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 - Archive ouverte HAL
Article Dans Une Revue Environmental Modelling and Software Année : 2015

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

Marie Launay
  • Fonction : Auteur
Bruno Mary
  • Fonction : Auteur
  • PersonId : 1202685
Inaki Garcia de Cortazar Atauri
Dominique Ripoche
  • Fonction : Auteur
  • PersonId : 1203111
Nicolas Beaudoin
  • Fonction : Auteur
  • PersonId : 1206197
  • IdRef : 120443007
Christine Le Bas

Résumé

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.
Fichier non déposé

Dates et versions

hal-01132243 , version 1 (16-03-2015)

Identifiants

Citer

Elsa Coucheney, Samuel Buis, Marie Launay, Julie Constantin, Bruno Mary, et al.. 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. Environmental Modelling and Software, 2015, 64, pp.177-190. ⟨10.1016/j.envsoft.2014.11.024⟩. ⟨hal-01132243⟩
226 Consultations
0 Téléchargements

Altmetric

Partager

More