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Ott, Cory W., Bishrant Adhikari, Simon P. Alexander, Paddington Hodza, Chen Xu, and Thomas A. Minckley. "Predicting Fire Propagation across Heterogeneous Landscapes Using WyoFire: A Monte Carlo-Driven Wildfire Model." Fire 3, no. 4 (December 11, 2020): 71. http://dx.doi.org/10.3390/fire3040071.
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The scope of wildfires over the previous decade has brought these natural hazards to the forefront of risk management. Wildfires threaten human health, safety, and property, and there is a need for comprehensive and readily usable wildfire simulation platforms that can be applied effectively by wildfire experts to help preserve physical infrastructure, biodiversity, and landscape integrity. Evaluating such platforms is important, particularly in determining the platforms’ reliability in forecasting the spatiotemporal trajectories of wildfire events. This study evaluated the predictive performance of a wildfire simulation platform that implements a Monte Carlo-based wildfire model called WyoFire. WyoFire was used to predict the growth of 10 wildfires that occurred in Wyoming, USA, in 2017 and 2019. The predictive quality of this model was determined by comparing disagreement and agreement areas between the observed and simulated wildfire boundaries. Overestimation–underestimation was greatest in grassland fires (>32) and lowest in mixed-forest, woodland, and shrub-steppe fires (<−2.5). Spatial and statistical analyses of observed and predicted fire perimeters were conducted to measure the accuracy of the predicated outputs. The results indicate that simulations of wildfires that occurred in shrubland- and grassland-dominated environments had the tendency to over-predict, while simulations of fires that took place within forested and woodland-dominated environments displayed the tendency to under-predict.
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Salis, Michele, Alan A. Ager, Bachisio Arca, Mark A. Finney, Valentina Bacciu, Pierpaolo Duce, and Donatella Spano. "Assessing exposure of human and ecological values to wildfire in Sardinia, Italy." International Journal of Wildland Fire 22, no. 4 (2013): 549. http://dx.doi.org/10.1071/wf11060.
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We used simulation modelling to analyse spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational values and highly valued agricultural areas that are increasingly being threatened by severe wildfires. Historical fire data and wildfire simulations were used to estimate burn probabilities, flame length and fire size. We examined how these risk factors varied among and within highly valued features located on the island. Estimates of burn probability excluding non-burnable fuels, ranged from 0–1.92 × 10–3, with a mean value of 6.48 × 10–5. Spatial patterns in modelled outputs were strongly related to fuel loadings, although topographic and other influences were apparent. Wide variation was observed among the land parcels for all the key values, providing a quantitative approach to inform wildfire risk management activities.
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Kelso, Joel K., Drew Mellor, Mary E. Murphy, and George J. Milne. "Techniques for evaluating wildfire simulators via the simulation of historical fires using the AUSTRALIS simulator." International Journal of Wildland Fire 24, no. 6 (2015): 784. http://dx.doi.org/10.1071/wf14047.
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A methodology for validating fire spread simulation systems using historical fire data is presented. The key features of this methodology are (a) quantitative comparison between simulator-generated fire perimeters and fire perimeters from an independently produced fire reconstruction at multiple time points during the fire, and (b) extensive sensitivity analyses on simulation variables including simulation spatial resolution, weather, vegetation coverage and fire behaviour model selection to determine the effect of each simulation input on the simulation output. The methodology is demonstrated in a case study in which the ability of the Australis high-performance wildfire simulator to replicate a large wildfire in Western Australia was examined. Simulation accuracy was found to be lower in extreme fire danger conditions and exhibited under-prediction of the head fire rate of spread. This was caused by inaccuracies in at least one of wind speed data, vegetation data or the fire behaviour model applied; however, the source of the inaccuracy could not be further diagnosed with the available data. The gathering of accurate data during and after active wildfires would facilitate more rigorous simulator and fire behaviour model validation studies as well as more accurate prediction of ‘live’ wildfires.
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Parisien, Marc-André, Denyse A. Dawe, Carol Miller, Christopher A. Stockdale, and O. Bradley Armitage. "Applications of simulation-based burn probability modelling: a review." International Journal of Wildland Fire 28, no. 12 (2019): 913. http://dx.doi.org/10.1071/wf19069.
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Wildland fire scientists and land managers working in fire-prone areas require spatial estimates of wildfire potential. To fulfill this need, a simulation-modelling approach was developed whereby multiple individual wildfires are modelled in an iterative fashion across a landscape to obtain location-based measures of fire likelihood and fire behaviour (e.g. fire intensity, biomass consumption). This method, termed burn probability (BP) modelling, takes advantage of fire spread algorithms created for operational uses and the proliferation of available data representing wildfire patterns, fuels and weather. This review describes this approach and provides an overview of its applications in wildland fire research, risk analysis and land management. We broadly classify the application of BP models as (1) direct examination, (2) neighbourhood processes, (3) fire hazard and risk and (4) integration with secondary models. Direct examination analyses are those that require no further processing of model outputs; they range from a simple visual examination of outputs to an assessment of alternate states (i.e. scenarios). Neighbourhood process analyses examine patterns of fire ignitions and subsequent spread across land designations. Fire hazard combines fire probability and a quantitative assessment of fire behaviour, whereas risk is the product of fire likelihood and potential impacts of wildfire. The integration with secondary models represents situations where BP model outputs are integrated into, or used in conjunction with, other models or modelling platforms.
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Filippi, Jean-Baptiste, Vivien Mallet, and Bahaa Nader. "Representation and evaluation of wildfire propagation simulations." International Journal of Wildland Fire 23, no. 1 (2014): 46. http://dx.doi.org/10.1071/wf12202.
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This paper provides a formal mathematical representation of a wildfire simulation, reviews the most common scoring methods using this formalism, and proposes new methods that are explicitly designed to evaluate a forest fire simulation from ignition to extinction. These scoring or agreement methods are tested with synthetic cases in order to expose strengths and weaknesses, and with more complex fire simulations using real observations. An implementation of the methods is provided as well as an overview of the software package. The paper stresses the importance of scores that can evaluate the dynamics of a simulation, as opposed to methods relying on snapshots of the burned surfaces computed by the model. The two new methods, arrival time agreement and shape agreement, take into account the dynamics of the simulation between observation times. Although no scoring method is able to perfectly synthesise a simulation error in a single number, the analysis of the scores obtained on idealised and real simulations provides insights into the advantages of these methods for the evaluation of fire dynamics.
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McEvoy, Andy, Max Nielsen-Pincus, Andrés Holz, Arielle J. Catalano, and Kelly E. Gleason. "Projected Impact of Mid-21st Century Climate Change on Wildfire Hazard in a Major Urban Watershed outside Portland, Oregon USA." Fire 3, no. 4 (December 8, 2020): 70. http://dx.doi.org/10.3390/fire3040070.
