Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France

• Published in: Environmental modelling & software : with environment data news Vol. 64; pp. 177 - 190
• Main Authors: Coucheney, Elsa, Buis, Samuel, Launay, Marie, Constantin, Julie, Mary, Bruno, García de Cortázar-Atauri, Iñaki, Ripoche, Dominique, Beaudoin, Nicolas, Ruget, Françoise, Andrianarisoa, Kasaina Sitraka, Le Bas, Christine, Justes, Eric, Léonard, Joël
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2015; Elsevier
• Subjects: Accuracy; Agricultural Science; Biomass; Computer programs; Crops; Environment management; Environmental Sciences related to Agriculture and Land-use; Jordbruksvetenskap; Life Sciences; Markvetenskap; Mathematical models; Miljö- och naturvårdsvetenskap; Model performances; Plant biomass; Plants (organisms); Robustness; Soil (material); Soil nitrogen; Soil Science; Soil water; Soil–crop model; STICS; France; ANE, France; STICS; Soil water; Model performances; Soil–crop model; Plant biomass; Soil nitrogen
• ISSN: 1364-8152; 1873-6726; 1873-6726
• DOI: 10.1016/j.envsoft.2014.11.024

Soil–crop models are increasingly used as predictive tools to assess yield and environmental impacts of agriculture in a growing diversity of contexts. They are however seldom evaluated at a given time over a wide domain of use. We tested here the performances of the STICS model (v8.2.2) with its standard set of parameters over a dataset covering 15 crops and a wide range of agropedoclimatic conditions in France. Model results showed a good overall accuracy, with little bias. Relative RMSE was larger for soil nitrate (49%) than for plant biomass (35%) and nitrogen (33%) and smallest for soil water (10%). Trends induced by contrasted environmental conditions and management practices were well reproduced. Finally, limited dependency of model errors on crops or environments indicated a satisfactory robustness. Such performances make STICS a valuable tool for studying the effects of changes in agro-ecosystems over the domain explored. •STICS v8.2.2 soil–crop model was evaluated over a large and varied dataset using its standard set of parameters.•Level of accuracy is 10–50% for plant, soil water and nitrate outputs.•Model reproduces well trends arising from contrasted agro-environmental conditions.•Errors are weakly dependent on the agro-environmental conditions tested.•Model accuracy and robustness is considered good for scenario testing and large scale use within the conditions tested here.