Fire Spread Rate Research Articles

Assessing large landscape patterns of potential fire connectivity using circuit methods

ContextMinimizing negative impacts of wildfire is a major societal objective in fire-prone landscapes. Models of fire connectivity can aid in understanding and managing wildfires by analyzing potential fire spread and conductance patterns. We define ‘fire connectivity’ as the landscape’s capacity to facilitate fire transmission from one point on the landscape to another.ObjectivesOur objective was to develop an approach for modeling fire connectivity patterns representing potential fire spread and relative flow across a broad landscape extent, particularly in the management-relevant context of fuel breaks.MethodsWe applied an omnidirectional circuit theory algorithm to model fire connectivity in the Great Basin of the western United States. We used predicted rates of fire spread to approximate conductance and calculated current densities to identify connections among areas with high spread rates. We compared existing and planned fuel breaks with fire connectivity patterns.ResultsFire connectivity and relative flow outputs were characterized by spatial heterogeneity in the landscape’s capacity to transmit fire. We found that existing fuel break networks were denser in areas with relatively diffuse and impeded flow patterns, rather than in locations with channelized flow.ConclusionsThis approach could be paired with traditional fire behavior and risk analyses to better understand wildfire spread as well as direct strategic placement of individual fuel breaks within larger networks to constrain fire spread. Thus, our findings may offer local- to landscape-level support for management actions that aim to disrupt fire spread and mitigate the costs of fire on the landscape.

Fuel weight and understorey hazard dynamics in mature karri (Eucalyptus diversicolor) forests in southwest Western Australia

ABSTRACT Fuel properties influence the behaviour of forest fires, so understanding how these change with time since fire is important for appraising the bushfire threat and planning and implementing bushfire mitigation operations. A space-for-time study in mature karri forests with fuel ages ranging from 1 to 92 years demonstrated that total fine-fuel weight (TFFW) increased with time since fire for about 30 years then plateaued at a mean value of about 50 t ha−1. For fuels older than four years, on average, 74% of TFFW was in the surface fuel layer (the litterbed) and 17% was in the near-surface layer (up to 1 m above the surface layer). Live understorey vegetation contributed only about 6% to TFFW. Predicting TFFW from time since fire was improved by including karri tree basal area. Mean understorey height (Uht) increased with time since fire, peaking at 6 m after about 30 years, then declining to about 4 m after 92 years. Mean understorey hazard (Uhaz), derived from Uht plus the proportion (%) of dead fuel in each fuel layer, followed a similar trend, peaking at 20–30 years post-fire, then declining. Although Uhaz had declined by 36% from the maximum value by 60+ years post-fire, it was 27% higher than the Uhaz value for young fuels (1−<5 years old). For a mean prescribed-burn interval of eight years, 50% of the forest fuel will be ≤four years old and so will be carrying about ≤19 t ha−1 of fine fuel (≤38% of the maximum value), with a Uhaz value of about <3.56 (<50% of the maximum value). Fuel weight and Uhaz directly influence fire intensity, flame size, spotting potential and rate of spread. Therefore, prescribed burning, done strategically and at the appropriate temporal and spatial scales, will make bushfires less damaging and easier and safer to suppress.

Study on the Minimum Fire-Extinguishing Concentration of Several Commonly Used Extinguishing Agents to Suppress Pyrolysis Gas of Red Pine Wood.

