Fire behavior modeling-a decision tool

Treesearch

Jack Cohen; Bill Bradshaw

1986-01-01

The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

A model-based approach to wildland fire reconstruction using sediment charcoal records

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; Hooten, Mevin B.; Higuera, Philip E.; Marlon, Jennifer R.; Kelly, Ryan; McLachlan, Jason S.

2017-01-01

Lake sediment charcoal records are used in paleoecological analyses to reconstruct fire history, including the identification of past wildland fires. One challenge of applying sediment charcoal records to infer fire history is the separation of charcoal associated with local fire occurrence and charcoal originating from regional fire activity. Despite a variety of methods to identify local fires from sediment charcoal records, an integrated statistical framework for fire reconstruction is lacking. We develop a Bayesian point process model to estimate the probability of fire associated with charcoal counts from individual-lake sediments and estimate mean fire return intervals. A multivariate extension of the model combines records from multiple lakes to reduce uncertainty in local fire identification and estimate a regional mean fire return interval. The univariate and multivariate models are applied to 13 lakes in the Yukon Flats region of Alaska. Both models resulted in similar mean fire return intervals (100–350 years) with reduced uncertainty under the multivariate model due to improved estimation of regional charcoal deposition. The point process model offers an integrated statistical framework for paleofire reconstruction and extends existing methods to infer regional fire history from multiple lake records with uncertainty following directly from posterior distributions.

Forest-fire model with natural fire resistance.

PubMed

Yoder, Mark R; Turcotte, Donald L; Rundle, John B

2011-04-01

Observations suggest that contemporary wildfire suppression practices in the United States have contributed to conditions that facilitate large, destructive fires. We introduce a forest-fire model with natural fire resistance that supports this theory. Fire resistance is defined with respect to the size and shape of clusters; the model yields power-law frequency-size distributions of model fires that are consistent with field observations in the United States, Canada, and Australia.

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

DOE PAGES

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; ...

2015-02-13

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

FARSITE: Fire Area Simulator-model development and evaluation

Treesearch

Mark A. Finney

1998-01-01

A computer simulation model, FARSITE, includes existing fire behavior models for surface, crown, spotting, point-source fire acceleration, and fuel moisture. The model's components and assumptions are documented. Simulations were run for simple conditions that illustrate the effect of individual fire behavior models on two-dimensional fire growth.

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Application of the NUREG/CR-6850 EPRI/NRC Fire PRA Methodology to a DOE Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tom Elicson; Bentley Harwood; Richard Yorg

2011-03-01

The application NUREG/CR-6850 EPRI/NRC fire PRA methodology to DOE facility presented several challenges. This paper documents the process and discusses several insights gained during development of the fire PRA. A brief review of the tasks performed is provided with particular focus on the following: • Tasks 5 and 14: Fire-induced risk model and fire risk quantification. A key lesson learned was to begin model development and quantification as early as possible in the project using screening values and simplified modeling if necessary. • Tasks 3 and 9: Fire PRA cable selection and detailed circuit failure analysis. In retrospect, it wouldmore » have been beneficial to perform the model development and quantification in 2 phases with detailed circuit analysis applied during phase 2. This would have allowed for development of a robust model and quantification earlier in the project and would have provided insights into where to focus the detailed circuit analysis efforts. • Tasks 8 and 11: Scoping fire modeling and detailed fire modeling. More focus should be placed on detailed fire modeling and less focus on scoping fire modeling. This was the approach taken for the fire PRA. • Task 14: Fire risk quantification. Typically, multiple safe shutdown (SSD) components fail during a given fire scenario. Therefore dependent failure analysis is critical to obtaining a meaningful fire risk quantification. Dependent failure analysis for the fire PRA presented several challenges which will be discussed in the full paper.« less

Managing wildland fires: integrating weather models into fire projections

Treesearch

Anne M. Rosenthal; Francis Fujioka

2004-01-01

Flames from the Old Fire sweep through lands north of San Bernardino during late fall of 2003. Like many Southern California fires, the Old Fire consumed susceptible forests at the urban-wildland interface and spread to nearby city neighborhoods. By incorporating weather models into fire perimeter projections, scientist Francis Fujioka is improving fire modeling as a...

Aids to determining fuel models for estimating fire behavior

Treesearch

Hal E. Anderson

1982-01-01

Presents photographs of wildland vegetation appropriate for the 13 fuel models used in mathematical models of fire behavior. Fuel model descriptions include fire behavior associated with each fuel and its physical characteristics. A similarity chart cross-references the 13 fire behavior fuel models to the 20 fuel models used in the National Fire Danger Rating System....

Standard fire behavior fuel models: a comprehensive set for use with Rothermel's surface fire spread model

Treesearch

Joe H. Scott; Robert E. Burgan

2005-01-01

This report describes a new set of standard fire behavior fuel models for use with Rothermel's surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.

Modeling forest fire occurrences using count-data mixed models in Qiannan autonomous prefecture of Guizhou province in China.

PubMed

Xiao, Yundan; Zhang, Xiongqing; Ji, Ping

2015-01-01

Forest fires can cause catastrophic damage on natural resources. In the meantime, it can also bring serious economic and social impacts. Meteorological factors play a critical role in establishing conditions favorable for a forest fire. Effective prediction of forest fire occurrences could prevent or minimize losses. This paper uses count data models to analyze fire occurrence data which is likely to be dispersed and frequently contain an excess of zero counts (no fire occurrence). Such data have commonly been analyzed using count data models such as a Poisson model, negative binomial model (NB), zero-inflated models, and hurdle models. Data we used in this paper is collected from Qiannan autonomous prefecture of Guizhou province in China. Using the fire occurrence data from January to April (spring fire season) for the years 1996 through 2007, we introduced random effects to the count data models. In this study, the results indicated that the prediction achieved through NB model provided a more compelling and credible inferential basis for fitting actual forest fire occurrence, and mixed-effects model performed better than corresponding fixed-effects model in forest fire forecasting. Besides, among all meteorological factors, we found that relative humidity and wind speed is highly correlated with fire occurrence.

Modeling Forest Fire Occurrences Using Count-Data Mixed Models in Qiannan Autonomous Prefecture of Guizhou Province in China

PubMed Central

Ji, Ping

2015-01-01

Forest fires can cause catastrophic damage on natural resources. In the meantime, it can also bring serious economic and social impacts. Meteorological factors play a critical role in establishing conditions favorable for a forest fire. Effective prediction of forest fire occurrences could prevent or minimize losses. This paper uses count data models to analyze fire occurrence data which is likely to be dispersed and frequently contain an excess of zero counts (no fire occurrence). Such data have commonly been analyzed using count data models such as a Poisson model, negative binomial model (NB), zero-inflated models, and hurdle models. Data we used in this paper is collected from Qiannan autonomous prefecture of Guizhou province in China. Using the fire occurrence data from January to April (spring fire season) for the years 1996 through 2007, we introduced random effects to the count data models. In this study, the results indicated that the prediction achieved through NB model provided a more compelling and credible inferential basis for fitting actual forest fire occurrence, and mixed-effects model performed better than corresponding fixed-effects model in forest fire forecasting. Besides, among all meteorological factors, we found that relative humidity and wind speed is highly correlated with fire occurrence. PMID:25790309

Numerical modeling of the effects of fire-induced convection and fire-atmosphere interactions on wildfire spread and fire plume dynamics

NASA Astrophysics Data System (ADS)

Sun, Ruiyu

It is possible due to present day computing power to produce a fluid dynamical physically-based numerical solution to wildfire behavior, at least in the research mode. This type of wildfire modeling affords a flexibility and produces details that are not available in either current operational wildfire behavior models or field experiments. However before using these models to study wildfire, validation is necessary, and model results need to be systematically and objectively analyzed and compared to real fires. Plume theory and data from the Meteotron experiment, which was specially designed to provide results from measurements for the theoretical study of a convective plume produced by a high heat source at the ground, are used here to evaluate the fire plume properties simulated by two numerical wildfire models, the Fire Dynamics Simulator or FDS, and the Clark coupled atmosphere-fire model. The study indicates that the FDS produces good agreement with the plume theory and the Meteotron results. The study also suggests that the coupled atmosphere-fire model, a less explicit and ideally less computationally demanding model than the FDS; can produce good agreement, but that the agreement is sensitive to the method of putting the energy released from the fire into the atmosphere. The WFDS (Wildfire and wildland-urban interface FDS), an extension of the FDS to the vegetative fuel, and the Australian grass fire experiments are used to evaluate and improve the UULES-wildfire coupled model. Despite the simple fire parameterization in the UULES-wildfire coupled model, the fireline is fairly well predicted in terms of both shape and location in the simulation of Australian grass fire experiment F19. Finally, the UULES-wildfire coupled model is used to examine how the turbulent flow in the atmospheric boundary layer (ABL) affects the growth of the grass fires. The model fires showed significant randomness in fire growth: Fire spread is not deterministic in the ABL, and a probabilistic prediction method is warranted. Of the two contributors to the variability in fire growth in the grass fire simulations in the ABL, fire-induced convection, as opposed to the turbulent ABL wind, appears to be the more important one. One mechanism associated with enhanced fire-induced flow is the downdraft behind the frontal fireline. The downdraft is the direct result of the random interaction between the fire plume and the large eddies in the ABL. This study indicates a connection between fire variability in rate of spread and area burnt and so-called convective velocity scale, and it may be possible to use this boundary-layer scale parameter to account for the effects of ABL turbulence on fire spread and fire behavior in today's operational fire prediction systems.

Probability model for analyzing fire management alternatives: theory and structure

Treesearch

Frederick W. Bratten

1982-01-01

A theoretical probability model has been developed for analyzing program alternatives in fire management. It includes submodels or modules for predicting probabilities of fire behavior, fire occurrence, fire suppression, effects of fire on land resources, and financial effects of fire. Generalized "fire management situations" are used to represent actual fire...

76 FR 46330 - NUREG-1934, Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG); Second Draft...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-02

... NUCLEAR REGULATORY COMMISSION [NRC-2009-0568] NUREG-1934, Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG); Second Draft Report for Comment AGENCY: Nuclear Regulatory Commission... 1023259), ``Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG), Second Draft Report for...

A Coupled Model for Simulating Future Wildfire Regimes in the Western U.S.

NASA Astrophysics Data System (ADS)

Bart, R. R.; Kennedy, M. C.; Tague, C.; Hanan, E. J.

2017-12-01

Higher temperatures and larger fuel loads in the western U.S. have increased the size and intensity of wildfires over the past decades. However, it is unclear if this trend will continue over the long-term since increased wildfire activity has the countering effect of reducing landscape fuel loads, while higher temperatures alter the rate of vegetation recovery following fire. In this study, we introduce a coupled ecohydrologic-fire model for investigating how changes in vegetation, forest management, climate, and hydrology may affect future fire regimes. The spatially-distributed ecohydrologic model, RHESSys, simulates hydrologic, carbon and nutrient fluxes at watershed scales; the fire-spread model, WMFire, stochastically propagates fire on a landscape based on conditions in the ecohydrologic model. We use the coupled model to replicate fire return intervals in multiple ecoregions within the western U.S., including the southern Sierra Nevada and southern California. We also examine the sensitivity of fire return intervals to various model processes, including litter production, fire severity, and post-fire vegetation recovery rates. Results indicate that the coupled model is able to replicate expected fire return intervals in the selected locations. Fire return intervals were highly sensitive to the rate of vegetation growth, with longer fire return intervals associated with slower growing vegetation. Application of the model is expected to aid in our understanding of how fuel treatments, climate change and droughts may affect future fire regimes.

The impact of a 2 X CO2 climate on lightning-caused fires

NASA Technical Reports Server (NTRS)

Price, Colin; Rind, David

1994-01-01

Future climate change could have significant repercussions for lightning-caused wildfires. Two empirical fire models are presented relating the frequency of lightning fires and the area burned by these fires to the effective precipitation and the frequency of thunderstorm activity. One model deals with the seasonal variations in lightning fires, while the second model deals with the interannual variations of lightning fires. These fire models are then used with the Goddard Institute for Space Studies General Circulation Model to investigate possible changes in fire frequency and area burned in a 2 X CO2 climate. In the United States, the annual mean number of lightning fires increases by 44%, while the area burned increases by 78%. On a global scale, the largest increase in lightning fires can be expected in untouched tropical ecosystems where few natural fires occur today.

Performance of fire behavior fuel models developed for the Rothermel Surface Fire Spread Model

Treesearch

Robert Ziel; W. Matt Jolly

2009-01-01

In 2005, 40 new fire behavior fuel models were published for use with the Rothermel Surface Fire Spread Model. These new models are intended to augment the original 13 developed in 1972 and 1976. As a compiled set of quantitative fuel descriptions that serve as input to the Rothermel model, the selected fire behavior fuel model has always been critical to the resulting...

Modeling the effects of vegetation heterogeneity on wildland fire behavior

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Sieg, C.; Middleton, R. S.

2017-12-01

Vegetation structure and densities are known to drive fire-spread rate and burn severity. Many fire-spread models incorporate an average, homogenous fuel density in the model domain to drive fire behavior. However, vegetation communities are rarely homogenous and instead present significant heterogeneous structure and fuel densities in the fires path. This results in observed patches of varied burn severities and mosaics of disturbed conditions that affect ecological recovery and hydrologic response. Consequently, to understand the interactions of fire and ecosystem functions, representations of spatially heterogeneous conditions need to be incorporated into fire models. Mechanistic models of fire disturbance offer insight into how fuel load characterization and distribution result in varied fire behavior. Here we use a physically-based 3D combustion model—FIRETEC—that solves conservation of mass, momentum, energy, and chemical species to compare fire behavior on homogenous representations to a heterogeneous vegetation distribution. Results demonstrate the impact vegetation heterogeneity has on the spread rate, intensity, and extent of simulated wildfires thus providing valuable insight in predicted wildland fire evolution and enhanced ability to estimate wildland fire inputs into regional and global climate models.

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

Modeling fire occurrence as a function of landscape

NASA Astrophysics Data System (ADS)

Loboda, T. V.; Carroll, M.; DiMiceli, C.

2011-12-01

Wildland fire is a prominent component of ecosystem functioning worldwide. Nearly all ecosystems experience the impact of naturally occurring or anthropogenically driven fire. Here, we present a spatially explicit and regionally parameterized Fire Occurrence Model (FOM) aimed at developing fire occurrence estimates at landscape and regional scales. The model provides spatially explicit scenarios of fire occurrence based on the available records from fire management agencies, satellite observations, and auxiliary geospatial data sets. Fire occurrence is modeled as a function of the risk of ignition, potential fire behavior, and fire weather using internal regression tree-driven algorithms and empirically established, regionally derived relationships between fire occurrence, fire behavior, and fire weather. The FOM presents a flexible modeling structure with a set of internal globally available default geospatial independent and dependent variables. However, the flexible modeling environment adapts to ingest a variable number, resolution, and content of inputs provided by the user to supplement or replace the default parameters to improve the model's predictive capability. A Southern California FOM instance (SC FOM) was developed using satellite assessments of fire activity from a suite of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, Monitoring Trends in Burn Severity fire perimeters, and auxiliary geospatial information including land use and ownership, utilities, transportation routes, and the Remote Automated Weather Station data records. The model was parameterized based on satellite data acquired between 2001 and 2009 and fire management fire perimeters available prior to 2009. SC FOM predictive capabilities were assessed using observed fire occurrence available from the MODIS active fire product during 2010. The results show that SC FOM provides a realistic estimate of fire occurrence at the landscape level: the fraction of area impacted by fire from the total available area within a given value of the Fire Occurrence Index (FOI) increased from 9.e-06 at FOI < 3 to 28.e-06 at 25 < FOI <= 28. Additionally, the model has revealed a new important relationship between fire occurrence, anthropogenic activity, and fire weather. Data analysis has demonstrated that human activity can alter the expected weather/fire occurrence relationships and result in considerable modifications of fire regimes contrary to the assumed ecological parameters. Specifically, between 2001 and 2009 over 50% of total fire impacted area burned during the low fire danger conditions (Canadian Fire Weather Index < 5). These findings and the FOM capabilities offer a new theoretical construct and an advanced tool for assessing the potential impacts of climate changes on fire regimes, particularly within landscapes which are impacted strongly by human activities. Future development of the FOM will focus on ingesting and internal downscaling of climate variables produced by General or Regional Circulation Models to develop scenarios of potential future change in fire occurrence under the influence of projected climate change at the appropriate regional or landscape scales.

A hierarchical fire frequency model to simulate temporal patterns of fire regimes in LANDIS

Treesearch

Jian Yang; Hong S. He; Eric J. Gustafson

2004-01-01

Fire disturbance has important ecological effects in many forest landscapes. Existing statistically based approaches can be used to examine the effects of a fire regime on forest landscape dynamics. Most examples of statistically based fire models divide a fire occurrence into two stages--fire ignition and fire initiation. However, the exponential and Weibull fire-...

FireStem2D — A two-dimensional heat transfer model for simulating tree stem injury in fires

Treesearch

Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...

Simulating wall and corner fire tests on wood products with the OSU room fire model

Treesearch

H. C. Tran

1994-01-01

This work demonstrates the complexity of modeling wall and corner fires in a compartment. The model chosen for this purpose is the Ohio State University (OSU) room fire model. This model was designed to simulate fire growth on walls in a compartment and therefore lends itself to direct comparison with standard room test results. The model input were bench-scale data...

Comparison of crown fire modeling systems used in three fire management applications

Treesearch

Joe H. Scott

2006-01-01

The relative behavior of surface-crown fire spread rate modeling systems used in three fire management applications-CFIS (Crown Fire Initiation and Spread), FlamMap and NEXUS- is compared using fire environment characteristics derived from a dataset of destructively measured canopy fuel and associated stand characteristics. Although the surface-crown modeling systems...

An Overview of FlamMap Fire Modeling Capabilities

Treesearch

Mark A. Finney

2006-01-01

Computerized and manual systems for modeling wildland fire behavior have long been available (Rothermel 1983, Andrews 1986). These systems focus on one-dimensional behaviors and assume the fire geometry is a spreading line-fire (in contrast with point or area-source fires). Models included in these systems were developed to calculate fire spread rate (Rothermel 1972,...

Using HFire for spatial modeling of fire in shrublands

Treesearch

Seth H. Peterson; Marco E. Morais; Jean M. Carlson; Philip E. Dennison; Dar A. Roberts; Max A. Moritz; David R. Weise

2009-01-01

An efficient raster fire-spread model named HFire is introduced. HFire can simulate single-fire events or long-term fire regimes, using the same fire-spread algorithm. This paper describes the HFire algorithm, benchmarks the model using a standard set of tests developed for FARSITE, and compares historical and predicted fire spread perimeters for three southern...

Decision modeling for analyzing fire action outcomes

Treesearch

Donald MacGregor; Armando Gonzalez-Caban

2008-01-01

A methodology for incident decomposition and reconstruction is developed based on the concept of an "event-frame model." The event-frame model characterizes a fire incident in terms of (a) environmental events that pertain to the fire and the fire context (e.g., fire behavior, weather, fuels) and (b) management events that represent responses to the fire...

Identifying the location of fire refuges in wet forest ecosystems.

PubMed

Berry, Laurence E; Driscoll, Don A; Stein, John A; Blanchard, Wade; Banks, Sam C; Bradstock, Ross A; Lindenmayer, David B

2015-12-01

The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas that experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models that identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. We used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be interpreted as management tools to identify potential fire refuges. We examined the relationship between the probability of fire refuge occurrence as predicted by an existing fire refuge model and fire severity experienced during a large wildfire. We also examined the extent to which local fire severity was influenced by fire severity in the surrounding landscape. We used a combination of statistical approaches, including generalized linear modeling, variogram analysis, and receiver operating characteristics and area under the curve analysis (ROC AUC). We found that the amount of unburned habitat and the factors influencing the retention and location of fire refuges varied with fire conditions. Under extreme fire conditions, the distribution of fire refuges was limited to only extremely sheltered, fire-resistant regions of the landscape. During extreme fire conditions, fire severity patterns were largely determined by stochastic factors that could not be predicted by the model. When fire conditions were moderate, physical landscape properties appeared to mediate fire severity distribution. Our study demonstrates that land managers can employ predictive landscape fire models to identify the broader climatic and spatial domain within which fire refuges are likely to be present. It is essential that within these envelopes, forest is protected from logging, roads, and other developments so that the ecological processes related to the establishment and subsequent use of fire refuges are maintained.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollingsworth, LaWen T.; Kurth, Laurie,; Parresol, Bernard, R.

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System. The fundamental fire intensity algorithms in these systems require surface fire behavior fuel models and canopy cover to model surface fire behavior. Canopy base height, stand height, and canopy bulk density are required in addition to surface fire behavior fuel models and canopy cover to model crown fire activity. Several surface fuelmore » and canopy classification efforts have used various remote sensing and ecological relationships as core methods to develop the spatial layers. All of these methods depend upon consistent and temporally constant interpretations of crown attributes and their ecological conditions to estimate surface fuel conditions. This study evaluates modeled fire behavior for an 80,000 ha tract of land in the Atlantic Coastal Plain of the southeastern US using three different data sources. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developed surface fire behavior fuel models and canopy attributes for the US using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern US using satellite imagery. Differences in modeled fire behavior, data development, and data utility are summarized to assist in determining which data source may be most applicable for various land management activities and required analyses. Characterizing fire behavior under different fuel relationships provides insights for natural ecological processes, management strategies for fire mitigation, and positive and negative features of different modeling systems. A comparison of flame length, rate of spread, crown fire activity, and burn probabilities modeled with FlamMap shows some similar patterns across the landscape from all three data sources, but there are potentially important differences. All data sources showed an expected range of fire behavior. Average flame lengths ranged between 1 and 1.4 m. Rate of spread varied the greatest with a range of 2.4-5.7 m min{sup -1}. Passive crown fire was predicted for 5% of the study area using FCCS and LANDFIRE while passive crown fire was not predicted using SWRA data. No active crown fire was predicted regardless of the data source. Burn probability patterns across the landscape were similar but probability was highest using SWRA and lowest using FCCS.« less

Stochastic representation of fire behavior in a wildland fire protection planning model for California.

Treesearch

J. Keith Gilless; Jeremy S. Fried

1998-01-01

A fire behavior module was developed for the California Fire Economics Simulator version 2 (CFES2), a stochastic simulation model of initial attack on wildland fire used by the California Department of Forestry and Fire Protection. Fire rate of spread (ROS) and fire dispatch level (FDL) for simulated fires "occurring" on the same day are determined by making...

Comparing effects of fire modeling methods on simulated fire patterns and succession: a case study in the Missouri Ozarks

Treesearch

Jian Yang; Hong S. He; Brian R. Sturtevant; Brian R. Miranda; Eric J. Gustafson

2008-01-01

We compared four fire spread simulation methods (completely random, dynamic percolation. size-based minimum travel time algorithm. and duration-based minimum travel time algorithm) and two fire occurrence simulation methods (Poisson fire frequency model and hierarchical fire frequency model) using a two-way factorial design. We examined these treatment effects on...

