Dr. Ming Ye

Associate Professor

Department of Scientific Computing
Florida State University

PhD, University of Arizona

Office: 489 Dirac Science Library
Phone: (850) 644-4587
Fax: (850) 644-0098
Email: mye@fsu.edu

Project Title:
Mult-Scale Assessment of Prediction Uncertainty in Coupled Reactive Transport Models

Sponsored by the DOE Subsurface Biogeochemical Research Program (SBR)

Collaborators:

Graduate Student: Dan Lu and Geo Miller

Post-doc: Xiaoqing Shi

Project Abstract:

Numerical simulation of reactive transport provides an important framework for the integration of hydrologic and biogeochemical conceptual process models into a quantitative description of subsurface behaviors. The ultimate goal for the development of these modeling analyses, however, is to assess risk and remediation performance for waste management decision-making. This will require an additional and commensurate effort to characterize and quantify uncertainty in the model predictions and assessments. Experience in groundwater hydrology has demonstrated the total uncertainty of a model simulation consists of both the the uncertainty of the the parameters and the uncertainty in the conceptual model with represents the scientific understanding of a particular hydrogeologic environment. Moreover, it has been demonstrated the conceptual uncertainty of groundwater flow modeling dominates the total simulation uncertainty. This project will assess the parametric and conceptual model uncertainty of hexavalent U(VI) transport at both the Naturita UMTRA site and the Rifle FRC. The parameter and conceptual model uncertainty will be evaluated using a maximum likelihood formulation of Bayseian model averging. The focus of the work at the Naturita site will be to investigate how conceptual model uncertainty varies across scales ranging from column tests to the plume scale. These will results will provide a fundamental understanding of the uncertainty associated with upscaling models from laboratory conditions to a field setting. The work at the Rifle site evaluate the parameter and conceptual model uncertainty for the stimulated bioreduction of U(VI) by microbial processes. The uncertainty analyses will also be extended to evaluate the value of new data in reducing prediction uncertainty. Together, the research at these two sites will provide complementary results which together can provide DOE with a quantitative understanding of how various scales and processes impacted simulation uncertainty.

Project Activities:

  • September 21 - 23, 2011: Dan attended SAMSI 2011-12 Workshop of Uncertainty Quantification Program: Geosciences Applications Opening Workshop.
  • September 4, 2011: Ming Ye gave an oral presentation entitled "Identifying Multimodal, Non-Gaussian Parameter Distributions in Groundwater Reactive Transport Modeling" on the conference of Cross-Pacific Conference on Environmental and Water Resources. Download Presentation Slides
  • June 6, 2011: Dan Lu gave an oral presentation entitled "Analysis of Regression and Bayesian Predictive Uncertainty Measure" at the MODFLOW and More 2011 Conferencethe based on her work with Dr. Mary Hill at USGS Boulder.
  • August 25-31, 2011: Ming Ye and Xiaoqing Shi visited the Oak Ridge National Laboratory (ORNL). Xiaoqing Shi worked in ORNL until October, 2011.
  • December 16, 2010: Geoffery Miller gave an oral presentation entitled "Assessment of Parametric Uncertainty using Markov Chain Monte Carlo Methods for Surface Complexation Models in Groundwater Reactive Transport Modeling" at the 2010 AGU meeting on his research of parametric uncertainty analysis of uranium transport in columns. Conference Abstract Download Presentation Slides
  • December 16, 2010: Dan Lu gave an oral presentation entitled "A Controlled Experiment for Investigating Uncertainty Measures in Groundwater Flow Modeling" at the 2010 AGU meeting on her research of uncertainty measure of multiple models. Conference abstract Download Presentation Slides
  • November 19, 2010: Submitted with Dr. Shlomo Neuman a manuscript entitled "Bayesian Analysis of Data-Worth Considering Model and Parameter Uncertainties" to Advanced in Water Resources.
  • June 15, 2010: Dr. Ming Ye presented at the 2010 Goldschmidt Conference the research on uncertainty assessment of groundwater reactive transport modeling. Presentation Slides

Conference Abstracts:

  • Ye, M., X. Shi, and G.P. Curtis (2011), Identifying Multimodal, Non-Gaussian Parameter Distributions in Groundwater Reactive Transport Modeling, Cross-Pacific Conference on Environmental and Water Resources, September 3 - 5, Orlando, FL.
  • Ye, M., D. Lu, G.P. Curtis, P.D. Meyer, and S. Yabusaki (2010), Effect of Temporal Residual Correlation on Estimation of Model Averaging Weights, AGU Fall Meeting, December 13-17, San Francisco, California.
  • Lu, D. (student), M.C. Hill, and M. Ye (2010), A Controlled Experiment for Investigating Uncertainty Measures in Groundwater Flow Modeling, AGU Fall Meeting, December 13-17, San Francisco, California.
  • Miller, G.L. (student), D. Lu, M. Ye, G.P. Curtis, B.S. Mendes, D. Draper (2010), Assessment of Parametric Uncertainty using Markov Chain Monte Carlo Methods for Surface Complexation Models in Groundwater Reactive Transport Modeling, AGU Fall Meeting, December 13-17, San Francisco, California.
  • Curtis, G.P., M. Ye, M. Kohler, P.M. Fox, and J.A. Davis (2010), Evaluating Prediction Uncertainty of Uranium Transport in Small Scale Tracer Tests, AGU Fall Meeting, December 13-17, San Francisco, California.
  • Neuman, S.P., M. Ye, L. Xue, and D. Lu (2010), Multimodel Bayesian Analysis of the Worth of Data, AGU Fall Meeting, December 13-17, San Francisco, California.
  • Ye, M. and D. Lu (2009), On model selection criteria and model complexity, Annual Meeting of the American Geophysical Unior, Dec. 14-18, San Francisco, CA.

Conference Proceedings:

  • Ye, M., D. Lu, S.P. Neuman, L. Xue (2011), Multimodel bayesian analysi\ s of data-worth applied to unsaturated fractured tuffs, International Conference on Groundwater: Our Source of Security in an Uncertain Future, September 19 - 21, 2011, Pretoria\ , South Africa.
  • Lu, D. (student), M.C. Hill, and M. Ye (2011), Analysis of regression and Bayesian predictive uncertainty measure, MODFLOW and More 2011Conference, June 5 - 8, 2011, Golden, CO.
  • Neuman, S.P., L. Xue, M. Ye, and D. Lu (2011), Multimodel Assessment of the Worth of Data Under Uncertainty, Waste Management Symposium, February 28 - March 3, 2011, Phoenix, Arizona.

Peer-Reviewed Journal Articles:

  • Lu, D. (student), M. Ye, S.P. Neuman, and L. Xue (2011), Multimodel Bayesian analysis of data-worth applied to unsaturated fractured tuffs, Advances in Water Resources, Submitted.
  • Dai, Z., A. Wolfsberg, P. Reimus, H. Deng, E. Kwicklis, M. Ding, D. Ware, and M. Ye (2011), Identification of sorption processes and parameter for radionuclide transport in fractured rock, Journal of Hydrology, Submitted.
  • Lu, D. (student), M.C. Hill, and M. Ye (2011), Analysis of regression confidence interval and Bayesian credible interval, Water Resources Research, Submitted.
  • Lu, D. (student), M. Ye, and S.P. Neuman (2010), Dependence of Bayesian model selection criteria and Fisher information matrix on sample size, Mathematical Geosciences, Accepted.
  • Neuman, S.P., L. Xue, M. Ye, and D. Lu (2011), Bayesian analysis of data-worth considering model and parameter uncertainties, Advances in Water Resources, doi:10.1016/j.advwatres.2011.02.007.
  • Ye, M. (2009), MMA: A computer code for multi-model analysis, Ground Water, doi: 10.1111/i.1745-6584.2009.00647.x.
  • Ye, M., D. Lu, S.P. Neuman, and P.D. Meyer (2010), Comment on "Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window" by Frank T.-C. Tsai and Xiaobao Li, Water Resour. Res., 46, W02801, doi:10.1029/2009WR008501.