/gmd-14-6711-2021, https://doi.org/10.5194/gmd-14-6711-2021, 2021
Short summary
Short summary
We have developed a software that allows the user to extract and standardize drill hole information from legacy datasets and/or different drilling campaigns. It also provides functionality to upscale the lithological information. These functionalities were possible by developing thesauri to identify and group geological terminologies together.
Mark Jessell, Vitaliy Ogarko, Yohan de Rose, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, and Guillaume Pirot
Geosci. Model Dev., 14, 5063–5092, https://doi.org/10.5194/gmd-14-5063-2021, https://doi.org/10.5194/gmd-14-5063-2021, 2021
Short summary
Short summary
We have developed software that allows the user to extract sufficient information from unmodified digital maps and associated datasets that we are able to use to automatically build 3D geological models. By automating the process we are able to remove human bias from the procedure, which makes the workflow reproducible.
Léonard Moracchini, Guillaume Pirot, Kerry Bardot, Mark W. Jessell, and James L. McCallum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-154, https://doi.org/10.5194/gmd-2024-154, 2024
Preprint under review for GMD
Short summary
Short summary
To facilitate the exploration of alternative hydrogeological scenarios, we propose to approximate costly physical simulations of contaminant transport by more affordable shortest distances computations. It enables to accept or reject scenarios within a predefined confidence interval. In particular, it can allow to estimate the probability of a fault acting as a preferential path or a barrier.
Alan Robert Alexander Aitken, Ian Delaney, Guillaume Pirot, and Mauro A. Werder
The Cryosphere, 18, 4111–4136, https://doi.org/10.5194/tc-18-4111-2024, https://doi.org/10.5194/tc-18-4111-2024, 2024
Short summary
Short summary
Understanding how glaciers generate sediment and transport it to the ocean is important for understanding ocean ecosystems and developing knowledge of the past cryosphere from marine sediments. This paper presents a new way to simulate sediment transport in rivers below ice sheets and glaciers and quantify volumes and characteristics of sediment that can be used to reveal the hidden record of the subglacial environment for both past and present glacial conditions.
Chloé Fandel, Ty Ferré, François Miville, Philippe Renard, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 4205–4215, https://doi.org/10.5194/hess-27-4205-2023, https://doi.org/10.5194/hess-27-4205-2023, 2023
Short summary
Short summary
From the surface, it is hard to tell where underground cave systems are located. We developed a computer model to create maps of the probable cave network in an area, based on the geologic setting. We then applied our approach in reverse: in a region where an old cave network was mapped, we used modeling to test what the geologic setting might have been like when the caves formed. This is useful because understanding past cave formation can help us predict where unmapped caves are located today.
Guillaume Pirot, Ranee Joshi, Jérémie Giraud, Mark Douglas Lindsay, and Mark Walter Jessell
Geosci. Model Dev., 15, 4689–4708, https://doi.org/10.5194/gmd-15-4689-2022, https://doi.org/10.5194/gmd-15-4689-2022, 2022
Short summary
Short summary
Results of a survey launched among practitioners in the mineral industry show that despite recognising the importance of uncertainty quantification it is not very well performed due to lack of data, time requirements, poor tracking of interpretations and relative complexity of uncertainty quantification. To alleviate the latter, we provide an open-source set of local and global indicators to measure geological uncertainty among an ensemble of geological models.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
Short summary
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Mark Jessell, Jiateng Guo, Yunqiang Li, Mark Lindsay, Richard Scalzo, Jérémie Giraud, Guillaume Pirot, Ed Cripps, and Vitaliy Ogarko
Earth Syst. Sci. Data, 14, 381–392, https://doi.org/10.5194/essd-14-381-2022, https://doi.org/10.5194/essd-14-381-2022, 2022
Short summary
Short summary
To robustly train and test automated methods in the geosciences, we need to have access to large numbers of examples where we know
the answer. We present a suite of synthetic 3D geological models with their gravity and magnetic responses that allow researchers to test their methods on a whole range of geologically plausible models, thus overcoming one of the fundamental limitations of automation studies.
