Fire managers tasked with assessing the hazard and risk of wildfire in Alaska, USA, tend to have more confidence in fire behavior prediction modeling systems developed in Canada than similar systems developed in the US. In 1992, Canadian fire behavior systems were adopted for modeling fire hazard and risk in Alaska and are used by fire suppression specialists and fire planners working within the state. However, as new US-based fire behavior modeling tools are developed, Alaskan fire managers are encouraged to adopt the use of US-based systems. Few studies exist in the scientific literature that inform fire managers as to the efficacy of fire behavior modeling tools in Alaska. In this study, I provide information to aid fire managers when tasked with deciding which system for modeling fire behavior is most appropriate for their use. On the Magitchlie Creek Fire in Alaska, I systematically collected fire behavior characteristics within a black spruce (Picea mariana [Mill.] Britton, Sterns & Poggenb.) ecosystem under head fire conditions. I compared my fire behavior observations including flame length, rate of spread, and head fire intensity with fire behavior predictions from the US fire modeling system BehavePlus, and three Canadian systems: RedAPP, CanFIRE, and the Crown Fire Initiation and Spread system (CFIS). All four modeling systems produced reasonable rate of spread predictions although the Canadian systems provided predictions slightly closer to the observed fire behavior. The Canadian fire behavior prediction modeling systems RedAPP and CanFIRE provided more accurate predictions of head fire intensity and fire type than BehavePlus or CFIS. The most appropriate fire behavior modeling system for use in Alaskan black spruce ecosystems depends on what type of questions are being asked. For determining the rate of fire movement across a landscape, REDapp, CanFIRE, CFIS, or BehavePlus can all be expected to provide reasonably accurate estimates of rate of spread. If fire managers are interested in using predicted flame length or energy produced for informing decisions such as which firefighting tactics will be successful, or for evaluating the ecological impacts due to burning, then the Canadian fire modeling systems outperformed BehavePlus in this case study.

中文翻译：

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阿拉斯加黑云杉林生态系统中观察到的火灾行为与预测的火灾行为：实验性火灾案例研究

负责评估美国阿拉斯加森林火灾危险性和风险的消防管理人员，对加拿大开发的火灾行为预测建模系统的信心要高于美国开发的类似系统。1992年，加拿大的火灾行为系统被采用来对阿拉斯加的火灾隐患和风险进行建模，并由该州的灭火专家和消防计划人员使用。但是，随着新的基于美国的火灾行为建模工具的开发，鼓励阿拉斯加的火灾管理人员采用基于美国的系统。在科学文献中，很少有研究能使消防管理人员了解阿拉斯加的火灾行为建模工具的功效。在这项研究中，我将提供信息，以协助消防管理人员确定最适合其使用的火灾行为建模系统。在阿拉斯加的Magitchlie Creek火灾中，我系统地收集了头部火灾条件下黑色云杉（Picea mariana [Mill。] Britton，Sterns和Poggenb。）生态系统内的火灾行为特征。我将我的火灾行为观察结果（包括火焰长度，蔓延速率和头部火灾强度）与美国火灾建模系统BehavePlus和三个加拿大系统的火灾行为预测进行了比较：RedAPP，CanFIRE和Crown Fire Initiation and Spread系统（CFIS） 。尽管加拿大系统提供的预测稍微接近观察到的火势，但所有四个建模系统均产生了合理的扩散预测率。与BehavePlus或CFIS相比，加拿大的火灾行为预测建模系统RedAPP和CanFIRE提供了对头部火灾强度和火灾类型的更准确的预测。在阿拉斯加黑云杉生态系统中使用的最合适的火灾行为建模系统取决于所问问题的类型。为了确定整个景观中的火势移动速率，可以期望REDapp，CanFIRE，CFIS或BehavePlus都能提供合理准确的传播速率估计。如果消防经理有兴趣使用预测的火焰长度或产生的能量来指导决策，例如哪种消防策略将获得成功，或者用于评估由于燃烧引起的生态影响，那么在本案例研究中，加拿大的消防建模系统的性能要优于BehavePlus。或BehavePlus都可以期望提供合理准确的价差估算。如果消防经理有兴趣使用预测的火焰长度或产生的能量来指导决策，例如哪种消防策略将获得成功，或者用于评估由于燃烧引起的生态影响，那么在本案例研究中，加拿大的消防建模系统的性能要优于BehavePlus。或BehavePlus都可以期望提供合理准确的价差估算。如果消防经理有兴趣使用预测的火焰长度或产生的能量来指导决策，例如哪种消防策略将获得成功，或者用于评估由于燃烧引起的生态影响，那么在本案例研究中，加拿大的消防建模系统的性能要优于BehavePlus。