TY - JOUR
T1 - Variance-based sensitivity analysis of a wind risk model - Model behaviour and lessons for forest modelling
AU - Locatelli, Tommaso
AU - Tarantola, Stefano
AU - Gardiner, Barry
AU - Patenaude, Genevieve
N1 - Genevieve was on maternity leave when this was accepted - see attached e-mail confirmation from HR. Unable to chase the AAM, will try again. Genevieve finally able to obtain AAM 11/18.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
U2 - 10.1016/j.envsoft.2016.10.010
DO - 10.1016/j.envsoft.2016.10.010
M3 - Article
SN - 1364-8152
VL - 87
SP - 84
EP - 109
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
ER -