Alexis Neven, Valentin Dall'Alba, Przemysław Juda, Julien Straubhaar, and Philippe Renard
The Cryosphere, 15, 5169–5186, https://doi.org/10.5194/tc-15-5169-2021, https://doi.org/10.5194/tc-15-5169-2021, 2021
Short summary
Short summary
We present and compare different geostatistical methods for underglacial bedrock interpolation. Variogram-based interpolations are compared with a multipoint statistics approach on both test cases and real glaciers. Using the modeled bedrock, the ice volume for the Scex Rouge and Tsanfleuron glaciers (Swiss Alps) was estimated to be 113.9 ± 1.6 million cubic meters. Complex karstic geomorphological features are reproduced and can be used to improve the precision of underglacial flow estimation.
Ranee Joshi, Kavitha Madaiah, Mark Jessell, Mark Lindsay, and Guillaume Pirot
Geosci. Model Dev., 14, 6711–6740, https://doi.org/10.5194/gmd-14-6711-2021, https://doi.org/10.5194/gmd-14-6711-2021, 2021
Short summary
Short summary
We have developed a software that allows the user to extract and standardize drill hole information from legacy datasets and/or different drilling campaigns. It also provides functionality to upscale the lithological information. These functionalities were possible by developing thesauri to identify and group geological terminologies together.
Mark Jessell, Vitaliy Ogarko, Yohan de Rose, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, and Guillaume Pirot
Geosci. Model Dev., 14, 5063–5092, https://doi.org/10.5194/gmd-14-5063-2021, https://doi.org/10.5194/gmd-14-5063-2021, 2021
Short summary
Short summary
We have developed software that allows the user to extract sufficient information from unmodified digital maps and associated datasets that we are able to use to automatically build 3D geological models. By automating the process we are able to remove human bias from the procedure, which makes the workflow reproducible.
Alexis Neven, Pradip Kumar Maurya, Anders Vest Christiansen, and Philippe Renard
Earth Syst. Sci. Data, 13, 2743–2752, https://doi.org/10.5194/essd-13-2743-2021, https://doi.org/10.5194/essd-13-2743-2021, 2021
Short summary
Short summary
The shallow underground is constituted of sediments that present high spatial variability. This upper layer is the most extensively used for resource exploitation (groundwater, geothermal heat, construction materials, etc.). Understanding and modeling the spatial variability of these deposits is crucial. We present a high-resolution electrical resistivity dataset that covers the upper Aare Valley in Switzerland. These data can help develop methods to characterize these geological formations.
Valentin Dall'Alba, Philippe Renard, Julien Straubhaar, Benoit Issautier, Cédric Duvail, and Yvan Caballero
Hydrol. Earth Syst. Sci., 24, 4997–5013, https://doi.org/10.5194/hess-24-4997-2020, https://doi.org/10.5194/hess-24-4997-2020, 2020
Short summary
Short summary
Due to climate and population evolution, increased pressure is put on the groundwater resource, which calls for better understanding and models. In this paper, we describe a novel workflow to model the geological heterogeneity of coastal aquifers and apply it to the Roussillon plain (southern France). The main strength of the workflow is its capability to model aquifer heterogeneity when only sparse data are available while honoring the local geological trends and quantifying uncertainty.
