New modelling technique for improving crop model performance - Application to the GLAM model. (August 2019)

• Record Type: Journal Article
• Authors: Droutsas, I.; Challinor, A.J.; Swiderski, M.; Semenov, M.A.
• Is Part Of: Environmental modelling & software. Volume 118(2019)
• Page Start: 187
• Page End: 200
• Publication Date: 2019-08
• Subjects: SEMAC -- GLAM-Parti -- Allometric relationships -- Model improvement -- Water stress; 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.2019.05.005
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Crop models simulate growth and development and they are often used for climate change applications. However, they have a variable skill in the simulation of crop responses to extreme climatic events. Here, we present a new dynamic crop modelling method for simulating the impact of abiotic stresses. The Simultaneous Equation Modelling for Annual Crops (SEMAC) uses simultaneous solution of the model equations to ensure internal model consistency within daily time steps; something that is not always guaranteed in the usual sequential method. The SEMAC approach is implemented in GLAM, resulting in a new model version (GLAM-Parti). The new model shows a clear improvement in skill under water stress conditions and it successfully simulates the acceleration of leaf senescence in response to drought. We conclude that SEMAC is a promising crop modelling technique that might be applied to a range of models. Highlights: A new simultaneous equation crop modelling technique (SEMAC) is presented. SEMAC provides higher internal model consistency than step-wise modelling approaches. Incorporation of SEMAC into GLAM improves model performance under water stress. SEMAC can be applied to other crop models.