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Characterizing wildfire regimes where wildfires are uncommon is challenged by a lack of empirical information. Moreover, climate change is projected to lead to increasingly frequent wildfires and additional annual area burned in forests historically characterized by long fire return intervals. Western Oregon and Washington, USA (westside) have experienced few large wildfires (fires greater than 100 hectares) the past century and are characterized to infrequent large fires with return intervals greater than 500 years. We evaluated impacts of climate change on wildfire hazard in a major urban watershed outside Portland, OR, USA. We simulated wildfire occurrence and fire regime characteristics under contemporary conditions (1992–2015) and four mid-century (2040–2069) scenarios using Representative Concentration Pathway (RCP) 8.5. Simulated mid-century fire seasons expanded in most scenarios, in some cases by nearly two months. In all scenarios, average fire size and frequency projections increased significantly. Fire regime characteristics under the hottest and driest mid-century scenarios illustrate novel disturbance regimes which could result in permanent changes to forest structure and composition and the provision of ecosystem services. Managers and planners can use the range of modeled outputs and simulation results to inform robust strategies for climate adaptation and risk mitigation.
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Hoang, Roger V., Matthew R. Sgambati, Timothy J. Brown, Daniel S. Coming, and Frederick C. Harris. "VFire: Immersive wildfire simulation and visualization." Computers & Graphics 34, no. 6 (December 2010): 655–64. http://dx.doi.org/10.1016/j.cag.2010.09.014.
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Benali, Akli, Ana C. L. Sá, João Pinho, Paulo M. Fernandes, and José M. C. Pereira. "Understanding the Impact of Different Landscape-Level Fuel Management Strategies on Wildfire Hazard in Central Portugal." Forests 12, no. 5 (April 23, 2021): 522. http://dx.doi.org/10.3390/f12050522.
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The extreme 2017 fire season in Portugal led to widespread recognition of the need for a paradigm shift in forest and wildfire management. We focused our study on Alvares, a parish in central Portugal located in a fire-prone area, which had 60% of its area burned in 2017. We evaluated how different fuel treatment strategies may reduce wildfire hazard in Alvares through (i) a fuel break network with different extents corresponding to different levels of priority and (ii) random fuel treatments resulting from a potential increase in stand-level management intensity. To assess this, we developed a stochastic wildfire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast and center-east areas of the parish that are very often associated with high fireline intensities. The different fuel treatment scenarios decreased burned area between 12.1–31.2%, resulting from 1–4.6% increases in the annual treatment area and reduced the likelihood of wildfires larger than 5000 ha by 10–40%. On average, simulated burned area decreased 0.22% per each ha treated, and cost-effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.
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Prestemon, Jeffrey P., David T. Butry, and Douglas S. Thomas. "The net benefits of human-ignited wildfire forecasting: the case of tribal land units in the United States." International Journal of Wildland Fire 25, no. 4 (2016): 390. http://dx.doi.org/10.1071/wf15128.
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Research shows that some categories of human-ignited wildfires may be forecastable, owing to their temporal clustering, with the possibility that resources could be predeployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an autoregressive conditional Poisson model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared with alternatives, and the simplest of the autoregressive conditional Poisson models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law-enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires.
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Xofis, Panteleimon, Pavlos Konstantinidis, Iakovos Papadopoulos, and Georgios Tsiourlis. "Integrating Remote Sensing Methods and Fire Simulation Models to Estimate Fire Hazard in a South-East Mediterranean Protected Area." Fire 3, no. 3 (July 19, 2020): 31. http://dx.doi.org/10.3390/fire3030031.
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Unlike low intensity fire which promotes landscape heterogeneity and important ecosystem services, large high-intensity wildfires constitute a significant destructive factor despite the increased amount of resources allocated to fire suppression and the improvement of firefighting tactics and levels of organization. Wildfires also affect properties, while an increasing number of fatalities are also associated with wildfires. It is now widely accepted that an effective wildfire management strategy can no longer rely on fire suppression alone. Scientific advances on fire behavior simulation and the increasing availability of remote sensing data, along with advanced systems of fire detection can significantly reduce fire hazards. In the current study remote sensing data and methods, and fire behavior simulation models are integrated to assess the fire hazard in a protected area of the southeast Mediterranean region and its surroundings. A spatially explicit fire hazard index was generated by combining fire intensity estimations and proxies of fire ignition probability. The results suggest that more than 50% of the study area, and the great majority of the protected area, is facing an extremely high hazard for a high-intensity fire. Pine forest formations, characterized by high flammability, low canopy base height and a dense shrub understory are facing the most critical hazard. The results are discussed in relation to the need for adopting an alternative wildfire management strategy.
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Alhaj-Khalaf, Mhd Wathek. "Improved forest fire spread mapping by developing custom fire fuel models in replanted forests in Hyrcanian forests, Iran." Forest Systems 30, no. 2 (August 2021): e008-e008. http://dx.doi.org/10.5424/fs/2021302-17980.
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Aim of the study: Forest fuel classification and characterization is a critical factor in wildfire management. The main purpose of this study was to develop custom fuel models for accurately mapping wildfire spread compared to standard models. Area of study: The study was conducted at a replanted forest dominated by coniferous species, in the Arabdagh region, Golestan Province, northern Iran. Material and methods: Six custom fuel models were developed to characterize the main vegetation types in the study area. Fuel samples were collected from 49 randomly selected plots. In each plot, the fuel load of 1-hr, 10-hr, 100-hr, 1000-hr, live herbs, live woody plants, surface area volume ratio, and fuel depth were estimated using the Fuel Load (FL) sampling method along three transects. Canopy fuel load was calculated for each fuel model. The performance of the custom fuel models versus standard fuel models on wildfire behavior simulations was compared using the FlamMap MTT simulator. Main results: The results showed that, despite the similarity in the burned area between observed and modeled fires, the custom fuel models produced an increase in simulation accuracy. Compared to the observed fire, simulation results did not give realistic results to the crown fire. The simulation using standard fuel models did not result in crown fire, while the simulation using custom fuel models showed a moderate rate of crown fire with a Kappa coefficient of 0.54. Research highlights: The results demonstrated the importance of developing custom fuel models to simulate wildfire maps with higher accuracy for wildfire risk management.
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Linn, Rodman, Jon Reisner, Jonah J. Colman, and Judith Winterkamp. "Studying wildfire behavior using FIRETEC." International Journal of Wildland Fire 11, no. 4 (2002): 233. http://dx.doi.org/10.1071/wf02007.
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A coupled atmospheric/wildfire behavior model is described that utilizes physics-based process models to represent wildfire behavior. Five simulations are presented, four of which are highly idealized situations that are meant to illustrate some of the dependencies of the model on environmental conditions. The fifth simulation consists of a fire burning in complex terrain with non-homogeneous vegetation and realistic meteorological conditions. The simulated fire behavior develops out of the coupling of a set of very complex processes and not from prescribed rules based on empirical data. This represents a new direction in wildfire modeling that we believe will eventually help decision makers and land managers do their jobs more effectively.
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Srivastava, Anurag, Joan Q. Wu, William J. Elliot, Erin S. Brooks, and Dennis C. Flanagan. "A Simulation Study to Estimate Effects of Wildfire and Forest Management on Hydrology and Sediment in a Forested Watershed, Northwestern U.S." Transactions of the ASABE 61, no. 5 (2018): 1579–601. http://dx.doi.org/10.13031/trans.12326.