F. Oriani, J. Straubhaar, P. Renard, and G. Mariethoz
Hydrol. Earth Syst. Sci., 18, 3015–3031, https://doi.org/10.5194/hess-18-3015-2014, https://doi.org/10.5194/hess-18-3015-2014, 2014
Related subject area
Subject: Groundwater hydrology | Techniques and Approaches: Mathematical applications
Technical note: Removing dynamic sea-level influences from groundwater-level measurements
Estimating karst groundwater recharge from soil moisture observations – a new method tested at the Swabian Alb, southwest Germany
Present and future thermal regimes of intertidal groundwater springs in a threatened coastal ecosystem
Understanding the potential of climate teleconnections to project future groundwater drought
Sources and fate of nitrate in groundwater at agricultural operations overlying glacial sediments
Analysis of three-dimensional unsaturated–saturated flow induced by localized recharge in unconfined aquifers
Analysis of groundwater flow and stream depletion in L-shaped fluvial aquifers
On the coupled unsaturated–saturated flow process induced by vertical, horizontal, and slant wells in unconfined aquifers
Technical Note: Three-dimensional transient groundwater flow due to localized recharge with an arbitrary transient rate in unconfined aquifers
Thermal damping and retardation in karst conduits
Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion
Estimation of heterogeneous aquifer parameters using centralized and decentralized fusion of hydraulic tomography data
Analysis of groundwater drought building on the standardised precipitation index approach
Anomalous frequency characteristics of groundwater level before major earthquakes in Taiwan
Transient drawdown solution for a constant pumping test in finite two-zone confined aquifers
Scale dependency of fractional flow dimension in a fractured formation
Groundwater fluctuations in heterogeneous coastal leaky aquifer systems
Application of integral pumping tests to investigate the influence of a losing stream on groundwater quality
Patrick Haehnel, Todd C. Rasmussen, and Gabriel C. Rau
Hydrol. Earth Syst. Sci., 28, 2767–2784, https://doi.org/10.5194/hess-28-2767-2024, https://doi.org/10.5194/hess-28-2767-2024, 2024
Short summary
Short summary
While groundwater recharge is important for water resources management, nearshore sea levels can obscure this signal. Regression deconvolution has previously been used to remove other influences from groundwater levels (e.g., barometric pressure, Earth tides) by accounting for time-delayed responses from these influences. We demonstrate that it can also remove sea-level influences from measured groundwater levels.
Romane Berthelin, Tunde Olarinoye, Michael Rinderer, Matías Mudarra, Dominic Demand, Mirjam Scheller, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 27, 385–400, https://doi.org/10.5194/hess-27-385-2023, https://doi.org/10.5194/hess-27-385-2023, 2023
Short summary
Short summary
Karstic recharge processes have mainly been explored using discharge analysis despite the high influence of the heterogeneous surface on hydrological processes. In this paper, we introduce an event-based method which allows for recharge estimation from soil moisture measurements. The method was tested at a karst catchment in Germany but can be applied to other karst areas with precipitation and soil moisture data available. It will allow for a better characterization of karst recharge processes.
Jason J. KarisAllen, Aaron A. Mohammed, Joseph J. Tamborski, Rob C. Jamieson, Serban Danielescu, and Barret L. Kurylyk
Hydrol. Earth Syst. Sci., 26, 4721–4740, https://doi.org/10.5194/hess-26-4721-2022, https://doi.org/10.5194/hess-26-4721-2022, 2022
Short summary
Short summary
We used a combination of aerial, thermal, hydrologic, and radionuclide monitoring to investigate intertidal springs flowing into a coastal lagoon with a threatened ecosystem. Field data highlight the critical hydrologic and thermal role of these springs in the nearshore zone, and modelling results reveal that the groundwater springs will likely warm substantially in the coming decades due to climate change. Springs sourced from shallower zones in the aquifer will warm first.
William Rust, Ian Holman, John Bloomfield, Mark Cuthbert, and Ron Corstanje
Hydrol. Earth Syst. Sci., 23, 3233–3245, https://doi.org/10.5194/hess-23-3233-2019, https://doi.org/10.5194/hess-23-3233-2019, 2019
Short summary
Short summary
We show that major groundwater resources in the UK exhibit strong multi-year cycles, accounting for up to 40 % of total groundwater level variability. By comparing these cycles with recorded widespread groundwater droughts over the past 60 years, we provide evidence that climatic systems (such as the North Atlantic Oscillation) ultimately drive drought-risk periods in UK groundwater. The recursive nature of these drought-risk periods may lead to improved preparedness for future droughts.
