International Journal of Wildland Fire最新文献

Wildfires are increasing in size and severity due to climate change combined with overstocked forests. Fire increases the likelihood of debris flows, posing significant threats to life, property, and water supplies.

We conducted a debris-flow hazard assessment of the Santa Fe Municipal Watershed (SFMW) to answer two questions: (1) where are debris flows most likely to occur; and (2) how much debris might they produce? We also document the influence of fuel treatments on fire severity and debris flows.

We modelled post-fire debris-flow likelihood and volume in 103 sub-basins for 2-year, 5-year, and Probable Maximum Precipitation rainfalls following modelled low-, moderate-, and high-severity wildfires.

Post-fire debris-flow likelihoods were >90% in all but the lowest fire and rain scenarios. Sub-basins with fuel treatments had the lowest burn severities, debris-flow likelihoods, and sediment volumes, but treatment effects decreased with increased fire severity and rain intensity.

Post-fire debris flows with varying debris volumes are likely to occur following wildfire in the SFMW, but fuel treatments can reduce likelihood and volume.

Future post-fire debris flows will continue to threaten water supplies, but fuel reduction treatments and debris-flow mitigation provide opportunities to minimise effects.

Indigenous fire management in northern Australian savannas (beginning at least 11,000 years ago) involved frequent, small, cool, early dry season fires. This fire regime changed after European arrival in the late 1700s to unmanaged fires that burn larger areas, late in the dry season, detrimental to carbon stocks and biodiversity.

Test the hypothesis that significant sequestration of pyrogenic carbon in soil accompanies the reimposition of an Indigenous fire regime.

Savanna soils under the same vegetation, but with the number of fires varying from 0 to 13 (irrespective of the season) between 2000 and 2022 were sampled. Organic and pyrogenic carbon stocks as well as carbon isotope composition of the 0–5 cm soil layer were determined along sample transects with varying fire return intervals.

An average increase of 0.25 MgC ha⁻¹ was observed in soil pyrogenic carbon stocks in transects with ≥5 fires, compared to transects with 0–4 fires, with a small increase in soil organic carbon stocks that was not significant.

A return to more frequent fires early in the dry season has the potential to sequester significant pyrogenic carbon in northern Australian savanna soils on decadal timescales.

Autumn and winter Santa Ana Winds (SAW) are responsible for the largest and most destructive wildfires in southern California.

(1) To contrast fires ignited on SAW days vs non-SAW days, (2) evaluate the predictive ability of the Canadian Fire Weather Index (CFWI) for these two fire types, and (3) determine climate and weather factors responsible for the largest wildfires.

CAL FIRE (California Department of Forestry and Fire Protection) FRAP (Fire and Resource Assessment Program) fire data were coupled with hourly climate data from four stations, and with regional indices of SAW wind speed, and with seasonal drought data from the Palmer Drought Severity Index.

Fires on non-SAW days were more numerous and burned more area, and were substantial from May to October. CFWI indices were tied to fire occurrence and size for both non-SAW and SAW days, and in the days following ignition. Multiple regression models for months with the greatest area burned explained up to a quarter of variation in area burned.

The drivers of fire size differ between non-SAW and SAW fires. The best predictor of fire size for non-SAW fires was drought during the prior 5 years, followed by a current year vapour pressure deficit. For SAW fires, wind speed followed by drought were most important.

Characterisation of fuel consumption provides critical insights into fire behaviour, effects, and emissions. Stand-replacing prescribed fire experiments in central Utah offered an opportunity to generate consumption estimates in coordination with other research efforts.

We sought to generate fuel consumption maps using pre- and post-fire airborne laser scanning (ALS) and ground measurements and to test the spatial transferability of the ALS-derived fuel models.

Using random forest (RF), we empirically modelled fuel load and estimated consumption from pre- and post-fire differences. We used cross-validation to assess RF model performance and test spatial transferability.

Consumption estimates for overstory fuels were more precise and accurate than for subcanopy fuels. Transferring RF models to provide consumption estimates in areas without ground training data resulted in loss of precision and accuracy.

Fuel consumption maps were produced and are available for researchers who collected coincident fire behaviour, effects, and emissions data. The precision and accuracy of these data vary by fuel type. Transferability of the models to novel areas depends on the user’s tolerance for error.

This study fills a critical need in the broader set of research efforts linking fire behaviour, effects, and emissions.

The expanding use of Uncrewed Aircraft System (UAS) technology in disaster response shows its immense potential to enhance emergency management. However, there is limited documentation on the challenges and data management procedures related to UAS operation.

This manuscript documents and analyses the operational, technical, political, and social challenges encountered during the deployment of UAS, providing insights into the complexities of using these technologies in disaster situations.

This manuscript documents and analyses the operational, technical, political, and social challenges encountered during the deployment of UAS, providing insights into the complexities of using these technologies in disaster situations.

UAS technology plays a significant role in search and rescue, reconnaissance, mapping, and damage assessment, alongside notable challenges such as extreme flying conditions, data processing difficulties, and airspace authorisation complexities.

The study concludes with the need for updated infrastructure standards, streamlined policies, and better coordination between technological advancements and political processes, emphasising the necessity for reform to enhance disaster response capabilities.

The findings of this study inform future guidelines for the effective and safe use of UAS in disaster situations, advocating for a bridge between state-of-the-art UAS research and its practical application in emergency response.