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Abstract. Suitable fuel reduction treatments are needed in the Colville National Forest, Washington, to reduce the risk of severe wildfire. This study aimed to identify high-risk erosion hillslopes following wildfire to aid in forest fuel reduction planning and to evaluate the effects of fuel treatments on the watershed hydrological response. The specific objectives were (1) to assess the soil burn severity associated with wildfires and use that information to identify critical hillslopes for forest fuel treatments, and (2) to evaluate the potential changes in water yield and peak flows from pre-treatment (undisturbed forest) to post-treatment (thinning and prescribed burn) conditions, in the East Deer Creek Watershed (EDCW), a subwatershed of the Colville National Forest. Assessments were made using a modeling approach for hypothetical wildfire and fuel treatment scenarios. FlamMap, a fire behavior model, was used to predict the spatial distribution of wildfire intensity for a hypothetical event under current vegetation conditions. WEPP simulations were subsequently completed to obtain sediment and water yields based on fire intensity and topography. WEPP erosion estimations following a simulated wildfire showed hillslope sediment yield varying from 0 to 49.4 Mg ha-1 year-1 from the 777 hillslopes, which were ranked in descending order of sediment yield to identify critical hillslopes for fuel treatments. The WEPP model calibrated for a nearby gauged watershed was then applied to the EDCW for pre-treatment and post-treatment conditions. At the watershed scale, the increase in water yield from pre-treatment to post-treatment conditions ranged from 0.7% to 5.6% on hillslopes delivering 10% to 50% of the predicted post-fire sediment. Simulated water balance components at the treated hillslopes showed substantial changes. Surface runoff, subsurface lateral flow, and deep percolation increased 150% (5 mm), 50% (9 mm), and 40% (41 mm), respectively, whereas evapotranspiration (ET) decreased 23% (124 mm). The relative differences between pre- and post-harvest peak flows showed no clear trends as treatment area increased. The results suggest that thinning and prescribed burns to treated hillslopes in the EDCW may lead to an increase in water yield and significant alterations in hydrological processes. Keywords: Fuel treatments, Modeling, Peak flows, Sediment, Water yield, Wildfire.
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Adame, Patricia, Isabel Cañellas, Daniel Moreno-Fernández, Tuula Packalen, Laura Hernández, and Iciar Alberdi. "Analyzing the Joint Effect of Forest Management and Wildfires on Living Biomass and Carbon Stocks in Spanish Forests." Forests 11, no. 11 (November 19, 2020): 1219. http://dx.doi.org/10.3390/f11111219.
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Research Highlights: This is the first study that has considered forest management and wildfires in the balance of living biomass and carbon stored in Mediterranean forests. Background and Objectives: The Kyoto Protocol and Paris Agreement request countries to estimate and report carbon emissions and removals from the forest in a transparent and reliable way. The aim of this study is to forecast the carbon stored in the living biomass of Spanish forests for the period 2000–2050 under two forest management alternatives and three forest wildfires scenarios. Materials and Methods: To produce these estimates, we rely on data from the Spanish National Forest Inventory (SNFI) and we use the European Forestry Dynamics Model (EFDM). SNFI plots were classified according to five static (forest type, known land-use restrictions, ownership, stand structure and bioclimatic region) and two dynamic factors (quadratic mean diameter and total volume). The results were validated using data from the latest SNFI cycle (20-year simulation). Results: The increase in wildfire occurrence will lead to a decrease in biomass/carbon between 2000 and 2050 of up to 22.7% in the medium–low greenhouse gas emissions scenario (B2 scenario) and of up to 32.8% in the medium–high greenhouse gas emissions scenario (A2 scenario). Schoolbook allocation management could buffer up to 3% of wildfire carbon loss. The most stable forest type under both wildfire scenarios are Dehesas. As regards bioregions, the Macaronesian area is the most affected and the Alpine region, the least affected. Our validation test revealed a total volume underestimation of 2.2% in 20 years. Conclusions: Forest wildfire scenarios provide more realistic simulations in Mediterranean forests. The results show the potential benefit of forest management, with slightly better results in schoolbook forest management compared to business-as-usual forest management. The EFDM harmonized approach simulates the capacity of forests to store carbon under different scenarios at national scale in Spain, providing important information for optimal decision-making on forest-related policies.
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Hu, Xiaolin, and Lewis Ntaimo. "Integrated simulation and optimization for wildfire containment." ACM Transactions on Modeling and Computer Simulation 19, no. 4 (October 2009): 1–29. http://dx.doi.org/10.1145/1596519.1596524.
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Bakhshaii, Atoossa, Edward A. Johnson, and Kiana Nayebi. "Wildfire Pyroconvection and CAPE: Buoyancy’s Drying and Atmospheric Intensification—Fort McMurray." Atmosphere 11, no. 7 (July 18, 2020): 763. http://dx.doi.org/10.3390/atmos11070763.
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The accurate prediction of wildfire behavior and spread is possible only when fire and atmosphere simulations are coupled. In this work, we present a mechanism that causes a small fire to intensify by altering the atmosphere. These alterations are caused by fire-related fluxes at the surface. The fire plume and fluxes increase the convective available potential energy (CAPE) and the chance of the development of a strong pyroconvection system. To study this possible mechanism, we used WRF-Fire to capture fire line propagation as the result of interactions between heat and moisture fluxes, pressure perturbations, wind shear development and dry air downdraft. The wind patterns and dynamics of the pyroconvection system are simulated for the Horse River wildfire at Fort McMurray, Canada. The results revealed that the updraft speed reached up to 12 m/s. The entrainment mixed the mid and upper-level dry air and lowered the atmospheric moisture. The mid-level and upper-level dew point temperature changed by 5–10 ∘ C in a short period of time. The buoyant air strengthened the ascent as soon as the nocturnal inversion was eliminated by daytime heating. The 887 J/kg total increase of CAPE in less than 5 h and the high bulk Richardson number (BRN) of 93 were indicators of the growing pyro-cumulus cell. The presented simulation has not improved the original model or supported leading-edge numerical weather prediction (NWP) achievements, except for adapting WRF-Fire for Canadian biomass fuel. However, we were able to present a great deal of improvements in wildfire nowcasting and short-term forecasting to save lives and costs associated with wildfires. The simulation is sufficiently fast and efficient to be considered for a real-time operational model. While the project was designed and succeeded as an NWP application, we are still searching for a solution for the intractable problems associated with political borders and the current liable authorities for the further development of a new generation of national atmosphere–wildfire forecasting systems.
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Johnston, Paul, Joel Kelso, and George J. Milne. "Efficient simulation of wildfire spread on an irregular grid." International Journal of Wildland Fire 17, no. 5 (2008): 614. http://dx.doi.org/10.1071/wf06147.
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A cell-based wildfire simulator that uses an irregular grid is presented. Cell-based methods are simpler to implement than fire front propagation methods but have traditionally been plagued by fire shape distortion caused by the fire only being able to travel in certain directions. Using an irregular grid randomises the error introduced by the grid, so that the shape of simulated fire spread is independent of the direction of the wind with respect to the underlying grid. The cell-based fire spread simulator is implemented using discrete event simulation, which is a much more efficient computational method than conventional wildfire simulation techniques because computing resources are not used in repeatedly computing small updates to parts of the fire whose dynamics change infrequently, namely those areas of a fire that move slowly. The resulting simulator is comparable in accuracy with traditional fire front propagation schemes but is much faster and can therefore be used as an engine for fire simulation applications that require large numbers of simulations, such as in the role of a risk analysis engine.