Sarah A. Bourke, Mike Iwanyshyn, Jacqueline Kohn, and M. Jim Hendry
Hydrol. Earth Syst. Sci., 23, 1355–1373, https://doi.org/10.5194/hess-23-1355-2019, https://doi.org/10.5194/hess-23-1355-2019, 2019
Short summary
Short summary
Agricultural operations can result in nitrate contamination of groundwater, lakes and streams. At two confined feeding operations in Alberta, Canada, nitrate in groundwater from temporary manure piles and pens exceeded nitrate from earthen manure storages. Identified denitrification reduced agriculturally derived nitrate concentrations in groundwater by at least half. Infiltration to groundwater systems where nitrate can be naturally attenuated is likely preferable to off-farm export via runoff.
Chia-Hao Chang, Ching-Sheng Huang, and Hund-Der Yeh
Hydrol. Earth Syst. Sci., 22, 3951–3963, https://doi.org/10.5194/hess-22-3951-2018, https://doi.org/10.5194/hess-22-3951-2018, 2018
Short summary
Short summary
Existing analytical solutions associated with groundwater recharge are only applicable to the studies of saturated flow in aquifers. This paper develops an analytical solution for 3-D unsaturated–saturated flow due to localized recharge into an unconfined aquifer. The effects of unsaturated flow on the recharge process are analyzed. The present solution agrees well with a finite-difference solution. The solution’s predictions also match well with observed data obtained by a field experiment.
Chao-Chih Lin, Ya-Chi Chang, and Hund-Der Yeh
Hydrol. Earth Syst. Sci., 22, 2359–2375, https://doi.org/10.5194/hess-22-2359-2018, https://doi.org/10.5194/hess-22-2359-2018, 2018
Short summary
Short summary
An semanalytical model is developed for estimating the groundwater flow and stream depletion rates (SDR) from two streams in an L-shaped fluvial aquifer located at Gyeonggi-do, Korea. The predicted spatial and temporal hydraulic heads agree well with those of simulations and measurements. The model can be applied to evaluate the contribution of extracted water from storage and nearby streams.
Xiuyu Liang, Hongbin Zhan, You-Kuan Zhang, and Jin Liu
Hydrol. Earth Syst. Sci., 21, 1251–1262, https://doi.org/10.5194/hess-21-1251-2017, https://doi.org/10.5194/hess-21-1251-2017, 2017
Chia-Hao Chang, Ching-Sheng Huang, and Hund-Der Yeh
Hydrol. Earth Syst. Sci., 20, 1225–1239, https://doi.org/10.5194/hess-20-1225-2016, https://doi.org/10.5194/hess-20-1225-2016, 2016
Short summary
Short summary
Most previous solutions for groundwater flow due to localized recharge assumed either aquifer incompressibility or 2-D flow without vertical flow. This paper develops a 3-D flow model for hydraulic head change induced by the recharge with random transient rates in a compressible unconfined aquifer. The analytical solution of the model for the head is derived. The quantitative criteria for the validity of those two assumptions are presented by the developed solution.
A. J. Luhmann, M. D. Covington, J. M. Myre, M. Perne, S. W. Jones, E. C. Alexander Jr., and M. O. Saar
Hydrol. Earth Syst. Sci., 19, 137–157, https://doi.org/10.5194/hess-19-137-2015, https://doi.org/10.5194/hess-19-137-2015, 2015
Short summary
Short summary
Water temperature is a non-conservative tracer. Variations in recharge temperature are damped and retarded as water moves through an aquifer due to heat exchange between water and rock. This paper presents relationships that describe thermal damping and retardation in karst conduits determined using analytical solutions and numerical simulations, with some support provided by field data. These relationships may be used with field data to estimate unknown flow path geometry in karst aquifers.