The suppression of forest wood burning has been one of the important research directions in the field of solid combustible fire safety. The process of forest wood flame propagation is a coupled process of solid-phase pyrolysis and gas-phase combustion chemical reactions; therefore, as long as the solid-phase pyrolysis or gas-phase combustion can be suppressed, the forest wood flame propagation can be suppressed and an important contribution can be made to the subsequent suppression of forest wood fires. Previous studies have focused on the inhibition of solid-phase pyrolysis of forest wood, so this paper examines the effectiveness of several common fire suppressants for suppressing forest wood gas-phase flames, starting with the inhibition of forest wood gas-phase combustion. In this paper, for the convenience of the study, we narrowed the scope of the research object to the previous research ideas for gas fires, established a simplified small-scale flame model for forest wood fire suppression, took red pine wood as the research object, analyzed the pyrolysis gas components after high-temperature pyrolysis, and constructed a Cup burner suitable for N2, CO2, fine water mist, and NH4H2PO4 powder to extinguish the pyrolysis gas flame of red pine wood, respectively. The experimental system, together with the 9306 fogging system and the improved powder delivery control system, shows the process of extinguishing fuel flames such as red pine pyrolysis gas at 350, 450, and 550 °C with various types of fire-extinguishing agents on this device. It was found that the flame morphology was related to the composition of the gas and the type of extinguishing agent. At the same time, NH4H2PO4 powder appeared to burn above the cup mouth when pyrolysis gas interacted with it at 450 °C, but this phenomenon did not occur when other extinguishing agents interacted with it and only appeared when pyrolysis gas interacted with it at 450 °C, so it was judged that this phenomenon was related to the CO2 content of the gas component and the type of extinguishing agent. The study found that the four extinguishing agents extinguish red pine pyrolysis gas flame MEC value. There's a big difference. The worst performance is N2. Compared with N2 suppression of red pine pyrolysis gas flame, CO2 suppression effectiveness is 60% higher, but compared to the suppression effectiveness of fine water mist and far away, the suppression effectiveness of fine water mist is much higher than the suppression effectiveness of CO2. However, the difference in effectiveness between fine water mist and NH4H2PO4 powder is almost double. In summary, in the suppression of red pine gas-phase flame, four kinds of fire-extinguishing agents are ranked as follows: N2 < CO2 < fine water mist < NH4H2PO4 powder. Finally, the suppression mechanism of each type of extinguishing agent was analyzed. The study of this paper can provide some data to support the extinguishing of open fires in forest fires or suppressing the rate of forest fire spread.

Thermal decomposition of vegetative fuels and the impact of measured variations on simulations of wildfire spread

This manuscript presents new measurement data from milligram-scale thermal decomposition experiments – thermogravimetric analysis (TGA) and microscale combustion calorimetry (MCC) – conducted on stems and leaves (i.e., needles) of six plant species commonly found across the United States. For each fuel, measurement data from TGA experiments was analyzed to determine effective thermal decomposition mechanisms and the associated kinetics of their constituent reactions. Results of this model calibration were compared to standard (i.e., ‘generalized’) approaches to obtain kinetic parameters available in the literature. MCC experiments were repeated under identical experimental conditions to determine the heats of complete combustion of all gaseous volatiles produced by these vegetative fuels and to validate the decomposition mechanisms and species char yields determined from TGA data. Through a coupled analysis of TGA and MCC measurement data, an estimate of the heats of combustion of the gaseous volatiles produced by individual reaction steps in the fuel’s decomposition was also made. Between different fuels, distinct differences were measured in the onset temperature of decomposition, the temperature range of decomposition, the number of apparent reactions, and the peak measured mass loss and heat release rates (as well as the temperatures at which they occur). To analyze the impact of these variations on predictions of wildfire behavior, a modeling study was then conducted in which simulations of wildland fire experiments were repeated using the thermal decomposition mechanisms and heats of combustion determined for each of the fuel species tested in this work. Model-predicted fire spread rate in these simulations varied between 0.34 m s−1 and 0.80 m s−1 demonstrating a notable dependence (up to a factor of 2x) on measured variations in thermal decomposition mechanism and a second-order dependence on the use of either reaction-step-specific or single (global) heats of combustion.

Investigation of Fire Weather Danger under a Changing Climate at High Resolution in Greece

Future fire weather conditions under climate change were investigated based on the Fire Weather Index (FWI), Initial Spread Index (ISI) and threshold-specific indicators in Greece. The indices were calculated from climate datasets derived from high-resolution validated simulations of 5 km. The dynamical downscaled simulations with the WRF model were driven by EC-Earth output for historical (1980–2004) and future periods, under two Representative Concentration Pathways (RCPs), RCP4.5 and 8.5. The analysis showed that the FWI is expected to increase substantially, particularly in the southern parts with extreme values found above 100. In addition, the number of days with an FWI above the 90th percentile is projected to increase considerably (above 30 days), under both scenarios. Over the eastern and northern mainland, the increase is estimated with more than 70 days under RCP4.5, in the near future (2025–2049). Moreover, central and north-eastern parts of the country will be affected with 30 or more extreme consecutive days of prolonged fire weather, under RCP4.5, in the near future and under RCP8.5 in the far future (2075–2099). Finally, the expected rate of fire spread is more spatially extended all over the country and particularly from southern to northern parts compared to the historical state.