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GU, FENG, and XIAOLIN HU. "ANALYSIS AND QUANTIFICATION OF DATA ASSIMILATION BASED ON SEQUENTIAL MONTE CARLO METHODS FOR WILDFIRE SPREAD SIMULATION." International Journal of Modeling, Simulation, and Scientific Computing 01, no. 04 (December 2010): 445–68. http://dx.doi.org/10.1142/s1793962310000298.
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Data assimilation is an important technique to improve simulation results by assimilating real time sensor data into a simulation model. A data assimilation framework based on Sequential Monte Carlo (SMC) methods for wildfire spread simulation has been developed in previous work. This paper provides systematic analysis and measurement to quantify the effectiveness and robustness of the developed data assimilation method. Measurement metrics are used to evaluate the robustness of SMC methods in data assimilation for wildfire spread simulation. Sensitivity analysis is carried out to examine the influences of important parameters to the data assimilation results. This work of analysis and quantification provides information to assess the effectiveness of the data assimilation method and suggests guidelines to further improve the data assimilation method for wildfire spread simulation.
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Salis, Michele, Bachisio Arca, Fermin Alcasena, Margarita Arianoutsou, Valentina Bacciu, Pierpaolo Duce, Beatriz Duguy, et al. "Predicting wildfire spread and behaviour in Mediterranean landscapes." International Journal of Wildland Fire 25, no. 10 (2016): 1015. http://dx.doi.org/10.1071/wf15081.
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The use of spatially explicit fire spread models to assess fire propagation and behaviour has several applications for fire management and research. We used the FARSITE simulator to predict the spread of a set of wildfires that occurred along an east–west gradient of the Euro-Mediterranean countries. The main purpose of this work was to evaluate the overall accuracy of the simulator and to quantify the effects of standard vs custom fuel models on fire simulation performance. We also analysed the effects of different fuel models and slope classes on the accuracy of FARSITE predictions. To run the simulations, several input layers describing each study area were acquired, and their effect on simulation outputs was analysed. Site-specific fuel models and canopy inputs were derived either from existing vegetation information and field sampling or through remote-sensing data. The custom fuel models produced an increase in simulation accuracy, and results were nearly unequivocal for all the case studies examined. We suggest that spatially explicit fire spread simulators and custom fuel models specifically developed for the heterogeneous landscapes of Mediterranean ecosystems can help improve fire hazard mapping and optimise fuel management practices across the Euro-Mediterranean region.
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David, Walter, Francesco Giannino, Duncan Heathfield, Antony Hubervic, Attila Aknai, Athanasios Sfetsos, and Silvia Elena Piovan. "Giving life to the map can save more lives. Wildfire scenario with interoperable simulations." Advances in Cartography and GIScience of the ICA 1 (July 3, 2019): 1–8. http://dx.doi.org/10.5194/ica-adv-1-4-2019.
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<p><strong>Abstract.</strong> In the Mediterranean region, drier and hotter summers are leading to more likely and severe wildfires. The authors propose an innovative approach for situational awareness by giving life to maps and exploiting interoperable GIS, hazard models, simulations, and interconnection analysis processes aimed to enhance preparedness and strengthen the resilience of responding organizations. The information related to a virtual city and its countryside has been implemented in the terrain of simulation systems. The TIGER wildfire model software has been adapted to a scenario where districts, refugee camps and critical infrastructures can be impacted by a fire and has been linked to a smoke dispersion model, and associated impacts to the electricity network and roads. The transfer of computed fire propagation and combustion data to the AI-powered SWORD simulation enable more accurate computing of damage and loss. In SWORD, civil protection, military assets and humanitarian actions can be performed for training and operation preparation. The simulation data about fire and assets’ deployments can feed a web app map or a command and control system, thus providing situational awareness for optimal decision-making, and analysis about people in danger, network interconnections and potential service disruption. Disaster managers and commanders can interact with simulated assets performing their chosen courses of action and analyse the outcomes.</p><p>In conclusion, tests in a wildfire case study demonstrated a high level of interoperability among those systems and the possibility to provide updated situational awareness leading to better emergency preparedness and critical infrastructure resilience building, finally contributing to save more lives.</p>
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Rabinovich, Sharon, Renwick E. Curry, and Gabriel H. Elkaim. "Toward Dynamic Monitoring and Suppressing Uncertainty in Wildfire by Multiple Unmanned Air Vehicle System." Journal of Robotics 2018 (November 18, 2018): 1–12. http://dx.doi.org/10.1155/2018/6892153.
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Containing a wildfire requires an efficient response and persistent monitoring. A crucial aspect is the ability to search for the boundaries of the wildfire by exploring a wide area. However, even as wildfires are increasing today, the number of available monitoring systems that can provide support is decreasing, creating an operational gap and slow response in such urgent situations. The objective of this work is to estimate a propagating boundary and create an autonomous system that works in real time. It proposes a coordination strategy with a new methodology for estimating the periphery of a propagating phenomenon using limited observations. The complete system design, tested on the high-fidelity simulation, demonstrates that steering the vehicles toward the highest perpendicular uncertainty generates the effective predictions. The results indicate that the new coordination scheme has a large beneficial impact on uncertainty suppression. This study thus suggests that an efficient solution for suppressing uncertainty in monitoring a wildfire is to use a fleet of low-cost unmanned aerial vehicles that can be deployed quickly. Further research is needed on other deployment schemes that work in different natural disaster case studies.
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Charney, Joseph J., and Daniel Keyser. "Mesoscale model simulation of the meteorological conditions during the 2 June 2002 Double Trouble State Park wildfire." International Journal of Wildland Fire 19, no. 4 (2010): 427. http://dx.doi.org/10.1071/wf08191.
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On the morning of 2 June 2002, an abandoned campfire grew into a wildfire in the Double Trouble State Park in east-central New Jersey, USA. The wildfire burned 526 ha (1300 acres) and forced the closure of the Garden State Parkway for several hours due to dense smoke. In addition to the presence of dead and dry fuels due to a late spring frost prior to the wildfire, the meteorological conditions at the time of the wildfire were conducive to erratic fire behaviour and rapid fire growth. Observations indicate the occurrence of a substantial drop in relative humidity at the surface accompanied by an increase in wind speed in the vicinity of the wildfire during the late morning and early afternoon of 2 June. The surface drying and increase in wind speed are hypothesised to result from the downward transport of dry, high-momentum air from the middle troposphere occurring in conjunction with a deepening mixed layer. This hypothesis is addressed using a high-resolution mesoscale model simulation to document the structure and evolution of the planetary boundary layer and lower-tropospheric features associated with the arrival of dry, high-momentum air at the surface coincident with the sudden and dramatic growth of the wildfire.
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Ager, A. A., M. A. Finney, A. McMahan, and J. Cathcart. "Measuring the effect of fuel treatments on forest carbon using landscape risk analysis." Natural Hazards and Earth System Sciences 10, no. 12 (December 7, 2010): 2515–26. http://dx.doi.org/10.5194/nhess-10-2515-2010.
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Abstract. Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the non-treatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the long-term balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.
