Advancing the Science of Wildland Fire Dynamics Using Process-Based Models
Advancing the Science of Wildland Fire Dynamics Using Process-Based Models
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DOI：
10.3390/fire1020032
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发表时间：
2018-09-01
期刊：
影响因子：
3.2
通讯作者：
Hiers, J. Kevin
中科院分区：
文献类型：
--
作者：
Hoffman, Chad M.;Sieg, Carolyn H.;Hiers, J. Kevin
随着科学家和管理人员寻求在超出我们当前经验模型和先前经验的限制的条件下理解火灾行为，他们将需要新的工具来促进对推动火灾动力学和影响的过程的更机械性的理解。在这里，我们认为基于过程的模型是强大的研究工具，对于研究荒地火灾科学中的大量新兴问题是有用的。这些模型可以在促进我们的理解方面发挥特别重要的作用，部分原因是它们允许用户从一个独特的角度评估推动火灾动力学和影响的潜在机制和相互作用，而这通常不是仅通过实验获得的。例如，基于流程的模型可以用于进行在物理世界中不可能、风险太高或代价高昂的实验。他们还可以通过启发新的实验、提供测量策略和协助解释物理观测来为发现过程做出贡献。最终，不断将模拟与实验数据进行比较，并以模拟为指导的协同方法，将深刻影响解决荒野火灾科学新问题的质量和进展速度。
As scientists and managers seek to understand fire behavior in conditions that extend beyond the limits of our current empirical models and prior experiences, they will need new tools that foster a more mechanistic understanding of the processes driving fire dynamics and effects. Here we suggest that process-based models are powerful research tools that are useful for investigating a large number of emerging questions in wildland fire sciences. These models can play a particularly important role in advancing our understanding, in part, because they allow their users to evaluate the potential mechanisms and interactions driving fire dynamics and effects from a unique perspective not often available through experimentation alone. For example, process-based models can be used to conduct experiments that would be impossible, too risky, or costly to do in the physical world. They can also contribute to the discovery process by inspiring new experiments, informing measurement strategies, and assisting in the interpretation of physical observations. Ultimately, a synergistic approach where simulations are continuously compared to experimental data, and where experiments are guided by the simulations will profoundly impact the quality and rate of progress towards solving emerging problems in wildland fire sciences.