Wildfire Suppression Difficulty Index 90th Percentile (2026)

Wildfire Suppression Difficulty Index (SDI) 90th Percentile is a rating of relative difficulty in performing fire control work under regionally appropriate fuel moisture and 15 mph uphill winds (@ 20 ft). SDI (Rodriguez y Silva et al. 2020) factors in topography, fuels, expected fire behavior under prevailing conditions, fireline production rates in various fuel types with and without heavy equipment, and access via roads, trails, or cross-country travel. SDI is currently classified into six categories representing low through extreme difficulty. Extreme SDI zones represented in red are “watch out” situations where engagement is likely to be very challenging given the combination of potential high intensity fire behavior and difficult suppression environment (high resistance fuel types, steep terrain, and low accessibility). Low difficulty zones represented in blue indicate areas where some combination of reduced potential for dangerous fire behavior and ideal suppression environment (low resistance fuel types, mellow terrain, and high accessibility) make suppression activities easier. SDI does not account for standing snags or other overhead hazards to firefighters, so it is not a firefighter hazard map. It is only showing in relative terms where it is harder or easier to perform suppression work. SDI incorporates flame length and heat per unit area from basic FlamMap runs (Finney et al. 2019). SDI is based on fire behavior modeled using regionally appropriate percentile fuel moisture conditions and uphill winds. This product uses the wind blowing uphill option to represent a consistent worst-case scenario. Input fuels data are updated to the most recent fire year using a crosswalk for surface and canopy fuel modifications for fires and fuel treatments that occurred after the most recent LANDFIRE version. For example, LANDFIRE 2016 model inputs are modified to incorporate fires (Monitoring Trends in Burn Severity (MTBS), Geospatial Multi- Agency Coordination (GeoMac), and Wildland Fire Interagency Geospatial Services (WFIGS) and fuel treatments (USFS Forest Activity Tracking System (FACTS) and DOI National Fire Plan Operations and Reporting System (NFPORS) hazardous fuels reduction treatments) from 2017-present. Road and trail inputs are developed from a combination of HERE 2020 Roads, USFS, and DOI road and trails databases. Hand crew and dozer fireline production rates are from FPA 2012 (Dillon et al. 2015). Classification of topography and accessibility thresholds are detailed in Rodriguez et al. (2020). Dillon, G.K.; Menakis, J.; Fay, F. (2015) Wildland Fire Potential: a tool for assessing wildfire risk and fuels management needs. In: Keane, R.E.; Jolly, M.; Parsons, R.; Riley, K., eds. Proceedings of the large wildland fires conference; May 19-23, 2014; Missoula, MT. Proc. RMRS-P-73. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 345 p. Finney, M.A.; Brittain, S.; Seli, R.C.; McHugh, C.W.; Gangi, L. (2019) FlamMap:Fire Mapping and Analysis System (Version 6.0) [Software]. Available from https://www.firelab.org/document/flammap-software Rodriguez y Silva, F.; O'Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E. (2020). Modeling Suppression Difficulty: Current and Future Applications. International Journal of Wildland Fire. More detail on SDI Methods can be found on the RMA Sharepoint Site (RMA Dashboard Analytics --> Suppression Difficulty Index (SDI) folder.野火抑制难度指数（Wildfire Suppression Difficulty Index, SDI）90分位值是用于评估在区域适宜的燃料湿度以及20英尺高度处15英里/小时上坡风条件下开展火情控制作业相对难度的评级体系。 SDI（Rodriguez y Silva等人，2020）纳入了地形、燃料、常规条件下的预期火灾行为、有无重型设备时不同燃料类型下的火线构建速率，以及通过道路、步道或越野通行的可达性等核心要素。 当前SDI被划分为六个等级，涵盖从低难度到极端难度的区间。 以红色标注的极端SDI区域属于"需警惕"场景：结合潜在高强度火灾行为与复杂作业环境（高灭火阻力燃料类型、陡峭地形以及可达性差），此类区域的灭火作业往往极具挑战性。 以蓝色标注的低难度区域则具备较低的危险火灾行为发生潜力与理想的作业环境（低灭火阻力燃料类型、平缓地形以及良好可达性），因此灭火作业更为便捷。 SDI未考虑站立枯木或其他针对消防员的头顶危险源，因此并非消防员风险地图，仅用于相对展示开展灭火作业的难易程度。 SDI纳入了基础FlamMap（Finney等人，2019）运行输出的火焰长度与单位面积热通量数据。 SDI基于采用区域适宜分位值燃料湿度条件与上坡风模拟得到的火灾行为模型构建，本产品采用上坡风参数以统一表征最坏情景。 输入的燃料数据通过匹配规则更新至最新火灾年度，该规则用于修正最新版LANDFIRE数据发布后发生的火灾与燃料处理项目带来的地表及冠层燃料变化。 例如，LANDFIRE 2016模型的输入数据会纳入2017年至今的火灾数据（含燃烧严重度监测趋势（Monitoring Trends in Burn Severity, MTBS）、多机构地理空间协调（Geospatial Multi-Agency Coordination, GeoMac）以及野地火灾跨机构地理空间服务（Wildland Fire Interagency Geospatial Services, WFIGS））与燃料处理项目数据（含美国林务局森林活动跟踪系统（USFS Forest Activity Tracking System, FACTS）以及内政部国家灭火计划运营与报告系统（DOI National Fire Plan Operations and Reporting System, NFPORS）的危险燃料削减处理数据）并进行修正。 道路与步道的输入数据整合自HERE 2020道路数据集、美国林务局以及内政部的道路与步道数据库。 手工作业班组与推土机的火线构建速率数据源自FPA 2012（Dillon等人，2015）。 地形与可达性阈值的分类标准详见Rodriguez等人（2020）的研究。 Dillon, G.K.; Menakis, J.; Fay, F.（2015）《野地火灾潜力：评估野火风险与燃料管理需求的工具》，收录于Keane, R.E.; Jolly, M.; Parsons, R.; Riley, K.主编的《大型野地火灾会议论文集》；2014年5月19-23日，蒙大拿州米苏拉市。RMRS-P-73会议论文集。科罗拉多州科林斯堡：美国农业部林务局落基山研究站，共345页。 Finney, M.A.; Brittain, S.; Seli, R.C.; McHugh, C.W.; Gangi, L.（2019）《FlamMap：火灾制图与分析系统（6.0版）》[软件]。可从https://www.firelab.org/document/flammap-software获取。 Rodriguez y Silva, F.; O'Connor, C.D.; Thompson, M.P.; Molina, J.R.; Calkin, D.E.（2020）《灭火难度建模：当前与未来应用》，《国际野地火灾期刊》。 有关SDI方法的更多详细信息可在RMA SharePoint网站（RMA仪表板分析 --> 野火抑制难度指数（SDI）文件夹）中获取。