Residual correlation and ensemble modelling to improve crop and grassland models - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue Environmental Modelling and Software Année : 2023

Residual correlation and ensemble modelling to improve crop and grassland models

1 UREP - Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR
2 ELKH CAR - Agricultural Institute
3 CODIR - Collège de Direction
4 RITTMO - RITTMO Agroenvironnement
5 QUT - Queensland University of Technology [Brisbane]
6 FARE - Fractionnement des AgroRessources et Environnement
7 INSTITUTE OF BIOLOGICAL AND ENVIRONMENTAL SCIENCES
8 AgResearch, Lincoln Res Ctr, PB 4749, Christchurch 8140, New Zealand
9 IARI - Indian Agricultural Research Institute
10 DAGRI - Department of Agriculture, Food, Environment and Forestry
11 IBE | CNR - Institute for BioEconomy [Sesto Fiorentino]
12 IRTA - Institut de Recerca i Tecnologia Agroalimentàries = Institute of Agrifood Research and Technology
13 NREL - Natural Resource Ecology Laboratory [Fort Collins]
14 Desertification Research Group
15 Texas A and M AgriLife Research
16 Canadian National Collection of Insects, Arachnids, and Nematodes, Science & Technology Branch, Agriculture and Agri-Food Canada, Ottawa, ON, K1A 0C6
17 UTAS - University of Tasmania [Launceston]
18 NERC Centre for Ecology and Hydrology, Penicuik, UK
19 Manaaki Whenua – Landcare Research [Lincoln]
20 ECOSYS - Ecologie fonctionnelle et écotoxicologie des agroécosystèmes
21 BioEcoAgro - UMR transfrontalière INRAe - UMRT1158
22 BioEcoAgro - Equipe 2 - Integrated functioning of the soil-plant system and exchanges between the ecosystem and the hydrosphere and the atmosphere
23 CSIRO - CSIRO Agriculture and Food
24 School of Geosciences [Edinburgh]
25 PIK - Potsdam Institute for Climate Impact Research
26 The New Zealand Institute for Plant and Food Research Limited
27 Rothamsted Research - Sustainable Agriculture Systems
28 LAPC - Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry
Pete Smith
  • Fonction : Auteur
  • PersonId : 1081631
Jean-François Soussana

Résumé

Model calibration Residual plot analysis rotations including fallow periods. We do that by exploring the correlation of model residuals. We restricted the distinction between partial and full calibration to the two most relevant calibration stages, i.e. with plant data only (partial) and with a combination of plant, soil physical and biogeochemical data (full). It introduces and evaluates the trade-off between (1) what is practical to apply for model users and beneficiaries, and (2) what constitutes best modelling practice. The lower correlations obtained overall with fully calibrated models highlight the centrality of the full calibration scenario for identifying areas of model structures that require further development.
Fichier principal
Vignette du fichier
Sandor, R_2023_Environmental_modelling_and_software_preprint.pdf (2.56 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-03997939 , version 1 (16-03-2023)

Licence

Identifiants

Citer

Renáta Sándor, Fiona Ehrhardt, Peter Grace, Sylvie Recous, Pete Smith, et al.. Residual correlation and ensemble modelling to improve crop and grassland models. Environmental Modelling and Software, 2023, 161, pp.105625. ⟨10.1016/j.envsoft.2023.105625⟩. ⟨hal-03997939⟩
145 Consultations
96 Téléchargements

Altmetric

Partager

More