Risk assessment of salt contamination of groundwater under uncertain aquifer properties

Handle URI:
http://hdl.handle.net/10754/626068
Title:
Risk assessment of salt contamination of groundwater under uncertain aquifer properties
Authors:
Litvinenko, Alexander ( 0000-0001-5427-3598 ) ; Keyes, David E. ( 0000-0002-4052-7224 ) ; Logashenko, Dmitry; Tempone, Raul ( 0000-0003-1967-4446 ) ; Wittum, Gabriel
Abstract:
One of the central topics in hydrogeology and environmental science is the investigation of salinity-driven groundwater flow in heterogeneous porous media. Our goals are to model and to predict pollution of water resources. We simulate a density driven groundwater flow with uncertain porosity and permeability. This strongly non-linear model describes the unstable transport of salt water with building ‘fingers’-shaped patterns. The computation requires a very fine unstructured mesh and, therefore, high computational resources. We run the highly-parallel multigrid solver, based on ug4, on supercomputer Shaheen II. A MPI-based parallelization is done in the geometrical as well as in the stochastic spaces. Every scenario is computed on 32 cores and requires a mesh with ~8M grid points and 1500 or more time steps. 200 scenarios are computed concurrently. The total number of cores in parallel computation is 200x32=6400. The main goal of this work is to estimate propagation of uncertainties through the model, to investigate sensitivity of the solution to the input uncertain parameters. Additionally, we demonstrate how the multigrid ug4-based solver can be applied as a black-box in the uncertainty quantification framework.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Conference/Event name:
KAUST-NSF Conference on Environmental Monitoring
Issue Date:
1-Oct-2017
Type:
Poster
Sponsors:
KAUST
Additional Links:
https://eeevents.kaust.edu.sa/nsfem2017/home
Appears in Collections:
Posters

Full metadata record

DC FieldValue Language
dc.contributor.authorLitvinenko, Alexanderen
dc.contributor.authorKeyes, David E.en
dc.contributor.authorLogashenko, Dmitryen
dc.contributor.authorTempone, Raulen
dc.contributor.authorWittum, Gabrielen
dc.date.accessioned2017-10-31T11:33:49Z-
dc.date.available2017-10-31T11:33:49Z-
dc.date.issued2017-10-01-
dc.identifier.urihttp://hdl.handle.net/10754/626068-
dc.description.abstractOne of the central topics in hydrogeology and environmental science is the investigation of salinity-driven groundwater flow in heterogeneous porous media. Our goals are to model and to predict pollution of water resources. We simulate a density driven groundwater flow with uncertain porosity and permeability. This strongly non-linear model describes the unstable transport of salt water with building ‘fingers’-shaped patterns. The computation requires a very fine unstructured mesh and, therefore, high computational resources. We run the highly-parallel multigrid solver, based on ug4, on supercomputer Shaheen II. A MPI-based parallelization is done in the geometrical as well as in the stochastic spaces. Every scenario is computed on 32 cores and requires a mesh with ~8M grid points and 1500 or more time steps. 200 scenarios are computed concurrently. The total number of cores in parallel computation is 200x32=6400. The main goal of this work is to estimate propagation of uncertainties through the model, to investigate sensitivity of the solution to the input uncertain parameters. Additionally, we demonstrate how the multigrid ug4-based solver can be applied as a black-box in the uncertainty quantification framework.en
dc.description.sponsorshipKAUSTen
dc.relation.urlhttps://eeevents.kaust.edu.sa/nsfem2017/homeen
dc.subjectunstructured grid UG4en
dc.subjectUncertainty Quantificationen
dc.subjectcontaminationen
dc.subjectgraundwater flowen
dc.subjectparallel computingen
dc.subjectgeneralized PCEen
dc.titleRisk assessment of salt contamination of groundwater under uncertain aquifer propertiesen
dc.typePosteren
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.conference.date6-8 November, 2017en
dc.conference.nameKAUST-NSF Conference on Environmental Monitoringen
dc.conference.locationKing Abdullah University of Science and Technologyen
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