Employing Numerical Weather Models to Enhance Fire Weather and Fire Behavior Predictions

Treesearch

Joseph J. Charney; Lesley A. Fusina

2006-01-01

This paper presents an assessment of fire weather and fire behavior predictions produced by a numerical weather prediction model similar to those used by operational weather forecasters when preparing their forecasts. The PSU/NCAR MM5 model is used to simulate the weather conditions associated with three fire episodes in June 2005. Extreme fire behavior was reported...

BehavePlus fire modeling system, version 5.0: Design and Features

Treesearch

Faith Ann Heinsch; Patricia L. Andrews

2010-01-01

The BehavePlus fire modeling system is a computer program that is based on mathematical models that describe wildland fire behavior and effects and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a host of fire management applications, including projecting the behavior of an ongoing fire, planning...

BehavePlus fire modeling system, version 4.0: User's Guide

Treesearch

Patricia L. Andrews; Collin D. Bevins; Robert C. Seli

2005-01-01

The BehavePlus fire modeling system is a program for personal computers that is a collection of mathematical models that describe fire and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a multitude of fire management applications including projecting the behavior of an ongoing fire, planning...

29 CFR Appendix A to Subpart P of... - Model Fire Safety Plan (Non-Mandatory)

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 7 2013-07-01 2013-07-01 false Model Fire Safety Plan (Non-Mandatory) A Appendix A to...—Model Fire Safety Plan (Non-Mandatory) Model Fire Safety Plan Note: This appendix is non-mandatory and provides guidance to assist employers in establishing a Fire Safety Plan as required in § 1915.502. Table...

29 CFR Appendix A to Subpart P to... - Model Fire Safety Plan (Non-Mandatory)

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 7 2012-07-01 2012-07-01 false Model Fire Safety Plan (Non-Mandatory) A Appendix A to...—Model Fire Safety Plan (Non-Mandatory) Model Fire Safety Plan Note: This appendix is non-mandatory and provides guidance to assist employers in establishing a Fire Safety Plan as required in § 1915.502. Table...

29 CFR Appendix A to Subpart P of... - Model Fire Safety Plan (Non-Mandatory)

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 7 2014-07-01 2014-07-01 false Model Fire Safety Plan (Non-Mandatory) A Appendix A to...—Model Fire Safety Plan (Non-Mandatory) Model Fire Safety Plan Note: This appendix is non-mandatory and provides guidance to assist employers in establishing a Fire Safety Plan as required in § 1915.502. Table...

2013 Annual Report: Fire Modeling Institute

Treesearch

Robin J. Innes; Faith Ann Heinsch; Kristine M. Lee

2014-01-01

The Fire Modeling Institute (FMI) of the U.S. Forest Service, Rocky Mountain Research Station (RMRS), is a national and international resource for fire managers. Located within the Fire, Fuel, and Smoke Science Program at the Missoula Fire Sciences Laboratory (Fire Lab) in Montana, FMI helps managers utilize fire and fuel science and technology developed throughout the...

Photochemical model estimated fire impacts on ozone and aerosol evaluated with field studies and routine data sources

NASA Astrophysics Data System (ADS)

Baker, K. R.

2017-12-01

Highly instrumented field studies provide a unique opportunity to evaluate multiple aspects of photochemical grid model representation of fire emissions, dispersion, and chemical evolution. Fuel information and burn area for a specific fire coupled with near-fire and downwind chemical measurements provides information needed to constrain model predicted fire plume transport and chemical evolution of important pollutants such as ozone and particulate matter (PM2.5) that have deleterious health effects. Most local to regional scale field campaigns to date have made relatively few transects through plumes from fires with well characterized fuel type and consumption. While more comprehensive field studies are being planned for 2018 and beyond (WE-CAN, FIREX, FIRE-CHEM, and FASMEE), existing measurement data from multiple field campaigns including 2013 SEAC4RS, satellite data, and routine surface networks are used to assess how a regulatory modeling system captures fire impacts on local to regional scale ozone and PM2.5. Key aspects of the regulatory modeling system include fire location and burn area from SMARTFIRE2, emissions from BlueSky framework, and predictions of ambient O3 and PM2.5 from the Community Multiscale Air Quality (CMAQ) photochemical transport model. A comparison of model estimated O3 from specific fires with routine surface measurements at rural locations in proximity to the 2013 Rim fire, 2011 Wallow fire, and 2011 Flint Hills fires suggest the modeling system over-estimates smoke impacts on hourly ozone. Sensitivity simulations where solar radiation and photolysis rates are more aggressively attenuated by smoke reduced O3 predictions but did not ameliorate the over prediction bias. PM2.5 organic carbon tends to be overpredicted at rural surface sites downwind from the 2011 Flint Hills prescribed fires while results were mixed at rural sites downwind of the 2013 Rim fire and 2011 Wallow fire suggesting differences in fuel characterization (e.g., emission factors, emissions speciation, burn period, etc.) between these areas may contribute to differences in model prediction. Aircraft plume transects made downwind of the 2013 Rim fire and satellite information suggest the model does well at regional scale plume transport.

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.

FARSITE: a fire area simulator for fire managers

Treesearch

Mark A. Finney

1995-01-01

A fire growth model (FARSITE) has been developed for use on personal computers (PC’s). Because PC’s are commonly used by land and fire managers, this portable platform would be an accustomed means to bring fire growth modeling technology to management applications. The FARSITE model is intended for use in projecting the growth of prescribed natural fires for wilderness...

Application of a Mesoscale Atmospheric Coupled Fire Model BRAMS-FIRE to Alentejo Woodland Fire and Comparison of Performance with the Fire Model WRF-Sfire.

NASA Astrophysics Data System (ADS)

Freitas, S. R.; Menezes, I. C.; Stockler, R.; Mello, R.; Ribeiro, N. A.; Corte-Real, J. A. M.; Surový, P.

2014-12-01

Models of fuel with the identification of vegetation patterns of Montado ecosystem in Portugal was incorporated in the mesoscale Brazilian Atmospheric Modeling System (BRAMS) and coupled with a spread woodland fire model. The BRAMS-FIRE is a new system developed by the "Centro de Previsão de Tempo e Estudos Climáticos" (CPTEC/INPE, Brazil) and the "Instituto de Ciências Agrárias e Ambientais Mediterrâneas" (ICAAM, Portugal). The fire model used in this effort was originally, developed by Mandel et al. (2013) and further incorporated in the Weather Research and Forecast model (WRF). Two grids of high spatial resolution were configured with surface input data and fuel models integrated for simulations using both models BRAMS-FIRE and WRF-SFIRE. One grid was placed in the plain land near Beja and the other one in the hills of Ossa to evaluate different types of fire propagation and calibrate BRAMS-FIRE. The objective is simulating the effects of atmospheric circulation in local scale, namely the movements of the heat front and energy release associated to it, obtained by this two models in an episode of woodland fire which took place in Alentejo area in the last decade, for application to planning and evaluations of agro woodland fire risks. We aim to model the behavior of forest fires through a set of equations whose solutions provide quantitative values of one or more variables related to the propagation of fire, described by semi-empirical expressions that are complemented by experimental data allow to obtain the main variables related advancing the perimeter of the fire, as the propagation speed, the intensity of the fire front and fuel consumption and its interaction with atmospheric dynamic system. References Mandel, J., J. D. Beezley, G. Kelman, A. K. Kochanski, V. Y. Kondratenko, B. H. Lynn, and M. Vejmelka, 2013. New features in WRF-SFIRE and the wildfire forecasting and danger system in Israel. Natural Hazards and Earth System Sciences, submitted, Numerical Wildfires, Cargèse, France, May 13-18, 2013.

Contribution of regional-scale fire events to ozone and PM2.5 air quality estimated by photochemical modeling approaches

NASA Astrophysics Data System (ADS)

Baker, K. R.; Woody, M. C.; Tonnesen, G. S.; Hutzell, W.; Pye, H. O. T.; Beaver, M. R.; Pouliot, G.; Pierce, T.

2016-09-01

Two specific fires from 2011 are tracked for local to regional scale contribution to ozone (O3) and fine particulate matter (PM2.5) using a freely available regulatory modeling system that includes the BlueSky wildland fire emissions tool, Spare Matrix Operator Kernel Emissions (SMOKE) model, Weather and Research Forecasting (WRF) meteorological model, and Community Multiscale Air Quality (CMAQ) photochemical grid model. The modeling system was applied to track the contribution from a wildfire (Wallow) and prescribed fire (Flint Hills) using both source sensitivity and source apportionment approaches. The model estimated fire contribution to primary and secondary pollutants are comparable using source sensitivity (brute-force zero out) and source apportionment (Integrated Source Apportionment Method) approaches. Model estimated O3 enhancement relative to CO is similar to values reported in literature indicating the modeling system captures the range of O3 inhibition possible near fires and O3 production both near the fire and downwind. O3 and peroxyacetyl nitrate (PAN) are formed in the fire plume and transported downwind along with highly reactive VOC species such as formaldehyde and acetaldehyde that are both emitted by the fire and rapidly produced in the fire plume by VOC oxidation reactions. PAN and aldehydes contribute to continued downwind O3 production. The transport and thermal decomposition of PAN to nitrogen oxides (NOX) enables O3 production in areas limited by NOX availability and the photolysis of aldehydes to produce free radicals (HOX) causes increased O3 production in NOX rich areas. The modeling system tends to overestimate hourly surface O3 at routine rural monitors in close proximity to the fires when the model predicts elevated fire impacts on O3 and Hazard Mapping System (HMS) data indicates possible fire impact. A sensitivity simulation in which solar radiation and photolysis rates were more aggressively attenuated by aerosol in the plume reduced model O3 but does not eliminate this bias. A comparison of model predicted daily average speciated PM2.5 at surface rural routine network sites when the model predicts fire impacts from either of these fires shows a tendency toward overestimation of PM2.5 organic aerosol in close proximity to these fires. The standard version of the CMAQ treats primarily emitted organic aerosol as non-volatile. An alternative approach for treating organic aerosol as semi-volatile resulted in lower PM2.5 organic aerosol from these fires but does not eliminate the bias. Future work should focus on modeling specific fire events that are well characterized in terms of size, emissions, and have extensive measurements taken near the fire and downwind to better constrain model representation of important physical and chemical processes (e.g. aerosol photolysis attenuation and organic aerosol treatment) related to wild and prescribed fires.

Smoke and Emissions Model Intercomparison Project (SEMIP)

NASA Astrophysics Data System (ADS)

Larkin, N. K.; Raffuse, S.; Strand, T.; Solomon, R.; Sullivan, D.; Wheeler, N.

2008-12-01

Fire emissions and smoke impacts from wildland fire are a growing concern due to increasing fire season severity, dwindling tolerance of smoke by the public, tightening air quality regulations, and their role in climate change issues. Unfortunately, while a number of models and modeling system solutions are available to address these issues, the lack of quantitative information on the limitations and difference between smoke and emissions models impedes the use of these tools for real-world applications (JFSP, 2007). We describe a new, open-access project to directly address this issue, the open-access Smoke Emissions Model Intercomparison Project (SEMIP) and invite the community to participate. Preliminary work utilizing the modular BlueSky framework to directly compare fire location and size information, fuel loading amounts, fuel consumption rates, and fire emissions from a number of current models that has found model-to-model variability as high as two orders of magnitude for an individual fire. Fire emissions inventories also show significant variability on both regional and national scales that are dependant on the fire location information used (ground report vs. satellite), the fuel loading maps assumed, and the fire consumption models employed. SEMIP expands on this work and creates an open-access database of model results and observations with the goal of furthering model development and model prediction usability for real-world decision support.

A second-order impact model for forest fire regimes.

PubMed

Maggi, Stefano; Rinaldi, Sergio

2006-09-01

We present a very simple "impact" model for the description of forest fires and show that it can mimic the known characteristics of wild fire regimes in savannas, boreal forests, and Mediterranean forests. Moreover, the distribution of burned biomasses in model generated fires resemble those of burned areas in numerous large forests around the world. The model has also the merits of being the first second-order model for forest fires and the first example of the use of impact models in the study of ecosystems.

One thousand years of fires: Integrating proxy and model data

USGS Publications Warehouse

Kehrwald, Natalie; Aleman, Julie C.; Coughlan, Michael; Courtney Mustaphi, Colin J.; Githumbi, Esther N.; Magi, Brian I.; Marlon, Jennifer R.; Power, Mitchell J.

2016-01-01

The expected increase in fire activity in the upcoming decades has led to a surge in research trying to understand their causes, the factors that may have influenced similar times of fire activity in the past, and the implications of such fire activity in the future. Multiple types of complementary data provide information on the impacts of current fires and the extent of past fires. The wide array of data encompasses different spatial and temporal resolutions (Figure 1) and includes fire proxy information such as charcoal and tree ring fire scars, observational records, satellite products, modern emissions data, fire models within global land cover and vegetation models, and sociodemographic data for modeling past human land use and ignition frequency. Any single data type is more powerful when combined with another source of information. Merging model and proxy data enables analyses of how fire activity modifies vegetation distribution, air and water quality, and proximity to cities; these analyses in turn support land management decisions relating to conservation and development.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-05-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In this study, 16 simulations are conducted using WRF-Fire to examine the sensitivity of resolving VDLS to spatial resolution and atmosphere-fire coupling within the WRF-Fire model framework. The horizontal grid spacing is varied between 25 and 90 m, and the two-way atmosphere-fire coupling is either enabled or disabled. At high spatial resolution, the atmosphere-fire coupling increases the peak uphill and lateral spread rate by a factor of up to 2.7 and 9.5. The enhancement of the uphill and lateral spread rate diminishes at coarser spatial resolution, and VDLS is not modelled for a horizontal grid spacing of 90 m. The laterally spreading fire fronts become the dominant contributors of the extreme pyro-convection. The resolved fire-induced vortices responsible for driving the lateral spread in the coupled simulations have non-zero vorticity along each unit vector direction, and develop due to an interaction between the background winds and vertical return circulations generated at the flank of the fire front as part of the pyro-convective updraft. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to reproduce VDLS within the current WRF-Fire model framework.

BLAZE, a novel Fire-Model for the CABLE Land-Surface Model applied to a Re-Assessment of the Australian Continental Carbon Budget

NASA Astrophysics Data System (ADS)

Nieradzik, L. P.; Haverd, V. E.; Briggs, P.; Meyer, C. P.; Canadell, J.

2015-12-01

Fires play a major role in the carbon-cycle and the development of global vegetation, especially on the continent of Australia, where vegetation is prone to frequent fire occurences and where regional composition and stand-age distribution is regulated by fire. Furthermore, the probable changes of fire behaviour under a changing climate are still poorly understood and require further investigation.In this presentation we introduce the fire-model BLAZE (BLAZe induced land-atmosphere flux Estimator), designed for a novel approach to simulate fire-frequencies, fire-intensities, fire related fluxes and the responses in vegetation. Fire frequencies are prescribed using SIMFIRE (Knorr et al., 2014) or GFED3 (e.g. Giglio et al., 2013). Fire-Line-Intensity (FLI) is computed from meteorological information and fuel loads which are state variables within the C-cycle component of CABLE (Community Atmosphere-Biosphere-Land Exchange model). This FLI is used as an input to the tree-demography model POP(Population-Order-Physiology; Haverd et al., 2014). Within POP the fire-mortality depends on FLI and tree height distribution. Intensity-dependent combustion factors (CF) are then generated for and applied to live and litter carbon pools as well as the transfers from live pools to litter caused by fire. Thus, both fire and stand characteristics are taken into account which has a legacy effect on future events. Gross C-CO2 emissions from Australian wild fires are larger than Australian territorial fossil fuel emissions. However, the net effect of fire on the Australian terrestrial carbon budget is unknown. We address this by applying the newly-developed fire module, integrated within the CABLE land surface model, and optimised for the Australian region, to a reassessment of the Australian Terrestrial Carbon Budget.

Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions.

PubMed

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition.

Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions

PubMed Central

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition. PMID:25679957

Implementing microscopic charcoal in a global climate-aerosol model

NASA Astrophysics Data System (ADS)

Gilgen, Anina; Lohmann, Ulrike; Brügger, Sandra; Adolf, Carole; Ickes, Luisa

2017-04-01

Information about past fire activity is crucial to validate fire models and to better understand their deficiencies. Several paleofire records exist, among them ice cores and sediments, which preserve fire tracers like levoglucosan, vanillic acid, or charcoal particles. In this work, we implement microscopic charcoal particles (maximum dimension 10-100 μm) into the global climate-aerosol model ECHAM6.3HAM2.3. Since we are not aware of any reliable estimates of microscopic charcoal emissions, we scaled black carbon emissions from GFAS to capture the charcoal fluxes from a calibration dataset. After that, model results were compared with a validation dataset. The coarse model resolution (T63L31; 1.9°x1.9°) impedes the model to capture local variability of charcoal fluxes. However, variability on the global scale is pronounced due to highly-variable fire emissions. In future, we plan to model charcoal fluxes in the past 1-2 centuries using fire emissions provided from fire models. Furthermore, we intend to compare modelled charcoal fluxes from prescribed fire emissions with those calculated by an interactive fire model.

FireStem2D – A Two-Dimensional Heat Transfer Model for Simulating Tree Stem Injury in Fires

PubMed Central

Chatziefstratiou, Efthalia K.; Bohrer, Gil; Bova, Anthony S.; Subramanian, Ravishankar; Frasson, Renato P. M.; Scherzer, Amy; Butler, Bret W.; Dickinson, Matthew B.

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by resolving stem moisture loss, temperatures through the stem, degree of bark charring, and necrotic depth around the stem. We present the results of numerical parameterization and model evaluation experiments for FireStem2D that simulate laboratory stem-heating experiments of 52 tree sections from 25 trees. We also conducted a set of virtual sensitivity analysis experiments to test the effects of unevenness of heating around the stem and with aboveground height using data from two studies: a low-intensity surface fire and a more intense crown fire. The model allows for improved understanding and prediction of the effects of wildland fire on injury and mortality of trees of different species and sizes. PMID:23894599

Modelling the impacts of reoccurring fires in tropical savannahs using Biome-BGC.

NASA Astrophysics Data System (ADS)

Fletcher, Charlotte; Petritsch, Richard; Pietsch, Stephan

2010-05-01

Fires are a dominant feature of tropical savannahs and have occurred throughout history by natural as well as human-induced means. These fires have a profound influence on the landscape in terms of flux dynamics and vegetative species composition. This study attempts to understand the impacts of fire regimes on flux dynamics and vegetation composition in savannahs using the Biome-BGC model. The Batéké Plateau, Gabon - an area of savannah grasslands in the Congo basin, serves as a case-study. To achieve model validation for savannahs, data sets from stands with differing levels of past burning are used. It is hypothesised that the field measurements from those stands with lower-levels of past burning will correlate with the Biome-BGC model output, meaning that the model is validated for the savannah excluding fire regimes. However, in reality, fire is frequent in the savannah. Data on past fire events are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) to provide the fire regimes of the model. As the field data-driven measurements of the burnt stands are influenced by fire in the savannah, this will therefore result in a Biome-BGC model validated for the impacts of fire on savannah ecology. The validated model can then be used to predict the savannah's flux dynamics under the fire scenarios expected with climate and/or human impact change.

Modelling Technology for Building Fire Scene with Virtual Geographic Environment

NASA Astrophysics Data System (ADS)

Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

2017-09-01

Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

Comparing the Global Charcoal Database with Burned Area Trends from an Offline Fire Model Driven by the NCAR Last Millennium Ensemble

NASA Astrophysics Data System (ADS)

Schaefer, A.; Magi, B. I.; Marlon, J. R.; Bartlein, P. J.

2017-12-01

This study uses an offline fire model driven by output from the NCAR Community Earth System Model Last Millennium Ensemble (LME) to evaluate how climate, ecological, and human factors contributed to burned area over the past millennium, and uses the Global Charcoal Database (GCD) record of fire activity as a constraint. The offline fire model is similar to the fire module within the NCAR Community Land Model. The LME experiment includes 13 simulations of the Earth system from 850 CE through 2005 CE, and the fire model simulates burned area using LME climate and vegetation with imposed land use and land cover change. The fire model trends are compared to GCD records of charcoal accumulation rates derived from sediment cores. The comparisons are a way to assess the skill of the fire model, but also set up a methodology to directly test hypotheses of the main drivers of fire patterns over the past millennium. The focus is on regions selected from the GCD with high data density, and that have lake sediment cores that best capture the last millennium. Preliminary results are based on a fire model which excludes burning cropland and pasture land cover types, but this allows some assessment of how climate variability is captured by the fire model. Generally, there is good agreement between modeled burned area trends and fire trends from GCD for many regions of interest, suggesting the strength of climate variability as a control. At the global scale, trends and features are similar from 850 to 1700, which includes the Medieval Climate Anomaly and the Little Ice Age. After 1700, the trends significantly deviate, which may be due to non-cultivated land being converted to cultivated. In key regions of high data density in the GCD such as the Western USA, the trends agree from 850 to 1200 but diverge from 1200 to 1300. From 1300 to 1800, the trends show good agreement again. Implementing processes to include burning cultivated land within the fire model is anticipated to improve the agreement, but also to test the sensitivity of models to different drivers of fire.

A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks

PubMed Central

Schaffer, Evan S.; Ostojic, Srdjan; Abbott, L. F.

2013-01-01

Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons. PMID:24204236

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

NASA Astrophysics Data System (ADS)

Rabin, Sam S.; Ward, Daniel S.; Malyshev, Sergey L.; Magi, Brian I.; Shevliakova, Elena; Pacala, Stephen W.

2018-03-01

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001-2009 (global totals: 0.434×106 and 2.02×106 km2 yr-1 modeled, 0.454×106 and 2.04×106 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgC yr-1 modeled, 0.194 and 0.538 PgC yr-1 observed). The non-agricultural fire module underestimates global burned area (1.91×106 km2 yr-1 modeled, 2.44×106 km2 yr-1 observed) and carbon emissions (1.14 PgC yr-1 modeled, 1.84 PgC yr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg-Marquardt algorithm in an interactive optimization for a dynamic global vegetation model.

Cinema Fire Modelling by FDS

NASA Astrophysics Data System (ADS)

Glasa, J.; Valasek, L.; Weisenpacher, P.; Halada, L.

