The chaos in calibrating crop models
Abstract
Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in essentially every application of crop models and process models in other fields and has an important impact on simulated values. The goal of this study is to develop a comprehensive list of the decisions involved in calibration and to identify the range of choices made in practice, as groundwork for developing guidelines for crop model calibration starting with phenology. Three groups of decisions are identified; the criterion for choosing the parameter values, the choice of parameters to estimate and numerical aspects of parameter estimation. It is found that in practice there is a large diversity of choices for every decision, even among modeling groups using the same model structure. These findings are relevant to process models in other fields.
Highlights
We documented calibration procedures in two multi-model studies
Groups differ in criteria for best parameters, parameters to estimate and software
There are important differences even between groups using the same model structure
Competing Interest Statement
The authors have declared no competing interest.
Subject Area
- Biochemistry (11752)
- Bioengineering (8752)
- Bioinformatics (29200)
- Biophysics (14974)
- Cancer Biology (12096)
- Cell Biology (17411)
- Clinical Trials (138)
- Developmental Biology (9421)
- Ecology (14182)
- Epidemiology (2067)
- Evolutionary Biology (18308)
- Genetics (12245)
- Genomics (16803)
- Immunology (11869)
- Microbiology (28097)
- Molecular Biology (11594)
- Neuroscience (60969)
- Paleontology (451)
- Pathology (1871)
- Pharmacology and Toxicology (3238)
- Physiology (4959)
- Plant Biology (10427)
- Synthetic Biology (2886)
- Systems Biology (7340)
- Zoology (1651)