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. (February 2015)

• Record Type: Journal Article
• 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
• Is Part Of: Environmental modelling & software. Volume 64(2015:Feb.)
• Page Start: 177
• Page End: 190
• Publication Date: 2015-02
• Subjects: Soil–crop model -- STICS -- Model performances -- Plant biomass -- Soil nitrogen -- Soil water; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.11.024
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Highlights: 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.