N. Foged, P. A. Marker, A. V. Christansen, P. Bauer-Gottwein, F. Jørgensen, A.-S. Høyer, and E. Auken
Hydrol. Earth Syst. Sci., 18, 4349–4362, https://doi.org/10.5194/hess-18-4349-2014, https://doi.org/10.5194/hess-18-4349-2014, 2014
A. H. Alzraiee, D. Baú, and A. Elhaddad
Hydrol. Earth Syst. Sci., 18, 3207–3223, https://doi.org/10.5194/hess-18-3207-2014, https://doi.org/10.5194/hess-18-3207-2014, 2014
J. P. Bloomfield and B. P. Marchant
Hydrol. Earth Syst. Sci., 17, 4769–4787, https://doi.org/10.5194/hess-17-4769-2013, https://doi.org/10.5194/hess-17-4769-2013, 2013
C.-H. Chen, C.-H. Wang, S. Wen, T.-K. Yeh, C.-H. Lin, J.-Y. Liu, H.-Y. Yen, C. Lin, R.-J. Rau, and T.-W. Lin
Hydrol. Earth Syst. Sci., 17, 1693–1703, https://doi.org/10.5194/hess-17-1693-2013, https://doi.org/10.5194/hess-17-1693-2013, 2013
C.-T. Wang, H.-D. Yeh, and C.-S. Tsai
Hydrol. Earth Syst. Sci., 16, 441–449, https://doi.org/10.5194/hess-16-441-2012, https://doi.org/10.5194/hess-16-441-2012, 2012
Y.-C. Chang, H.-D. Yeh, K.-F. Liang, and M.-C. T. Kuo
Hydrol. Earth Syst. Sci., 15, 2165–2178, https://doi.org/10.5194/hess-15-2165-2011, https://doi.org/10.5194/hess-15-2165-2011, 2011
M.-H. Chuang, C.-S. Huang, G.-H. Li, and H.-D. Yeh
Hydrol. Earth Syst. Sci., 14, 1819–1826, https://doi.org/10.5194/hess-14-1819-2010, https://doi.org/10.5194/hess-14-1819-2010, 2010
S. Leschik, A. Musolff, R. Krieg, M. Martienssen, M. Bayer-Raich, F. Reinstorf, G. Strauch, and M. Schirmer
Hydrol. Earth Syst. Sci., 13, 1765–1774, https://doi.org/10.5194/hess-13-1765-2009, https://doi.org/10.5194/hess-13-1765-2009, 2009
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.
Ala, N. K. and Domenico, P. A.: Inverse analytical techniques applied to
coincident contaminant distributions at Otis Air Force Base, Massachusetts,
Groundwater, 30, 212–218, 1992.
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.
Aral, M. M., Guan, J., and Maslia, M. L.: Identification of contaminant source
location and release history in aquifers, J. Hydrol. Eng.,
6, 225–234, 2001.
Atmadja, J. and Bagtzoglou, A. C.: State of the art report on mathematical
methods for groundwater pollution source identification, Environ. Forensics, 2, 205–214, 2001.
Ayvaz, M. T.: A hybrid simulation–optimization approach for solving the areal
groundwater pollution source identification problems, J. Hydrol.,
538, 161–176, 2016.
Bayer, P., Huggenberger, P., Renard, P., and Comunian, A.: Three-dimensional
high resolution fluvio-glacial aquifer analog – Part 1: Field study,
J. Hydrol., 405, 1–9, 2011.
Bect, J., Bachoc, F., and Ginsbourger, D.: A supermartingale approach to
Gaussian process based sequential design of experiments, Bernoulli,
accepted, 2018.
Cornaton, F. J.: Ground water: a 3-D ground water and surface water flow,
mass transport and heat transfer finite element simulator, reference manual,
University of Neuchâtel, Neuchâtel, Switzerland, 2007.
Datta, B., Chakrabarty, D., and Dhar, A.: Identification of unknown groundwater
pollution sources using classical optimization with linked simulation,
J. Hydro-Environ. Res., 5, 25–36, 2011.
De Marsily, G.: Quantitative hydrogeology, Academic Press, Paris School of Mines, Fontainebleau, France,
1986.