2013-02-01

Recent advances in computer fluid dynamics (CFD) and rapid increase of computational power of current computers have led to the development of CFD models capable to describe fire in complex geometries incorporating a wide variety of physical phenomena related to fire. In this paper, we demonstrate the use of Fire Dynamics Simulator (FDS) for cinema fire modelling. FDS is an advanced CFD system intended for simulation of the fire and smoke spread and prediction of thermal flows, toxic substances concentrations and other relevant parameters of fire. The course of fire in a cinema hall is described focusing on related safety risks. Fire properties of flammable materials used in the simulation were determined by laboratory measurements and validated by fire tests and computer simulations

Obtaining a Pragmatic Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Earth Observation Data

NASA Astrophysics Data System (ADS)

Kantzas, Euripides; Quegan, Shaun

2015-04-01

Fire constitutes a violent and unpredictable pathway of carbon from the terrestrial biosphere into the atmosphere. Despite fire emissions being in many biomes of similar magnitude to that of Net Ecosystem Exchange, even the most complex Dynamic Vegetation Models (DVMs) embedded in IPCC General Circulation Models poorly represent fire behavior and dynamics, a fact which still remains understated. As DVMs operate on a deterministic, grid cell-by-grid cell basis they are unable to describe a host of important fire characteristics such as its propagation, magnitude of area burned and stochastic nature. Here we address these issues by describing a model-independent methodology which assimilates Earth Observation (EO) data by employing image analysis techniques and algorithms to offer a realistic fire disturbance regime in a DVM. This novel approach, with minimum model restructuring, manages to retain the Fire Return Interval produced by the model whilst assigning pragmatic characteristics to its fire outputs thus allowing realistic simulations of fire-related processes such as carbon injection into the atmosphere and permafrost degradation. We focus our simulations in the Arctic and specifically Canada and Russia and we offer a snippet of how this approach permits models to engage in post-fire dynamics hitherto absent from any other model regardless of complexity.

Influences of coupled fire-atmosphere interaction on wildfire behavior

NASA Astrophysics Data System (ADS)

Linn, R.; Winterkamp, J.; Jonko, A. K.; Runde, I.; Canfield, J.; Parsons, R.; Sieg, C.

2017-12-01

Two-way interactions between fire and the environment affect fire behavior at scales ranging from buoyancy-induced mixing and turbulence to fire-scale circulations that retard or increase fire spread. Advances in computing have created new opportunities for the exploration of coupled fire-atmosphere behavior using numerical models that represent interactions between the dominant processes driving wildfire behavior, including convective and radiative heat transfer, aerodynamic drag and buoyant response of the atmosphere to heat released by the fire. Such models are not practical for operational, faster-than-real-time fire prediction due to their computational and data requirements. However, they are valuable tools for exploring influences of fire-atmosphere feedbacks on fire behavior as they explicitly simulate atmospheric motions surrounding fires from meter to kilometer scales. We use the coupled fire-atmosphere model FIRETEC to gain new insights into aspects of fire behavior that have been observed in the field and laboratory, to carry out sensitivity analysis that is impractical through observations and to pose new hypotheses that can be tested experimentally. Specifically, we use FIRETEC to study the following multi-scale coupled fire-atmosphere interactions: 1) 3D fire-atmosphere interaction that dictates multi-scale fire line dynamics; 2) influence of vegetation heterogeneity and variability in wind fields on predictability of fire spread; 3) fundamental impacts of topography on fire spread. These numerical studies support new conceptual models for the dominant roles of multi-scale fluid dynamics in determining fire spread, including the roles of crosswind fire line-intensity variations on heat transfer to unburned fuels and the role of fire line depth expansion in upslope acceleration of fires.

Numerical Modelling of Fire-Atmosphere Interactions and the 2003 Canberra Bushfires

NASA Astrophysics Data System (ADS)

Simpson, C.; Sturman, A.; Zawar-Reza, P.

2010-12-01

It is well known that the behaviour of a wildland fire is strongly associated with the conditions of its surrounding atmosphere. However, the two-way interactions between fire behaviour and the atmospheric conditions are not well understood. A numerical model is used to simulate wildland fires so that the nature of these fire-atmosphere interactions, and how they might affect fire behaviour, can be further investigated. The 2003 Canberra bushfires are used as a case study due to their highly destructive and unusual behaviour. On the 18th January 2003, these fires spread to the urban suburbs of Canberra, resulting in the loss of four lives and the destruction of over 500 homes. Fire-atmosphere interactions are believed to have played an important role in making these fires so destructive. WRF-Fire is used to perform real data simulations of the 2003 Canberra bushfires. WRF-Fire is a coupled fire-atmosphere model, which combines a semi-empirical fire spread model with an atmospheric model, allowing it to directly simulate the two-way interactions between a fire and its surrounding atmosphere. These simulations show the impact of the presence of a fire on conditions within the atmospheric boundary layer. This modification of the atmosphere, resulting from the injection of heat and moisture released by the fire, appears to have a direct feedback onto the overall fire behaviour. The bushfire simulations presented in this paper provide important scientific insights into the nature of fire-atmosphere interactions for a real situation. It is expected that they will also help fire managers in Australia to better understand why the 2003 Canberra bushfires were so destructive, as well as to gain improved insight into bushfire behaviour in general.

Linking 3D spatial models of fuels and fire: Effects of spatial heterogeneity on fire behavior

Treesearch

Russell A. Parsons; William E. Mell; Peter McCauley

2011-01-01

Crownfire endangers fire fighters and can have severe ecological consequences. Prediction of fire behavior in tree crowns is essential to informed decisions in fire management. Current methods used in fire management do not address variability in crown fuels. New mechanistic physics-based fire models address convective heat transfer with computational fluid dynamics (...

Assessing crown fire potential by linking models of surface and crown fire behavior

Treesearch

Joe H. Scott; Elizabeth D. Reinhardt

2001-01-01

Fire managers are increasingly concerned about the threat of crown fires, yet only now are quantitative methods for assessing crown fire hazard being developed. Links among existing mathematical models of fire behavior are used to develop two indices of crown fire hazard-the Torching Index and Crowning Index. These indices can be used to ordinate different forest...

A fire management simulation model using stochastic arrival times

Treesearch

Eric L. Smith

1987-01-01

Fire management simulation models are used to predict the impact of changes in the fire management program on fire outcomes. As with all models, the goal is to abstract reality without seriously distorting relationships between variables of interest. One important variable of fire organization performance is the length of time it takes to get suppression units to the...

Modeling fuels and fire effects in 3D: Model description and applications

Treesearch

Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

2016-01-01

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-09-01

Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecasting) coupled atmosphere-fire model is used to examine the sensitivity of resolving VLS to both the horizontal and vertical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the dominant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to model VLS with WRF-Fire.

Assessing the effects of fire disturbances on ecosystems: A scientific agenda for research and management

USGS Publications Warehouse

Schmoldt, D.L.; Peterson, D.L.; Keane, R.E.; Lenihan, J.M.; McKenzie, D.; Weise, D.R.; Sandberg, D.V.

1999-01-01

A team of fire scientists and resource managers convened 17-19 April 1996 in Seattle, Washington, to assess the effects of fire disturbance on ecosystems. Objectives of this workshop were to develop scientific recommendations for future fire research and management activities. These recommendations included a series of numerically ranked scientific and managerial questions and responses focusing on (1) links among fire effects, fuels, and climate; (2) fire as a large-scale disturbance; (3) fire-effects modeling structures; and (4) managerial concerns, applications, and decision support. At the present time, understanding of fire effects and the ability to extrapolate fire-effects knowledge to large spatial scales are limited, because most data have been collected at small spatial scales for specific applications. Although we clearly need more large-scale fire-effects data, it will be more expedient to concentrate efforts on improving and linking existing models that simulate fire effects in a georeferenced format while integrating empirical data as they become available. A significant component of this effort should be improved communication between modelers and managers to develop modeling tools to use in a planning context. Another component of this modeling effort should improve our ability to predict the interactions of fire and potential climatic change at very large spatial scales. The priority issues and approaches described here provide a template for fire science and fire management programs in the next decade and beyond.

Applications of Living Fire PRA models to Fire Protection Significance Determination Process in Taiwan

DOE Office of Scientific and Technical Information (OSTI.GOV)

De-Cheng, Chen; Chung-Kung, Lo; Tsu-Jen, Lin

2004-07-01

The living fire probabilistic risk assessment (PRA) models for all three operating nuclear power plants (NPPs) in Taiwan had been established in December 2000. In that study, a scenario-based PRA approach was adopted to systematically evaluate the fire and smoke hazards and associated risks. Using these fire PRA models developed, a risk-informed application project had also been completed in December 2002 for the evaluation of cable-tray fire-barrier wrapping exemption. This paper presents a new application of the fire PRA models to fire protection issues using the fire protection significance determination process (FP SDP). The fire protection issues studied may involvemore » the selection of appropriate compensatory measures during the period when an automatic fire detection or suppression system in a safety-related fire zone becomes inoperable. The compensatory measure can either be a 24-hour fire watch or an hourly fire patrol. The living fire PRA models were used to estimate the increase in risk associated with the fire protection issue in terms of changes in core damage frequency (CDF) and large early release frequency (LERF). In compliance with SDP at-power and the acceptance guidelines specified in RG 1.174, the fire protection issues in question can be grouped into four categories; red, yellow, white and green, in accordance with the guidelines developed for FD SDP. A 24-hour fire watch is suggested only required for the yellow condition, while an hourly fire patrol may be adopted for the white condition. More limiting requirement is suggested for the red condition, but no special consideration is needed for the green condition. For the calculation of risk measures, risk impacts from any additional fire scenarios that may have been introduced, as well as more severe initiating events and fire damages that may accompany the fire protection issue should be considered carefully. Examples are presented in this paper to illustrate the evaluation process. (authors)« less

Fire Detection Organizing Questions

NASA Technical Reports Server (NTRS)

2004-01-01

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Assessing the predictability of fire occurrence and area burned across phytoclimatic regions in Spain

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2014-01-01

Most fire protection agencies throughout the world have developed forest fire risk forecast systems, usually building upon existing fire danger indices and meteorological forecast data. In this context, the daily predictability of wildfires is of utmost importance in order to allow the fire protection agencies to issue timely fire hazard alerts. In this study, we address the predictability of daily fire occurrence using the components of the Canadian Fire Weather Index (FWI) System and related variables calculated from the latest ECMWF (European Centre for Medium Range Weather Forecasts) reanalysis, ERA-Interim. We develop daily fire occurrence models in peninsular Spain for the period 1990-2008 and, considering different minimum burned area thresholds for fire definition, assess their ability to reproduce the inter-annual fire frequency variability. We based the analysis on a phytoclimatic classification aiming the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climate/fuel conditions. We then extend the analysis in order to assess the predictability of monthly burned areas. The sensitivity of the models to the level of spatial aggregation of the data is also evaluated. Additionally, we investigate the gain in model performance with the inclusion of socioeconomic and land use/land cover (LULC) covariates in model formulation. Fire occurrence models have attained good performance in most of the phytoclimatic zones considered, being able to faithfully reproduce the inter-annual variability of fire frequency. Total area burned has exhibited some dependence on the meteorological drivers, although model performance was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, highlighting the adequacy of the FWI system for fire occurrence prediction in the study area. The results were improved when using aggregated data across regions compared to when data were sampled at the grid-box level. The inclusion of socioeconomic and LULC covariates contributed marginally to the improvement of the models, and in most cases attained no relevant contribution to total explained variance - excepting northern Spain, where anthropogenic factors are known to be the major driver of fires. Models of monthly fire counts performed better in the case of fires larger than 0.1 ha, and for the rest of the thresholds (1, 10 and 100 ha) the daily occurrence models improved the predicted inter-annual variability, indicating the added value of daily models. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as a response variable. Our results leave the door open to the development a more complex modelling framework based on daily data from numerical climate model outputs based on the FWI system.

Probabilistic calibration of the SPITFIRE fire spread model using Earth observation data

NASA Astrophysics Data System (ADS)

Gomez-Dans, Jose; Wooster, Martin; Lewis, Philip; Spessa, Allan

2010-05-01

There is a great interest in understanding how fire affects vegetation distribution and dynamics in the context of global vegetation modelling. A way to include these effects is through the development of embedded fire spread models. However, fire is a complex phenomenon, thus difficult to model. Statistical models based on fire return intervals, or fire danger indices need large amounts of data for calibration, and are often prisoner to the epoch they were calibrated to. Mechanistic models, such as SPITFIRE, try to model the complete fire phenomenon based on simple physical rules, making these models mostly independent of calibration data. However, the processes expressed in models such as SPITFIRE require many parameters. These parametrisations are often reliant on site-specific experiments, or in some other cases, paremeters might not be measured directly. Additionally, in many cases, changes in temporal and/or spatial resolution result in parameters becoming effective. To address the difficulties with parametrisation and the often-used fitting methodologies, we propose using a probabilistic framework to calibrate some areas of the SPITFIRE fire spread model. We calibrate the model against Earth Observation (EO) data, a global and ever-expanding source of relevant data. We develop a methodology that tries to incorporate the limitations of the EO data, reasonable prior values for parameters and that results in distributions of parameters, which can be used to infer uncertainty due to parameter estimates. Additionally, the covariance structure of parameters and observations is also derived, whcih can help inform data gathering efforts and model development, respectively. For this work, we focus on Southern African savannas, an important ecosystem for fire studies, and one with a good amount of EO data relevnt to fire studies. As calibration datasets, we use burned area data, estimated number of fires and vegetation moisture dynamics.

Survey of Fire Modeling Efforts with Application to Transportation Vehicles

DOT National Transportation Integrated Search

1981-07-01

This report presents the results of a survey of analytical fire models with applications pertinent to fires in the compartments of transportation vehicles; a brief discussion of the background of fire phenomena and an overview of various fire modelin...

Fire-probability maps for the Brazilian Amazonia

NASA Astrophysics Data System (ADS)

Cardoso, M.; Nobre, C.; Obregon, G.; Sampaio, G.

2009-04-01

Most fires in Amazonia result from the combination between climate and land-use factors. They occur mainly in the dry season and are used as an inexpensive tool for land clearing and management. However, their unintended consequences are of important concern. Fire emissions are the most important sources of greenhouse gases and aerosols in the region, accidental fires are a major threat to protected areas, and frequent fires may lead to permanent conversion of forest areas into savannas. Fire-activity models have thus become important tools for environmental analyses in Amazonia. They are used, for example, in warning systems for monitoring the risk of burnings in protected areas, to improve the description of biogeochemical cycles and vegetation composition in ecosystem models, and to help estimate the long-term potential for savannas in biome models. Previous modeling studies for the whole region were produced in units of satellite fire pixels, which complicate their direct use for environmental applications. By reinterpreting remote-sensing based data using a statistical approach, we were able to calibrate models for the whole region in units of probability, or chance of fires to occur. The application of these models for years 2005 and 2006 provided maps of fire potential at 3-month and 0.25-deg resolution as a function of precipitation and distance from main roads. In both years, the performance of the resulting maps was better for the period July-September. During these months, most of satellite-based fire observations were located in areas with relatively high chance of fire, as determined by the modeled probability maps. In addition to reproduce reasonably well the areas presenting maximum fire activity as detected by remote sensing, the new results in units of probability are easier to apply than previous estimates from fire-pixel models.

Fire-probability maps for the Brazilian Amazonia

NASA Astrophysics Data System (ADS)

Cardoso, Manoel; Sampaio, Gilvan; Obregon, Guillermo; Nobre, Carlos

2010-05-01

Most fires in Amazonia result from the combination between climate and land-use factors. They occur mainly in the dry season and are used as an inexpensive tool for land clearing and management. However, their unintended consequences are of important concern. Fire emissions are the most important sources of greenhouse gases and aerosols in the region, accidental fires are a major threat to protected areas, and frequent fires may lead to permanent conversion of forest areas into savannas. Fire-activity models have thus become important tools for environmental analyses in Amazonia. They are used, for example, in warning systems for monitoring the risk of burnings in protected areas, to improve the description of biogeochemical cycles and vegetation composition in ecosystem models, and to help estimate the long-term potential for savannas in biome models. Previous modeling studies for the whole region were produced in units of satellite fire pixels, which complicate their direct use for environmental applications. By reinterpreting remote-sensing based data using a statistical approach, we were able to calibrate models for the whole region in units of probability, or chance of fires to occur. The application of these models for years 2005 and 2006 provided maps of fire potential at 3-month and 0.25-deg resolution as a function of precipitation and distance from main roads. In both years, the performance of the resulting maps was better for the period July-September. During these months, most of satellite-based fire observations were located in areas with relatively high chance of fire, as determined by the modeled probability maps. In addition to reproduce reasonably well the areas presenting maximum fire activity as detected by remote sensing, the new results in units of probability are easier to apply than previous estimates from fire-pixel models.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local parameter estimates for all the variables and an important reduction of the autocorrelation in the residuals of the GW linear model. Despite the fitting improvement of local models, GW regression, more than an alternative to "global" or traditional regression modelling, seems to be a valuable complement to explore the non-stationary relationships between the response variable and the explanatory variables. The synergy of global and local modelling provides insights into fire management and policy and helps further our understanding of the fire problem over large areas while at the same time recognizing its local character.

Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

Treesearch

Patricia L. Andrews

2012-01-01

Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

A landscape-scale wildland fire study using coupled weather-wildland fire model and airborne remote sensing

Treesearch

J.L. Coen; Philip Riggan

2011-01-01

We examine the Esperanza fire, a Santa Ana-driven wildland fire that occurred in complex terrain in spatially heterogeneous chaparral fuels, using airborne remote sensing imagery from the FireMapper thermal-imaging radiometer and a coupled weather-wildland fire model. The radiometer data maps fire intensity and is used to evaluate the error in the extent of the...

Pre-fire and post-fire surface fuel and cover measurements collected in the southeastern United States for model evaluation and development - RxCADRE 2008, 2011 and 2012

Treesearch

Roger D. Ottmar; Andrew T. Hudak; Susan J. Prichard; Clinton S. Wright; Joseph C. Restaino; Maureen C. Kennedy; Robert E. Vihnanek

2016-01-01

A lack of independent, quality-assured data prevents scientists from effectively evaluating predictions and uncertainties in fire models used by land managers. This paper presents a summary of pre-fire and post-fire fuel, fuel moisture and surface cover fraction data that can be used for fire model evaluation and development. The data were collected in the...

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests

Treesearch

Bernard R. Parresol; Joe H. Scott; Anne Andreu; Susan Prichard; Laurie Kurth

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or...

What determines area burned in large landscapes? Insights from a decade of comparative landscape-fire modelling

Treesearch

Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan; Ian D. Davies; Russ A. Parsons

2015-01-01

Understanding what determines area burned in large landscapes is critical for informing wildland fire management in fire-prone environments and for representing fire activity in Dynamic Global Vegetation Models. For the past ten years, a group of landscape-fire modellers have been exploring the relative influence of key determinants of area burned in temperate and...

Seasonality of Fire Weather Strongly Influences Fire Regimes in South Florida Savanna-Grassland Landscapes

PubMed Central

Platt, William J.; Orzell, Steve L.; Slocum, Matthew G.

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide. PMID:25574667

Seasonality of fire weather strongly influences fire regimes in South Florida savanna-grassland landscapes.

PubMed

Platt, William J; Orzell, Steve L; Slocum, Matthew G

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993-2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997-2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide.

Fire in the Earth System: Bridging data and modeling research

USGS Publications Warehouse

Hantson, Srijn; Kloster, Silvia; Coughlan, Michael; Daniau, Anne-Laure; Vanniere, Boris; Bruecher, Tim; Kehrwald, Natalie; Magi, Brian I.

2016-01-01

Significant changes in wildfire occurrence, extent, and severity in areas such as western North America and Indonesia in 2015 have made the issue of fire increasingly salient in both the public and scientific spheres. Biomass combustion rapidly transforms land cover, smoke pours into the atmosphere, radiative heat from fires initiates dramatic pyrocumulus clouds, and the repeated ecological and atmospheric effects of fire can even impact regional and global climate. Furthermore, fires have a significant impact on human health, livelihoods, and social and economic systems.Modeling and databased methods to understand fire have rapidly coevolved over the past decade. Satellite and ground-based data about present-day fire are widely available for applications in research and fire management. Fire modeling has developed in part because of the evolution in vegetation and Earth system modeling efforts, but parameterizations and validation are largely focused on the present day because of the availability of satellite data. Charcoal deposits in sediment cores have emerged as a powerful method to evaluate trends in biomass burning extending back to the Last Glacial Maximum and beyond, and these records provide a context for present-day fire. The Global Charcoal Database version 3 compiled about 700 charcoal records and more than 1,000 records are expected for the future version 4. Together, these advances offer a pathway to explore how the strengths of fire data and fire modeling could address the weaknesses in the overall understanding of human-climate–fire linkages.A community of researchers studying fire in the Earth system with individual expertise that included paleoecology, paleoclimatology, modern ecology, archaeology, climate, and Earth system modeling, statistics, geography, biogeochemistry, and atmospheric science met at an intensive workshop in Massachusetts to explore new research directions and initiate new collaborations. Research themes, which emerged from the workshop participants via preworkshop surveys, focused on addressing the following questions: What are the climatic, ecological, and human drivers of fire regimes, both past and future? What is the role of humans in shaping historical fire regimes? How does fire ecology affect land cover changes, biodiversity, carbon storage, and human land uses? What are the historical fire trends and their impacts across biomes? Are their impacts local and/or regional? Are the fire trends in the last two decades unprecedented from a historical perspective? The workshop1 aimed to develop testable hypotheses about fire, climate, vegetation, and human interactions by leveraging the confluence of proxy, observational, and model data related to decadal- to millennial-scale fire activity on our planet. New research directions focused on broad interdisciplinary approaches to highlight how knowledge about past fire activity could provide a more complete understanding of the predictive capacity of fire models and inform fire policy in the face of our changing climate.

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

USGS Publications Warehouse

Syphard, A.D.; Yang, J.; Franklin, J.; He, H.S.; Keeley, J.E.

2007-01-01

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes. ?? 2007 Elsevier Ltd. All rights reserved.

Modeling tree-level fuel connectivity to evaluate the effectiveness of thinning treatments for reducing crown fire potential

Treesearch

Marco A. Contreras; Russell A. Parsons; Woodam Chung

2012-01-01

Land managers have been using fire behavior and simulation models to assist in several fire management tasks. These widely-used models use average attributes to make stand-level predictions without considering spatial variability of fuels within a stand. Consequently, as the existing models have limitations in adequately modeling crown fire initiation and propagation,...

Investigating fire emissions and smoke transport during the Summer of 2013 using an operational smoke modeling system and chemical transport model

NASA Astrophysics Data System (ADS)

ONeill, S. M.; Chung, S. H.; Wiedinmyer, C.; Larkin, N. K.; Martinez, M. E.; Solomon, R. C.; Rorig, M.

