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Assessing errors during simulation configuration in crop models - A global case study using APSIM-Potato


Ojeda, JJ and Huth, N and Holzworth, D and Raymundo, R and Zyskowski, RF and Sinton, SM and Michel, AJ and Brown, HE, Assessing errors during simulation configuration in crop models - A global case study using APSIM-Potato, Ecological Modelling, 458 Article 109703. ISSN 0304-3800 (2021) [Refereed Article]

Copyright Statement

2021 Elsevier B.V. All rights reserved

DOI: doi:10.1016/j.ecolmodel.2021.109703


Crop models are usually developed using a test set of data and simulations representing a range of environment, soil, management and genotype combinations. Previous studies demonstrated that errors in the configuration of test simulations and aggregation of observed data sets are common and can cause major problems for model development. However, the extent and effect of such errors using Agricultural Production system SIMulator Next Generation (APSIM) crop models are not usually considered as a source of model uncertainty. This is a methodological paper describing several approaches for testing the APSIM simulation configuration to detect anomalies in the input and observed data. In this study, we assess the simulation configuration process through (i) quality control analysis based on a standardised climate dataset (ii) outlier identification and (iii) a palette of visualization tools. A crop model - APSIM-Potato is described to demonstrate the main sources of error during the simulation configuration and data collation processes. Input data from 426 experiments conducted from 1970 to 2019 in 19 countries were collected and configured to run a model simulation. Plots were made comparing simulation configuration data and observed data across the entire test set so these values could be checked relative to others in the test set and with independent datasets. Errors were found in all steps of the simulation configuration process (climate, soil, crop management and observed data). We identified a surprising number of errors and inappropriate assumptions that had been made which could influence model predictions. The approach presented here moved the bulk of the effort from fitting 1000 model processes to setting up broad simulation configuration testing and detailed interrogation to identify current gaps for further model development.

Item Details

Item Type:Refereed Article
Keywords:Data visualization, Apsim, uncertainty, potato, model inputs, crop models
Research Division:Agricultural, Veterinary and Food Sciences
Research Group:Agriculture, land and farm management
Research Field:Agricultural production systems simulation
Objective Division:Plant Production and Plant Primary Products
Objective Group:Horticultural crops
Objective Field:Field grown vegetable crops
UTAS Author:Ojeda, JJ (Dr Jonathan Ojeda)
ID Code:151646
Year Published:2021
Web of Science® Times Cited:5
Deposited By:TIA - Research Institute
Deposited On:2022-08-02
Last Modified:2022-09-14

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