Evaluating the AgMIP calibration protocol for crop models, case study and new diagnostic tests

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00636670" target="_blank" >RIV/86652079:_____/25:00636670 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1161030125001558" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1161030125001558</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eja.2025.127659" target="_blank" >10.1016/j.eja.2025.127659</a>

Result language

angličtina

Original language name

Evaluating the AgMIP calibration protocol for crop models, case study and new diagnostic tests

Original language description

Crop simulation models are important tools in agronomy. Typically, they need to be calibrated before being used for new environments or cultivars. However, there is a large variability in calibration approaches, which contributes to uncertainty in simulated values, so it is important to develop improved calibration procedures that are widely applicable. The AgMIP calibration group recently proposed a comprehensive, generic calibration protocol that is directly based on standard statistical parameter estimation in regression models. Weighted least squares (WLS) is used to handle multiple response variables and forward regression using the corrected Akaike Information Criterion (AICc) is used to select the parameters to be calibrated. The protocol includes two adaptations, which are specific to each model and data set. First, initial approximations to the WLS parameters are obtained by fitting variables one group at a time. Secondly, major parameters are identified that are intended to reduce bias, analogously to the constant in linear regression. In this study, new diagnostic tools to be included in the protocol are proposed and tested in a case study. The diagnostics test whether the protocol does indeed lead to good initial approximations to the WLS parameters, and whether the protocol does indeed substantially reduce bias. These diagnostics provide in-depth understanding of the calibration process, reveal problems and help suggest solutions. The diagnostics should increase confidence in the results of the protocol. Having a reliable, generic calibration approach, like the augmented AgMIP protocol, is essential to using crop models more effectively.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

40101 - Agriculture

Project

<a href="/en/project/EH22_008%2F0004635" target="_blank" >EH22_008/0004635: AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

European Journal of Agronomy

ISSN

1161-0301

e-ISSN

1873-7331

Volume of the periodical

168

Issue of the periodical within the volume

JUL

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

12

Pages from-to

127659

UT code for WoS article

001487379200001

EID of the result in the Scopus database

2-s2.0-105004189843