Utility Support Software

PEST is accompanied by a suite of utility programs that make PEST, PEST_HP and PEST++ easier to use, and that provide important insights into the history-matching and uncertainty analysis processes.

Utility Families

When you download PEST, you also download about 190 supplementary programs which can be used with PEST. These are referred to as “PEST utilities”. Some of the tasks that these programs perform are listed below.

However these are not the only programs that you can download from these pages to enhance, expedite and facilitate the use of PEST. A comprehensive suite of programs supports the use of PEST/PEST_HP/PEST++ specifically in groundwater model parameterization and history-matching. These are discussed on other pages. They include:

  • The PEST Groundwater Utilities Suite;
  • PLPROC (a parameter list processor);
  • OLPROC (an observation list processor); and
  • TS6PROC (a time series processor for MODFLOW 6).

In similar fashion, the PEST surface water utilities expedite the use of PEST in calibrating surface water and land use models.

PEST Utilities

The utility suite supplied with PEST and PEST_HP can be subdivided into two broad groups, namely those that undertake linear analysis of one kind or another, and those that do not. Linear analysis is so important that it has its own page. Tasks performed by utilities that do not perform linear analysis include the following:

  • Comprehensive checking of full or partial PEST datasets for correctness and consistency;
  • Automatic construction of partial PEST datasets;
  • Automatic addition of Tikhonov regularization to a PEST input dataset;
  • Balancing of observation weights;
  • Parameter pre-processing and observation post-processing as part of a PEST-managed model run;
  • Manipulation and management of Jacobian matrix files and parts thereof;
  • Setup for SVD-assisted parameter estimation;
  • Setup for ensemble space inversion (ENSI);
  • Generation of random parameter sets;
  • Latin Hypercube parameter sampling;
  • Matrix operations and manipulation;
  • Collation and tabulation of parallelized model runs undertaken with arbitrary sets of parameters;
  • Pre-processing and post-processing for PESTPP-IES (the PEST++ ensemble smoother);
  • Adding and subtracting rows/columns to/from CSV files;
  • Data space inversion (a form of posterior predictive uncertainty analysis that does not require parameter adjustment).
History Matching Uncertainty Analysis