Geodesic
Sensitivity analysis and uncertainty quantification for environmental models
Thomas Cartailler1 ; Anais Guaus2, 1 ; Alexandre Janon3, 4, 5 ; Hervé Monod6, 5 ; Clémentine Prieur4, 5 ; Nathalie Saint-Geours7, 5
1 ITK, Montpellier 
2 INRA, UMR Eco&Sols, Montpellier 
3 Université Lyon 1, ISFA 
4 MOISE (INRIA Grenoble Rhne-Alpes / LJK Laboratoire Jean Kuntzmann) 
5 GdR MASCOT-NUM (Méthodes d’Analyse Stochastique des Codes et Traitements Numériques) 
6 INRA, UR0341 MIA-Jouy, Jouy en Josas 
7 Irstea, UMR TETIS Montpellier 
ESAIM. Proceedings, Tome 44 (2014), pp. 300-321 Cet article a éte moissonné depuis la source EDP Sciences

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Environmental models often involve complex dynamic and spatial inputs and outputs. This raises specific issues when performing uncertainty and sensitivity analyses (SA). Based on applications in flood risk assessment and agro-ecology, we present current research to adapt the methods of variance-based SA to such models. After recalling the basic principles, we propose a metamodelling approach of dynamic models based on a reduced-basis approximation of PDEs and we show how the error on the subsequent sensitivity indices can be quantified. We then present a mix of pragmatic and methodological solutions to perform the SA of a dynamic agro-climatic model with non standard input factors. SA is then applied to a flood risk model with spatially distributed inputs and outputs. Block sensitivity indices are defined and a precise relationship between these indices and their support size is established. Finally, we show how the whole support landscape and its key features can be incorporated in the SA of a spatial model.
DOI : 10.1051/proc/201444019

Thomas Cartailler 1 ; Anais Guaus 2, 1 ; Alexandre Janon 3, 4, 5 ; Hervé Monod 6, 5 ; Clémentine Prieur 4, 5 ; Nathalie Saint-Geours 7, 5

1 ITK, Montpellier 
2 INRA, UMR Eco&Sols, Montpellier 
3 Université Lyon 1, ISFA 
4 MOISE (INRIA Grenoble Rhne-Alpes / LJK Laboratoire Jean Kuntzmann) 
5 GdR MASCOT-NUM (Méthodes d’Analyse Stochastique des Codes et Traitements Numériques) 
6 INRA, UR0341 MIA-Jouy, Jouy en Josas 
7 Irstea, UMR TETIS Montpellier  
@article{EP_2014_44_a19,
     author = {Thomas Cartailler and Anais Guaus and Alexandre Janon and Herv\'e Monod and Cl\'ementine Prieur and Nathalie Saint-Geours},
     title = {Sensitivity analysis and uncertainty quantification for environmental models},
     journal = {ESAIM. Proceedings},
     pages = {300--321},
     year = {2014},
     volume = {44},
     doi = {10.1051/proc/201444019},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1051/proc/201444019/}
}
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%0 Journal Article
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%A Alexandre Janon
%A Hervé Monod
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%A Nathalie Saint-Geours
%T Sensitivity analysis and uncertainty quantification for environmental models
%J ESAIM. Proceedings
%D 2014
%P 300-321
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%U http://geodesic.mathdoc.fr/articles/10.1051/proc/201444019/
%R 10.1051/proc/201444019
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%F EP_2014_44_a19
Thomas Cartailler; Anais Guaus; Alexandre Janon; Hervé Monod; Clémentine Prieur; Nathalie Saint-Geours. Sensitivity analysis and uncertainty quantification for environmental models. ESAIM. Proceedings, Tome 44 (2014), pp. 300-321. doi: 10.1051/proc/201444019

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