2014-12-01

Emissions from fires in the Western US are substantial and can impact air quality and regional climate. Many methods exist that estimate the particulate and gaseous emissions from fires, including those run operationally for use with chemical forecast models. The US Forest Service Smartfire2/BlueSky modeling framework uses satellite data and reported information about fire perimeters to estimate emissions of pollutants to the atmosphere. The emission estimates are used as inputs to dispersion models, such as HYSPLIT, and chemical transport models, such as CMAQ and WRF-Chem, to assess the chemical and physical impacts of fires on the atmosphere. Here we investigate the use of Smartfire2/BlueSky and WRF-Chem to simulate emissions from the 2013 fire summer fire season, with special focus on the Rim Fire in northern California. The 2013 Rim Fire ignited on August 17 and eventually burned more than 250,000 total acres before being contained on October 24. Large smoke plumes and pyro-convection events were observed. In this study, the Smartfire2/BlueSky operational emission estimates are compared to other estimation methods, such as the Fire INventory from NCAR (FINN) and other global databases to quantify variations in emission estimation methods for this wildfire event. The impact of the emissions on downwind chemical composition is investigated with the coupled meteorology-chemistry WRF-Chem model. The inclusion of aerosol-cloud and aerosol-radiation interactions in the model framework enables the evaluation of the downwind impacts of the fire plume. The emissions and modeled chemistry can also be evaluated with data collected from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) aircraft field campaign, which intersected the fire plume.

Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2013-09-01

We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990-2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter-annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

Utilization of geoinformation tools for the development of forest fire hazard mapping system: example of Pekan fire, Malaysia

NASA Astrophysics Data System (ADS)

Mahmud, Ahmad Rodzi; Setiawan, Iwan; Mansor, Shattri; Shariff, Abdul Rashid Mohamed; Pradhan, Biswajeet; Nuruddin, Ahmed

2009-12-01

A study in modeling fire hazard assessment will be essential in establishing an effective forest fire management system especially in controlling and preventing peat fire. In this paper, we have used geographic information system (GIS), in combination with other geoinformation technologies such as remote sensing and computer modeling, for all aspects of wild land fire management. Identifying areas that have a high probability of burning is an important component of fire management planning. The development of spatially explicit GIS models has greatly facilitated this process by allowing managers to map and analyze variables contributing to fire occurrence across large, unique geographic units. Using the model and its associated software engine, the fire hazard map was produced. Extensive avenue programming scripts were written to provide additional capabilities in the development of these interfaces to meet the full complement of operational software considering various users requirements. The system developed not only possesses user friendly step by step operations to deliver the fire vulnerability mapping but also allows authorized users to edit, add or modify parameters whenever necessary. Results from the model can support fire hazard mapping in the forest and enhance alert system function by simulating and visualizing forest fire and helps for contingency planning.

Predicting hydrological and erosional risks in fire-affected watersheds: recent advances and research gaps

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Keizer, Jan Jacob

2017-04-01

Models can be invaluable tools to assess and manage the impacts of forest fires on hydrological and erosion processes. Immediately after fires, models can be used to identify priority areas for post-fire interventions or assess the risks of flooding and downstream contamination. In the long term, models can be used to evaluate the long-term implications of a fire regime for soil protection, surface water quality and potential management risks, or determine how changes to fire regimes, caused e.g. by climate change, can impact soil and water quality. However, several challenges make post-fire modelling particularly difficult: • Fires change vegetation cover and properties, such as by changing soil water repellency or by adding an ash layer over the soil; these processes, however are not described in currently used models, so that existing models need to be modified and tested. • Vegetation and soils recover with time since fire, changing important model parameters, so that the recovery processes themselves also need to be simulated, including the role of post-fire interventions. • During the window of vegetation and soil disturbance, particular weather conditions, such as the occurrence of severe droughts or extreme rainfall events, can have a large impact on the amount of runoff and erosion produced in burnt areas, so that models that smooth out these peak responses and rather simulate "long-term" average processes are less useful. • While existing models can simulate reasonable well slope-scale runoff generation and associated sediment losses and their catchment-scale routing, few models can accommodate the role of the ash layer or its transport by overland flow, in spite of its importance for soil fertility losses and downstream contamination. This presentation will provide an overview of the importance of post-fire hydrological and erosion modelling as well as of the challenges it faces and of recent efforts made to overcome these challenges. It will illustrate these challenges with two examples: probabilistic approaches to simulate the impact of different vegetation regrowth and post-fire climate combinations on runoff and erosion; and model developments for post-fire soil water repellency with different levels of complexity. It will also present an inventory of the current state-of-the-art and propose future research directions, both on post-fire models themselves and on their integration with other models in large-scale water resource assessment management.

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Fire Modeling Institute: FY2012 Annual Report: Bridging scientists and managers

Treesearch

Robin J. Innes

2013-01-01

The Fire Modeling Institute (FMI) brings the best available fire and fuel science and technology developed throughout the research community to bear in fire-related management issues. Although located within the Fire, Fuel, and Smoke Science Program of the U.S. Forest Service Rocky Mountain Research Station, FMI is a national and international resource, serving fire...

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

PubMed Central

Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu

2014-01-01

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164

Contribution of regional-scale fire events to ozone and PM2.5 ...

EPA Pesticide Factsheets

Two specific fires from 2011 are tracked for local to regional scale contribution to ozone (O3) and fine particulate matter (PM2.5) using a freely available regulatory modeling system that includes the BlueSky wildland fire emissions tool, Spare Matrix Operator Kernel Emissions (SMOKE) model, Weather and Research Forecasting (WRF) meteorological model, and Community Multiscale Air Quality (CMAQ) photochemical grid model. The modeling system was applied to track the contribution from a wildfire (Wallow) and prescribed fire (Flint Hills) using both source sensitivity and source apportionment approaches. The model estimated fire contribution to primary and secondary pollutants are comparable using source sensitivity (brute-force zero out) and source apportionment (Integrated Source Apportionment Method) approaches. Model estimated O3 enhancement relative to CO is similar to values reported in literature indicating the modeling system captures the range of O3 inhibition possible near fires and O3 production both near the fire and downwind. O3 and peroxyacetyl nitrate (PAN) are formed in the fire plume and transported downwind along with highly reactive VOC species such as formaldehyde and acetaldehyde that are both emitted by the fire and rapidly produced in the fire plume by VOC oxidation reactions. PAN and aldehydes contribute to continued downwind O3 production. The transport and thermal decomposition of PAN to nitrogen oxides (NOX) enables O3 production in areas

Mediterranean maquis fuel model development and mapping to support fire modeling

NASA Astrophysics Data System (ADS)

Bacciu, V.; Arca, B.; Pellizzaro, G.; Salis, M.; Ventura, A.; Spano, D.; Duce, P.

2009-04-01

Fuel load data and fuel model maps represent a critical issue for fire spread and behaviour modeling. The availability of accurate input data at different spatial and temporal scales can allow detailed analysis and predictions of fire hazard and fire effects across a landscape. Fuel model data are used in spatially explicit fire growth models to attain fire behaviour information for fuel management in prescribed fires, fire management applications, firefighters training, smoke emissions, etc. However, fuel type characteristics are difficult to be parameterized due to their complexity and variability: live and dead materials with different size contribute in different ways to the fire spread and behaviour. In the last decades, a strong help was provided by the use of remote sensing imagery at high spatial and spectral resolution. Such techniques are able to capture fine scale fuel distributions for accurate fire growth projections. Several attempts carried out in Europe were devoted to fuel classification and map characterization. In Italy, fuel load estimation and fuel model definition are still critical issues to be addressed due to the lack of detailed information. In this perspective, the aim of the present work was to propose an integrated approach based on field data collection, fuel model development and fuel model mapping to provide fuel models for the Mediterranean maquis associations. Field data needed for the development of fuel models were collected using destructive and non destructive measurements in experimental plots located in Northern Sardinia (Italy). Statistical tests were used to identify the main fuel types that were classified into four custom fuel models. Subsequently, a supervised classification by the Maximum Likelihood algorithm was applied on IKONOS images to identify and map the different types of maquis vegetation. The correspondent fuel model was then associated to each vegetation type to obtain the fuel model map. The results show the potential of this approach in achieving a reasonable accuracy in fuel model development and mapping; fine scale fuel model maps can be potentially helpful to obtain realistic predictions of fire behaviour and fire effects.

Analysis of NASA JP-4 fire tests data and development of a simple fire model

NASA Technical Reports Server (NTRS)

Raj, P.

1980-01-01

The temperature, velocity and species concentration data obtained during the NASA fire tests (3m, 7.5m and 15m diameter JP-4 fires) were analyzed. Utilizing the data analysis, a sample theoretical model was formulated to predict the temperature and velocity profiles in JP-4 fires. The theoretical model, which does not take into account the detailed chemistry of combustion, is capable of predicting the extent of necking of the fire near its base.

Climate drives inter-annual variability in probability of high severity fire occurrence in the western United States

NASA Astrophysics Data System (ADS)

Keyser, Alisa; Westerling, Anthony LeRoy

2017-05-01

A long history of fire suppression in the western United States has significantly changed forest structure and ecological function, leading to increasingly uncharacteristic fires in terms of size and severity. Prior analyses of fire severity in California forests showed that time since last fire and fire weather conditions predicted fire severity very well, while a larger regional analysis showed that topography and climate were important predictors of high severity fire. There has not yet been a large-scale study that incorporates topography, vegetation and fire-year climate to determine regional scale high severity fire occurrence. We developed models to predict the probability of high severity fire occurrence for the western US. We predict high severity fire occurrence with some accuracy, and identify the relative importance of predictor classes in determining the probability of high severity fire. The inclusion of both vegetation and fire-year climate predictors was critical for model skill in identifying fires with high fractional fire severity. The inclusion of fire-year climate variables allows this model to forecast inter-annual variability in areas at future risk of high severity fire, beyond what slower-changing fuel conditions alone can accomplish. This allows for more targeted land management, including resource allocation for fuels reduction treatments to decrease the risk of high severity fire.

Large, high-intensity fire events in southern California shrublands: debunking the fine-grain age patch model.

PubMed

Keeley, Jon E; Zedler, Paul H

2009-01-01

We evaluate the fine-grain age patch model of fire regimes in southern California shrublands. Proponents contend that the historical condition was characterized by frequent small to moderate size, slow-moving smoldering fires, and that this regime has been disrupted by fire suppression activities that have caused unnatural fuel accumulation and anomalously large and catastrophic wildfires. A review of more than 100 19th-century newspaper reports reveals that large, high-intensity wildfires predate modern fire suppression policy, and extensive newspaper coverage plus first-hand accounts support the conclusion that the 1889 Santiago Canyon Fire was the largest fire in California history. Proponents of the fine-grain age patch model contend that even the very earliest 20th-century fires were the result of fire suppression disrupting natural fuel structure. We tested that hypothesis and found that, within the fire perimeters of two of the largest early fire events in 1919 and 1932, prior fire suppression activities were insufficient to have altered the natural fuel structure. Over the last 130 years there has been no significant change in the incidence of large fires greater than 10,000 ha, consistent with the conclusion that fire suppression activities are not the cause of these fire events. Eight megafires (> or = 50,000 ha) are recorded for the region, and half have occurred in the last five years. These burned through a mosaic of age classes, which raises doubts that accumulation of old age classes explains these events. Extreme drought is a plausible explanation for this recent rash of such events, and it is hypothesized that these are due to droughts that led to increased dead fine fuels that promoted the incidence of firebrands and spot fires. A major shortcoming of the fine-grain age patch model is that it requires age-dependent flammability of shrubland fuels, but seral stage chaparral is dominated by short-lived species that create a dense surface layer of fine fuels. Results from the Behave Plus fire model with a custom fuel module for young chaparral shows that there is sufficient dead fuel to spread fire even under relatively little winds. Empirical studies of fuel ages burned in recent fires illustrate that young fuels often comprise a major portion of burned vegetation, and there is no difference between evergreen chaparral and semi-deciduous sage scrub. It has also been argued that the present-day fire size distribution in northern Baja California is a model of the historical patterns that were present on southern California landscapes. Applying this model with historical fire frequencies shows that the Baja model is inadequate to maintain these fire-prone ecosystems and further demonstrates that fire managers in southern California are not likely to learn much from studying modern Baja California fire regimes. Further supporting this conclusion are theoretical cellular automata models of fire spread, which show that, even in systems with age dependent flammability, landscapes evolve toward a complex age mosaic with a plausible age structure only when there is a severe stopping rule that constrains fire size, and only if ignitions are saturating.

Large, high-intensity fire events in Southern California shrublands: Debunking the fine-grain age patch model

USGS Publications Warehouse

Keeley, J.E.; Zedler, P.H.

2009-01-01

We evaluate the fine-grain age patch model of fire regimes in southern California shrublands. Proponents contend that the historical condition was characterized by frequent small to moderate size, slow-moving smoldering fires, and that this regime has been disrupted by fire suppression activities that have caused unnatural fuel accumulation and anomalously large and catastrophic wildfires. A review of more than 100 19th-century newspaper reports reveals that large, high-intensity wildfires predate modern fire suppression policy, and extensive newspaper coverage plus first-hand accounts support the conclusion that the 1889 Santiago Canyon Fire was the largest fire in California history. Proponents of the fine-grain age patch model contend that even the very earliest 20th-century fires were the result of fire suppression disrupting natural fuel structure. We tested that hypothesis and found that, within the fire perimeters of two of the largest early fire events in 1919 and 1932, prior fire suppression activities were insufficient to have altered the natural fuel structure. Over the last 130 years there has been no significant change in the incidence of large fires greater than 10000 ha, consistent with the conclusion that fire suppression activities are not the cause of these fire events. Eight megafires (???50 000 ha) are recorded for the region, and half have occurred in the last five years. These burned through a mosaic of age classes, which raises doubts that accumulation of old age classes explains these events. Extreme drought is a plausible explanation for this recent rash of such events, and it is hypothesized that these are due to droughts that led to increased dead fine fuels that promoted the incidence of firebrands and spot fires. A major shortcoming of the fine-grain age patch model is that it requires age-dependent flammability of shrubland fuels, but seral stage chaparral is dominated by short-lived species that create a dense surface layer of fine fuels. Results from the Behave Plus fire model with a custom fuel module for young chaparral shows that there is sufficient dead fuel to spread fire even under relatively little winds. Empirical studies of fuel ages burned in recent fires illustrate that young fuels often comprise a major portion of burned vegetation, and there is no difference between evergreen chaparral and semi-deciduous sage scrub. It has also been argued that the present-day fire size distribution in northern Baja California is a model of the historical patterns that were present on southern California landscapes. Applying this model with historical fire frequencies shows that the Baja model is inadequate to maintain these fire-prone ecosystems and further demonstrates that fire managers in southern California are not likely to learn much from studying modern Baja California fire regimes. Further supporting this conclusion are theoretical cellular automata models of fire spread, which show that, even in systems with age dependent flammability, landscapes evolve toward a complex age mosaic with a plausible age structure only when there is a severe stopping rule that constrains fire size, and only if ignitions are saturating. ?? 2009 by the Ecological Society of America.

The changing strength and nature of fire-climate relationships in the northern Rocky Mountains, U.S.A., 1902-2008

USGS Publications Warehouse

Littell, Jeremy

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008

PubMed Central

Higuera, Philip E.; Abatzoglou, John T.; Littell, Jeremy S.; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity. PMID:26114580

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

PubMed

Higuera, Philip E; Abatzoglou, John T; Littell, Jeremy S; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

The Effects of Vegetative Type, Edges, Fire History, Rainfall and Management in Fire-Maintained Ecosystems

NASA Technical Reports Server (NTRS)

Breininger, David R.; Foster, Tammy E.; Carter, Geoffrey M.; Duncan, Brean W.; Stolen, Eric D.; Lyon, James E.

2017-01-01

The combined effects of repeated fires, climate, and landscape features (e.g., edges) need greater focus in fire ecology studies, which usually emphasize characteristics of the most recent fire and not fire history. Florida scrub-jays are an imperiled, territorial species that prefer medium (1.2-1.7 m) shrub heights. We measured short, medium, and tall habitat quality states annually within 10 ha grid cells that represented potential territories because frequent fires and vegetative recovery cause annual variation in habitat quality. We used multistate models and model selection to test competing hypotheses about how transition probabilities between states varied annually as functions of environmental covariates. Covariates included vegetative type, edges, precipitation, openings (gaps between shrubs), mechanical cutting, and fire characteristics. Fire characteristics not only included an annual presenceabsence of fire covariate, but also fire history covariates: time since the previous fire, the maximum fire-free interval, and the number of repeated fires. Statistical models with support included many covariates for each transition probability, often including fire history, interactions and nonlinear relationships. Tall territories resulted from 28 years of fire suppression and habitat fragmentation that reduced the spread of fires across landscapes. Despite 35 years of habitat restoration and prescribed fires, half the territories remained tall suggesting a regime shift to a less desirable habitat condition. Measuring territory quality states and environmental covariates each year combined with multistate modeling provided a useful empirical approach to quantify the effects of repeated fire in combinations with environmental variables on transition probabilities that drive management strategies and ecosystem change.

Analytical modeling of fire growth on fire-resistive wood-based materials with changing conditions

Treesearch

Mark A. Dietenberger

2006-01-01

Our analytical model of fire growth for the ASTM E 84 tunnel, which simultaneously predicts heat release rate, flame-over area, and pyrolysis area as functions of time for constant conditions, was documented in the 2001 BCC Symposium for different treated wood materials. The model was extended to predict ignition and fire growth on exterior fire-resistive structures...

Validation of BEHAVE fire behavior predictions in oak savannas using five fuel models

Treesearch

Keith Grabner; John Dwyer; Bruce Cutter

1997-01-01

Prescribed fire is a valuable tool in the restoration and management of oak savannas. BEHAVE, a fire behavior prediction system developed by the United States Forest Service, can be a useful tool when managing oak savannas with prescribed fire. BEHAVE predictions of fire rate-of-spread and flame length were validated using four standardized fuel models: Fuel Model 1 (...

Sensitivity of fire behavior simulations to fuel model variations

Treesearch

Lucy A. Salazar

1985-01-01

Stylized fuel models, or numerical descriptions of fuel arrays, are used as inputs to fire behavior simulation models. These fuel models are often chosen on the basis of generalized fuel descriptions, which are related to field observations. Site-specific observations of fuels or fire behavior in the field are not readily available or necessary for most fire management...

Decision modeling for fire incident analysis

Treesearch

Donald G. MacGregor; Armando González-Cabán

2009-01-01

This paper reports on methods for representing and modeling fire incidents based on concepts and models from the decision and risk sciences. A set of modeling techniques are used to characterize key fire management decision processes and provide a basis for incident analysis. The results of these methods can be used to provide insights into the structure of fire...

BehavePlus fire modeling system, version 5.0: Variables

Treesearch

Patricia L. Andrews

2009-01-01

This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...

Global vegetation-fire pattern under different land use and climate conditions

NASA Astrophysics Data System (ADS)

Thonicke, K.; Poulter, B.; Heyder, U.; Gumpenberger, M.; Cramer, W.

2008-12-01

Fire is a process of global significance in the Earth System influencing vegetation dynamics, biogeochemical cycling and biophysical feedbacks. Naturally ignited wildfires have long history in the Earth System. Humans have been using fire to shape the landscape for their purposes for many millenia, sometimes influencing the status of the vegetation remarkably as for example in Mediterranean-type ecosystems. Processes and drivers describing fire danger, ignitions, fire spread and effects are relatively well-known for many fire-prone ecosystems. Modeling these has a long tradition in fire-affected regions to predict fire risk and behavior for fire-fighting purposes. On the other hand, the global vegetation community realized the importance of disturbances to be recognized in their global vegetation models with fire being globally most important and so-far best studied. First attempts to simulate fire globally considered a minimal set of drivers, whereas recent developments attempt to consider each fire process separately. The process-based fire model SPITFIRE (SPread and InTensity of FIRE) simulates these processes embedded in the LPJ DGVM. Uncertainties still arise from missing measurements for some parameters in less-studied fire regimes, or from broad PFT classifications which subsume different fire-ecological adaptations and tolerances. Some earth observation data sets as well as fire emission models help to evaluate seasonality and spatial distribution of simulated fire ignitions, area burnt and fire emissions within SPITFIRE. Deforestation fires are a major source of carbon released to the atmosphere in the tropics; in the Amazon basin it is the second-largest contributor to Brazils GHG emissions. How ongoing deforestation affects fire regimes, forest stability and biogeochemical cycling in the Amazon basin under present climate conditions will be presented. Relative importance of fire vs. climate and land use change is analyzed. Emissions resulting from wildfires, agricultural and woodfuel burning will be quantified and drivers identified. Future projections of climate and land use change are applied to the model to investigate joint effects on future changes in fire, deforestation and vegetation dynamics in the Amazon basin.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S.

PubMed

Hu, Xuefei; Waller, Lance A; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2014-10-16

Multiple studies have developed surface PM 2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM 2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM 2.5 . In this paper, we examined whether remotely sensed fire count data could improve PM 2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM 2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM 2.5 across the models considered. Cross validation (CV) generated an R 2 of 0.69, a mean prediction error of 2.75 µg/m 3 , and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m 3 , indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m 3 , exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM 2.5 concentration estimation, especially in areas and seasons prone to fire events.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S

PubMed Central

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2017-01-01

Multiple studies have developed surface PM2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM2.5. In this paper, we examined whether remotely sensed fire count data could improve PM2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM2.5 across the models considered. Cross validation (CV) generated an R2 of 0.69, a mean prediction error of 2.75 µg/m3, and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m3, indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m3, exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM2.5 concentration estimation, especially in areas and seasons prone to fire events. PMID:28967648

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Treesearch

LaWen T. Hollingsworth; Laurie L. Kurth; Bernard R. Parresol; Roger D. Ottmar; Susan J. Prichard

2012-01-01

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation...

Predicting post-fire tree mortality for 12 western US conifers using the First-Order Fire Effects Model (FOFEM)

Treesearch

Sharon Hood; Duncan Lutes

2017-01-01

Accurate prediction of fire-caused tree mortality is critical for making sound land management decisions such as developing burning prescriptions and post-fire management guidelines. To improve efforts to predict post-fire tree mortality, we developed 3-year post-fire mortality models for 12 Western conifer species - white fir (Abies concolor [Gord. &...

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC.

PubMed

Keane, R E; Ryan, K C; Running, S W

1996-03-01

A mechanistic, biogeochemical succession model, FIRE-BGC, was used to investigate the role of fire on long-term landscape dynamics in northern Rocky Mountain coniferous forests of Glacier National Park, Montana, USA. FIRE-BGC is an individual-tree model-created by merging the gap-phase process-based model FIRESUM with the mechanistic ecosystem biogeochemical model FOREST-BGC-that has mixed spatial and temporal resolution in its simulation architecture. Ecological processes that act at a landscape level, such as fire and seed dispersal, are simulated annually from stand and topographic information. Stand-level processes, such as tree establishment, growth and mortality, organic matter accumulation and decomposition, and undergrowth plant dynamics are simulated both daily and annually. Tree growth is mechanistically modeled based on the ecosystem process approach of FOREST-BGC where carbon is fixed daily by forest canopy photosynthesis at the stand level. Carbon allocated to the tree stem at the end of the year generates the corresponding diameter and height growth. The model also explicitly simulates fire behavior and effects on landscape characteristics. We simulated the effects of fire on ecosystem characteristics of net primary productivity, evapotranspiration, standing crop biomass, nitrogen cycling and leaf area index over 200 years for the 50,000-ha McDonald Drainage in Glacier National Park. Results show increases in net primary productivity and available nitrogen when fires are included in the simulation. Standing crop biomass and evapotranspiration decrease under a fire regime. Shade-intolerant species dominate the landscape when fires are excluded. Model tree increment predictions compared well with field data.

