International Journal of Wildland Fire最新文献

To effectively reduce future wildfire risk, several management strategies must be evaluated under plausible future scenarios, requiring models that provide estimates of how likely wildfires are to spread to community assets (wildfire likelihood) in a computationally efficient manner. Approaches to quantifying wildfire likelihood using fire simulation models cannot practically achieve this because they are too computationally expensive.

This study aimed to develop an approach for quantifying wildfire likelihood that is both computationally efficient and able to consider contagious and directionally specific fire behaviour properties across multiple spatial ‘neighbourhood’ scales.

A novel, computationally efficient index for quantifying wildfire likelihood is proposed. This index is evaluated against historical and simulated data on a case study in South Australia.

The neighbourhood index explains historical burnt areas and closely replicates patterns in burn probability calculated using landscape fire simulation (ρ = 0.83), while requiring 99.7% less computational time than the simulation-based model.

The neighbourhood index represents patterns in wildfire likelihood similar to those represented in burn probability, with a much-reduced computational time.

By using the index alongside existing approaches, managers can better explore problems involving many evaluations of wildfire likelihood, thereby improving planning processes and reducing future wildfire risks.

Spot fires play a significant role in the rapid spread of wildland and wildland–urban interface fires.

This paper presents an experimental and modelling study on the flaming and smouldering burning of wood firebrands under forced convection.

The firebrand burning experiments were conducted with different wind speeds and firebrand sizes.

The burning rate of firebrands under forced convection is quantified by wood pyrolysis rate, char oxidation rate and a convective term. The firebrand projected area is correlated with firebrand diameter, char density, wind speed, and flaming or smouldering burning. A surface temperature model is derived in terms of condensed-phase energy conservation. We finally establish a simplified firebrand transport model based on the burning rate, projected area and surface temperature of firebrands.

The mass loss due to wood pyrolysis is much greater than that due to char oxidation in self-sustaining burning. The burning rate is proportional to U^1/2, where U is wind speed. The projected area for flaming firebrands decreases more rapidly than that for smouldering ones. The firebrand surface temperature is mainly determined by radiation.

Knowledge about firebrand burning characteristics is essential for predicting the flight distance and trajectory in firebrand transport.

Fire behaviour assessments of past wildfire events have major implications for anticipating post-fire ecosystem responses and fuel treatments to mitigate extreme fire behaviour of subsequent wildfires.

This study evaluates for the first time the potential of remote sensing techniques to provide explicit estimates of fire type (surface fire, intermittent crown fire, and continuous crown fire) in Mediterranean ecosystems.

Random Forest classification was used to assess the capability of spectral indices and multiple endmember spectral mixture analysis (MESMA) image fractions (char, photosynthetic vegetation, non-photosynthetic vegetation) retrieved from Sentinel-2 data to predict fire type across four large wildfires

MESMA fraction images procured more accurate fire type estimates in broadleaf and conifer forests than spectral indices, without remarkable confusion among fire types. High crown fire likelihood in conifer and broadleaf forests was linked to a post-fire MESMA char fractional cover of about 0.8, providing a direct physical interpretation.

Intrinsic biophysical characteristics such as the fractional cover of char retrieved from sub-pixel techniques with physical basis are accurate to assess fire type given the direct physical interpretation.

MESMA may be leveraged by land managers to determine fire type across large areas, but further validation with field data is advised.

Fire simulators are increasingly used to predict fire spread. Australian fire agencies have been concerned at not having an objective basis to choose simulators for this purpose.

We evaluated wildland fire simulators currently used in Australia: Australis, Phoenix, Prometheus and Spark. The evaluation results are outlined here, together with the evaluation framework.

Spatial metrics and visual aids were designed in consultation with simulator end-users to assess simulator performance. Simulations were compared against observations of fire progression data from 10 Australian historical fire case studies. For each case, baseline simulations were produced using as inputs fire ignition and fuel data together with gridded weather forecasts available at the time of the fire. Perturbed simulations supplemented baseline simulations to explore simulator sensitivity to input uncertainty.

Each simulator showed strengths and weaknesses. Some simulators displayed greater sensitivity to different parameters under certain conditions.

No simulator was clearly superior to others. The evaluation framework developed can facilitate future assessment of Australian fire simulators.

Collection of fire behaviour observations for routine simulator evaluation using this framework would benefit future simulator development.

Tropical savannas represent a large proportion of the area burnt each year globally, with growing evidence that management to curtail fire frequency and intensity in some of these regions can contribute to mitigation of climate change. Approximately 25% of Australia’s fire-prone tropical savanna region is currently managed for carbon projects, contributing significantly to Australia’s National Greenhouse Gas Inventory.

To improve the accuracy of Australia’s national carbon accounting model (FullCAM) for reporting of fire emissions and sequestration of carbon in savanna ecosystems.

Field data from Australian savannas were collated and used to calibrate FullCAM parameters for the prediction of living biomass, standing dead biomass and debris within seven broad vegetation types.

Revised parameter sets and improved predictions of carbon stocks and fluxes across Australia’s savanna ecosystems in response to wildfire and planned fire were obtained.

The FullCAM model was successfully calibrated to include fire impacts and post-fire recovery in savanna ecosystems.

This study has expanded the capability of FullCAM to simulate both reduced emissions and increased sequestration of carbon in response to management of fire in tropical savanna regions of Australia, with implications for carbon accounting at national and project scales.