Dupuy, D., Helbert, C., and Franco, J.: DiceDesign and DiceEval: Two R
Packages for Design and Analysis of Computer Experiments, J. Stat. Softw., 65, 1–38, 2015.
European Union: Good-quality water in Europe (EU Water Directive),
available at:
https://www.epa.gov/laws-regulations/summary-clean-water-act (last
access: 14 January 2019),
2000.
Ginsbourger, D.: Sequential Design of Computer Experiments, pp. 1–9, American
Cancer Society, https://doi.org/10.1002/9781118445112.stat08124, 2018.
Hansen, S. K. and Vesselinov, V. V.: Contaminant point source localization
error estimates as functions of data quantity and model quality, J. Contam. Hydrol., 193, 74–85, 2016.
Jones, D., Schonlau, M., and Welch, W.: Efficient Global optimization of
Expensive Black-Box Functions, J. Global Optim., 13, 455–492,
1998.
Jussel, P., Stauffer, F., and Dracos, T.: Transport modeling in heterogeneous
aquifers: 1. Statistical description and numerical generation of gravel
deposits, Water Resour. Res., 30, 1803–1817, 1994.
Koch, J. and Nowak, W.: Identification of contaminant source architectures-A
statistical inversion that emulates multiphase physics in a computationally
practicable manner, Water Resour. Res., 52, 1009–1025, 2016.
Mahar, P. S. and Datta, B.: Identification of pollution sources in transient
groundwater systems, Water Resour. Manag., 14, 209–227, 2000.
Mansuy, L., Philp, R. P., and Allen, J.: Source identification of oil spills
based on the isotopic composition of individual components in weathered oil
samples, Envir. Sci. Tech. Lib., 31, 3417–3425, 1997.
Marmin, S., Chevalier, C., and Ginsbourger, D.: Differentiating the multipoint
Expected Improvement for optimal batch design, in: Machine Learning,
optimization, and Big Data, edited by: Pardalos, P., Pavone, M., Farinella,
G., and Cutello, V., no. 9432 in Lecture Notes in Computer Science,
37–48, Springer International Publishing, 2015.
McKay, M. D., Beckman, R. J., and Conover, W. J.: A Comparison of Three Methods
for Selecting Values of Input Variables in the Analysis of Output from a
Computer Code, Technometrics, 21, 239–245, 1979.
Milnes, E. and Perrochet, P.: Simultaneous identification of a single pollution
point-source location and contamination time under known flow field
conditions, Adv. Water Resour., 30, 2439–2446, 2007.
Mirghani, B. Y., Zechman, E. M., Ranjithan, R. S., and Mahinthakumar, G.:
Enhanced simulation-optimization approach using surrogate modeling for
solving inverse problems, Environ. Forensics, 13, 348–363, 2012.
Mockus, J.: Bayesian Approach to Gobal optimization, vol. 37, Kluwer Academic
Pub, Springer, the Netherlands, 1989.
OECD: Guiding Principles Concerning International Economic Aspects of
Environmental Policies, Recommendation,
available at:
http://acts.oecd.org/Instruments/ShowInstrumentView.aspx?InstrumentID=4&InstrumentPID=255&Lang=en&Book=
(last access: 14 January 2019),
c(72)128, reprinted in 11 I.L.M. 1172, 1972.
Picheny, V. and Ginsbourger, D.: Noisy kriging-based optimization methods: a
unified implementation within the DiceOptim package, Comput. Stat. Data An., 71, 1035–1053, 2014.
Picheny, V., Wagner, T., and Ginsbourger, D.: A benchmark of kriging-based
infill criteria for noisy optimization, Struct. Multidiscip.
O., 48, 607–626, 2013.
Pirot, G.: gpirot/BGICLP v1.0, Benchmark Generator Inspired by Contaminant Localization
Problem, https://doi.org/10.5281/zenodo.2476286, 2018.