The use of computer models to predict temperature and smoke movement in high bay spaces

NASA Technical Reports Server (NTRS)

Notarianni, Kathy A.; Davis, William D.

1993-01-01

The Building and Fire Research Laboratory (BFRL) was given the opportunity to make measurements during fire calibration tests of the heat detection system in an aircraft hangar with a nominal 30.4 (100 ft) ceiling height near Dallas, TX. Fire gas temperatures resulting from an approximately 8250 kW isopropyl alcohol pool fire were measured above the fire and along the ceiling. The results of the experiments were then compared to predictions from the computer fire models DETACT-QS, FPETOOL, and LAVENT. In section A of the analysis conducted, DETACT-QS AND FPETOOL significantly underpredicted the gas temperature. LAVENT at the position below the ceiling corresponding to maximum temperature and velocity provided better agreement with the data. For large spaces, hot gas transport time and an improved fire plume dynamics model should be incorporated into the computer fire model activation routines. A computational fluid dynamics (CFD) model, HARWELL FLOW3D, was then used to model the hot gas movement in the space. Reasonable agreement was found between the temperatures predicted from the CFD calculations and the temperatures measured in the aircraft hangar. In section B, an existing NASA high bay space was modeled using the CFD model. The NASA space was a clean room, 27.4 m (90 ft) high with forced horizontal laminar flow. The purpose of this analysis is to determine how the existing fire detection devices would respond to various size fires in the space. The analysis was conducted for 32 MW, 400 kW, and 40 kW fires.

Differences in simulated fire spread over Askervein Hill using two advanced wind models and a traditional uniform wind field

Treesearch

Jason Forthofer; Bret Butler

2007-01-01

A computational fluid dynamics (CFD) model and a mass-consistent model were used to simulate winds on simulated fire spread over a simple, low hill. The results suggest that the CFD wind field could significantly change simulated fire spread compared to traditional uniform winds. The CFD fire spread case may match reality better because the winds used in the fire...

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

D'Andrea, M.; Fiorucci, P.; Holmes, T. P.

2010-10-01

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.

Fuel models and fire potential from satellite and surface observations

USGS Publications Warehouse

Burgan, R.E.; Klaver, R.W.; Klarer, J.M.

1998-01-01

A national 1-km resolution fire danger fuel model map was derived through use of previously mapped land cover classes and ecoregions, and extensive ground sample data, then refined through review by fire managers familiar with various portions of the U.S. The fuel model map will be used in the next generation fire danger rating system for the U.S., but it also made possible immediate development of a satellite and ground based fire potential index map. The inputs and algorithm of the fire potential index are presented, along with a case study of the correlation between the fire potential index and fire occurrence in California and Nevada. Application of the fire potential index in the Mediterranean ecosystems of Spain, Chile, and Mexico will be tested.

Application of a mesoscale atmospheric coupled fire model BRAMS-SFIRE to Alentejo wildland fire and comparison of performance with the fire model WRF-SFIRE

NASA Astrophysics Data System (ADS)

Menezes, Isilda; Freitas, Saulo; Stockler, Rafael; Mello, Rafael; Ribeiro, Nuno; Corte-Real, João; Surový, Peter

2015-04-01

Models of fuel with the identification of vegetation patterns of Montado ecosystem in Portugal was incorporated in the mesoscale Brazilian Atmospheric Modeling System (BRAMS) and coupled with a spread wildland fire model. The BRAMS-FIRE is a new system developed by the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE, Brazil) and the Instituto de Ciências Agrárias e Ambientais Mediterrâneas (ICAAM, Portugal). The fire model used in this effort was originally, developed by Mandel et al. (2013) and further incorporated in the Weather Research and Forecast model (WRF). Two grids of high spatial resolution were configured with surface input data and fuel models integrated for simulations using both models BRAMS-SFIRE and WRF-SFIRE. One grid was placed in the plain land and the other one in the hills to evaluate different types of fire propagation and calibrate BRAMS-SFIRE. The objective is simulating the effects of atmospheric circulation in local scale, namely the movements of the heat front and energy release associated to it, obtained by this two models in an episode of wildland fire which took place in Alentejo area in the last decade, for application to planning and evaluations of agro wildland fire risks. We aim to model the behavior of forest fires through a set of equations whose solutions provide quantitative values of one or more variables related to the propagation of fire, described by semi-empirical expressions that are complemented by experimental data allow to obtain the main variables related advancing the perimeter of the fire, as the propagation speed, the intensity of the fire front and fuel consumption and its interaction with atmospheric dynamic system References Mandel, J., J. D. Beezley, G. Kelman, A. K. Kochanski, V. Y. Kondratenko, B. H. Lynn, and M. Vejmelka, 2013. New features in WRF-SFIRE and the wildfire forecasting and danger system in Israel. Natural Hazards and Earth System Sciences, submitted, Numerical Wildfires, Cargèse, France, May 13-18, 2013.

Theory-Based Cartographic Risk Model Development and Application for Home Fire Safety.

PubMed

Furmanek, Stephen; Lehna, Carlee; Hanchette, Carol

There is a gap in the use of predictive risk models to identify areas at risk for home fires and burn injury. The purpose of this study was to describe the creation, validation, and application of such a model using a sample from an intervention study with parents of newborns in Jefferson County, KY, as an example. Performed was a literature search to identify risk factors for home fires and burn injury in the target population. Obtained from the American Community Survey at the census tract level and synthesized to create a predictive cartographic risk model was risk factor data. Model validation was performed through correlation, regression, and Moran's I with fire incidence data from open records. Independent samples t-tests were used to examine the model in relation to geocoded participant addresses. Participant risk level for fire rate was determined and proximity to fire station service areas and hospitals. The model showed high and severe risk clustering in the northwest section of the county. Strongly correlated with fire rate was modeled risk; the best predictive model for fire risk contained home value (low), race (black), and non high school graduates. Applying the model to the intervention sample, the majority of participants were at lower risk and mostly within service areas closest to a fire department and hospital. Cartographic risk models were useful in identifying areas at risk and analyzing participant risk level. The methods outlined in this study are generalizable to other public health issues.

The effectiveness and limitations of fuel modeling using the fire and fuels extension to the Forest Vegetation Simulator

Treesearch

Erin K. Noonan-Wright; Nicole M. Vaillant; Alicia L. Reiner

2014-01-01

Fuel treatment effectiveness is often evaluated with fire behavior modeling systems that use fuel models to generate fire behavior outputs. How surface fuels are assigned, either using one of the 53 stylized fuel models or developing custom fuel models, can affect predicted fire behavior. We collected surface and canopy fuels data before and 1, 2, 5, and 8 years after...

On wildfire complexity, simple models and environmental templates for fire size distributions

NASA Astrophysics Data System (ADS)

Boer, M. M.; Bradstock, R.; Gill, M.; Sadler, R.

2012-12-01

Vegetation fires affect some 370 Mha annually. At global and continental scales, fire activity follows predictable spatiotemporal patterns driven by gradients and seasonal fluctuations of primary productivity and evaporative demand that set constraints for fuel accumulation rates and fuel dryness, two key ingredients of fire. At regional scales, fires are also known to affect some landscapes more than others and within landscapes to occur preferentially in some sectors (e.g. wind-swept ridges) and rarely in others (e.g. wet gullies). Another common observation is that small fires occur relatively frequent yet collectively burn far less country than relatively infrequent large fires. These patterns of fire activity are well known to management agencies and consistent with their (informal) models of how the basic drivers and constraints of fire (i.e. fuels, ignitions, weather) vary in time and space across the landscape. The statistical behaviour of these landscape fire patterns has excited the (academic) research community by showing some consistency with that of complex dynamical systems poised at a phase transition. The common finding that the frequency-size distributions of actual fires follow power laws that resemble those produced by simple cellular models from statistical mechanics has been interpreted as evidence that flammable landscapes operate as self-organising systems with scale invariant fire size distributions emerging 'spontaneously' from simple rules of contagious fire spread and a strong feedback between fires and fuel patterns. In this paper we argue that the resemblance of simulated and actual fire size distributions is an example of equifinality, that is fires in model landscapes and actual landscapes may show similar statistical behaviour but this is reached by qualitatively different pathways or controlling mechanisms. We support this claim with two key findings regarding simulated fire spread mechanisms and fire-fuel feedbacks. Firstly, we demonstrate that the power law behaviour of fire size distributions in the widely used Drossel and Schwabl (1992) Forest Fire Model (FFM) is strictly conditional on simulating fire spread as a cell-to-cell contagion over a fixed distance; the invariant scaling of fire sizes breaks down under the slightest variation in that distance, suggesting that pattern formation in the FFM is irreconcilable with the reality of disparate rates and modes of fire spread observed in the field. Secondly, we review field evidence showing that fuel age effects on the probability of fire spread, a key assumption in simulation models like the FFM, do not generally apply across flammable environments. Finally, we explore alternative explanations for the formation of scale invariant fire sizes in real landscapes. Using observations from southern Australian forest regions we demonstrate that the spatiotemporal patterns of fuel dryness and magnitudes of fire driving weather events set strong environmental templates for regional fire size distributions.

Modeling In-Stream Hydro-Geomorphic Processes After 2012 Waldo Canyon Fire, Colorado

NASA Astrophysics Data System (ADS)

Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

2016-12-01

Wildfires can have significant impacts on hydrologic and geomorphic processes. Post-fire sediment transport and runoff generation vary by burn severity, precipitation, and vegetation. A need exists to understand these variable relationships and improve parameterization of post-fire hydro-geomorphic models. This research aims to model pre-fire geomorphic and hydrologic processes in Williams Canyon, a watershed burned by the 2012 Waldo Canyon Fire in Colorado. We develop the KINematic Runoff and EROSion (KINEROS) model with Geographical Information System (GIS)-based information, including a Digital Elevation Model, land cover, soil classification, precipitation, and soil burn severity for a local reference watershed that is unburned. We transfer these parameters to a channel reach in Williams Canyon (Williams Downstream) and adjust them toward post-fire conditions. We model runoff and sediment yield for several storms following the fire. Three post-fire terrestrial Light Detection and Ranging (LiDAR) images (21 April 2013, 14 September 2013, and 16 September 2014) are used to estimate total erosion and deposition at the reach scale. We use the LiDAR-based information to calibrate the post-fire model. Preliminary modeling results indicate 3870-125 kg/ha of sediment in the Williams Downstream reach. The uncalibrated model overestimated (410% in the first year) and underestimated (87.2% in the second year) the erosion. Model calibration reduced the Root Mean Square Error (RMSE) of sediment to 0.016% for the first year and 0.09% for the second year. The parameters calibrated for the Williams Downstream channel reach will be used to develop models for seven other channel reaches within the area burned by the Waldo Canyon Fire, where the performance can be evaluated with LiDAR estimates. Results of this research will enhance our understanding of wildfire disturbance on coupled hydrologic and geomorphic processes. Findings will also improve model parameterization that can be used to guide post-fire management and predictions.

Using a stochastic model and cross-scale analysis to evaluate controls on historical low-severity fire regimes

Treesearch

Maureen C. Kennedy; Donald McKenzie

2010-01-01

Fire-scarred trees provide a deep temporal record of historical fire activity, but identifying the mechanisms therein that controlled landscape fire patterns is not straightforward. We use a spatially correlated metric for fire co-occurrence between pairs of trees (the Sørensen distance variogram), with output from a neutral model for fire history, to infer the...

Simulation and thermal imaging of the 2006 Esperanza Wildfire in southern California: application of a coupled weather-wildland fire model

Treesearch

Janice L. Coen; Philip J Riggan

2014-01-01

The 2006 Esperanza Fire in Riverside County, California, was simulated with the Coupled Atmosphere-Wildland Fire Environment (CAWFE) model to examine how dynamic interactions of the atmosphere with large-scale fire spread and energy release may affect observed patterns of fire behavior as mapped using the FireMapper thermal imaging radiometer. CAWFE simulated the...

Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds

Treesearch

Lindsay M. Grayson; Robert A. Progar; Sharon M. Hood

2017-01-01

Fire is a driving force in the North American landscape and predicting post-fire tree mortality is vital to land management. Post-fire tree mortality can have substantial economic and social impacts, and natural resource managers need reliable predictive methods to anticipate potential mortality following fire events. Current fire mortality models are limited to a few...

Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

PubMed

Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet T

2014-09-15

Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

Fire spread estimation on forest wildfire using ensemble kalman filter

NASA Astrophysics Data System (ADS)

Syarifah, Wardatus; Apriliani, Erna

2018-04-01

Wildfire is one of the most frequent disasters in the world, for example forest wildfire, causing population of forest decrease. Forest wildfire, whether naturally occurring or prescribed, are potential risks for ecosystems and human settlements. These risks can be managed by monitoring the weather, prescribing fires to limit available fuel, and creating firebreaks. With computer simulations we can predict and explore how fires may spread. The model of fire spread on forest wildfire was established to determine the fire properties. The fire spread model is prepared based on the equation of the diffusion reaction model. There are many methods to estimate the spread of fire. The Kalman Filter Ensemble Method is a modified estimation method of the Kalman Filter algorithm that can be used to estimate linear and non-linear system models. In this research will apply Ensemble Kalman Filter (EnKF) method to estimate the spread of fire on forest wildfire. Before applying the EnKF method, the fire spread model will be discreted using finite difference method. At the end, the analysis obtained illustrated by numerical simulation using software. The simulation results show that the Ensemble Kalman Filter method is closer to the system model when the ensemble value is greater, while the covariance value of the system model and the smaller the measurement.

Fire control method and analytical model for large liquid hydrocarbon pool fires

NASA Technical Reports Server (NTRS)

Fenton, D. L.

1986-01-01

The dominate parameter governing the behavior of a liquid hydrocarbon (JP-5) pool fire is wind speed. The most effective method of controlling wind speed in the vicinity of a large circular (10 m dia.) pool fire is a set of concentric screens located outside the perimeter. Because detailed behavior of the pool fire structure within one pool fire diameter is unknown, an analytical model supported by careful experiments is under development. As a first step toward this development, a regional pool fire model was constructed for the no-wind condition consisting of three zones -- liquid fuel, combustion, and plume -- where the predicted variables are mass burning rate and characteristic temperatures of the combustion and plume zones. This zone pool fire model can be modified to incorporate plume bending by wind, radiation absorption by soot particles, and a different ambient air flow entrainment rate. Results from the zone model are given for a pool diameter of 1.3 m and are found to reproduce values in the literature.

Validation of behave fire behavior predictions in oak savannas

USGS Publications Warehouse

Grabner, Keith W.; Dwyer, John; Cutter, Bruce E.

1997-01-01

Prescribed fire is a valuable tool in the restoration and management of oak savannas. BEHAVE, a fire behavior prediction system developed by the United States Forest Service, can be a useful tool when managing oak savannas with prescribed fire. BEHAVE predictions of fire rate-of-spread and flame length were validated using four standardized fuel models: Fuel Model 1 (short grass), Fuel Model 2 (timber and grass), Fuel Model 3 (tall grass), and Fuel Model 9 (hardwood litter). Also, a customized oak savanna fuel model (COSFM) was created and validated. Results indicate that standardized fuel model 2 and the COSFM reliably estimate mean rate-of-spread (MROS). The COSFM did not appreciably reduce MROS variation when compared to fuel model 2. Fuel models 1, 3, and 9 did not reliably predict MROS. Neither the standardized fuel models nor the COSFM adequately predicted flame lengths. We concluded that standardized fuel model 2 should be used with BEHAVE when predicting fire rates-of-spread in established oak savannas.

Mathematical modeling of forest fire initiation in three dimensional setting

Treesearch

Valeriy Perminov

2007-01-01

In this study, the assignment and theoretical investigations of the problems of forest fire initiation were carried out, including development of a mathematical model for description of heat and mass transfer processes in overterrestrial layer of atmosphere at crown forest fire initiation, taking into account their mutual influence. Mathematical model of forest fire...

Integrating fire management analysis into land management planning

Treesearch

Thomas J. Mills

1983-01-01

The analysis of alternative fire management programs should be integrated into the land and resource management planning process, but a single fire management analysis model cannot meet all planning needs. Therefore, a set of simulation models that are analytically separate from integrated land management planning models are required. The design of four levels of fire...

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation modelORCHIDEE - Part 1: Simulating historical global burned area and fire regimes

Treesearch

C. Yue; P. Ciais; P. Cadule; K. Thonicke; S. Archibald; B. Poulter; W. M. Hao; S. Hantson; F. Mouillot; P. Friedlingstein; F. Maignan; N. Viovy

2014-01-01

Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE...

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

NASA Technical Reports Server (NTRS)

Veraverbeke, Sander; Sedano, Fernando; Hook, Simon J.; Randerson, James T.; Jin, Yufang; Rogers, Brendan

2013-01-01

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

NASA Astrophysics Data System (ADS)

Vacchiano, Giorgio; Foderi, Cristiano; Berretti, Roberta; Marchi, Enrico; Motta, Renzo

2018-03-01

Modeling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an Alpine region in Italy using a regional wildfire archive (1995-2009) and MaxEnt modeling. We analyzed separately (i) winter forest fires, (ii) winter fires on grasslands and fallow land, and (iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component. Collinearity among predictors was reduced by a principal component analysis. Regarding ignitions, 30 % occurred in agricultural areas and 24 % in forests. Ignitions peaked in the late winter-early spring. Negligence from agrosilvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study time frame, but increased from 6 to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of fit (AUC 0.90-0.95). Temperature was proportional to the probability of ignition, and precipitation was inversely proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different effect on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such a spatially explicit approach allows us to carry out spatially targeted fire management strategies and may assist in developing better fire management plans.

Classifying and comparing spatial models of fire dynamics

Treesearch

Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan

2007-01-01

Wildland fire is a significant disturbance in many ecosystems worldwide and the interaction of fire with climate and vegetation over long time spans has major effects on vegetation dynamics, ecosystem carbon budgets, and patterns of biodiversity. Landscape-Fire-Succession Models (LFSMs) that simulate the linked processes of fire and vegetation development in a spatial...

A neutral model of low-severity fire regimes

Treesearch

Don McKenzie; Amy E. Hessl

2008-01-01

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire occurrence is a stochastic process, an understanding of baseline variability is necessary in order to identify constraints on surface fire regimes. With a suitable null, or neutral, model, characteristics of natural fire regimes estimated...

Using neutral models to identify constraints on low-severity fire regimes.

Treesearch

Donald McKenzie; Amy E. Hessl; Lara-Karena B. Kellogg

2006-01-01

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire is modeled as a stochastic process, for which each fire history is only one realization, a simulation approach is necessary to understand baseline variability, thereby identifying constraints, or forcing functions, that affect fire regimes...

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

PubMed

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling

PubMed Central

Iglesias, Virginia; Yospin, Gabriel I.; Whitlock, Cathy

2015-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity. PMID:25657652

Changes in future fire regimes under climate change

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; von Bloh, Werner; Lutz, Julia; Knorr, Wolfgang; Wu, Minchao; Arneth, Almut

2013-04-01

Fires are expected to change under future climate change, climatic fire is is increasing due to increase in droughts and heat waves affecting vegetation productivity and ecosystem function. Vegetation productivity influences fuel production, but can also limit fire spread. Vegetation-fire models allow investigating the interaction between wildfires and vegetation dynamics, thus non-linear effects between changes in fuel composition and production on fire as well as changes in fire regimes on fire-related plant mortality and fuel combustion. Here we present results from simulation experiments, where the vegetation-fire models LPJmL-SPITFIRE and LPJ-GUESS are applied to future climate change scenarios from regional climate models in Europe and Northern Africa. Climate change impacts on fire regimes, vegetation dynamics and carbon fluxes are quantified and presented. New fire-prone regions are mapped and changes in fire regimes of ecosystems with a long-fire history are analyzed. Fuel limitation is likely to increase in Mediterranean-type ecosystems, indicating non-linear connection between increasing fire risk and fuel production. Increased warming in temperate ecosystems in Eastern Europe and continued fuel production leads to increases not only in climatic fire risk, but also area burnt and biomass burnt. This has implications for fire management, where adaptive capacity to this new vulnerability might be limited.

The analysis of factors of management of safety of critical information infrastructure with use of dynamic models

NASA Astrophysics Data System (ADS)

Trostyansky, S. N.; Kalach, A. V.; Lavlinsky, V. V.; Lankin, O. V.

2018-03-01

Based on the analysis of the dynamic model of panel data by region, including fire statistics for surveillance sites and statistics of a set of regional socio-economic indicators, as well as the time of rapid response of the state fire service to fires, the probability of fires in the surveillance sites and the risk of human death in The result of such fires from the values of the corresponding indicators for the previous year, a set of regional social-economics factors, as well as regional indicators time rapid response of the state fire service in the fire. The results obtained are consistent with the results of the application to the fire risks of the model of a rational offender. Estimation of the economic equivalent of human life from data on surveillance objects for Russia, calculated on the basis of the analysis of the presented dynamic model of fire risks, correctly agrees with the known literary data. The results obtained on the basis of the econometric approach to fire risks allow us to forecast fire risks at the supervisory sites in the regions of Russia and to develop management solutions to minimize such risks.

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model.

PubMed

McMichael, Christine E; Hope, Allen S

2007-08-01

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.

Influence of daily versus monthly fire emissions on atmospheric model applications in the tropics

NASA Astrophysics Data System (ADS)

Marlier, M. E.; Voulgarakis, A.; Faluvegi, G.; Shindell, D. T.; DeFries, R. S.

2012-12-01

Fires are widely used throughout the tropics to create and maintain areas for agriculture, but are also significant contributors to atmospheric trace gas and aerosol concentrations. However, the timing and magnitude of fire activity can vary strongly by year and ecosystem type. For example, frequent, low intensity fires dominate in African savannas whereas Southeast Asian peatland forests are susceptible to huge pulses of emissions during regional El Niño droughts. Despite the potential implications for modeling interactions with atmospheric chemistry and transport, fire emissions have commonly been input into global models at a monthly resolution. Recognizing the uncertainty that this can introduce, several datasets have parsed fire emissions to daily and sub-daily scales with satellite active fire detections. In this study, we explore differences between utilizing the monthly and daily Global Fire Emissions Database version 3 (GFED3) products as inputs into the NASA GISS-E2 composition climate model. We aim to understand how the choice of the temporal resolution of fire emissions affects uncertainty with respect to several common applications of global models: atmospheric chemistry, air quality, and climate. Focusing our analysis on tropical ozone, carbon monoxide, and aerosols, we compare modeled concentrations with available ground and satellite observations. We find that increasing the temporal frequency of fire emissions from monthly to daily can improve correlations with observations, predominately in areas or during seasons more heavily affected by fires. Differences between the two datasets are more evident with public health applications: daily resolution fire emissions increases the number of days exceeding World Health Organization air quality targets.

