PEST: Model-Independent Parameter Estimation and Uncertainty Analysis
PEST, the software package, automates calibration, and calibration-constrained uncertainty analysis of any numerical model. It interacts with a model through the model’s own input and output files. While estimating or adjusting its parameters, it runs a model many times. These model runs can be conducted either in serial or in parallel. PEST records what it does in easily-understood output files.
PEST, the software suite, performs a plethora of tasks that assist and complement model parameter estimation and uncertainty analysis. These include:
- setup facilitation;
- flexible spatial parameterization;
- objective function definition;
- linear prior and posterior uncertainty analysis;
- nonlinear prior and posterior uncertainty analysis.
Parameter estimation and uncertainty analysis are key to effective environmental management. A GMDSI monograph discusses metrics for decision-support groundwater modelling, and how these metrics are best pursued through appropriate design of the modelling process. It focusses particularly on the thorny issue of model complexity.
Many thanks to ESI and SSPA for funding these pages.
Latest change: April 28, 2023 - structural overlay parameters in PLPROC; improved data space inversion in PEST.