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Summers, Rebecca. "Fanning the flames: House burns in wildfire simulation." New Scientist 218, no. 2916 (May 2013): 24–25. http://dx.doi.org/10.1016/s0262-4079(13)61180-x.
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Johnston, Paul, George Milne, and Joel Kelso. "A heat transfer simulation model for wildfire spread." Forest Ecology and Management 234 (November 2006): S78. http://dx.doi.org/10.1016/j.foreco.2006.08.114.
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Palaiologou, Palaiologos, Alan A. Ager, Max Nielsen-Pincus, Cody R. Evers, and Kostas Kalabokidis. "Using transboundary wildfire exposure assessments to improve fire management programs: a case study in Greece." International Journal of Wildland Fire 27, no. 8 (2018): 501. http://dx.doi.org/10.1071/wf17119.
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Numerous catastrophic wildfires in Greece have demonstrated that relying on fire suppression as the primary risk-management strategy is inadequate and that existing wildfire-risk governance needs to be re-examined. In this research, we used simulation modelling to assess the spatial scale of wildfire exposure to communities and cultural monuments in Chalkidiki, Greece. The study area typifies many areas in Greece in terms of fire regimes, ownership patterns and fire-risk mitigation. Fire-transmission networks were built to quantify connectivity among land tenures and populated places. We found that agricultural and unmanaged wildlands are key land categories that transmit fire exposure to other land tenures. In addition, fires ignited within protected lands and community boundaries are major sources of structure exposure. Important cultural monuments in the study area had fairly low exposure but higher potential for fires with moderate to high intensity. The results show how the spatial diversity of vegetation and fuels, in combination with vegetation management practices on private and public tracts of land, contribute to transboundary risk. We use the results to motivate a discussion of integrating transboundary risk assessments to improve the current wildfire-risk rating system and begin the process of reforming risk governance in Greece.
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HOMCHAUDHURI, BAISRAVAN, MANISH KUMAR, and KELLY COHEN. "GENETIC ALGORITHM BASED SIMULATION–OPTIMIZATION FOR FIGHTING WILDFIRES." International Journal of Computational Methods 10, no. 06 (May 2, 2013): 1350035. http://dx.doi.org/10.1142/s0219876213500357.
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Wildfire is one of the most significant disturbances responsible for reshaping the terrain and changing the ecosystem of a particular region. Its detrimental effects on environment as well as human lives and properties, and growing trend in terms of frequency and intensity of wildfires over the last decade have necessitated the development of efficient forest fire management techniques. During the last three decades, Forest Fire Decision Support Systems (FFDSS) have been developed to help in the decision-making processes during forest fires by providing necessary information on fire detection, their status and behavior, and other aspects of forest fires. However, most of these decision support systems lack the capability of developing intelligent fire suppression strategies based upon current status and predicted behavior of forest fire. This paper presents an approach for development of efficient fireline building strategies via intelligent resource allocation. A Genetic Algorithm based approach has been proposed in this paper for resource allocation and optimum fireline building that minimizes the total damage due to wildland fires. The approach is based on a simulation–optimization technique in which the Genetic Algorithm uses advanced forest fire propagation models based upon Huygens principles for evaluation of cost index of its solutions. Both homogeneous and heterogeneous environmental conditions have been considered. Uncertainties in weather conditions as well as imperfect knowledge about exact vegetation and topographical conditions make exact prediction of wildfires very difficult. The paper incorporates Monte-Carlo simulations to develop robust strategies in uncertain conditions. Extensive simulations demonstrate the effectiveness of the proposed approach in efficient resource allocation for fighting complex wildfires in uncertain and dynamic conditions.
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D'Andrea, M., P. Fiorucci, and T. P. Holmes. "A stochastic Forest Fire Model for future land cover scenarios assessment." Natural Hazards and Earth System Sciences 10, no. 10 (October 13, 2010): 2161–67. http://dx.doi.org/10.5194/nhess-10-2161-2010.
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Abstract. Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary – each cell either contains a tree or it is empty – and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.
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Lucash, Melissa S., Robert M. Scheller, Alec M. Kretchun, Kenneth L. Clark, and John Hom. "Impacts of fire and climate change on long-term nitrogen availability and forest productivity in the New Jersey Pine Barrens." Canadian Journal of Forest Research 44, no. 5 (May 2014): 404–12. http://dx.doi.org/10.1139/cjfr-2013-0383.
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Increased wildfires and temperatures due to climate change are expected to have profound effects on forest productivity and nitrogen (N) cycling. Forecasts about how wildfire and climate change will affect forests seldom consider N availability, which may limit forest response to climate change, particularly in fire-prone landscapes. The overall objective of this study was to examine how wildfire and climate change affect long-term mineral N availability in a fire-prone landscape. We employed a commonly used landscape simulation model (LANDIS-II) in the New Jersey Pine Barrens, a landscape characterized by frequent small fires and fire-resilient vegetation. We found that fire had little effect on mineral N, whereas climate change and fire together reduced mineral N by the end of the century. Though N initially limited forest productivity, mineral N was no longer limiting after 50 years. Our results suggest that mineral N is resilient to fire under our current climate but not under climate change. Also, predictions that do not consider N limitation may underestimate short-term but not long-term productivity responses to climate change. Together these results illustrate the importance of including N dynamics when simulating the effects of climate change on forest productivity, particularly in fire-prone regions such as the New Jersey Pine Barrens.
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Flannigan, M. D., and C. E. Van Wagner. "Climate change and wildfire in Canada." Canadian Journal of Forest Research 21, no. 1 (January 1, 1991): 66–72. http://dx.doi.org/10.1139/x91-010.
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This study investigates the impact of postulated greenhouse warming on the severity of the forest fire season in Canada. Using CO2 levels that are double those of the present (2 × CO2), simulation results from three general circulation models (Geophysical Fluid Dynamics Laboratory, Goddard Institute for Space Studies, and Oregon State University) were used to calculate the seasonal severity ratings for six stations across Canada. Monthly anomalies from the 2 × CO2 simulation results were superimposed over historical sequences of daily weather. Then, seasonal severity ratings of the present were compared with those for 2 × CO2 using five variations involving temperature, precipitation, and relative humidity. The relationship between seasonal severity rating and annual provincial area burned by wildfire was explored. The results suggest a 46% increase in seasonal severity rating, with a possible similar increase in area burned, in a 2 × CO2 climate.
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Hu, Xiaolin, Yi Sun, and Lewis Ntaimo. "DEVS-FIRE: design and application of formal discrete event wildfire spread and suppression models." SIMULATION 88, no. 3 (October 23, 2011): 259–79. http://dx.doi.org/10.1177/0037549711414592.
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DEVS-FIRE is a discrete event system specification (DEVS) model for simulating wildfire spread and suppression. It employs a cellular space model to simulate fire spread and agent models that interact with the cellular space to simulate fire suppression with realistic tactics. The complex interplay among forest cells and agents calls for formal treatment of the fire spread and fire suppression models to verify the correctness of DEVS-FIRE. This paper gives formal design specifications of fire spread and suppression agent models used in DEVS-FIRE and applies DEVS-FIRE to both artificially generated and real topography, fuels and weather data for a study area located in the US state of Texas. The paper also develops a new method, called pre_Schedule, for scheduling ignition events of forest cells more efficiently than the original onTime_Schedule event scheduling method used in DEVS-FIRE. Simulation results show the performance improvement of the new method, and demonstrate the utility of DEVS-FIRE as a viable discrete event model for wildfire simulations.