The extent of past Indigenous cultural burning in the eastern US remains contested. Historical documents (e.g. early histories, journals, and reports) contain descriptions of burning. Scholars have summarised descriptions, but few have compiled them into databases.

This paper presents efforts to compile descriptions of past Indigenous burning in the eastern US and early results from mapped descriptions.

Utilising previously cited descriptions and those discovered from digitised historical texts, the current dataset mapped >250 descriptions of burning in the northeastern US. Most were historical summaries from 19th century authors, and fewer were firsthand observations. Descriptions are currently shared as a GIS data layer, a tabular file, and an interactive web map.

Descriptions correspond with fire-adapted vegetation, and clusters of descriptions suggest burning over large extents (e.g. southern New England, western New York). Estimated dates of burning or initial Euro-American settlement show an east–west succession in Indigenous fire exclusion and replacement with early Euro-American burning.

Historical descriptions suggest regional-extent influence of Indigenous burning upon past forested ecosystems, but the veracity of descriptions should be carefully evaluated.

This study provides a dataset for further examination of Indigenous burning and comparison with other methodologies for historical cultural fire reconstruction.

As fire seasons in the Western US intensify and lengthen, fire managers have been grappling with increases in simultaneous, significant incidents that compete for response resources and strain capacity of the current system.

To address this challenge, we explore a key research question: what precursors are associated with ignitions that evolve into incidents requiring high levels of response personnel?

We develop statistical models linking human, fire weather and fuels related factors with cumulative and peak personnel deployed.

Our analysis generates statistically significant models for personnel deployment based on precursors observable at the time and place of ignition.

We find that significant precursors for fire suppression resource deployment are location, fire weather, canopy cover, Wildland–Urban Interface category, and history of past fire. These results align partially with, but are distinct from, results of earlier research modelling expenditures related to suppression which include precursors such as total burned area which become observable only after an incident.

Understanding factors associated with both the natural system and the human system of decision-making that accompany high deployment fires supports holistic risk management given increasing simultaneity of ignitions and competition for resources for both fuel treatment and wildfire response.

Intentional management of naturally ignited wildfires has emerged as a valuable tool for addressing the social and ecological consequences of a century of fire exclusion in policy and practice. Policy in the United States now allows wildfires to be managed for suppression and other than full suppression (OTFS) objectives simultaneously, giving flexibility to local decision makers.

To extend existing research on the history of wildfire management, investigate how wildfire professionals interpret current policy with respect to OTFS management, and better understand how they translate policy into implementation.

Interviews were conducted in south-west United States with wildfire professionals to explore policy’s impact on OTFS management.

Respondents reported that while flexible federal policy and interagency guidance was important, suitable landscape conditions, organisational capacity, support from national and regional leadership, updated management plans, increased monitoring capacity, and adequate performance measures also influence the decision to use OTFS strategies.

Translating flexible options into feasible operations requires aligning many layers of policy and people using proactive, collaborative, ongoing preparation.

Our research may prompt targeted discussions between management agencies and policymakers to determine how to best support successful management of wildfires OTFS.

Calculating greenhouse gas emissions from fires relies on estimation of available fuels at time of burn. Fuel accumulation and decomposition occur throughout the year, with seasonality of decomposition poorly researched in monsoonal Australia.

We investigate the decomposition and accumulation of litter fuels (leaves, twigs), and coarse woody debris (CWD >6 mm–<5 cm diameter) across a full monsoonal cycle.

The study was undertaken at three sites in long unburned (10 years+) eucalypts-dominated mesic savanna woodland. For measuring decomposition, twelve 50 g samples of leaves and twigs were placed in situ on the soil surface, with one sample removed and dried each month; one sample of CWD was tested after 12 months. Fine fuel accumulation was recorded monthly.

Significant statistical relationships were observed between soil moisture and leaf decomposition. Across the study period 66% of leaves, 35% of twig, and 27.2% of CWD decomposed. Fine fuel accumulation was consistent with previous studies and peaking in August. Combining monthly rates of accumulation and decomposition, net fine fuel loads were observed to be much greater late in the dry season.

The present study provides enhanced fine fuel load calculations by including seasonality of decomposition which allows for better estimates of emissions from savanna fires.

Wildfire fuels are commonly mapped via manual interpretation of aerial photos. Alternatively, RGB satellite imagery offers data across large spatial extents. A method of individual tree detection and classification is developed with implications to fuel mapping and community wildfire exposure assessments.

Convolutional neural networks are trained using a novel generational training process to detect trees in 0.50 m/px RGB imagery collected in Rocky Mountain and Boreal natural regions in Alberta, Canada by Pleiades-1 and WorldView-2 satellites. The workflow classifies detected trees as ‘green-in-winter’/‘brown-in-winter’, a proxy for coniferous/deciduous, respectively.

A k-fold testing procedure compares algorithm detections to manual tree identification densities reaching an R² of 0.82. The generational training process increased achieved R² by 0.23. To assess classification accuracy, satellite detections are compared to manual annotations of 2 cm/px drone imagery resulting in average F1 scores of 0.85 and 0.82 for coniferous and deciduous trees respectively. The use of model outputs in tree density mapping and community-scale wildfire exposure assessments is demonstrated.

The proposed workflow automates fine-scale overstorey tree mapping anywhere seasonal (winter and summer) 0.50 m/px RGB satellite imagery exists. Further development could enable the extraction of additional properties to inform a more complete fuel map.