Variance-based sensitivity analysis of a wind risk model - Model behaviour and lessons for forest modelling

Tommaso Locatelli, Stefano Tarantola, Barry Gardiner, Genevieve Patenaude

Research output: Contribution to journalArticlepeer-review

Abstract

We submitted the semi-empirical, process-based wind-risk model ForestGALES to a variance-based sensitivity analysis using the method of Soboĺ for correlated variables proposed by Kucherenko et al. (2012). Our results show that ForestGALES is able to simulate very effectively the dynamics of wind damage to forest stands, as the model architecture reflects the significant influence of tree height, stocking density, dbh, and size of an upwind gap, on the calculations of the critical wind speeds of damage. These results highlight the importance of accurate knowledge of the values of these variables when calculating the risk of wind damage with ForestGALES. Conversely, rooting depth and soil type, i.e. the model input variables on which the empirical component of ForestGALES that describes the resistance to overturning is based, contribute only marginally to the variation in the outputs. We show that these two variables can confidently be fixed at a nominal value without significantly affecting the model's predictions. The variance-based method used in this study is equally sensitive to the accurate description of the probability distribution functions of the scrutinised variables, as it is to their correlation structure.
Original languageEnglish
Pages (from-to)84-109
JournalEnvironmental Modelling and Software
Volume87
Early online date11 Nov 2016
DOIs
Publication statusPublished - 1 Jan 2017

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