Management of aquifer recharge and discharge processes and aquifer
Risk assessment of salt contamination of groundwater under uncertain aquifer properties
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Goal: Model of groundwater contamination under uncertainties in porosity and permeability. Applications: Prediction of availability of pure water resources, ecology and environmental science Modeling of uncertainty: Build a generalized Polynomial Chaos Expansion with coefficients computed on sparse grids. Numerics: We run a highly-parallel multigrid solver, based on ug4, on Shaheen II. Parallelization in spatial and stochastic spaces. Methods and software: build-in MPI based parallelization, FV spatial discretization, implicit and explicit in time, Newton for non-linearity, Krylov and geometric/algebraic multigrids + ILU as a smoother. Two different scenarios of the salt/pollution propagation. Under gravity forces salt forms ‘finger’-shaped pattern. Risk assessment of salt contamina/on of groundwater under uncertain aquifer proper/es D. Keyes 1 , A. Litvinenko 2 , D. Logashenko 1 , R. Tempone 2 , G. WiEum 1 1 Extreme Computing Research Center, 2 Stochastic Numerics group, KAUST Model (density-driven flow): Darcy flow, @ t (φ⇢c)+ r · (⇢cq - ⇢Drc)=0 @ t (φ⇢)+ r · (⇢q)=0 x 2 ⌦ ⇢ R 3 is mass fraction of the salt, p pressure 200 scenarios are computed concurrently. Every scenario is computed on 32 cores and requires a mesh with ~8M points and 1500 time steps. Total number of cores is 200x32=6400. Future plans: high resolution 3D simulations. φ porosity, D permeability, density, is velocity. The mean and the variance of salt concentration where c ⇢ = ⇢(c) q = - K μ (rp - ⇢g )
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Transcript of Risk assessment of salt contamination of groundwater under uncertain aquifer properties
Goal: Model of groundwater contamination under uncertainties in porosity and permeability. Applications: Prediction of availability of pure water resources, ecology and environmental science Modeling of uncertainty: Build a generalized Polynomial Chaos Expansion with coefficients computed on sparse grids.
Numerics: We run a highly-parallel multigrid solver, based on ug4, on Shaheen II. Parallelization in spatial and stochastic spaces. Methods and software: build-in MPI based parallelization, FV spatial discretization, implicit and explicit in time, Newton for non-linearity, Krylov and geometric/algebraic multigrids + ILU as a smoother.
Two different scenarios of the salt/pollution propagation. Under gravity forces salt forms ‘finger’-shaped pattern.
Riskassessmentofsaltcontamina/onofgroundwaterunderuncertainaquiferproper/es
D.Keyes1,A.Litvinenko2,D.Logashenko1,R.Tempone2,G.WiEum1
1Extreme Computing Research Center, 2Stochastic Numerics group, KAUST
Model (density-driven flow): Darcy flow,
@t(�⇢c) +r · (⇢cq� ⇢Drc) = 0@t(�⇢) +r · (⇢q) = 0
�x 2 ⌦ ⇢ R3
is mass fraction of the salt, p pressure
200 scenarios are computed concurrently. Every scenario is computed on 32 cores and requires a mesh with ~8M points and 1500 time steps. Total number of cores is 200x32=6400. Future plans: high resolution 3D simulations.
� porosity, D permeability,
density, is velocity.
The mean and the variance of salt concentration
where c⇢ = ⇢(c) q = �K
µ (rp� ⇢g)