Numerical Study of the Effect of the Ignition Procedure on the Front of a Surface Fire from a 3D Numerical Model

In instrumented prescribed fires, the ignition procedure requires much attention. In this paper, we investigate the effects of two ignition procedures on the fire head using a 3D numerical model. The first procedure is to ignite the fire from the edges of the fire line towards the centre of the line. The second procedure consists of igniting the fire from the centre of the fire line to the edges of the line. The 3D numerical model used is based on the modelling of the fuel layer from Lagrangian particles, and the fire propagation is based on a two-phase model. The model was tested on an experimental fire in a wheat field in southern Australia. The model predicted the experimental fire front well. Analysis of the impact of the ignition procedure on the fire head showed that the quasi-steady-state rate of fire spread was the same for both procedures. However, before the quasi-stationary state, the front of the first procedure spread faster than that of the second procedure. The fire front in the first procedure was wider than in the second procedure. It was also found that the length of the head fire in the first procedure remained the same as that of the ignition line. In the second procedure, the length of the head fire was one-third of that of the ignition line.

Numerical simulation of two parallel merging wildfires

Background Wildfire often shows complex dynamic behaviour due to the inherent nature of ambient conditions, vegetation and ignition patterns. Merging fire is one such dynamic behaviour that plays a critical role in the safety of structures and firefighters. Aim &amp; method The aim of this study was to develop better insight and understanding of the interaction of parallel merging firelines, using a numerical validation of a physics-based CFD wildfire model concerning merging fires. Conclusions The validated model shows a relative error of 5–35% in estimating the rate of fire spread compared with the experimental observation in most of the cases. A physical interpretation is presented to show how parallel fire behaves and interacts with the ambient conditions, providing complementary information to the experimental study. Implications The validated numerical model serves as a base case for further study in developing a better correlation for the rate of fire spread between parallel firelines with different ambient conditions, especially at the field scale.

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key results Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

Adaptation of QES-Fire, a dynamically coupled fast response wildfire model for heterogeneous environments

Background Modelling of fire front progression is challenging due to the large range of spatial and temporal scales involved in the interactions between the atmosphere and fire fronts. Further modelling complications arise when heterogeneous terrain and fuels are considered. Aims The aim of this study was to create a new parameterisation for wildfire-induced winds that accounts for the effects of heterogeneous terrain and fuels within the QES-Fire modelling framework – a fast-response wildfire model. Methods QES-Fire’s new turbulent plume merging model allows for distinct plumes to be merged together from fires burning in heterogeneous terrain with heterogeneous fuels. Additionally, fuel inputs from the LANDFIRE database developed for the Rothermel rate of spread (ROS) model, are translated to the Balbi ROS model. Key results The model was evaluated against the forested RxCADRE field experiment, with and without the effects of heterogeneity. Inclusion of heterogeneity reduced the relative error in burned area from 36 to 6%. Conclusions Small variations in terrain and fuel heterogeneity lead to large errors in rate and direction of fire front spread. Implications The modelled effects of terrain and fuel heterogeneity indicated the importance of capturing the complex coupled wildfire–atmospheric dynamics at the fire front.