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Prestemon, Jeffrey P., Uma Shankar, Aijun Xiu, K. Talgo, D. Yang, Ernest Dixon, Donald McKenzie, and Karen L. Abt. "Projecting wildfire area burned in the south-eastern United States, 2011–60." International Journal of Wildland Fire 25, no. 7 (2016): 715. http://dx.doi.org/10.1071/wf15124.
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Future changes in society and climate are expected to affect wildfire activity in the south-eastern United States. The objective of this research was to understand how changes in both climate and society may affect wildfire in the coming decades. We estimated a three-stage statistical model of wildfire area burned by ecoregion province for lightning and human causes (1992–2010) based on precipitation, temperature, potential evapotranspiration, forest land use, human population and personal income. Estimated parameters from the statistical models were used to project wildfire area burned from 2011 to 2060 under nine climate realisations, using a combination of three Intergovernmental Panel on Climate Change-based emissions scenarios (A1B, A2, B2) and three general circulation models. Monte Carlo simulation quantifies ranges in projected area burned by county by year, and in total for higher-level spatial aggregations. Projections indicated, overall in the Southeast, that median annual area burned by lightning-ignited wildfire increases by 34%, human-ignited wildfire decreases by 6%, and total wildfire increases by 4% by 2056–60 compared with 2016–20. Total wildfire changes vary widely by state (–47 to +30%) and ecoregion province (–73 to +79%). Our analyses could be used to generate projections of wildfire-generated air pollutant exposures, relevant to meeting the National Ambient Air Quality Standards.
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Hanson, Howard P., Michael M. Bradley, James E. Bossert, Rodman R. Linn, and Leland W. Younker. "The potential and promise of physics-based wildfire simulation." Environmental Science & Policy 3, no. 4 (August 2000): 161–72. http://dx.doi.org/10.1016/s1462-9011(00)00083-6.
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Palaiologou, Palaiologos, Alan A. Ager, Cody R. Evers, Max Nielsen-Pincus, Michelle A. Day, and Haiganoush K. Preisler. "Fine-scale assessment of cross-boundary wildfire events in the western United States." Natural Hazards and Earth System Sciences 19, no. 8 (August 14, 2019): 1755–77. http://dx.doi.org/10.5194/nhess-19-1755-2019.
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Abstract. We report a fine-scale assessment of cross-boundary wildfire events for the western US. We used simulation modeling to quantify the extent of fire exchange among major federal, state, and private land tenures and mapped locations where fire ignitions can potentially affect populated places. We examined how parcel size affects wildfire transmission and partitioned the relative amounts of transmitted fire between human and natural ignitions. We estimated that 85 % of the total predicted wildfire activity, as measured by area burned, originates from four land tenures (Forest Service, Bureau of Land Management, private, and state lands) and 63 % of the total amount results from natural versus human ignitions. On average, one-third of the area burned by predicted wildfires was nonlocal, meaning that the source ignition was on a different land tenure. Land tenures with smaller parcels tended to receive more incoming fire on a proportional basis, while the largest fires were generated from ignitions in national parks, national forests, and public and tribal lands. Among the 11 western states, the amount and pattern of cross-boundary fire varied substantially in terms of which land tenures were mostly exposed, by whom, and to what extent. We also found spatial variability in terms of community exposure among states, and more than half of the predicted structure exposure was caused by ignitions on private lands or within the wildland–urban interface areas. This study addressed gaps in existing wildfire risk assessments that do not explicitly consider cross-boundary fire transmission and do not identify the source of fire. The results can be used by state, federal, and local fire planning organizations to help improve risk mitigation programs.
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Polyakov, Viktor, Jeffry Stone, Chandra Holifield Collins, Mark A. Nearing, Ginger Paige, Jared Buono, and Rae-Landa Gomez-Pond. "Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator." Earth System Science Data 10, no. 1 (January 9, 2018): 19–26. http://dx.doi.org/10.5194/essd-10-19-2018.
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Abstract. This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583).
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Ryu, Juyeol, and Wonjik Yang. "Experimental Study on Reducing the Risk of Wildland Fires by Prescribed Fire." Journal of the Korean Society of Hazard Mitigation 21, no. 2 (April 30, 2021): 45–52. http://dx.doi.org/10.9798/kosham.2021.21.2.45.
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Many countries, such as the United States, Australia, and Japan, use prescribed fire to treat fuel in forests as their primary wildfire prevention and management tool. However, to date we have not applied such method in our country. Therefore, in this research, we investigate the current status and method of prescribed fire for application. Then, the research target area was selected, and the possibility of the domestic application was evaluated through a prescribed fire and wildfire reproduction simulation. Our simulation results showed that a split fire drop (1<sup>st</sup>, 2<sup>nd</sup>, and 3<sup>rd</sup> fire) using the prescribed fire reduced the burning area by 26.6% compared to wildfire reproduction. We confirmed that the prescribed fire was carried out safely and effectively.
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Marshall, Ginny, Dan Thompson, Kerry Anderson, Brian Simpson, Rodman Linn, and Dave Schroeder. "The Impact of Fuel Treatments on Wildfire Behavior in North American Boreal Fuels: A Simulation Study Using FIRETEC." Fire 3, no. 2 (June 5, 2020): 18. http://dx.doi.org/10.3390/fire3020018.
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Current methods of predicting fire spread in Canadian forests are suited to large wildfires that spread through natural forests. Recently, the use of mechanical and thinning treatments of forests in the wildland-urban interface of Canada has increased. To assist in community wildfire protection planning in forests not covered by existing operational fire spread models, we use FIRETEC to simulate fire spread in lowland black spruce fuel structures, the most common tree stand in Canada. The simulated treatments included the mechanical mulching of strips, and larger, irregularly shaped areas. In all cases, the removal of fuel by mulch strips broke up the fuels, but also caused wind speed increases, so little decrease in fire spread rate was modelled. For large irregular clearings, the fire spread slowly through the mulched wood chips, and large decreases in fire spread and intensity were simulated. Furthermore, some treatments in the black spruce forest were found to be effective in decreasing the distance and/or density of firebrands. The simulations conducted can be used alongside experimental fires and documented wildfires to examine the effectiveness of differing fuel treatment options to alter multiple components of fire behavior.
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Kalabokidis, Kostas, Alan Ager, Mark Finney, Nikos Athanasis, Palaiologos Palaiologou, and Christos Vasilakos. "AEGIS: a wildfire prevention and management information system." Natural Hazards and Earth System Sciences 16, no. 3 (March 4, 2016): 643–61. http://dx.doi.org/10.5194/nhess-16-643-2016.
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Abstract. We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.
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Freire, Joana Gouveia, and Carlos Castro DaCamara. "Using cellular automata to simulate wildfire propagation and to assist in fire management." Natural Hazards and Earth System Sciences 19, no. 1 (January 22, 2019): 169–79. http://dx.doi.org/10.5194/nhess-19-169-2019.
