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  • Tonkin, Mathew
    This is a preliminary announcement for an upcoming course Apologies for any double postings Best wishes for the New Year Matt Tonkin, SSP&A _____ Model
    Message 1 of 1 , Jan 3, 2003
      This is a preliminary announcement for an upcoming course
      Apologies for any double postings
      Best wishes for the New Year
      Matt Tonkin, SSP&A

      Model Calibration and Predictive Uncertainty Analysis using PEST
      San Francisco, April 2003
      This is a preliminary announcement for an upcoming PEST course in San
      Francisco, April 2003. This course represents a combined effort between
      Watermark Numerical Computing (AKA Dr. John Doherty), ESI
      <http://www.groundwatermodels.com/> , SSP&A
      <http://www.sspa.com/news/index.html> , and a number of not-for-profit
      environmental organizations based on the West Coast of the USA. Details
      of this course have not been finalized, but will be forwarded in the
      next seven days.
      This short course will focus upon the use of PEST, the most advanced
      available technology for groundwater water, surface water, and all other
      environmental model calibrations. Using PEST you can apply
      state-of-the-art calibration and predictive uncertainty analysis methods
      in your every day modelling applications. Using PEST you can:
      * Apply advanced regularisation techniques for improved
      numerical stability;
      * Undertake nonlinear predictive uncertainty analysis of key
      model outputs;
      * Simultaneously parameterise one or a number of models on the
      basis of multiple datasets including heads, flows and contaminant
      * Accommodate geological heterogeneity using advanced spatial
      parameterization methods;
      * Combine PEST with the use of stochastic field generation to
      explore model parameter uncertainty in heterogeneous systems;
      * Parallelize model runs across PC or UNIX networks;
      * Convert a MODFLOW-2000 parameter estimation dataset to a PEST
      dataset by typing a simple command.
      Perhaps the most exiting advance in parameter estimation technology over
      the last few years is the combination of PEST's advanced regularisation
      functionality with the use of pilot points as a spatial parameterisation
      device. When employed in regularised parameter estimation, you can use
      more pilot points than ever before while maintaining unconditional
      numerical stability. This allows vastly improved model parameterisation
      in complex geological environments where representation of true or
      potential heterogeneity may be important, either for accurate model
      predictions, of for allowing the uncertainty of predictions to be fully
      explored. When used in conjunction with stochastic field generation to
      produce a set of calibration-constrained parameter fields, you will have
      the ability to use models in more powerful and informative ways than has
      been possible up until now.
      The course will provide a attendees with a foundation for parameter
      estimation theory and PEST's implementation of the theory, followed by
      demonstrations and computer lab exercises from a variety of
      environmental disciplines, principally focussed on groundwater modeling
      Additional Day for Surface Water Modeling Applications
      Contingent upon the level of interest from the surface water modeling
      community, an additional fourth day of PEST may be added, devoted to
      detailed discussion and demonstration of the use of PEST in the surface
      water modeling context. Dr. Doherty has given several classes in the
      application of PEST with HSPF, and PEST is gaining wide acceptance for
      parameterization of complex surface water models.

      Principal Instructor: Dr. John Doherty - author of PEST

      Location: San Francisco, CA, April 2003 (dates to be finalized)

      For more information about the PEST course, or to receive updated
      details directly when they are finalized, please contact PEST@...

      [Non-text portions of this message have been removed]
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