A review of forest visualization and forest fire simulation technology research

A review of forest visualization and forest fire simulation technology research

不同烈度林火对油松林潜在地表火行为的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 不同烈度林火对油松林潜在地表火行为的影响 DOI: 10.5846/stxb202111223283 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2020YFC1511601） Effects of wildfire of different severities on potential surface fire behavior of Pinus tabuliformis forest Author: Affiliation: Fund Project: the Key Project of National Key Research and Development Plan 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:油松是我国华北地区代表性树种之一，含有丰富油脂，容易引发大面积高烈度森林火灾。阐明不同烈度林火对油松林地表可燃物负荷量和潜在地表火行为的影响，对于油松林林火管理具有重要意义。以辽河源自然保护区2014年不同烈度林火干扰后油松林分为研究对象，根据不同烈度（重度、中度、轻度）和对照（未过火）分别设置3块20 m×20 m样地，共12块样地，调查地表可燃物和林分结构指标，结合室内实验，利用BehavePlus 5.0软件进行潜在火行为模拟，探讨不同烈度林火5年后油松林地表可燃物负荷量和潜在地表火行为特点，并分析影响潜在地表火行为的主要因素。研究结果表明：（1）不同烈度林火之间，细小可燃物负荷量和地表可燃物总负荷量均不存在显著性差异（P>0.05）。（2）不同烈度林火后，在不同风速和可燃物含水率条件下，油松林潜在地表火蔓延速度、火线强度不存在显著性差异（P>0.05），单位面积发热量、火焰高度、反应强度存在显著性差异（P<0.05）。（3）不同烈度林火后油松林潜在地表火行为主要受油松更新幼苗基径、灌木负荷量、油松平均冠幅、上层枯叶负荷量、油松更新幼苗密度的影响。研究结果表明不同烈度林火均可以降低再次燃烧的火烈度和风险。 Abstract:Pinus tabuliformis is one of the representative tree species in North China, which is rich in oil and easy to cause large area and high severity wildfire. It is of great significance for wildfire management of Pinus tabuliformis forest to elucidate the influence of wildfire of different severities on the surface fuel load and potential surface fire behavior of Pinus tabuliformis forest. In this study, Pinus tabuliformis forests with different severities of wildfire disturbance in Liaoheyuan Nature Reserve in 2014 were taken as the research object. According to different severities (high, moderate, low) and control (unburned), three 20 m×20 m sample plots were set, and a total of 12 plots were set. Based on the investigation of surface fuel and stand structure index, combined with indoor experiments, the potential fire behavior was simulated by BehavePlus 5.0 software. The characteristics of surface fuel load and potential surface fire behavior of Pinus tabuliformis forest after 5 years of fire with different severities were discussed, and the main factors affecting the potential surface fire behavior were analyzed. The results indicated that (1) there was no significant difference in the fine fuel load and the total surface fuel load between different severities wildfire disturbance (P>0.05). (2) Under the conditions of different wind speeds and fuel moisture content, there were no significant differences in the potential surface fire spread rate and fireline intensity (P>0.05), but there were significant differences in the calorific value per unit area, flame height and reaction intensity (P<0.05) after forest fire disturbance with different severities. (3) The potential surface fire behavior of Pinus tabuliformis forest with different severities was mainly affected by the regeneration seedling base diameter of Pinus tabuliformis, shrub load, average canopy width of Pinus tabuliformis, load of upper dead leaves, and the regeneration seedling density of Pinus tabuliformis. The results showed that forest fires with different severities could reduce the severity and risk of reburning. 参考文献 相似文献 引证文献

Calculating fire danger of cured grasslands in temperate climates – the elements of the Grassland Fire Index (GLFI)

Background Increasing extreme weather events due to climate change require updated environmental monitoring and prediction systems in Germany. Aim The Grassland Fire Index (GLFI), developed by the German Meteorological Service ~15 years ago for temperate climates, was revised to improve fire-danger predictions during the fire season. Our paper gives insight into the new model version. Methods The former fire-behaviour core, i.e. Fosberg’s Fire Weather Index (FWI), is replaced by the standardised fire-reaction intensity, a different fuel-moisture of extinction term, and a replica of the fire-spread rate of the Canadian FFBP-System. A standardised ease-of-ignition index is added as a measure of ignition success. The fire module is supplied with diurnal dead-grass fuel-moisture calculations based on the water-budget and energy-balance concept. Key results The GLFI output is compared with diurnal fuel-moisture measurements and results of Wotton’s Grass-Fuel-Moisture model, Fosberg’s FWI, and Cheney’s rate of spread equation. The GLFI computes periods with a high fuel moisture more realistically, whereas it exceeds Cheney’s rate-of-fire spread systematically at lower wind speeds, which leads to higher danger ratings during calm-air conditions (as requested by users). Conclusions and Implications The GLFI estimates dead-fuel moisture and fire danger on open, horizontal topography according to the current scientific level. Model extensions are necessary to run the model on complex topography under varying greenness and occasional frost conditions.

Measurement of Pyrolysis Properties for Fire Spread Simulation of Cables

The analysis and review of the thermal decomposition properties required for the fire spread simulation of cables composed of multiple materials were performed. Thus, a typical two-step pyrolysis reaction was identified independent of cable type. It is expected that the Kissinger and flynn–wall–ozawa (FWO) methods, which are calculated using various heating rates, more accurately predict fire spread than the input method that uses the and values calculated using a single heating rate. Consequently, in the case of flame-retardant cables (CLASS 1E and TFR-8), the Kissinger method is more likely to overestimate the fire spread rate than the FWO method. In the case of polyvinyl chloride (PVC) cables (vinyl cabtire power cable, VCTF), the fire spread rate may be underestimated.

