H41B:
Concepts and Practice of Model Verification, Validation, and Uncertainty Quantification in Computational Geosciences I Posters


Session ID#: 8549

Session Description:
Model inadequacy and uncertainty poses many challenges for prediction and decision-making in subsurface problems (groundwater contamination, carbon storage, nuclear waste storage, geothermal and petroleum energy production). Often these problems require forecasting based on numerical models. This session encompasses data and model analyses and their relation to efficient model and parameter space exploration for forecasting, uncertainty reduction, and risk assessment. We encourage presentations on data assimilation and inversion, uncertainty in parameter identification, uncertainty propagation through deterministic or probabilistic models, or strategies for efficient data collection to reduce model uncertainty. Verification and validation of theoretical advances as well experimental results are encouraged.
Primary Convener:  Souheil M Ezzedine, Lawrence Livermore National Laboratory, Livermore, CA, United States
Conveners:  Kaveh Zamani, University of California Davis, Davis, CA, United States, Daniel M Tartakovsky, Stanford University, Department of Energy Resources Engineering, Stanford, CA, United States and Dr. Velimir monty V Vesselinov, Los Alamos National Laboratory, Los Alamos, United States
Chairs:  Daniel M Tartakovsky, Stanford University, Department of Energy Resources Engineering, Stanford, CA, United States, Souheil M Ezzedine, Lawrence Livermore National Laboratory, Livermore, CA, United States, Dr. Velimir monty V Vesselinov, Los Alamos National Laboratory, Los Alamos, NM, United States and Kaveh Zamani, University of California Davis, Davis, CA, United States
OSPA Liaison:  Souheil M Ezzedine, Lawrence Livermore National Laboratory, Livermore, CA, United States

Cross-Listed:
  • A - Atmospheric Sciences
Index Terms:

0550 Model verification and validation [COMPUTATIONAL GEOPHYSICS]
1805 Computational hydrology [HYDROLOGY]
1846 Model calibration [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]

Abstracts Submitted to this Session:

An efficient distribution method for nonlinear transport problems in stochastic porous media (58854)
Fayadhoi Ibrahima, Stanford University, Stanford, CA, United States, Hamdi Tchelepi, Stanford University, Energy Science and Engineering, Stanford, United States and Daniel W Meyer, ETH Swiss Federal Institute of Technology Zurich, Institute of Fluid Dynamics, Zurich, Switzerland
A Bayesian approach to model structural error and input variability in groundwater modeling (70014)
Tianfang Xu, Michigan State University, Department of Earth and Environmental Sciences, East Lansing, United States, Albert J Valocchi, University of Illinois at Urbana-Champaign, Department of Civil and Environmental Engineering, Urbana, United States, Dr. Yu-Feng Forrest Lin, PhD, Illinois State Geological Survey, Champaign, United States and Feng Liang, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, IL, China
Uncertainty Quantification of Tracer Dispersion with the PMVP Model under Realistic Conditions (60322)
Simon Duenser and Daniel W Meyer, ETH Swiss Federal Institute of Technology Zurich, Institute of Fluid Dynamics, Zurich, Switzerland
Impact of Temporally Variable and Uniform Pumping Regimes on Contaminant Transport in Heterogeneous Aquifers (71434)
Arianna Libera, University of Southern California, Los Angeles, CA, United States, Felipe de Barros, University of Southern California, Sonny Astani Department of Civil and Environmental Engineering, Los Angeles, United States and Alberto Guadagnini, Politecnico di Milano, Milano, 20133, Italy
Volcanic Event Recurrence Rate Model (VERRM): Incorporating Radiometric Ages, Volcanic Stratigraphy and Paleomagnetic Data into a Monte Carlo Simulation to Estimate Uncertainty in Recurrence Rate through Time (79482)
James Adams Wilson and Jacob A Richardson, University of South Florida Tampa, Tampa, FL, United States
Global Sensitivity Analysis for Multiple Scenarios and Models of Nitrogen Processes (86168)
Zhuowei Chen1, Liangsheng Shi1 and Ming Ye2, (1)Wuhan University, Wuhan, China, (2)Florida State University, Earth, Ocean, and Atmospheric Science, Tallahassee, United States
Model validation for karst flow using sandbox experiments (67470)
Roger Benito Pacheco Castro, National Autonomous University of Mexico, Laboratory of Engineering and Coastal Processes, Sisal, YC, Mexico, Xiaohu Tao, Hohai University, College of Water Conservancy and Hydropower Engineering, Nanjing, China, Ming Ye, Florida State University, Earth, Ocean, and Atmospheric Science, Tallahassee, United States and Jian Zhao, Guangdong Ocean University, Zhanjiang, China
Stochastic collocation using Kronrod-Patterson-Hermite quadrature with moderate delay for subsurface flow and transport (71008)
Qinzhuo Liao, Stanford University, Stanford, CA, United States, Hamdi Tchelepi, Stanford University, Energy Science and Engineering, Stanford, United States and Dongxiao Zhang, Peking University, Department of Energy and Resources Engineering, Beijing, China
Improving Uncertainty Quantification Through Better Bayesian Inference (72676)
Ashish Sharma, University of New South Wales, Sydney, NSW, Australia, Tyler J Smith, Clarkson University, Department of Civil & Environmental Engineering, Potsdam, NY, United States and Lucy Amanda Marshall, University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia
Robust Bayesian Experimental Design for Conceptual Model Discrimination (73286)
Hai V Pham and Frank T-C Tsai, Louisiana State University, Department of Civil and Environmental Engineering, Baton Rouge, LA, United States
A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion (73343)
Youzuo Lin, Los Alamos National Laboratory, Los Alamos, United States, Daniel O'Malley, Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, United States and Dr. Velimir monty V Vesselinov, Los Alamos National Laboratory, Los Alamos, NM, United States
Training image analysis for model error assessment and dimension reduction in Bayesian-MCMC solutions to inverse problems (77778)
Corinna Koepke, University of Lausanne, Lausanne, Switzerland and James Irving, University of Lausanne, Institute of Earth Sciences, Lausanne, Switzerland
Using Multi-level Methods for Geospatial Data Representation to Enable Efficient Analytics of Large Scale Simulation Outputs (79554)
Abani K Patra1, Ramona Elena Stefanescu1 and Prashant Shekhar2, (1)University at Buffalo, Buffalo, United States, (2)University at Buffalo, Buffalo, NY, United States
VAVUQ, Python and Matlab freeware for Verification and Validation, Uncertainty Quantification (85212)
Kaveh Zamani1, Fabian A Bombardelli1, William E Fleenor1 and James Edward Courtney2, (1)University of California Davis, Davis, CA, United States, (2)Humboldt State University, Arcata, CA, United States

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