Extreme wildfires have increased in recent decades, yet the consequences of extreme fire behaviour are not fully comprehended. The study of prescribed burning provides opportunities to advance understanding of some overlooked processes in fire behaviour, such as the role of the release of volatile organic compounds (VOC).

The aim of this study was to assess VOC (α-pinene, β-pinene, and limonene), NH₃, CO and CO₂ emissions during prescribed fires in pine barrens vegetation at the Albany Pine Bush Preserve, USA.

Measurements performed by open-path Fourier transform infra-red spectroscopy (OP-FTIR) quantified VOC concentrations and characterised emissions during four independent prescribed burns.

Combustion products (e.g. CO₂, CO, CH₄) and VOC exhibited similar emission behaviour during thermal degradation, though VOC concentrations appeared to be independent of the type of biomass burned, unlike those of combustion products; Pinus strobus L. emitted two orders of magnitude higher than Pinus rigida Mill.; VOC and CO are statistically correlated (R² = 0.84).

These results confirmed that OP-FTIR is a feasible approach for gathering qualitative and quantitative information regarding VOC emission during prescribed fires.

Quantification of VOC concentrations during prescribed fires helps characterise its relationships with greenhouse gas emissions (e.g. CO₂ and CO) at different burning conditions (e.g. wind, biomass type), which could be incorporated into existing fire behaviour models to enhance their ability to better predict fire propagation.

The Australian Fire Danger Rating System (AFDRS) was implemented operationally throughout Australia in September 2022, providing calculation of fire danger forecasts based on peer-reviewed fire behaviour models. The system is modular and allows for ongoing incorporation of new scientific research and improved datasets.

Prior to operational implementation of the AFDRS, a Research Prototype (AFDRS_RP), described here, was built to test the input data and systems and evaluate the performance and potential outputs.

Fire spread models were selected and aligned with fuel types in a process that captured bioregional variation in fuel characteristics. National spatial datasets were created to identify fuel types and fire history in alignment with existing spatial weather forecast layers.

The AFDRS_RP demonstrated improvements over the McArthur Forest and Grass Fire Danger systems due to its use of improved fire behaviour models, as well as more accurately reflecting the variation in fuels.

The system design was robust and allowed for the incorporation of updates to the models and datasets prior to implementation of the AFDRS.

Wildfires represent a significant threat to peatlands globally, but whether peat fires can be initiated by a lofted firebrand is still unknown.

We investigated the ignition threshold of peat fires by a glowing firebrand through laboratory-scale experiments.

The oven-dried weight (ODW) moisture content (MC) of peat samples varied from 5% ODW to 100% ODW, and external wind (ν) with velocities up to 1 m/s was provided in a wind tunnel.

When MC < 35%, ignition is always achieved, regardless of wind velocity. However, if MC is between 35 and 85%, an external wind (increasing with peat moisture) is required to increase the reaction rate of the firebrand and thus heating to the peat sample. Further increasing the MC to be higher than 85%, no ignition could be achieved by a single laboratory firebrand. Finally, derived from the experimental results, a 90% ignition probability curve was produced by a logistic regression model.

This work indicates the importance of maintaining a high moisture content of peat to prevent ignition by firebrands and helps us better understand the progression of large peat fires.

The prediction accuracy for the rate of surface fire spread varies in different regions; thus, increasing the prediction accuracy for local fuel types to reduce the destructive consequences of fire is critically needed.

The objective of this study is to improve the Rothermel model’s accuracy in predicting the ROS for surface fuel burning in planted forests of Pinus koraiensis in the eastern mountains of north-east China.

Fuel beds with various fuel loads and moisture content was constructed on a laboratory burning bed, 276 combustion experiments were performed under multiple slope conditions, and the ROS data from the combustion experiments were used to modify the related parameters in the Rothermel model.

The surface fire spread rate in Pinus koraiensis plantations was directly predicted using the Rothermel model but had significant errors. The Rothermel model after modification predicted the following: MRE = 25.09%, MAE = 0.46 m min⁻¹, and R² = 0.80.

The prediction accuracy of the Rothermel model was greatly enhanced through parameter tuning based on in-lab combustion experiments

This study provides a method for the local application of the Rothermel model in China and helps with forest fire fighting and management in China.

Geodiversity elements contribute significantly to local and global hydrological, biogeochemical and ecosystem services and as such, fire is a potentially disruptive force with long-term implications. from limiting karstic speleothems formation, to compounding impacts of peat-fire-erosion cycles. Geodiversity elements additionally possess important cultural, aesthetic, and environmental values, including the support of ecosystem services. Hence, assessments of potential fire damage should consider implications for land users, society, and culture, alongside the geomorphic impacts on geodiversity elements. With a view to providing a concise set of descriptors of the response of geodiversity elements to fire, we qualify and in places, quantify, how fire may degrade geosystem function. Where possible, we highlight the influence of fire intensity and frequency gradients, and cumulative fire, in the deterioration of geodiversity values. Geoconservation is integral to protected areas with implications from fire effected geodiversity functions and values presenting issues for management, with potential consequences extending through to delisting, degazetting, and resizing of protected areas. Future research in reserve systems should concentrate on understanding the synergistic and compounding effects of fire on the geophysical landscape.