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Are the applications of wildland fire behaviour models getting ahead of their evaluation again?

机译:野火行为模型的应用是否再次超出了评估的范围?

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Evaluation is a crucial component for model credibility and acceptance by researchers and resource managers. The nature and characteristics of free-burning wildland fires pose challenges to acquiring the kind of quality data necessary for adequate fire behaviour model evaluation. As a result, in some circles it has led to a research culture that tends to avoid evaluating model performance. Operational fire modelling systems commonly used in western North America have been shown to exhibit an under-prediction bias when employed to determine the threshold conditions necessary for the onset of crowning and the associated spread rate of active crown fires in conifer forest stands. This pronouncement was made a few years ago after at least a decade of model misapplication in fire and fuel management simulation modelling stemming from a lack of model evaluation. There are signs that the same situation may be repeated with developing physics-based models that simulate potential wildland fire behaviour; these models have as yet undergone limited testing against observations garnered from planned and/or accidental wildland fires. We propose a broad co-operative project encompassing modellers and experimentalists is needed to define and acquire the benchmark fire behaviour data required for model calibration and evaluation.
机译:评估是模型可信度和被研究人员和资源经理接受的关键组成部分。自由燃烧的野火的性质和特征对获取适当的火行为模型评估所必需的那种质量数据提出了挑战。结果,在某些领域它导致了一种研究文化,这种文化倾向于避免评估模型性能。北美西部地区常用的作战火场建模系统已被证明在确定针叶林林分中发生树冠爆发所需的阈值条件和相关活动树冠火势蔓延率时表现出预测不足。几年前,由于缺乏模型评估而在火灾和燃料管理模拟模型中至少有将模型误用了10年,才做出了这一声明。有迹象表明,开发基于物理的模拟潜在野火行为的模型可能会重复同样的情况。这些模型针对经过计划和/或意外的野外大火收集的观测值,仅经过了有限的测试。我们提出了一个广泛的合作项目,需要建模人员和实验人员来定义和获取模型校准和评估所需的基准火灾行为数据。

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