The influence of prefire tree growth and crown condition on postfire mortality of sugar pine following prescribed fire in Sequoia National Park

USGS Publications Warehouse

Nesmith, Jonathan C. B.; Das, Adrian J.; O'Hara, Kevin L.; van Mantgem, Phillip J.

2015-01-01

Tree mortality is a vital component of forest management in the context of prescribed fires; however, few studies have examined the effect of prefire tree health on postfire mortality. This is especially relevant for sugar pine (Pinus lambertiana Douglas), a species experiencing population declines due to a suite of anthropogenic factors. Using data from an old-growth mixed-conifer forest in Sequoia National Park, we evaluated the effects of fire, tree size, prefire radial growth, and crown condition on postfire mortality. Models based only on tree size and measures of fire damage were compared with models that included tree size, fire damage, and prefire tree health (e.g., measures of prefire tree radial growth or crown condition). Immediately following the fire, the inclusion of different metrics of prefire tree health produced variable improvements over the models that included only tree size and measures of fire damage, as models that included measures of crown condition performed better than fire-only models, but models that included measures of prefire radial growth did not perform better. However, 5 years following the fire, sugar pine mortality was best predicted by models that included measures of both fire damage and prefire tree health, specifically, diameter at breast height (DBH, 1.37 m), crown scorch, 30-year mean growth, and the number of sharp declines in growth over a 30-year period. This suggests that factors that influence prefire tree health (e.g., drought, competition, pathogens, etc.) may partially determine postfire mortality, especially when accounting for delayed mortality following fire.

Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography: A comparison of two fire-vegetation models

NASA Astrophysics Data System (ADS)

Wu, Minchao; Knorr, Wolfgang; Thonicke, Kirsten; Schurgers, Guy; Camia, Andrea; Arneth, Almut

2015-11-01

Global environmental changes and human activity influence wildland fires worldwide, but the relative importance of the individual factors varies regionally and their interplay can be difficult to disentangle. Here we evaluate projected future changes in burned area at the European and sub-European scale, and we investigate uncertainties in the relative importance of the determining factors. We simulated future burned area with LPJ-GUESS-SIMFIRE, a patch-dynamic global vegetation model with a semiempirical fire model, and LPJmL-SPITFIRE, a dynamic global vegetation model with a process-based fire model. Applying a range of future projections that combine different scenarios for climate changes, enhanced CO2 concentrations, and population growth, we investigated the individual and combined effects of these drivers on the total area and regions affected by fire in the 21st century. The two models differed notably with respect to the dominating drivers and underlying processes. Fire-vegetation interactions and socioeconomic effects emerged as important uncertainties for future burned area in some European regions. Burned area of eastern Europe increased in both models, pointing at an emerging new fire-prone region that should gain further attention for future fire management.

Grid cell mechanisms and function: Contributions of entorhinal persistent spiking and phase resetting

PubMed Central

Hasselmo, Michael E.

2008-01-01

This article presents a model of grid cell firing based on the intrinsic persistent firing shown experimentally in neurons of entorhinal cortex. In this model, the mechanism of persistent firing allows individual neurons to hold a stable baseline firing frequency. Depolarizing input from speed modulated head direction cells transiently shifts the frequency of firing from baseline, resulting in a shift in spiking phase in proportion to the integral of velocity. The convergence of input from different persistent firing neurons causes spiking in a grid cell only when the persistent firing neurons are within similar phase ranges. This model effectively simulates the two-dimensional firing of grid cells in open field environments, as well as the properties of theta phase precession. This model provides an alternate implementation of oscillatory interference models. The persistent firing could also interact on a circuit level with rhythmic inhibition and neurons showing membrane potential oscillations to code position with spiking phase. These mechanisms could operate in parallel with computation of position from visual angle and distance of stimuli. In addition to simulating two-dimensional grid patterns, models of phase interference can account for context-dependent firing in other tasks. In network simulations of entorhinal cortex, hippocampus and postsubiculum, the reset of phase effectively replicates context-dependent firing by entorhinal and hippocampal neurons during performance of a continuous spatial alternation task, a delayed spatial alternation task with running in a wheel during the delay period, and a hairpin maze task. PMID:19021258

Risk of large-scale fires in boreal forests of Finland under changing climate

NASA Astrophysics Data System (ADS)

Lehtonen, I.; Venäläinen, A.; Kämäräinen, M.; Peltola, H.; Gregow, H.

2016-01-01

The target of this work was to assess the impact of projected climate change on forest-fire activity in Finland with special emphasis on large-scale fires. In addition, we were particularly interested to examine the inter-model variability of the projected change of fire danger. For this purpose, we utilized fire statistics covering the period 1996-2014 and consisting of almost 20 000 forest fires, as well as daily meteorological data from five global climate models under representative concentration pathway RCP4.5 and RCP8.5 scenarios. The model data were statistically downscaled onto a high-resolution grid using the quantile-mapping method before performing the analysis. In examining the relationship between weather and fire danger, we applied the Canadian fire weather index (FWI) system. Our results suggest that the number of large forest fires may double or even triple during the present century. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to active and efficient fire suppression. However, the results reveal substantial inter-model variability in the rate of the projected increase of forest-fire danger, emphasizing the large uncertainty related to the climate change signal in fire activity. We moreover showed that the majority of large fires in Finland occur within a relatively short period in May and June due to human activities and that FWI correlates poorer with the fire activity during this time of year than later in summer when lightning is a more important cause of fires.

Mid-21st-century climate changes increase predicted fire occurrence and fire season length, Northern Rocky Mountains, United States

USGS Publications Warehouse

Riley, Karin L.; Loehman, Rachel A.

2016-01-01

Climate changes are expected to increase fire frequency, fire season length, and cumulative area burned in the western United States. We focus on the potential impact of mid-21st-century climate changes on annual burn probability, fire season length, and large fire characteristics including number and size for a study area in the Northern Rocky Mountains. Although large fires are rare they account for most of the area burned in western North America, burn under extreme weather conditions, and exhibit behaviors that preclude methods of direct control. Allocation of resources, development of management plans, and assessment of fire effects on ecosystems all require an understanding of when and where fires are likely to burn, particularly under altered climate regimes that may increase large fire occurrence. We used the large fire simulation model FSim to model ignition, growth, and containment of wildfires under two climate scenarios: contemporary (based on instrumental weather) and mid-century (based on an ensemble average of global climate models driven by the A1B SRES emissions scenario). Modeled changes in fire patterns include increased annual burn probability, particularly in areas of the study region with relatively short contemporary fire return intervals; increased individual fire size and annual area burned; and fewer years without large fires. High fire danger days, represented by threshold values of Energy Release Component (ERC), are projected to increase in number, especially in spring and fall, lengthening the climatic fire season. For fire managers, ERC is an indicator of fire intensity potential and fire economics, with higher ERC thresholds often associated with larger, more expensive fires. Longer periods of elevated ERC may significantly increase the cost and complexity of fire management activities, requiring new strategies to maintain desired ecological conditions and limit fire risk. Increased fire activity (within the historical range of frequency and severity, and depending on the extent to which ecosystems are adapted) may maintain or restore ecosystem functionality; however, in areas that are highly departed from historical fire regimes or where there is disequilibrium between climate and vegetation, ecosystems may be rapidly and persistently altered by wildfires, especially those that burn under extreme conditions.

Firing patterns in the adaptive exponential integrate-and-fire model.

PubMed

Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

2008-11-01

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

A Model-Based Approach to Infer Shifts in Regional Fire Regimes Over Time Using Sediment Charcoal Records

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; Hooten, M.; Higuera, P. E.; Marlon, J. R.; McLachlan, J. S.; Kelly, R.

2016-12-01

Sediment charcoal records are used in paleoecological analyses to identify individual local fire events and to estimate fire frequency and regional biomass burned at centennial to millenial time scales. Methods to identify local fire events based on sediment charcoal records have been well developed over the past 30 years, however, an integrated statistical framework for fire identification is still lacking. We build upon existing paleoecological methods to develop a hierarchical Bayesian point process model for local fire identification and estimation of fire return intervals. The model is unique in that it combines sediment charcoal records from multiple lakes across a region in a spatially-explicit fashion leading to estimation of a joint, regional fire return interval in addition to lake-specific local fire frequencies. Further, the model estimates a joint regional charcoal deposition rate free from the effects of local fires that can be used as a measure of regional biomass burned over time. Finally, the hierarchical Bayesian approach allows for tractable error propagation such that estimates of fire return intervals reflect the full range of uncertainty in sediment charcoal records. Specific sources of uncertainty addressed include sediment age models, the separation of local versus regional charcoal sources, and generation of a composite charcoal record The model is applied to sediment charcoal records from a dense network of lakes in the Yukon Flats region of Alaska. The multivariate joint modeling approach results in improved estimates of regional charcoal deposition with reduced uncertainty in the identification of individual fire events and local fire return intervals compared to individual lake approaches. Modeled individual-lake fire return intervals range from 100 to 500 years with a regional interval of roughly 200 years. Regional charcoal deposition to the network of lakes is correlated up to 50 kilometers. Finally, the joint regional charcoal deposition rate exhibits changes over time coincident with major climatic and vegetation shifts over the past 10,000 years. Ongoing work will use the regional charcoal deposition rate to estimate changes in biomass burned as a function of climate variability and regional vegetation pattern.

Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices

Treesearch

Haiganoush K. Preisler; Shyh-Chin Chen; Francis Fujioka; John W. Benoit; Anthony L. Westerling

2008-01-01

The National Fire Danger Rating System indices deduced from a regional simulation weather model were used to estimate probabilities and numbers of large fire events on monthly and 1-degree grid scales. The weather model simulations and forecasts are ongoing experimental products from the Experimental Climate Prediction Center at the Scripps Institution of Oceanography...

New global fire emission estimates and evaluation of volatile organic compounds

Treesearch

C. Wiedinmyer; L. K. Emmons; S. K. Akagi; R. J. Yokelson; J. J. Orlando; J. A. Al-Saadi; A. J. Soja

2010-01-01

A daily, high-resolution, global fire emissions model has been built to estimate emissions from open burning for air quality modeling applications: The Fire INventory from NCAR (FINN version 1). The model framework uses daily fire detections from the MODIS instruments and updated emission factors, specifically for speciated non-methane organic compounds (NMOC). Global...

Chapter 2: Fire and Fuels Extension: Model description

Treesearch

Sarah J. Beukema; Elizabeth D. Reinhardt; Julee A. Greenough; Donald C. E. Robinson; Werner A. Kurz

2003-01-01

The Fire and Fuels Extension to the Forest Vegetation Simulator is a model that simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. Existing models are used to represent forest stand development (the Forest Vegetation Simulator, Wykoff and others 1982), fire behavior (Rothermel 1972, Van Wagner 1977, and...

75 FR 20516 - Special Conditions: Cirrus Design Corporation, Model SF50; Fire Extinguishing for Upper Aft...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-20

...; Special Conditions No. 23-245-SC] Special Conditions: Cirrus Design Corporation, Model SF50; Fire... protect such installed engines from fires, were not envisioned in the development of the part 23 normal... condition for the fire extinguishing system for the engine on the model SF50 is required. Regulations...

Computer evaluation of existing and proposed fire lookouts

Treesearch

Romain M. Mees

1976-01-01

A computer simulation model has been developed for evaluating the fire detection capabilities of existing and proposed lookout stations. The model uses coordinate location of fires and lookouts, tower elevation, and topographic data to judge location of stations, and to determine where a fire can be seen. The model was tested by comparing it with manual detection on a...

First Order Fire Effects Model: FOFEM 4.0, user's guide

Treesearch

Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown

1997-01-01

A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.

Modeling regional-scale wildland fire emissions with the wildland fire emissions information system

Treesearch

Nancy H.F. French; Donald McKenzie; Tyler Erickson; Benjamin Koziol; Michael Billmire; K. Endsley; Naomi K.Y. Scheinerman; Liza Jenkins; Mary E. Miller; Roger Ottmar; Susan Prichard

2014-01-01

As carbon modeling tools become more comprehensive, spatial data are needed to improve quantitative maps of carbon emissions from fire. The Wildland Fire Emissions Information System (WFEIS) provides mapped estimates of carbon emissions from historical forest fires in the United States through a web browser. WFEIS improves access to data and provides a consistent...

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.

Axonal properties determine somatic firing in a model of in vitro CA1 hippocampal sharp wave/ripples and persistent gamma oscillations

PubMed Central

Traub, Roger D.; Schmitz, Dietmar; Maier, Nikolaus; Whittington, Miles A.; Draguhn, Andreas

2012-01-01

Evidence has been presented that CA1 pyramidal cells, during spontaneous in vitro sharp wave/ripple (SPW-R) complexes, generate somatic action potentials that originate in axons. ‘Participating’ (somatically firing) pyramidal cells fire (almost always) at most once during a particular SPW-R whereas non-participating cells virtually never fire during an SPW-R. Somatic spikelets were small or absent, while ripple-frequency EPSCs and IPSCs occurred during the SPW-R in pyramidal neurons. These experimental findings could be replicated with a network model in which electrical coupling was present between small pyramidal cell axonal branches. Here, we explore this model in more depth. Factors that influence somatic participation include: (i) the diameter of axonal branches that contain coupling sites to other axons, because firing in larger branches injects more current into the main axon, increasing antidromic firing probability; (ii) axonal K+ currents; and (iii) somatic hyperpolarization and shunting. We predict that portions of axons fire at high frequency during SPW-R, while somata fire much less. In the model, somatic firing can occur by occasional generation of full action potentials in proximal axonal branches, which are excited by high-frequency spikelets. When the network contains phasic synaptic inhibition, at the axonal gap junction site, gamma oscillations result, again with more frequent axonal firing than somatic firing. Combining the models, so as to generate gamma followed by sharp waves, leads to strong overlap between the population of cells firing during gamma the population of cells firing during a subsequent sharp wave, as observed in vivo. PMID:22697272

Aerosols from fires: an examination of the effects on ozone photochemistry in the Western United States.

PubMed

Jiang, Xiaoyan; Wiedinmyer, Christine; Carlton, Annmarie G

2012-11-06

This study presents a first attempt to investigate the roles of fire aerosols in ozone (O(3)) photochemistry using an online coupled meteorology-chemistry model, the Weather Research and Foresting model with Chemistry (WRF-Chem). Four 1-month WRF-Chem simulations for August 2007, with and without fire emissions, were carried out to assess the sensitivity of O(3) predictions to the emissions and subsequent radiative feedbacks associated with large-scale fires in the Western United States (U.S.). Results show that decreases in planetary boundary layer height (PBLH) resulting from the radiative effects of fire aerosols and increases in emissions of nitrogen oxides (NO(x)) and volatile organic compounds (VOCs) from the fires tend to increase modeled O(3) concentrations near the source. Reductions in downward shortwave radiation reaching the surface and surface temperature due to fire aerosols cause decreases in biogenic isoprene emissions and J(NO(2)) photolysis rates, resulting in reductions in O(3) concentrations by as much as 15%. Thus, the results presented in this study imply that considering the radiative effects of fire aerosols may reduce O(3) overestimation by traditional photochemical models that do not consider fire-induced changes in meteorology; implementation of coupled meteorology-chemistry models are required to simulate the atmospheric chemistry impacted by large-scale fires.

The simulation of surface fire spread based on Rothermel model in windthrow area of Changbai Mountain (Jilin, China)

NASA Astrophysics Data System (ADS)

Yin, Hang; Jin, Hui; Zhao, Ying; Fan, Yuguang; Qin, Liwu; Chen, Qinghong; Huang, Liya; Jia, Xiang; Liu, Lijie; Dai, Yuhong; Xiao, Ying

2018-03-01

The forest-fire not only brings great loss to natural resources, but also destructs the ecosystem and reduces the soil fertility, causing some natural disasters as soil erosion and debris flow. However, due to the lack of the prognosis for forest fire spreading trend in forest fire fighting, it is difficult to formulate rational and effective fire-fighting scheme. In the event of forest fire, achieving accurate judgment to the fire behavior would greatly improve the fire-fighting efficiency, and reduce heavy losses caused by fire. Researches on forest fire spread simulation can effectively reduce the loss of disasters. The present study focused on the simulation of "29 May 2012" wildfire in windthrow area of Changbai Mountain. Basic data were retrieved from the "29 May 2012" wildfire and field survey. A self-development forest fire behavior simulated program based on Rothermel Model was used in the simulation. Kappa coefficient and Sørensen index were employed to evaluate the simulation accuracy. The results showed that: The perimeter of simulated burned area was 4.66 km, the area was 56.47 hm2 and the overlapped burned area was 33.68 hm2, and the estimated rate of fire spread was 0.259 m/s. Between the simulated fire and actual fire, the Kappa coefficient was 0.7398 and the Sørensen co-efficient was 0.7419. This proved the application of Rothermel model to conduct fire behavior simulation in windthrow meadow was feasible. It can achieve the goal of forecasting for the spread behavior in windthrow area of Changbai Mountain. Thus, our self-development program based on the Rothermel model can provide a effective forecast of fire spread, which will facilitate the fire suppression work.

Wildland Fire Forecasting: Predicting Wildfire Behavior, Growth, and Feedbacks on Weather

NASA Astrophysics Data System (ADS)

Coen, J. L.

2005-12-01

Recent developments in wildland fire research models have represented more complex of fire behavior. The cost has been to increase the computational requirements. When operational constraints are included, such as the need to produce such forecasts faster than real time, the challenge becomes a balance of how much complexity (with corresponding gains in realism) and accuracy can be achieved in producing the quantities of interest while meeting the specified operational constraints. Current field tools are calculator or Palm-Pilot based algorithms such as BEHAVE and BEHAVE Plus that produce timely estimates of instantaneous fire spread rates, flame length, and fire intensity at a point using readily estimated inputs of fuel model, terrain slope, and atmospheric wind speed at a point. At the cost of requiring a PC and slower calculation, FARSITE represents two-dimensional fire spread and adds capabilities including a parameterized representation of crown fire ignition, This work describes how a coupled atmosphere-fire model previously used as a research tool has been adapted for production of real-time forecasts of fire growth and its interactions with weather over a domain focusing on Colorado during summer 2004. The coupled atmosphere-wildland fire-environment (CAWFE) model composed of a 3-dimensional atmospheric prediction model that has been two-way coupled with an empirical fire spread model. The models are connected in that atmospheric conditions (and fuel conditions influenced by the atmosphere) affect the rate and direction of fire propagation, which releases sensible and latent heat (i.e. thermal and water vapor fluxes) to the atmosphere that in turn alter the winds and atmospheric structure around the fire. Thus, it can represent time and spatially-varying weather and the fire feedbacks on the atmospheric which are at the heart of sudden changes in fire behavior and examples of extreme fire behavior such as blow ups, which are now not predictable with current tools. Thus, although this work shows that is it possible to perform more detailed simulations in real time, fire behavior forecasting remains a challenging problem. This is due to challenges in weather prediction, particularly at fine spatial and temporal scales considered "nowcasting" (0-6 hrs), uncertainties in fire behavior even with known meteorological conditions, limitations in quantitative datasets on fuel properties such as fuel loading, and verification. This work describes efforts to advance these capabilities with input from remote sensing data on fuel characteristics and dynamic steering and object-based verification with remotely sensed fire perimeters.

FEMME- post-Fire Emergency ManageMEnt tool.

NASA Astrophysics Data System (ADS)

Vieira, Diana; Serpa, Dalila; Rocha, João; Nunes, João; Keizer, Jacob

2017-04-01

Wildfires can have important impacts on hydrological and soil erosion processes in forest catchments, due to the destruction of vegetation cover and changes to soil properties. The involved processes however, are non-linear and not fully understood. This has severely limited the understanding on the impacts of wildfires, and, as a consequence, current runoff-erosion models are poorly adapted to recently burned forest conditions. Furthermore, while post-fire forestry operations and, to a lesser extent, post-fire soil conservation measures are commonly applied, their hydrological and erosion impacts continue poorly known, hampering decision-making by land owners and managers. Past post-wildfire research in Portugal has involved simple adaptations of plot-scale runoff-erosion models to post-fire conditions. This follow-up study focusses on model adaptation to selected post-fire soil conservation measures. To this end, full stock is taken of various datasets collected by several (past and ongoing research projects. The selected model is the Morgan-Morgan-Finney model (MMF, Morgan,2001), which already proved its suitability for post-fire conditions in Portugal (Vieira et al, 2010, 2014) as well as NW-Spain ( Fernández et al., 2010). The present results concerned runoff and erosion different burn severities and various post-fire mitigation treatments (mulch, hydromulch, needle cast, barriers), focussing on the plot and field scale. The results for both the first and the second year following the wildfire revealed good model efficiency, not only for burned and untreated conditions but also for burned and treated conditions. These results thus reinforced earlier findings that MMF is a suitable model for the envisaged post-fire soil erosion assessment tool, coined "FEMME". The data used for post-fire soil erosion calibration with the MMF already allows the delineation of the post-fire management FEMME tool. Nevertheless, further model assessment will address additional post-fire forestry operations (e.g. plowing) as well as upscaling to the catchment scale with the MMF model and compare it with the SWAT model.

Impact of fire disturbance on soil thermal and carbon dynamics in Alaskan Tundra and Boreal forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastetter, E.; Shaver, G. R.; Rocha, A. V.

2012-12-01

In Alaska, fire disturbance is a major component influencing the soil water and energy balance in both tundra and boreal forest ecosystems. Fire-caused changes in soil environment further affect both above- and below-ground carbon cycles depending on different fire severities. Understanding the effects of fire disturbance on soil thermal change requires implicit modeling work on the post-fire soil thawing and freezing processes. In this study, we model the soil temperature profiles in multiple burned and non-burned sites using a well-developed soil thermal model which fully couples soil water and heat transport. The subsequent change in carbon dynamics is analyzed based on site level observations and simulations from the Multiple Element Limitation (MEL) model. With comparison between burned and non-burned sites, we compare and contrast fire effects on soil thermal and carbon dynamics in continuous permafrost (Anaktuvik fire in north slope), discontinuous permafrost (Erickson Creek fire at Hess Creek) and non-permafrost zone (Delta Junction fire in interior Alaska). Then we check the post-fire recovery of soil temperature profiles at sites with different fire severities in both tundra and boreal forest fire areas. We further project the future changes in soil thermal and carbon dynamics using projected climate data from Scenarios Network for Alaska & Arctic Planning (SNAP). This study provides information to improve the understanding of fire disturbance on soil thermal and carbon dynamics and the consequent response under a warming climate.

Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions

PubMed Central

Shipston‐Sharman, Oliver; Solanka, Lukas

2016-01-01

Abstract Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing. PMID:27870120

The Role of Temporal Evolution in Modeling Atmospheric Emissions from Tropical Fires

NASA Technical Reports Server (NTRS)

Marlier, Miriam E.; Voulgarakis, Apostolos; Shindell, Drew T.; Faluvegi, Gregory S.; Henry, Candise L.; Randerson, James T.

2014-01-01

Fire emissions associated with tropical land use change and maintenance influence atmospheric composition, air quality, and climate. In this study, we explore the effects of representing fire emissions at daily versus monthly resolution in a global composition-climate model. We find that simulations of aerosols are impacted more by the temporal resolution of fire emissions than trace gases such as carbon monoxide or ozone. Daily-resolved datasets concentrate emissions from fire events over shorter time periods and allow them to more realistically interact with model meteorology, reducing how often emissions are concurrently released with precipitation events and in turn increasing peak aerosol concentrations. The magnitude of this effect varies across tropical ecosystem types, ranging from smaller changes in modeling the low intensity, frequent burning typical of savanna ecosystems to larger differences when modeling the short-term, intense fires that characterize deforestation events. The utility of modeling fire emissions at a daily resolution also depends on the application, such as modeling exceedances of particulate matter concentrations over air quality guidelines or simulating regional atmospheric heating patterns.

Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System

PubMed Central

Blomquist, Patrick; Devor, Anna; Indahl, Ulf G.; Ulbert, Istvan; Einevoll, Gaute T.; Dale, Anders M.

2009-01-01

A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population. PMID:19325875

Projecting climate-driven increases in North American fire activity

NASA Astrophysics Data System (ADS)

Wang, D.; Morton, D. C.; Collatz, G. J.

2013-12-01

Climate regulates fire activity through controls on vegetation productivity (fuels), lightning ignitions, and conditions governing fire spread. In many regions of the world, human management also influences the timing, duration, and extent of fire activity. These coupled interactions between human and natural systems make fire a complex component of the Earth system. Satellite data provide valuable information on the spatial and temporal dynamics of recent fire activity, as active fires, burned area, and land cover information can be combined to separate wildfires from intentional burning for agriculture and forestry. Here, we combined satellite-derived burned area data with land cover and climate data to assess fire-climate relationships in North America between 2000-2012. We used the latest versions of the Global Fire Emissions Database (GFED) burned area product and Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate data to develop regional relationships between burned area and potential evaporation (PE), an integrated dryness metric. Logistic regression models were developed to link burned area with PE and individual climate variables during and preceding the fire season, and optimal models were selected based on Akaike Information Criterion (AIC). Overall, our model explained 85% of the variance in burned area since 2000 across North America. Fire-climate relationships from the era of satellite observations provide a blueprint for potential changes in fire activity under scenarios of climate change. We used that blueprint to evaluate potential changes in fire activity over the next 50 years based on twenty models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). All models suggest an increase of PE under low and high emissions scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5, respectively), with largest increases in projected burned area across the western US and central Canada. Overall, near-term climate projections point to pronounced changes in fire season length, total burned area, and the frequency of extreme events across North America by 2050.

Impact of forest fires on particulate matter and ozone levels during the 2003, 2004 and 2005 fire seasons in Portugal.

PubMed

Martins, V; Miranda, A I; Carvalho, A; Schaap, M; Borrego, C; Sá, E

2012-01-01

The main purpose of this work is to estimate the impact of forest fires on air pollution applying the LOTOS-EUROS air quality modeling system in Portugal for three consecutive years, 2003-2005. Forest fire emissions have been included in the modeling system through the development of a numerical module, which takes into account the most suitable parameters for Portuguese forest fire characteristics and the burnt area by large forest fires. To better evaluate the influence of forest fires on air quality the LOTOS-EUROS system has been applied with and without forest fire emissions. Hourly concentration results have been compared to measure data at several monitoring locations with better modeling quality parameters when forest fire emissions were considered. Moreover, hourly estimates, with and without fire emissions, can reach differences in the order of 20%, showing the importance and the influence of this type of emissions on air quality. Copyright © 2011 Elsevier B.V. All rights reserved.

Application of fire and evacuation models in evaluation of fire safety in railway tunnels

NASA Astrophysics Data System (ADS)

Cábová, Kamila; Apeltauer, Tomáš; Okřinová, Petra; Wald, František

2017-09-01

The paper describes an application of numerical simulation of fire dynamics and evacuation of people in a tunnel. The software tool Fire Dynamics Simulator is used to simulate temperature resolution and development of smoke in a railway tunnel. Comparing to temperature curves which are usually used in the design stage results of the model show that the numerical model gives lower temperature of hot smoke layer. Outputs of the numerical simulation of fire also enable to improve models of evacuation of people during fires in tunnels. In the presented study the calculated high of smoke layer in the tunnel is in 10 min after the fire ignition lower than the level of 2.2 m which is considered as the maximal limit for safe evacuation. Simulation of the evacuation process in bigger scale together with fire dynamics can provide very valuable information about important security conditions like Available Safe Evacuation Time (ASET) vs Required Safe Evacuation Time (RSET). On given example in software EXODUS the paper summarizes selected results of evacuation model which should be in mind of a designer when preparing an evacuation plan.

Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs.

PubMed

Vitolo, Claudia; Di Giuseppe, Francesca; D'Andrea, Mirko

2018-01-01

The name caliver stands for CALIbration and VERification of forest fire gridded model outputs. This is a package developed for the R programming language and available under an APACHE-2 license from a public repository. In this paper we describe the functionalities of the package and give examples using publicly available datasets. Fire danger model outputs are taken from the modeling components of the European Forest Fire Information System (EFFIS) and observed burned areas from the Global Fire Emission Database (GFED). Complete documentation, including a vignette, is also available within the package.

Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs

PubMed Central

Di Giuseppe, Francesca; D’Andrea, Mirko

2018-01-01

The name caliver stands for CALIbration and VERification of forest fire gridded model outputs. This is a package developed for the R programming language and available under an APACHE-2 license from a public repository. In this paper we describe the functionalities of the package and give examples using publicly available datasets. Fire danger model outputs are taken from the modeling components of the European Forest Fire Information System (EFFIS) and observed burned areas from the Global Fire Emission Database (GFED). Complete documentation, including a vignette, is also available within the package. PMID:29293536

The Effects of Vegetative Type, Edges, Fire History, Rainfall and Management in Fire-Maintained Habitat

NASA Technical Reports Server (NTRS)

Breininger, David R.; Foster, Tammy E.; Carter, Geoffrey M.; Duncan, Brean W.; Stolen, Eric D.; Lyon, James E.

2018-01-01

The combined effects of fire history, climate, and landscape features (e.g., edges) on habitat specialists need greater focus in fire ecology studies, which usually only emphasize characteristics of the most recent fire. Florida scrub-jays are an imperiled, territorial species that prefer medium (1.2-1.7 m) shrub heights, which are dynamic because of frequent fires. We measured short, medium, and tall habitat quality states annually within 10 ha grid cells (that represented potential territories) because fires and vegetative recovery cause annual variation in habitat quality. We used multistate models and model selection to test competing hypotheses about how transition probabilities vary between states as functions of environmental covariates. Covariates included vegetative type, edges (e.g., roads, forests), precipitation, openings (gaps between shrubs), mechanical cutting, and fire characteristics. Fire characteristics not only included an annual presence/absence of fire covariate, but also fire history covariates: time since the previous fire, the longest fire-free interval, and the number of repeated fires. Statistical models with support included many covariates for each transition probability, often including fire history, interactions and nonlinear relationships. Tall territories resulted from 28 years of fire suppression and habitat fragmentation that reduced the spread of fires across landscapes. Despite 35 years of habitat restoration and prescribed fires, half the territories remained tall suggesting a regime shift to a less desirable habitat condition. Edges reduced the effectiveness of fires in setting degraded scrub and flatwoods into earlier successional states making mechanical cutting an important tool to compliment frequent prescribed fires.

A new method for the analysis of fire spread modeling errors

Treesearch

Francis M. Fujioka

2002-01-01

Fire spread models have a long history, and their use will continue to grow as they evolve from a research tool to an operational tool. This paper describes a new method to analyse two-dimensional fire spread modeling errors, particularly to quantify the uncertainties of fire spread predictions. Measures of error are defined from the respective spread distances of...

First-order fire effects models for land Management: Overview and issues

Treesearch

Elizabeth D. Reinhardt; Matthew B. Dickinson

2010-01-01

We give an overview of the science application process at work in supporting fire management. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days to centuries. Fire effects may be modeled using empirical, rule based, or process...

Probability based models for estimation of wildfire risk

Treesearch

Haiganoush Preisler; D. R. Brillinger; R. E. Burgan; John Benoit

2004-01-01

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km²-day cell level. We fit a spatially and temporally explicit non-...

A chance-constrained programming model to allocate wildfire initial attack resources for a fire season

Treesearch

Yu Wei; Michael Bevers; Erin Belval; Benjamin Bird

2015-01-01

This research developed a chance-constrained two-stage stochastic programming model to support wildfire initial attack resource acquisition and location on a planning unit for a fire season. Fire growth constraints account for the interaction between fire perimeter growth and construction to prevent overestimation of resource requirements. We used this model to examine...

A simple physical model for forest fire spread

Treesearch

E. Koo; P. Pagni; J. Woycheese; S. Stephens; D. Weise; J. Huff

2005-01-01

Based on energy conservation and detailed heat transfer mechanisms, a simple physical model for fire spread is presented for the limit of one-dimensional steady-state contiguous spread of a line fire in a thermally-thin uniform porous fuel bed. The solution for the fire spread rate is found as an eigenvalue from this model with appropriate boundary conditions through a...

Fire severity estimated from remote sensing data to evaluate the Coupled Atmosphere-Wildland Fire-Environment (CAWFE) model

NASA Astrophysics Data System (ADS)

Oliva, P.; Coen, J.; Schroeder, W.

2013-12-01

Fire severity defined as the degree of damage originated from fire on soils and vegetation immediately after the fire, is affected by weather conditions (i.e. wind, air humidity), terrain characteristics (i.e. slope, aspect) and fuel properties (i.e. tree density, fuel moisture content). In this study we evaluated the relationships between fire severity estimated from Earth Observing Advance Land Imager (EO-ALI) images and the heat fluxes produced by the Coupled Atmosphere-Wildland Fire-Environment (CAWFE) model (Coen 2013). We present the results for a large fire occurred in New Mexico in June 2012 which burned 44,330 acres. The EO-ALI sensor (30 m spatial resolution) has nine spectral bands, six of them were designed to mimic Landsat bands and the three additional bands cover 443, 867.5 and 1250 nm. We used a physically-based approach to estimate fire severity developed by De Santis et al. (2009). This method classifies the satellite image into Geophysical Composite burned index (GeoCBI) values, which represent the fire severity within the fire-affected area, using radiative transfer model simulated spectra as reference. This method has been used to characterize fire severity levels using Landsat images and validated with field data (R2 > 0.85). Based on those results we expected a better performance of EO-ALI images due to its improved spectral resolution. On the other hand, CAWFE is composed of two parts: a numerical weather prediction model and a fire behavior module that represents the growth of a wildland fire in response to factors such as wind, terrain, and fuels, and includes the fire's impact on the atmosphere. To perform the evaluation we selected a stratified random sample by fire severity level. The values of maximum heat flux (sensible, latent), and total heat flux showed a higher correlation with the higher levels of fire severity (GeoCBI: 2.8-3) than with the medium levels of fire severity (GeoCBI: 2.3-2.8). However, the total heat flux proved to have a high correlation with the fire severity estimated in terms of GeoCBI values. The GeoCBI is a semi-quantitative index that takes into account the effects on vegetation by means of evaluating several variables such as, percentage of scorched leaves, height of carbon and change in LAI. Therefore, the results obtained in this study pointed out the good performance of the CAWFE model simulating the effects of fire in vegetation. Interpreting the outputs of the CAWFE model in terms of fire severity will help fire managers and decision makers understand the effects of the fire and prioritize the areas more severely affected. Fire severity classification estimated as GeoCBI values. The GeoCBI range from 0 to 3, where 0 means not affected by fire, and 3 means very high fire severity.

Integrating climatic and fuels information into National Fire Risk Decision Support Tools

Treesearch

W. Cooke; V. Anantharaj; C. Wax; J. Choi; K. Grala; M. Jolly; G.P. Dixon; J. Dyer; D.L. Evans; G.B. Goodrich

2007-01-01

The Wildland Fire Assessment System (WFAS) is a component of the U.S. Department of Agriculture, Forest Service Decision Support Systems (DSS) that support fire potential modeling. Fire potential models for Mississippi and for Eastern fire environments have been developed as part of a National Aeronautic and Space Agency-funded study aimed at demonstrating the utility...

Bits or Shots in Combat? The Generalized Deitchman Model of Guerrilla Warfare

DTIC Science & Technology

2013-08-13

fire; absence of intelligence leads to unaimed fire, dependent on targets’ density. We propose a new Lanchester -type model that mixes aimed and unaimed...military hardware. The idea of modeling the trade-off between firepower and intelligence in a Lanchester setting was first suggested by Schreiber [4...of intelligence leads to unaimed fire, dependent on targets? density. We propose a new Lanchester -type model that mixes aimed and unaimed fire, the

Fire frequency, area burned, and severity: A quantitative approach to defining a normal fire year

USGS Publications Warehouse

Lutz, J.A.; Key, C.H.; Kolden, C.A.; Kane, J.T.; van Wagtendonk, J.W.

2011-01-01

Fire frequency, area burned, and fire severity are important attributes of a fire regime, but few studies have quantified the interrelationships among them in evaluating a fire year. Although area burned is often used to summarize a fire season, burned area may not be well correlated with either the number or ecological effect of fires. Using the Landsat data archive, we examined all 148 wildland fires (prescribed fires and wildfires) >40 ha from 1984 through 2009 for the portion of the Sierra Nevada centered on Yosemite National Park, California, USA. We calculated mean fire frequency and mean annual area burned from a combination of field- and satellite-derived data. We used the continuous probability distribution of the differenced Normalized Burn Ratio (dNBR) values to describe fire severity. For fires >40 ha, fire frequency, annual area burned, and cumulative severity were consistent in only 13 of 26 years (50 %), but all pair-wise comparisons among these fire regime attributes were significant. Borrowing from long-established practice in climate science, we defined "fire normals" to be the 26 year means of fire frequency, annual area burned, and the area under the cumulative probability distribution of dNBR. Fire severity normals were significantly lower when they were aggregated by year compared to aggregation by area. Cumulative severity distributions for each year were best modeled with Weibull functions (all 26 years, r2 ??? 0.99; P < 0.001). Explicit modeling of the cumulative severity distributions may allow more comprehensive modeling of climate-severity and area-severity relationships. Together, the three metrics of number of fires, size of fires, and severity of fires provide land managers with a more comprehensive summary of a given fire year than any single metric.

Fire activity as a function of fire-weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

NASA Astrophysics Data System (ADS)

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquín; Gutiérrez, José M.; San Miguel-Ayanz, Jesús; Camia, Andrea; Keeley, Jon E.; Moreno, José M.

2015-11-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire-weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Vegetation Fires in the Coupled Human-Earth System Under Future Environmental and Policy Perspectives

NASA Astrophysics Data System (ADS)

le page, Y.; Morton, D. C.; Hurtt, G. C.

2013-12-01

Fires play a major role in terrestrial ecosystems dynamics and the carbon cycle. Potential changes in fire regimes due to climate change, land use change, or human management could have substantial ecological, climatic and socio-economic impacts, and have recently been emphasized as a source of uncertainty for policy-makers and climate mitigation cost estimates. Anticipating these interactions thus entails interdisciplinary models. Here we describe the development of a new fire modeling framework, which features the essential integration of climatic, vegetation and anthropogenic drivers. The model is an attempt to realistically account for ignition, spread and termination processes, on a 12-hour time step and at 1 degree spatial resolution globally. Because the quantitative influence of fire drivers on these processes are often poorly constrained, the framework includes an optimization procedure whereby key parameters (e.g. influence of moisture on fire spread, probability of cloud-to-ground lightning flashes to actually ignite a fire, human ignition frequency as a function of land use density) are determined to maximize the agreement between modeled and observed burned area over the past decade. The model performs surprisingly well across all biomes, and shows good agreement on non-optimized features, such as seasonality and fire size, which suggests some potential for robust projections. We couple the model to an integrated assessment model and explore the consequences of mitigation policies, land use decisions and climate change on future fire regimes with a focus on the Amazon basin. The coupled model future projections show that business-as-usual land use expansion would increase the frequency of escaped fires in the remaining forest, especially when combined with models projecting a drier climate. Inversely, climate mitigation policies as projected in the IPCC RCP4.5 scenario achieve synergistic benefits, with increased forest extent, less fire ignitions, and higher moisture levels.

Quantitative Risk Modeling of Fire on the International Space Station

NASA Technical Reports Server (NTRS)

Castillo, Theresa; Haught, Megan

2014-01-01

The International Space Station (ISS) Program has worked to prevent fire events and to mitigate their impacts should they occur. Hardware is designed to reduce sources of ignition, oxygen systems are designed to control leaking, flammable materials are prevented from flying to ISS whenever possible, the crew is trained in fire response, and fire response equipment improvements are sought out and funded. Fire prevention and mitigation are a top ISS Program priority - however, programmatic resources are limited; thus, risk trades are made to ensure an adequate level of safety is maintained onboard the ISS. In support of these risk trades, the ISS Probabilistic Risk Assessment (PRA) team has modeled the likelihood of fire occurring in the ISS pressurized cabin, a phenomenological event that has never before been probabilistically modeled in a microgravity environment. This paper will discuss the genesis of the ISS PRA fire model, its enhancement in collaboration with fire experts, and the results which have informed ISS programmatic decisions and will continue to be used throughout the life of the program.

Evaluation of short-term changes of hydrological response in mountainous basins of the Vitim Plateau (Russia) after forest fires based on data analysis and hydrological modelling

NASA Astrophysics Data System (ADS)

Semenova, O. M.; Lebedeva, L. S.; Nesterova, N. V.; Vinogradova, T. A.

2015-06-01

Twelve mountainous basins of the Vitim Plateau (Eastern Siberia, Russia) with areas ranging from 967 to 18 200 km2 affected by extensive fires in 2003 (from 13 to 78% of burnt area) were delineated based on MODIS Burned Area Product. The studied area is characterized by scarcity of hydrometeorological observations and complex hydrological processes. Combined analysis of monthly series of flow and precipitation was conducted to detect short-term fire impact on hydrological response of the basins. The idea of basin-analogues which have significant correlation of flow with "burnt" watersheds in stationary (pre-fire) period with the assumption that fire impact produced an outlier of established dependence was applied. Available data allowed for qualitative detection of fire-induced changes at two basins from twelve studied. Summer flow at the Amalat and Vitimkan Rivers (22 and 78% proportion of burnt area in 2003, respectively) increased by 40-50% following the fire.The impact of fire on flow from the other basins was not detectable.The hydrological model Hydrograph was applied to simulate runoff formation processes for stationary pre-fire and non-stationary post-fire conditions. It was assumed that landscape properties changed after the fire suggest a flow increase. These changes were used to assess the model parameters which allowed for better model performance in the post-fire period.

New tendencies in wildland fire simulation for understanding fire phenomena: An overview of the WFDS system capabilities in Mediterranean ecosystems

NASA Astrophysics Data System (ADS)

Pastor, E.; Tarragó, D.; Planas, E.

2012-04-01

Wildfire theoretical modeling endeavors predicting fire behavior characteristics, such as the rate of spread, the flames geometry and the energy released by the fire front by applying the physics and the chemistry laws that govern fire phenomena. Its ultimate aim is to help fire managers to improve fire prevention and suppression and hence reducing damage to population and protecting ecosystems. WFDS is a 3D computational fluid dynamics (CFD) model of a fire-driven flow. It is particularly appropriate for predicting the fire behaviour burning through the wildland-urban interface, since it is able to predict the fire behaviour in the intermix of vegetative and structural fuels that comprise the wildland urban interface. This model is not suitable for operational fire management yet due to computational costs constrains, but given the fact that it is open-source and that it has a detailed description of the fuels and of the combustion and heat transfer mechanisms it is currently a suitable system for research purposes. In this paper we present the most important characteristics of the WFDS simulation tool in terms of the models implemented, the input information required and the outputs that the simulator gives useful for understanding fire phenomena. We briefly discuss its advantages and opportunities through some simulation exercises of Mediterranean ecosystems.

Resuspension and redistribution of radionuclides during grassland and forest fires in the Chernobyl exclusion zone: part II. Modeling the transport process.

PubMed

Yoschenko, V I; Kashparov, V A; Levchuk, S E; Glukhovskiy, A S; Khomutinin, Yu V; Protsak, V P; Lundin, S M; Tschiersch, J

2006-01-01

To predict parameters of radionuclide resuspension, transport and deposition during forest and grassland fires, several model modules were developed and adapted. Experimental data of controlled burning of prepared experimental plots in the Chernobyl exclusion zone have been used to evaluate the prognostic power of the models. The predicted trajectories and elevations of the plume match with those visually observed during the fire experiments in the grassland and forest sites. Experimentally determined parameters could be successfully used for the calculation of the initial plume parameters which provide the tools for the description of various fire scenarios and enable prognostic calculations. In summary, the model predicts a release of some per thousand from the radionuclide inventory of the fuel material by the grassland fires. During the forest fire, up to 4% of (137)Cs and (90)Sr and up to 1% of the Pu isotopes can be released from the forest litter according to the model calculations. However, these results depend on the parameters of the fire events. In general, the modeling results are in good accordance with the experimental data. Therefore, the considered models were successfully validated and can be recommended for the assessment of the resuspension and redistribution of radionuclides during grassland and forest fires in contaminated territories.

Numerical study of propagation of forest fires in the presence of fire breaks using an averaged setting

NASA Astrophysics Data System (ADS)

Marzaeva, S. I.; Galtseva, O. V.

2018-05-01

The forest fires spread in the pine forests have been numerically simulated using a three-dimensional mathematical model. The model was integrated with respect to the vertical coordinate because horizontal sizes of forest are much greater than the heights of trees. In this paper, the assignment and theoretical investigations of the problems of crown forest fires spread pass the firebreaks were carried out. In this context, a study ( mathematical modeling) of the conditions of forest fire spreading that would make it possible to obtain a detailed picture of the change in the temperature and component concentration fields with time, and determine as well as the limiting condition of fire propagation in forest with these fire breaks.

Selection of fire spread model for Russian fire behavior prediction system

Treesearch

Alexandra V. Volokitina; Kevin C. Ryan; Tatiana M. Sofronova; Mark A. Sofronov

2010-01-01

Mathematical modeling of fire behavior prediction is only possible if the models are supplied with an information database that provides spatially explicit input parameters for modeled area. Mathematical models can be of three kinds: 1) physical; 2) empirical; and 3) quasi-empirical (Sullivan, 2009). Physical models (Grishin, 1992) are of academic interest only because...