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Abstract. Cellular automata have been successfully applied to simulate the propagation of wildfires with the aim of assisting fire managers in defining fire suppression tactics and in planning fire risk management policies. We present a cellular automaton designed to simulate a severe wildfire episode that took place in Algarve (southern Portugal) in July 2012. During the episode almost 25 000 ha burned and there was an explosive stage between 25 and 33 h after the onset. Results obtained show that the explosive stage is adequately modeled when introducing a wind propagation rule in which fire is allowed to spread to nonadjacent cells depending on wind speed. When this rule is introduced, deviations in modeled time of burning (from estimated time based on hot spots detected from satellite) have a root-mean-square difference of 7.1 for a simulation period of 46 h (i.e., less than 20 %). The simulated pattern of probabilities of burning as estimated from an ensemble of 100 simulations shows a marked decrease out of the limits of the observed scar, indicating that the model represents an added value to help decide locations of where to allocate resources for fire fighting.
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Heilman, Warren E., and Xindi Bian. "Turbulent kinetic energy during wildfires in the north central and north-eastern US." International Journal of Wildland Fire 19, no. 3 (2010): 346. http://dx.doi.org/10.1071/wf08076.
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The suite of operational fire-weather indices available for assessing the atmospheric potential for extreme fire behaviour typically does not include indices that account for atmospheric boundary-layer turbulence or wind gustiness that can increase the erratic behaviour of fires. As a first step in testing the feasibility of using a quantitative measure of turbulence as a stand-alone fire-weather index or as a component of a fire-weather index, simulations of the spatial and temporal patterns of turbulent kinetic energy during major recent wildfire events in the western Great Lakes and north-eastern US regions were performed. Simulation results indicate that the larger wildfires in these regions of the US were associated with episodes of significant boundary-layer ambient turbulence. Case studies of the largest recent wildfires to occur in these regions indicate that the periods of most rapid fire growth were generally coincident with occurrences of the product of the Haines Index and near-surface turbulent kinetic energy exceeding a value of 15 m2 s–2, a threshold indicative of a highly turbulent boundary layer beneath unstable and dry atmospheric layers, which is a condition that can be conducive to erratic fire behaviour.
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Dupuy, J. L., R. R. Linn, V. Konovalov, F. Pimont, J. A. Vega, and E. Jiménez. "Exploring three-dimensional coupled fire–atmosphere interactions downwind of wind-driven surface fires and their influence on backfires using the HIGRAD-FIRETEC model." International Journal of Wildland Fire 20, no. 6 (2011): 734. http://dx.doi.org/10.1071/wf10035.
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The obstruction of ambient winds and the possible existence of indrafts downwind of a wildfire are aspects of coupled fire–atmosphere interaction influencing the effectiveness of a backfiring operation. The fire-influenced winds behind a headfire as well as their influences on backfire spread are explored using the three-dimensional HIGRAD-FIRETEC model. Fires are simulated under weak to strong wind speeds and in shrubland and grassland fuel types. The importance of three-dimensionality in the simulation of such phenomena is demonstrated. Results suggest that when fire–atmosphere interaction is constrained to two-dimensions, the limitations of air moving through the head fire could lead to overestimation of downwind indrafts and effectiveness of backfiring. Three-dimensional simulations in surface fuels suggest that backfires benefit from the obstruction of ambient winds and potentially the existence of an indraft flow in only a limited range of environmental conditions. Simulations show that flows are most favourable when the wildfire is driven downslope by a weak wind and the backfire is ignited at bottom of the slope. Model simulations are compared with backfiring experiments conducted in a dense shrubland. Although this exercise encountered significant difficulties linked to the ambient winds data and their incorporation into the simulation, predictions and observations are in reasonable agreement.
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Kochanski, Adam K., Mary Ann Jenkins, Kara Yedinak, Jan Mandel, Jonathan Beezley, and Brian Lamb. "Toward an integrated system for fire, smoke and air quality simulations." International Journal of Wildland Fire 25, no. 5 (2016): 534. http://dx.doi.org/10.1071/wf14074.
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In this study, WRF-Sfire is coupled with WRF-Chem to construct WRFSC, an integrated forecast system for wildfire behaviour and smoke prediction. WRF-Sfire directly predicts wildfire spread, plume and plume-top heights, providing comprehensive meteorology and fire emissions to chemical transport model WRF-Chem, eliminating the need for an external plume-rise model. Evaluation of WRFSC was based on comparisons between available observations of fire perimeter and fire intensity, smoke spread, PM2.5 (particulate matter less than 2.5 μm in diameter), NO and ozone concentrations, and plume-top heights with the results of two WRFSC simulations, a 48-h simulation of the 2007 Witch–Guejito Santa Ana fires and a 96-h WRF-Sfire simulation with passive tracers of the 2012 Barker Canyon fire. The study found overall good agreement between forecast and observed local- and long-range fire spread and smoke transport for the Witch–Guejito fire. However, ozone, PM2.5 and NO concentrations were generally underestimated and peaks mistimed in the simulations. This study found overall good agreement between simulated and observed plume-top heights, with slight underestimation by the simulations. Two promising results were the agreement between plume-top heights for the Barker Canyon fire and faster than real-time execution, making WRFSC a possible operational tool.
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Beloglazov, Anton, Mahathir Almashor, Ermyas Abebe, Jan Richter, and Kent Charles Barton Steer. "Simulation of wildfire evacuation with dynamic factors and model composition." Simulation Modelling Practice and Theory 60 (January 2016): 144–59. http://dx.doi.org/10.1016/j.simpat.2015.10.002.
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Lutsch, Erik, Kimberly Strong, Dylan B. A. Jones, Thomas Blumenstock, Stephanie Conway, Jenny A. Fisher, James W. Hannigan, et al. "Detection and attribution of wildfire pollution in the Arctic and northern midlatitudes using a network of Fourier-transform infrared spectrometers and GEOS-Chem." Atmospheric Chemistry and Physics 20, no. 21 (November 5, 2020): 12813–51. http://dx.doi.org/10.5194/acp-20-12813-2020.
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Abstract. We present a multiyear time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier-transform infrared (FTIR) spectrometers at 10 sites affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Ålesund, Thule, Kiruna, Poker Flat, and St. Petersburg, and four are midlatitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the interannual trends and seasonal variabilities of the CO time series are accounted for, allowing background column amounts to be determined. Enhancements above the seasonal background were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFASv1.2) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003 to 2018. For each detected wildfire pollution event, FLEXPART back-trajectory simulations were performed to determine the transport times of the smoke plume. Accounting for the loss of each species during transport, the enhancement ratios of HCN and C2H6 with respect to CO were converted to emission ratios. We report mean emission ratios with respect to CO for HCN and C2H6 of 0.0047 and 0.0092, respectively, with a standard deviation of 0.0014 and 0.0046, respectively, determined from 23 boreal North American wildfire events. Similarly, we report mean emission ratios for HCN and C2H6 of 0.0049 and 0.0100, respectively, with a standard deviation of 0.0025 and 0.0042, respectively, determined from 39 boreal Asian wildfire events. The agreement of our emission ratios with literature values illustrates the capability of ground-based FTIR measurements to quantify biomass burning emissions. We provide a comprehensive dataset that quantifies HCN and C2H6 emission ratios from 62 wildfire pollution events. Our dataset provides novel emission ratio estimates, which are sparsely available in the published literature, particularly for boreal Asian sources.
