Sensitivity analysis of spatio-temporal models describing nitrogen transfers, transformations and losses at the landscape scale. (January 2019)

• Record Type: Journal Article
• Authors: Ferrer Savall, Jordi; Franqueville, Damien; Barbillon, Pierre; Benhamou, Cyril; Durand, Patrick; Taupin, Marie-Luce; Monod, Hervé; Drouet, Jean-Louis
• Is Part Of: Environmental modelling & software. Volume 111(2019)
• Page Start: 356
• Page End: 367
• Publication Date: 2019-01
• Subjects: Sensitivity analysis -- Cluster analysis -- Nitrogen cascade -- Spatial model -- Landscape scale; 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.2018.09.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Modelling complex systems such as agroecosystems often requires the quantification of a large number of input factors. Sensitivity analyses are useful to determine the appropriate spatial and temporal resolution of models and to reduce the number of factors to be measured or estimated accurately. Comprehensive spatial and temporal sensitivity analyses were applied to the NitroScape model, a deterministic spatially distributed model describing nitrogen transfers and transformations in rural landscapes. Simulations were led on a theoretical landscape that represented five years of intensive farm management and covering an area of 3 km 2 . Cluster analyses were applied to summarize the results of the sensitivity analysis on the ensemble of model outputs. The methodology we applied is useful to synthesize sensitivity analyses of models with multiple space-time input and output variables and could be ported to other models than NitroScape. Highlights: Novel analytical methods for dynamic and spatially distributed models were proposed. Spatial resolution at which the model is run was found to impact most of outputs. Visualization methods summarized spatially distributed output and temporal outputs. Cluster analysis grouped together outputs that are sensitive to same sets of inputs.