Variance-based sensitivity analysis of a wind risk model - Model behaviour and lessons for forest modelling
Variance-based sensitivity analysis of a wind risk model - Model behaviour and lessons for forest modelling
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DOI：
10.1016/j.envsoft.2016.10.010
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Tommaso Locatelli;S. Tarantola;B. Gardiner;G. Patenaude
中科院分区：
文献类型：
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作者：
Tommaso Locatelli;S. Tarantola;B. Gardiner;G. Patenaude
我们提交了半经验的，基于过程的风风险模型ForestGALES的方差为基础的敏感性分析，使用的方法Sobosit的相关变量提出的Kucherenko等人。（2012年）。我们的研究结果表明，ForestGALES是能够非常有效地模拟动态的风损害的林分，模型架构反映了显着的影响，树高，放养密度，胸径，和大小的逆风间隙，对计算的临界风速的损害。这些结果突出了在使用ForestGALES计算风灾风险时准确了解这些变量值的重要性。相反，生根深度和土壤类型，即ForestGALES描述抗倾覆性的经验成分所依据的模型输入变量，对输出的变化贡献很小。我们表明，这两个变量可以自信地固定在名义值，而不会显着影响模型的预测。在这项研究中使用的方差为基础的方法是同样敏感的精确描述的概率分布函数的仔细变量，因为它是他们的相关性结构。
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.