Pirot, G., Straubhaar, J., and Renard, P.: Simulation of braided river
elevation model time series with multiple-point statistics, Geomorphology,
214, 148–156, 2014.
Pirot, G., Straubhaar, J., and Renard, P.: A pseudo genetic model of coarse
braided-river deposits, Water Resour. Res., 51, 9595–9611, 2015.
Rachdawong, P. and Christensen, E. R.: Determination of PCB sources by a
principal component method with nonnegative constraints, Envir. Sci. Tech. Lib., 31, 2686–2691, 1997.
Ramsey, M. H. and Argyraki, A.: Estimation of measurement uncertainty from
field sampling: implications for the classification of contaminated land,
Sci. Total Environ., 198, 243–257, 1997.
Rasmussen, C. E. and Williams, C. K. I.: Gaussian Processes for Machine
Learning, MIT Press, Cambridge, Massachusetts,
2006.
Rios, L. M. and Sahinidis, N. V.: Derivative-free optimization: a review of
algorithms and comparison of software implementations, J. Global Optim., 56, 1247–1293, 2013.
Roustant, O., Ginsbourger, D., and Deville, Y.: Dicekriging, Diceoptim: Two R
packages for the analysis of computer experiments by kriging-based
metamodelling and optimization, J. Stat. Softw., 51, p. 54,
2012.
Shahriari, B., Swersky, K., Wang, Z., Adams, R., and de Freitas, N.: Taking the
human out of the loop: A review of bayesian optimization, P.
IEEE, 104, 148–175, 2016.
Skaggs, T. H. and Kabala, Z.: Recovering the history of a groundwater
contaminant plume: Method of quasi-reversibility, Water Resour. Res.,
31, 2669–2673, 1995.
Snoek, J., Swersky, K., Zemel, R., and Adams, R.: Input Warping for Bayesian
optimization of Non-stationary Functions, Proceedings of the 31 st International Conference on Machine Learning, Beijing,
China, 2014.
Straubhaar, J., Renard, P., and Mariethoz, G.: Conditioning multiple-point
statistics simulations to block data, Spat. Stat.-Neth., 16, 53–71, 2016.
Swiss Confederation: Federal Act on the Protection of the Environment,
available at:
https://www.admin.ch/opc/en/classified-compilation/19830267/index.html (last
access: 14 January 2019),
1983.
USA: Clean Water Act, available at:
https://www.epa.gov/laws-regulations/summary-clean-water-act (last
access: 14 January 2019),
1972.
Vazquez, E. and Bect, J.: Convergence properties of the expected improvement
algorithm with fixed mean and covariance functions, J. Stat. Plan. Infer., 140, 3088–3095, 2010.
Venkatramanan, S., Chung, S. Y., Kim, T. H., Kim, B.-W., and Selvam, S.:
Geostatistical techniques to evaluate groundwater contamination and its
sources in Miryang City, Korea, Environ. Earth Sci., 75, 1–14,
2016.
Wang, Z., Gehring, C., Kohli, P., and Jegelka, S.: Batched Large-scale
Bayesian optimization in High-dimensional Spaces, Proceedings of the 21st International Conference on Artificial Intelligence and Statistics
(AISTATS), Lanzarote, Spain, 2018.
Wu, J., Poloczek, M., Wilson, A., and Frazier, P.: Bayesian optimization with
Gradients, 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA,
2017.
Yeh, H.-D., Chang, T.-H., and Lin, Y.-C.: Groundwater contaminant source
identification by a hybrid heuristic approach, Water Resour. Res., 43,
W09420, https://doi.org/10.1029/2005WR004731, 2007.
Zhang, J., Li, W., Zeng, L., and Wu, L.: An adaptive Gaussian process-based
method for efficient Bayesian experimental design in groundwater contaminant
source identification problems, Water Resour. Res., 52, 5971–5984,
2016.
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.
To localize the source of a contaminant in the subsurface, based on concentration observations...