Measurement of Pyrolysis Properties for Fire Spread Simulations of Spray Polyurethane Foam

In this study, measurements and a review of the pyrolysis properties required for fire spread simulations of rigid spray polyurethane foam (SPF) were performed. The change in the mass ratio of the hardener and resin during the foaming of the SPF had little effect on the reference temperature and reaction rate at which the pyrolysis reaction most actively occurred. As the heating rate increased in TGA, a higher pyrolysis reaction rate was predicted. The Kissinger method to calculate the activation energy (&lt;i&gt;E&lt;sub&gt;a&lt;/sub&gt;&lt;/i&gt;) under various heating rates was expected to more accurately predict fire spread phenomena compared to the method that applied &lt;i&gt;T&lt;sub&gt;p&lt;/sub&gt;&lt;/i&gt; and &lt;i&gt;r&lt;sub&gt;p&lt;/sub&gt;&lt;/i&gt; measured with a single heating rate. However, the &lt;i&gt;E&lt;sub&gt;a&lt;/sub&gt;&lt;/i&gt; determined by the Kissinger method was similar to the value at a degree of conversion of approximately 30% using the Flynn-Wall-Ozawa method. Consequently, considering the initial fire spread on the SPF surface, the Kissinger method could potentially overestimate the fire spread rate.

Characterization of land cover-specific fire regimes in the Brazilian Amazon

Humans profoundly alter fire regimes both directly, by introducing changes in fuel dynamics and ignitions, and indirectly, by increasing the release of greenhouse gases and aerosols from fires, which can alter regional climate and, as a consequence, modify fuel moisture and availability. Interactions between vegetation dynamics, regional climate change and anthropogenic pressure lead to high heterogeneity in the spatio-temporal fire distribution. We use the new FireTracks Scientific Dataset that tracks the spatio-temporal development of individual fires to analyse fire regimes in the Brazilian Legal Amazon over the period 2002–2020. We analyse fire size, duration, intensity and rate of spread in six different land-cover classes. Particular combinations of fire features determine the dominant and characteristic fire regime in each of them. We find that fires in savannas and evergreen forests burn the largest areas and are the most long lasting. Forest fires have the potential for burning at the highest intensities, whereas higher rates of spread are found in savannas. Woody savanna and grassland fires are usually affected by smaller, shorter, less-intense fires compared with fires in evergreen forest and savanna. However, fires in grasslands can burn at rates of spread as high as savanna fires as a result of the easily flammable fuel. We observe that fires in deciduous forests and croplands are generally small, short and low intense, although the latter can sustain high rates of spread due to the dry post-harvest residuals. The reconstructed fire regimes for each land cover can be used to improve the simulated fire characteristics by models and, thus, future projections.

Yangın Şiddetinin Uzaktan Algılama ve Coğrafi Bilgi Sistemleri ile Hesaplanması: 2021 Yılı Milas-Karacahisar Yangını

Aim of the study: The objective of this study is to calculate fireline intensity using remote sensing and geographic information systems, to investigate relationship between fireline intensity and VIIRS active fire data, and to develop a practical fireline intensity estimation model. Material and methods: The Visible Infrared Imaging Radiometer Suite (VIIRS) active fire/hotspot data provided by Suomi National Polar Orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration (NOAA-20) satellites were used to estimate the rate of fire spread. Fuel consumption was estimated using Sentinel-2 images, stand type maps and surface and available crown fuel loading models for Turkish red pine (Pinus brutia Ten.). The fireline intensity was then calculated using Byram’s (1959) fireline intensity equation. Main results: The results indicated that the number of VIIRS active fire data was well correlated with fireline intensity, rate of fire spread and fuel consumption. The calculated fireline intensity ranged between 175.0 and 47597.2 kW/m with an average value of 9280.4 kW/m. The number of VIIRS active fire data alone explained 72% of the variation in fireline intensity. Highlights: Satellite based products can be effectively used to calculate fireline intensity through estimating rate of fire spread and fuel consumption easily and effectively in burned areas.