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Zhang, Shuo, Demin Gao, Haifeng Lin, and Quan Sun. "Wildfire Detection Using Sound Spectrum Analysis Based on the Internet of Things." Sensors 19, no. 23 (November 21, 2019): 5093. http://dx.doi.org/10.3390/s19235093.
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Wildfire is a sudden and hazardous natural disaster. Currently, many schemes based on optical spectrum analysis have been proposed to detect wildfire, but obstacles in forest areas can decrease the efficiency of spectral monitoring, resulting in a wildfire detection system not being able to monitor the occurrence of wildfire promptly. In this paper, we propose a novel wildfire detection system using sound spectrum analysis based on the Internet of Things (IoT), which utilizes a wireless acoustic detection system to probe wildfire and distinguish the difference in the sound between the crown and the surface fire. We also designed a new power supply unit: tree-energy device, which utilizes the biological energy of the living trees to generate electricity. We implemented sound spectrum analysis on the data collected by sound sensors and then combined our classification algorithms. The results describe that the sound frequency of the crown fire is about 0–400 Hz, while the sound frequency of the surface fire ranges from 0 to 15,000 Hz. However, the accuracy of the classification method is affected by some factors, such as the distribution of sensors, the loss of energy in sound transmission, and the delay of data transmission. In the simulation experiments, the recognition rate of the method can reach about 70%.
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Josephson, Alexander J., Troy M. Holland, Sara Brambilla, Michael J. Brown, and Rodman R. Linn. "Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions." Fire 3, no. 1 (February 25, 2020): 4. http://dx.doi.org/10.3390/fire3010004.
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A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.
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Gallego Arrubla, Julián A., Lewis Ntaimo, and Curt Stripling. "Wildfire initial response planning using probabilistically constrained stochastic integer programming." International Journal of Wildland Fire 23, no. 6 (2014): 825. http://dx.doi.org/10.1071/wf13204.
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This paper presents a new methodology for making strategic dozer deployment plans for wildfire initial response planning for a given fire season. This approach combines a fire behaviour simulation, a wildfire risk model and a probabilistically constrained stochastic integer programming model, and takes into account the level of risk the decision-maker is willing to take when making deployment and dispatching plans. The new methodology was applied to Texas District 12, a Texas A&M Forest Service fire planning unit located in East Texas. This study demonstrates the effect of the decision-maker’s risk attitude level on deployment decisions in terms of the dozers positioned at each operations base, fires contained and their associated wildfire risk, and total containment cost. The results show that the total number of fires contained and their associated total expected cost increase when the tolerance towards risk decreases. Thus, more dozers are deployed to operations bases in areas with high wildfire risk and a high need for initial response.
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Linn, Rodman R., Judith L. Winterkamp, David R. Weise, and Carleton Edminster. "A numerical study of slope and fuel structure effects on coupled wildfire behaviour." International Journal of Wildland Fire 19, no. 2 (2010): 179. http://dx.doi.org/10.1071/wf07120.
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Slope and fuel structure are commonly accepted as major factors affecting the way wildfires behave. However, it is possible that slope affects fire differently depending on the fuel bed. Six FIRETEC simulations using three different fuel beds on flat and upslope topography were used to examine this possibility. Fuel beds resembling grass, chaparral, and ponderosa pine forests were created in such a way that there were two specific locations with identical local fuel beds located around them. These fuel beds were each used for a flat-terrain simulation and an idealised-hill simulation in order to isolate the impacts of the topography without the complications of having different local fuels. In these simulations, fuel bed characteristics have a significant effect on the spread rate and perimeter shape of the fires on both flat ground and on the idealised smooth hill topography. The analysis showed that these simulated fires evolved as they travelled between the locations even on flat ground, and the accelerations and decelerations that affect the fire occurred at different times and at different rates depending on the fuel bed. The results of these simulations and analyses indicate that though some general principles are true for all fuel beds, there are differences in the way that fires react to non-homogeneous topographies depending on the fuel bed.
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Rios, O., W. Jahn, E. Pastor, M. M. Valero, and E. Planas. "Interpolation framework to speed up near-surface wind simulations for data-driven wildfire applications." International Journal of Wildland Fire 27, no. 4 (2018): 257. http://dx.doi.org/10.1071/wf17027.
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Local wind fields that account for topographic interaction are a key element for any wildfire spread simulator. Currently available tools to generate near-surface winds with acceptable accuracy do not meet the tight time constraints required for data-driven applications. This article presents the specific problem of data-driven wildfire spread simulation (with a strategy based on using observed data to improve results), for which wind diagnostic models must be run iteratively during an optimisation loop. An interpolation framework is proposed as a feasible alternative to keep a positive lead time while minimising the loss of accuracy. The proposed methodology was compared with the WindNinja solver in eight different topographic scenarios with multiple resolutions and reference – pre-run– wind map sets. Results showed a major reduction in computation time (~100 times once the reference fields are available) with average deviations of 3% in wind speed and 3° in direction. This indicates that high-resolution wind fields can be interpolated from a finite set of base maps previously computed. Finally, wildfire spread simulations using original and interpolated maps were compared showing minimal deviations in the fire shape evolution. This methodology may have an important effect on data assimilation frameworks and probabilistic risk assessment where high-resolution wind fields must be computed for multiple weather scenarios.
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Jenkins, Mary Ann. "An examination of the sensitivity of numerically simulated wildfires to low-level atmospheric stability and moisture, and the consequences for the Haines Index." International Journal of Wildland Fire 11, no. 4 (2002): 213. http://dx.doi.org/10.1071/wf02006.
Full textAbstract:
The Haines Index, an operational fire–weather index introduced in 1988 and based on the observed stability and moisture content of the near-surface atmosphere, has been a useful indicator of the potential for high-risk fires in low wind conditions and flat terrain. The Haines Index is of limited use, however, as a predictor of actual fire behavior. To develop a fire–weather index to predict severe or erratic wildfire behavior, an understanding of how the ambient lower-level atmospheric stability and moisture affects the growth of a wildfire is needed. This study is a first step in this process. This study investigates, through four comparative numerical simulations with a coupled wildfire–atmosphere model, the sensitivity of wildland fires to atmospheric stability and moisture, and in the process explores the correspondence between atmospheric stability and moisture, wildfire behavior, and the Haines Index. In the first three fire simulations, the model atmosphere was initially set to identical moisture but different instability conditions that correspond to Haines Indexes for low, moderate, and high potential for severe fire development. In the fourth fire simulation, the initial atmospheric and moisture conditions were for a high-risk fire Haines Index rating, but different from the initial conditions of dryness and stability of the previous experiments. The study indicates that high-risk fire development is sensitive to near-surface atmospheric stability and moisture, and that there is a range of atmospheric stability and moisture conditions that is important to the development of severe or erratic fire behavior, and that this range is within the atmospheric stability and moisture conditions represented by a Haines Index for high potential for severe fire. The analyses also suggest that there is a substantial latitude of fire behavior for fires rated as this Index, indicating that this Index should be further divided, or refined.