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Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

May 30, 2012

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.

Publication Year 2012
Title Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models
DOI 10.3133/tm7C5
Authors David E. Welter, John E. Doherty, Randall J. Hunt, Christopher T. Muffels, Matthew J. Tonkin, Willem A. Schreuder
Publication Type Report
Publication Subtype USGS Numbered Series
Series Title Techniques and Methods
Series Number 7-C5
Index ID tm7C5
Record Source USGS Publications Warehouse
USGS Organization Wisconsin Water Science Center