Workshop Summary

The Groundwater Resources Association (GRA) is conducting a three-day workshop "Model Calibration and Predictive Uncertainty Analysis Using PEST" on September 27-29, 2004. GRA is pleased to announce that the principal instructor for the workshop is Dr. John Doherty, author of PEST and Principal of Watermark Numerical Computing; he will be assisted by Matt Tonkin of SS Papadopulos & Associates, Inc. The workshop will provide attendees with a foundation for parameter estimation theory, an understanding of how the PEST code was developed to apply parameter estimation theory, and will incorporate extensive demonstrations and "hands-on" computer lab exercises from a variety of environmental disciplines, including applications of PEST to groundwater/surface water modeling.

Optional Additional Day -- Individual Modeling Studies

Contingent upon the level of interest, an additional fourth day of PEST will be added, devoted to detailed discussion and demonstration of the use of PEST with attendees particular projects.

About PEST

Parameter Estimation (PEST) is a general-purpose parameter estimation utility developed by John Doherty of Watermark Computing. The course will focus upon the use of PEST, the most advanced available technology for groundwater, surface water, and all other environmental model calibrations. Using PEST you can apply state-of-the-art calibration and predictive uncertainty analysis methods on your everyday modeling applications. Using PEST you can:

• Apply advanced regularization techniques for improved numerical stability;
• Undertake nonlinear predictive uncertainty analysis of key model outputs;
• Simultaneously parameterize a number of models using multiple datasets;
• Accommodate geological heterogeneity using advanced spatial parameterization;
• Combine PEST with the use of stochastic field generation to explore model parameter uncertainty in heterogeneous systems;
• Conduct parallel model optimization runs across PC or UNIX networks;
• Convert a MODFLOW-2000 parameter estimation dataset to a PEST dataset by typing a simple command.

Some of the advances in parameter estimation over the last few years as encapsulated in PEST, that support the use of models in powerful and informative ways, include:

1. The combination of regularization with the use of pilot points as a spatial parameterization device. When employed in regularized parameter estimation, the modeler can use more pilot points than ever before while maintaining unconditional numerical stability.
2. The combination of regularized pilot points with stochastic field generation to produce calibration-constrained parameter fields.
3. The combination of these advanced regularization schemes with subspace approaches in order to rapidly investigate highly parameterized models without the necessity of adopting a-priori parsimony that undermines model flexibility.

These developments together provide for improved model parameterization in complex geological environments where the representation of true (or potential) heterogeneity may be important, either for accurate model predictions, or for allowing the uncertainty of predictions to be fully explored.

The course will provide attendees with a foundation for parameter estimation theory and implementation of PEST, followed by demonstrations and computer lab exercises from a variety of environmental disciplines, including applications of PEST to groundwater/surface water modeling.

Course Attendee Information

Practitioners from a wide range of experience will benefit from this course, whether new to PEST, or with previous PEST experience. To get the most out of the course, attendees should have some modeling experience, preferably in the groundwater or surface water disciplines. However, hands-on labs are GUI-independent, and cover a variety of modeling disciplines, so that anyone interested in model calibration, parameter optimization, or the analysis of numerical model uncertainty could attend.

Program Agenda - Complete Course Description & Agenda >>

Course Location

Best Western Americania Hotel
121 Seventh Street, San Francisco, 94103
Tel: (415) 626-0200 - (800) 444-5816
(One block from Civic Center BART station)

Accommodation: $99
(please indicate “PEST Course Attendee” to obtain block rate)

Free parking for hotel guests (other nearby parking $6 to $10 per day). Catered breakfast and lunch are included in the course fee.

Registration Fees (prices assume laptop provided by attendee)

$1000 GRA member, $1175 Private / non-member, $1065 Registration plus GRA Membership, $750 Full time student or state employee.

Register For This Event >>

Additional Information

Go to http://www.sspa.com/pest for more information on PEST, together with the latest version available for download. Contact Mathew Tonkin at pest@sspa.com for information about the course content. For all other information, contact Mary Megarry at mmegarry@nossaman.com or 916-446-3626.