Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models
Techniques and Methods
7-C5
Great Lakes Restoration Initiative: Computation Water Resource Engineering, Flinders University and Watermark Numerical Computing, S.S. Papadopulos and Associates, Inc., Principia Mathematica, Inc.
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Abstract
An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.
Suggested Citation
Welter, D.E., Doherty, J.E., Hunt, R.J., Muffels, C.T., Tonkin, M.J., and Schreuder, W.A., 2012, Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models: U.S. Geological Survey Techniques and Methods 7-C5, iii, 9 p.; Appendices; Software Download, https://doi.org/10.3133/tm7C5.
ISSN: 2328-7055 (online)
| Publication type | Report |
|---|---|
| Publication Subtype | USGS Numbered Series |
| Title | Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models |
| Series title | Techniques and Methods |
| Series number | 7-C5 |
| DOI | 10.3133/tm7C5 |
| Year Published | 2012 |
| Language | English |
| Publisher | U.S. Geological Survey |
| Publisher location | Reston, VA |
| Contributing office(s) | Wisconsin Water Science Center |
| Description | iii, 9 p.; Appendices; Software Download |
| Online Only (Y/N) | Y |