International audienceWe demonstrate the use of sensitivity analysis to rank sources of uncertainty in models for economic appraisal of flood risk management policies, taking into account spatial scale issues. A methodology of multi-scale variance-based global sensitivity analysis is developed, and illustrated on the NOE model on the Orb River, France. The variability of the amount of expected annual flood avoided damages, and the associated sensitivity indices, are estimated over different spatial supports, ranging from small cells to the entire floodplain. Both uncertainty maps and sensitivity maps are produced to identify the key input variables in the NOE model at different spatial scales. Our results show that on small spatial supports, v...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...
International audienceCost-benefit analyses (CBA) of flood management plans usually require estimati...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-AMOS [TR2_IRSTEA]GEUSIInterna...
International audienceWe demonstrate the use of sensitivity analysis to rank sources of uncertainty ...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-AMOS [TR2_IRSTEA]GEUSIInterna...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
International audienceFlood risk mapping is recognized as an effective tool in flood risk management...
International audienceIn order to increase the reliability of flood damage assessment, we need to qu...
International audienceVariance-based Sobol' global sensitivity analysis (GSA) was initially designed...
L'analyse de sensibilité globale basée sur la variance permet de hiérarchiser les sources d'incertit...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...
International audienceCost-benefit analyses (CBA) of flood management plans usually require estimati...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-AMOS [TR2_IRSTEA]GEUSIInterna...
International audienceWe demonstrate the use of sensitivity analysis to rank sources of uncertainty ...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-AMOS [TR2_IRSTEA]GEUSIInterna...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
Variance-based global sensitivity analysis is used to study how the variability of the output of a n...
International audienceFlood risk mapping is recognized as an effective tool in flood risk management...
International audienceIn order to increase the reliability of flood damage assessment, we need to qu...
International audienceVariance-based Sobol' global sensitivity analysis (GSA) was initially designed...
L'analyse de sensibilité globale basée sur la variance permet de hiérarchiser les sources d'incertit...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...
International audienceCost-benefit analyses (CBA) of flood management plans usually require estimati...
National audienceEnvironmental models often involve complex dynamic and spatial inputs and outputs. ...