Simulation of variations in the speed of fire propagation, during a prescribed burn

Fire behavior simulations are generally based on standardized models of forest fuels, which can hardly represent allpossible variations in forest ecosystems, which can result in biased estimates of fire behavior. Due to this, in the presentwork a comparative analysis of simulations of fire behavior (propagation rate [m/min]) is made, during the course of aprescribed burning in favor of the slope, in a pine-oak forest stand from the state of Chihuahua. These simulations varied inrelation to: a) fuel models; b) fuel loads; and c) wind speed. The models tested were: 1) the one that resulted from amultiple regression (considering temperature, relative humidity and slope); 2) the fuel model M-8 and its variant M-8R(includes the values of fuel charges obtained in the field); and 3) the fuel model M-9 and its variant M-9R (includes thevalues of fuel charges obtained in the field). The equations of the trends defined by the correlation between the relativehumidity (%) and the speed of fire propagation (m/min) were generated. Although neither model was found to bestatistically significant, the best fit was defined with the regression equation:, which can be used in apractical way for a rough estimation of the rate of fire spread (RP). It is concluded that, in general, the selected modelswere not appropriate for simulating fire behavior during prescribed burning. This highlights the need to generate specificfuel models for the analyzed vegetation and its variations in density, structure and composition

Fire behavior prediction with artificial intelligence in thinned black pine (Pinus nigra Arnold) stand

Modeling forest fire behavior is very important for the effective control of forest fires and the setting up of necessary precautions before fires start. However, studies of forest fire behavior are complex studies that depend on many variables and usually involve large data sets. For this reason, the predictive power and speed of classical forecasting models are lower than of artificial intelligence models in cases involving big data and many variables. Moreover, classical forecasting models must satisfy certain statistical assumptions, unlike artificial intelligence methods. Thus, in this study, predictions were made of surface fire behavior, especially the rate of fire spread and the fire intensity, at the location at which fires started using two artificial intelligence methods, an artificial neural network and a decision tree. The accuracy of the developed models was fitted and tested. Finally, the classical regression model for predicting surface fire behavior was compared with the two artificial intelligence methods. The accuracy measures of the artificial intelligence models were found to be better than those of the classical model.

Modelling decisions concerning the dispatch of airtankers for initial attack on forest fires in Ontario, Canada

Airtankers are commonly used for initial attack (IA) to reduce the likelihood of wildland fires escaping containment efforts. We examined IA airtanker dispatch decisions for forest fires in Ontario, Canada, through an analysis of historical fire records from 2001 to 2019. A hurdle modelling approach that predicts the probability of airtanker(s) being dispatched and then the number of airtankers sent was used. Two different hurdle models were considered depending on the timing of the information available to the decision maker: a “fire report model” based upon the information available when a fire is first reported, and an “initial attack model” using information available at the time IA action began. Both models indicated that the most influential covariates for airtanker dispatch are the fire weather index, fuel volatility, observed fire rate of spread, fire size at IA, and cause of ignition. When evaluating the predictive ability of the models on a validation data set, the “initial attack model” performed better than the “fire report model”. Our models generally perform well when predicting none, one, or two airtankers on IA, but they generally underpredict when more than two airtankers are dispatched, which suggests risk-averse decision-making in fire management resource dispatching.

Spatiotemporal patterns of fire-driven forest mortality in China

Wildfire is one of the most prevalent natural or human-induced disturbances across the world, which can kill trees directly during the active combustion phase or cause delayed forest mortality through interactions with other disturbance agents. With its diverse range of climate and forest ecosystems, China also has diverse forest fire regimes. However, the spatial and temporal patterns of fire-driven forest mortality on the national scale remain largely unexplored. In this study, we employed satellite observations and statistical models to investigate the spatiotemporal patterns and underlying drivers of fire-induced forest mortality across China. Our results demonstrate pronounced temporal patterns of forest burned area and fire-driven forest mortality. On the seasonal scale, forest fires mostly occurred in the winter and spring, whereas the forest mortality is highest from May to July. Both forest burned area and fire-driven mortality exhibited a significant decreasing trend during 2003–2016. Forest burned areas are mainly distributed in Northeast China, Southwest China and South China. There exists a tight spatial consistency between areas with high mortality and burned area with East China as an exception. Correlation analysis and multiple linear regression analysis show that fire size, fire spread rate, fire duration and drought intensity had significant impacts on postfire forest mortality, with fire size and fire spread rate accounting for 38.3% and 37.1%, respectively, of the model’s explanatory power. Our results highlight the importance of fire regime impacts on postfire forest mortality. Future climate change that drives more intense fire regimes might thus lead to enhanced forest mortality and increase the loss of forest ecosystem services.