Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122nd Street, Edmonton, AB T6H 3S5, Canada.
Dept of Natural Resource Science, Faculty of Science, Thompson Rivers University, 805 TRU Way, Kamloops, BC V2C 0C8, Canada.
Sci Total Environ. 2023 Apr 15;869:161831. doi: 10.1016/j.scitotenv.2023.161831. Epub 2023 Jan 25.
A spread day is defined as a day in which fires grow a substantial amount of area; such days usually occur during high or extreme fire weather conditions. The identification and prediction of a spread day based on fire weather conditions could help both our understanding of fire regimes as well as forecasting and managing fires operationally. This study explores the relationships between fire weather and spread days in the forested areas of Canada by spatially and temporally matching a daily fire growth database to a daily gridded fire weather database that spans from 2001 to 2019. By examining the correlations between spread day fire weather conditions and location, conifer coverage (%), and elevation, we found that a spread day happens under less severe fire weather conditions as latitude increases for the entire study area and as conifer coverage increases within non-mountainous study areas. In the western mountain areas, however, with increasing conifer coverage more severe fire weather conditions are required for a spread day to occur. Using two modeling approaches, we were able to identify spread day indicators (generalized additive model) and to predict the occurrence of spread days (semi-binomial regression model) by Canadian Ecozones both annually and seasonally. Overall, Fine Fuel Moisture Code (FFMC), Initial Spread Index (ISI), and Fire Weather Index (FWI) performed the best in all models built for spread day identification and prediction but varied depending on the conditions mentioned above. FFMC was the most consistent across all spatial and temporal scales.
蔓延日是指火灾面积大幅增长的一天;这种天气通常发生在高火险或极端火险天气条件下。根据火险条件识别和预测蔓延日可以帮助我们更好地了解火灾规律,并在操作上预测和管理火灾。本研究通过将每日火灾增长数据库与 2001 年至 2019 年期间的每日网格化火险数据库在空间和时间上进行匹配,探讨了加拿大森林地区火险与蔓延日之间的关系。通过研究蔓延日火险条件与位置、针叶林覆盖率(%)和海拔之间的相关性,我们发现,在整个研究区域内,随着纬度的增加,以及在非山区研究区域内针叶林覆盖率的增加,蔓延日发生在火险条件较轻的情况下。然而,在西部山区,随着针叶林覆盖率的增加,发生蔓延日需要更严重的火险条件。使用两种建模方法,我们能够确定蔓延日的指标(广义加性模型),并按加拿大生态区预测蔓延日的发生(半二项式回归模型),无论是每年还是季节性。总体而言,细可燃物湿度代码(FFMC)、初始蔓延指数(ISI)和火险指数(FWI)在所有用于识别和预测蔓延日的模型中表现最好,但因上述条件而异。FFMC 在所有空间和时间尺度上都是最一致的。