Fires, storms, and water supplies: a case of compound extremes?

NASA Astrophysics Data System (ADS)

Sheridan, G. J.; Nyman, P.; Langhans, C.; Jones, O.; Lane, P. N.

2013-12-01

Intense rainfall events following fire can wash sediment and ash into streams and reservoirs, contaminating water supplies for cities and towns. Post fire flooding and debris flows damage infrastructure and endanger life. These kinds of risks which are associated with a combination of two or more events (which may or may not be extreme when occurring independently) are an example of what the IPCC recently referred to as ';compound extremes'. Detailed models exist for modeling fire and erosion events separately, however there have been few attempts to integrate these models so as to estimate the water quality and infrastructure risks associated with combined fire and rainfall regimes. This presentation will articulate the issues associated with modeling the compound effects of fire and subsequent rainfall events on erosion, debris flows and water quality, and will describe and contrast several new approaches to modeling this problem developed and applied to SE Australian fire prone landscapes under the influence of climate change.

Calculation of precise firing statistics in a neural network model

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2017-08-01

A precise prediction of neural firing dynamics is requisite to understand the function of and the learning process in a biological neural network which works depending on exact spike timings. Basically, the prediction of firing statistics is a delicate manybody problem because the firing probability of a neuron at a time is determined by the summation over all effects from past firing states. A neural network model with the Feynman path integral formulation is recently introduced. In this paper, we present several methods to calculate firing statistics in the model. We apply the methods to some cases and compare the theoretical predictions with simulation results.

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fire dynamics during the 20th century simulated by the Community Land Model

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Thornton, P. E.; Hoffman, F. M.; Levis, S.; Lawrence, P. J.; Feddema, J. J.; Oleson, K. W.; Lawrence, D. M.

2010-01-01

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite based estimates in terms of magnitude, spatial extent as well as interannual and seasonal variability. Longterm trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtain substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997-2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000-2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we simulated a slight downward trend in global fire emissions, which is explained by reduced fuels as a consequence of wood harvesting and partly by increasing fire suppression. The model predicted an upward trend in the last three decades of the 20th century caused by climate variations and large burning events associated with ENSO induced drought conditions.

Fire dynamics during the 20th century simulated by the Community Land Model

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Thornton, P. E.; Hoffman, F. M.; Levis, S.; Lawrence, P. J.; Feddema, J. J.; Oleson, K. W.; Lawrence, D. M.

2010-06-01

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997-2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000-2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.

Normalized burn ratios link fire severity with patterns of avian occurrence

USGS Publications Warehouse

Rose, Eli T.; Simons, Theodore R.; Klein, Rob; McKerrow, Alexa

2016-01-01

ContextRemotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.ObjectivesWe evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.MethodsWe identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.ResultsAgreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.ConclusionsDNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

Historical, observed, and modeled wildfire severity in montane forests of the Colorado Front Range.

PubMed

Sherriff, Rosemary L; Platt, Rutherford V; Veblen, Thomas T; Schoennagel, Tania L; Gartner, Meredith H

2014-01-01

Large recent fires in the western U.S. have contributed to a perception that fire exclusion has caused an unprecedented occurrence of uncharacteristically severe fires, particularly in lower elevation dry pine forests. In the absence of long-term fire severity records, it is unknown how short-term trends compare to fire severity prior to 20th century fire exclusion. This study compares historical (i.e. pre-1920) fire severity with observed modern fire severity and modeled potential fire behavior across 564,413 ha of montane forests of the Colorado Front Range. We used forest structure and tree-ring fire history to characterize fire severity at 232 sites and then modeled historical fire-severity across the entire study area using biophysical variables. Eighteen (7.8%) sites were characterized by low-severity fires and 214 (92.2%) by mixed-severity fires (i.e. including moderate- or high-severity fires). Difference in area of historical versus observed low-severity fire within nine recent (post-1999) large fire perimeters was greatest in lower montane forests. Only 16% of the study area recorded a shift from historical low severity to a higher potential for crown fire today. An historical fire regime of more frequent and low-severity fires at low elevations (<2260 m) supports a convergence of management goals of ecological restoration and fire hazard mitigation in those habitats. In contrast, at higher elevations mixed-severity fires were predominant historically and continue to be so today. Thinning treatments at higher elevations of the montane zone will not return the fire regime to an historic low-severity regime, and are of questionable effectiveness in preventing severe wildfires. Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone. Recent large wildfires in the Front Range are not fundamentally different from similar events that occurred historically under extreme weather conditions.

Historical, Observed, and Modeled Wildfire Severity in Montane Forests of the Colorado Front Range

PubMed Central

Sherriff, Rosemary L.; Platt, Rutherford V.; Veblen, Thomas T.; Schoennagel, Tania L.; Gartner, Meredith H.

2014-01-01

Large recent fires in the western U.S. have contributed to a perception that fire exclusion has caused an unprecedented occurrence of uncharacteristically severe fires, particularly in lower elevation dry pine forests. In the absence of long-term fire severity records, it is unknown how short-term trends compare to fire severity prior to 20th century fire exclusion. This study compares historical (i.e. pre-1920) fire severity with observed modern fire severity and modeled potential fire behavior across 564,413 ha of montane forests of the Colorado Front Range. We used forest structure and tree-ring fire history to characterize fire severity at 232 sites and then modeled historical fire-severity across the entire study area using biophysical variables. Eighteen (7.8%) sites were characterized by low-severity fires and 214 (92.2%) by mixed-severity fires (i.e. including moderate- or high-severity fires). Difference in area of historical versus observed low-severity fire within nine recent (post-1999) large fire perimeters was greatest in lower montane forests. Only 16% of the study area recorded a shift from historical low severity to a higher potential for crown fire today. An historical fire regime of more frequent and low-severity fires at low elevations (<2260 m) supports a convergence of management goals of ecological restoration and fire hazard mitigation in those habitats. In contrast, at higher elevations mixed-severity fires were predominant historically and continue to be so today. Thinning treatments at higher elevations of the montane zone will not return the fire regime to an historic low-severity regime, and are of questionable effectiveness in preventing severe wildfires. Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone. Recent large wildfires in the Front Range are not fundamentally different from similar events that occurred historically under extreme weather conditions. PMID:25251103

Modeling the disturbance of vegetation by fire in the boreal forest

NASA Astrophysics Data System (ADS)

Crevoisier, C.; Shevliakova, E.; Gloor, M.; Wirth, C.

2006-12-01

Boreal regions are important for the global carbon cycle because it is the largest forested area on earth and there are large belowground carbon pools (~1000 PgC). It is also a region where largest warming trends on the globe over the last decades have been observed and changes of the land ecosystems have already started. A major factor that determines the structure and carbon dynamics of the boreal forest is fire. As fire frequency depends strongly on climate, increased fire occurrence and related losses to the atmosphere are likely, and have already been reported. In order to predict with more confidence the occurrence and effect of fire on forest ecosystems in the boreal region, we have developed a fire model that takes advantage of the large on-ground, remote sensing and climate data from Canada, Alaska and Siberia. This prognostic model estimates the monthly burned area in a grid cell of 2 by 2.5 degrees, from four climate (air temperature, air relative humidity, precipitation and soil water content) and one human-related (road density) variables. Parameters are estimated using a Markov Chain Monte Carlo method applied to a dataset of observed burned area for Canada. The model is able to reproduce the seasonality of fire, the interannual variability, as well as the location of fire events, not only for Canada (on which data the model is based), but also for Siberia and Alaska, for which the results compare well with remote sensing observation, and are in the range of various current estimations of burned area. The fire model is being implemented in LM3V, the new vegetation model of GFDL earth system model, in order to make prediction of future fire behavior in boreal regions, and the related disturbance of the vegetation and carbon emissions.

Climate Variability and Wildfires: Insights from Global Earth System Models

NASA Astrophysics Data System (ADS)

Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.

2016-12-01

Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in climate over long timescales.

A numerical solution of the problem of crown forest fire initiation and spread

NASA Astrophysics Data System (ADS)

Marzaeva, S. I.; Galtseva, O. V.

2018-05-01

Mathematical model of forest fire was based on an analysis of known experimental data and using concept and methods from reactive media mechanics. The study takes in to account the mutual interaction of the forest fires and three-dimensional atmosphere flows. The research is done by means of mathematical modeling of physical processes. It is based on numerical solution of Reynolds equations for chemical components and equations of energy conservation for gaseous and condensed phases. It is assumed that the forest during a forest fire can be modeled as a two-temperature multiphase non-deformable porous reactive medium. A discrete analog for the system of equations was obtained by means of the control volume method. The developed model of forest fire initiation and spreading would make it possible to obtain a detailed picture of the variation in the velocity, temperature and chemical species concentration fields with time. Mathematical model and the result of the calculation give an opportunity to evaluate critical conditions of the forest fire initiation and spread which allows applying the given model for of means for preventing fires.

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

Fiorucci, P.; Holmes, T.; Gaetani, F.; D'Andrea, M.

2009-04-01

Land cover change and forest fire interaction under climate and socio-economics changes, is one of the main issues of the 21th century. The capability of defining future scenarios of land cover and fire regime allow forest managers to better understand the best actions to be carried out and their long term effects. In this paper a new methodology for land cover change simulations under climate change and fire disturbance is presented and discussed. The methodology is based on the assumption that forest fires exhibits power law frequency-area distribution. The well known Forest Fire Model (FFM), which is an example of self organized criticality, is able to reproduce this behavior. Starting from this observation, a modified version of the FFM has been developed. The new model, called Modified Forest Fire Model (MFFM) introduces several new features. A stochastic model for vegetation growth and regrowth after fire occurrence has been implemented for different kind of vegetations. In addition, a stochastic fire propagation model taking into account topography and vegetation cover has been introduced. The MFFM has been developed with the purpose of estimating vegetation cover changes and fire regimes over a time windows of many years for a given spatial region. Two different case studies have been carried out. The first case study is related with Liguria (Italy), a region of 5400 km2 lying between the Cote d'Azur, France, and Tuscany, Italy, on the northwest coast of the Tyrrhenian Sea. This region is characterized by Mediterranean fire regime. The second case study has been carried out in California (Florida) on a region having similar area and characterized by similar climate conditions. In both cases the model well represents the actual fire regime in terms of power law parameters proving interesting results about future land cover scenarios under climate, land use and socio-economics change.

Empirical evidence for multi-scaled controls on wildfire size distributions in California

NASA Astrophysics Data System (ADS)

Povak, N.; Hessburg, P. F., Sr.; Salter, R. B.

2014-12-01

Ecological theory asserts that regional wildfire size distributions are examples of self-organized critical (SOC) systems. Controls on SOC event-size distributions by virtue are purely endogenous to the system and include the (1) frequency and pattern of ignitions, (2) distribution and size of prior fires, and (3) lagged successional patterns after fires. However, recent work has shown that the largest wildfires often result from extreme climatic events, and that patterns of vegetation and topography may help constrain local fire spread, calling into question the SOC model's simplicity. Using an atlas of >12,000 California wildfires (1950-2012) and maximum likelihood estimation (MLE), we fit four different power-law models and broken-stick regressions to fire-size distributions across 16 Bailey's ecoregions. Comparisons among empirical fire size distributions across ecoregions indicated that most ecoregion's fire-size distributions were significantly different, suggesting that broad-scale top-down controls differed among ecoregions. One-parameter power-law models consistently fit a middle range of fire sizes (~100 to 10000 ha) across most ecoregions, but did not fit to larger and smaller fire sizes. We fit the same four power-law models to patch size distributions of aspect, slope, and curvature topographies and found that the power-law models fit to a similar middle range of topography patch sizes. These results suggested that empirical evidence may exist for topographic controls on fire sizes. To test this, we used neutral landscape modeling techniques to determine if observed fire edges corresponded with aspect breaks more often than expected by random. We found significant differences between the empirical and neutral models for some ecoregions, particularly within the middle range of fire sizes. Our results, combined with other recent work, suggest that controls on ecoregional fire size distributions are multi-scaled and likely are not purely SOC. California wildfire ecosystems appear to be adaptive, governed by stationary and non-stationary controls, which may be either exogenous or endogenous to the system.

Modeling topographic influences on fuel moisture and fire danger in complex terrain to improve wildland fire management decision support

Treesearch

Zachary A. Holden; W. Matt Jolly

2011-01-01

Fire danger rating systems commonly ignore fine scale, topographically-induced weather variations. These variations will likely create heterogeneous, landscape-scale fire danger conditions that have never been examined in detail. We modeled the evolution of fuel moistures and the Energy Release Component (ERC) from the US National Fire Danger Rating System across the...

Combining turbulent kinetic energy and Haines Index predictions for fire-weather assessments

Treesearch

Warren E. Heilman; Xindi Bian

2007-01-01

The 24- to 72-hour fire-weather predictions for different regions of the United States are now readily available from the regional Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS) that were established as part of the U.S. National Fire Plan. These predictions are based on daily real-time MM5 model simulations of atmospheric conditions and fire-...

Understanding effects of fire suppression, fuels treatment, and wildfire on bird communities in the Klamath-Siskiyou ecoregion

Treesearch

John D. Alexander; C. John Ralph; Bill Hogoboom; Nathaniel E. Seavy; Stewart Janes

2004-01-01

Although fire management is increasingly recognized as an important component of conservation in Klamath-Siskiyou ecosystems, empirical evidence on the ecological effects of fire in this region is limited. Here we describe a conceptual model as a framework for understanding the effects of fire and fire management on bird abundance. This model identifies three major...

Simulating fire regimes in the Amazon in response to climate change and deforestation.

PubMed

Silvestrini, Rafaella Almeida; Soares-Filho, Britaldo Silveira; Nepstad, Daniel; Coe, Michael; Rodrigues, Hermann; Assunção, Renato

2011-07-01

Fires in tropical forests release globally significant amounts of carbon to the atmosphere and may increase in importance as a result of climate change. Despite the striking impacts of fire on tropical ecosystems, the paucity of robust spatial models of forest fire still hampers our ability to simulate tropical forest fire regimes today and in the future. Here we present a probabilistic model of human-induced fire occurrence for the Amazon that integrates the effects of a series of anthropogenic factors with climatic conditions described by vapor pressure deficit. The model was calibrated using NOAA-12 night satellite hot pixels for 2003 and validated for the years 2002, 2004, and 2005. Assessment of the fire risk map yielded fitness values > 85% for all months from 2002 to 2005. Simulated fires exhibited high overlap with NOAA-12 hot pixels regarding both spatial and temporal distributions, showing a spatial fit of 50% within a radius of 11 km and a maximum yearly frequency deviation of 15%. We applied this model to simulate fire regimes in the Amazon until 2050 using IPCC's A2 scenario climate data from the Hadley Centre model and a business-as-usual (BAU) scenario of deforestation and road expansion from SimAmazonia. Results show that the combination of these scenarios may double forest fire occurrence outside protected areas (PAs) in years of extreme drought, expanding the risk of fire even to the northwestern Amazon by midcentury. In particular, forest fires may increase substantially across southern and southwestern Amazon, especially along the highways slated for paving and in agricultural zones. Committed emissions from Amazon forest fires and deforestation under a scenario of global warming and uncurbed deforestation may amount to 21 +/- 4 Pg of carbon by 2050. BAU deforestation may increase fires occurrence outside PAs by 19% over the next four decades, while climate change alone may account for a 12% increase. In turn, the combination of climate change and deforestation would boost fire occurrence outside PAs by half during this period. Our modeling results, therefore, confirm the synergy between the two Ds of REDD (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries).

Joint modeling of human dwellings and the natural ecosystem at the wildland-urban interface helps mitigation of forest-fire risk

NASA Astrophysics Data System (ADS)

Ghil, M.; Spyratos, V.; Bourgeron, P. S.

2007-12-01

The late summer of 2007 has seen again a large number of catastrophic forest fires in the Western United States and Southern Europe. These fires arose in or spread to human habitats at the so-called wildland-urban interface (WUI). Within the conterminous United States alone, the WUI occupies just under 10 percent of the surface and contains almost 40 percent of all housing units. Recent dry spells associated with climate variability and climate change make the impact of such catastrophic fires a matter of urgency for decision makers, scientists and the general public. In order to explore the qualitative influence of the presence of houses on fire spread, we considered only uniform landscapes and fire spread as a simple percolation process, with given house densities d and vegetation flammabilities p. Wind, topography, fuel heterogeneities, firebrands and weather affect actual fire spread. The present theoretical results would therefore, need to be integrated into more detailed fire models before practical, quantitative applications of the present results. Our simple fire-spread model, along with housing and vegetation data, shows that fire-size probability distributions can be strongly modified by the density d and flammability of houses. We highlight a sharp transition zone in the parameter space of vegetation flammability p and house density d. The sharpness of this transition is related to the critical thresholds that arise in percolation theory for an infinite domain; it is their translation into our model's finite-area domain, which is a more realistic representation of actual fire landscapes. Many actual fire landscapes in the United States appear to have spreading properties close to this transition zone. Hence, and despite having neglected additional complexities, our idealized model's results indicate that more detailed models used for assessing fire risk in the WUI should integrate the density and flammability of houses in these areas. Furthermore, our results imply that fire proofing houses and their immediate surroundings within the WUI would not only reduce the houses' flammability and increase the security of the inhabitants, but also reduce fire risk for the entire landscape.

Characterization of potential fire regimes: applying landscape ecology to fire management in Mexico

NASA Astrophysics Data System (ADS)

Jardel, E.; Alvarado, E.; Perez-Salicrup, D.; Morfín-Rios, J.

2013-05-01

Knowledge and understanding of fire regimes is fundamental to design sound fire management practices. The high ecosystem diversity of Mexico offers a great challenge to characterize the fire regime variation at the landscape level. A conceptual model was developed considering the main factors controlling fire regimes: climate and vegetation cover. We classified landscape units combining bioclimatic zones from the Holdridge life-zone system and actual vegetation cover. Since bioclimatic conditions control primary productivity and biomass accumulation (potential fuel), each landscape unit was considered as a fuel bed with a particular fire intensity and behavior potential. Climate is also a determinant factor of post-fire recovery rates of fuel beds, and climate seasonality (length of the dry and wet seasons) influences fire probability (available fuel and ignition efficiency). These two factors influence potential fire frequency. Potential fire severity can be inferred from fire frequency, fire intensity and behavior, and vegetation composition and structure. Based in the conceptual model, an exhaustive literature review and expert opinion, we developed rules to assign a potential fire regime (PFR) defined by frequency, intensity and severity (i.e. fire regime) to each bioclimatic-vegetation landscape unit. Three groups and eight types of potential fire regimes were identified. In Group A are fire-prone ecosystems with frequent low severity surface fires in grasslands (PFR type I) or forests with long dry season (II) and infrequent high-severity fires in chaparral (III), wet temperate forests (IV, fire restricted by humidity), and dry temperate forests (V, fire restricted by fuel recovery rate). Group B includes fire-reluctant ecosystems with very infrequent or occasional mixed severity surface fires limited by moisture in tropical rain forests (VI) or fuel availability in seasonally dry tropical forests (VII). Group C and PFR VIII include fire-free environments that correspond to deserts. Application of PFR model to fire management is discussed.

[Prediction model of human-caused fire occurrence in the boreal forest of northern China].

PubMed

Guo, Fu-tao; Su, Zhang-wen; Wang, Guang-yu; Wang, Qiang; Sun, Long; Yang, Ting-ting

2015-07-01

The Chinese boreal forest is an important forest resource in China. However, it has been suffering serious disturbances of forest fires, which were caused equally by natural disasters (e.g., lightning) and human activities. The literature on human-caused fires indicates that climate, topography, vegetation, and human infrastructure are significant factors that impact the occurrence and spread of human-caused fires. But the studies on human-caused fires in the boreal forest of northern China are limited and less comprehensive. This paper applied the spatial analysis tools in ArcGIS 10.0 and Logistic regression model to investigate the driving factors of human-caused fires. Our data included the geographic coordinates of human-caused fires, climate factors during year 1974-2009, topographic information, and forest map. The results indicated that distance to railway (x1) and average relative humidity (x2) significantly impacted the occurrence of human-caused fire in the study area. The logistic model for predicting the fire occurrence probability was formulated as P= 1/[11+e-(3.026-0.00011x1-0.047x2)] with an accuracy rate of 80%. The above model was used to predict the monthly fire occurrence during the fire season of 2015 based on the HADCM2 future weather data. The prediction results showed that the high risk of human-caused fire occurrence concentrated in the months of April, May, June and August, while April and May had higher risk of fire occurrence than other months. According to the spatial distribution of possibility of fire occurrence, the high fire risk zones were mainly in the west and southwest of Tahe, where the major railways were located.

Measuring behaviours for escaping from house fires: use of latent variable models to summarise multiple behaviours.

PubMed

Ploubidis, G B; Edwards, P; Kendrick, D

2015-12-15

This paper reports the development and testing of a construct measuring parental fire safety behaviours for planning escape from a house fire. Latent variable modelling of data on parental-reported fire safety behaviours and plans for escaping from a house fire and multivariable logistic regression to quantify the association between groups defined by the latent variable modelling and parental-report of having a plan for escaping from a house fire. Data comes from 1112 participants in a cluster randomised controlled trial set in children's centres in 4 study centres in the UK. A two class model provided the best fit to the data, combining responses to five fire safety planning behaviours. The first group ('more behaviours for escaping from a house fire') comprised 86% of participants who were most likely to have a torch, be aware of how their smoke alarm sounds, to have external door and window keys accessible, and exits clear. The second group ('fewer behaviours for escaping from a house fire') comprised 14% of participants who were less likely to report these five behaviours. After adjusting for potential confounders, participants allocated to the 'more behaviours for escaping from a house fire group were 2.5 times more likely to report having an escape plan (OR 2.48; 95% CI 1.59-3.86) than those in the "fewer behaviours for escaping from a house fire" group. Multiple fire safety behaviour questions can be combined into a single binary summary measure of fire safety behaviours for escaping from a house fire. Our findings will be useful to future studies wishing to use a single measure of fire safety planning behaviour as measures of outcome or exposure. NCT 01452191. Date of registration 13/10/2011.

Comparison of Interglacial fire dynamics in Southern Africa

NASA Astrophysics Data System (ADS)

Brücher, Tim; Daniau, Anne-Laure

2016-04-01

Responses of fire activity to a change in climate are still uncertain and biases exist by integrating this non-linear process into global modeling of the Earth system. Warming and regional drying can force fire activity in two opposite directions: an increase in fire in fuel supported ecosystems or a fire reduction in fuel-limited ecosystems. Therefore, climate variables alone can not be used to estimate the fire risk because vegetation variability is an important determinant of fire dynamics and responds itself to change in climate. Southern Africa (south of 20°S) paleofire history reconstruction obtained from the analysis of microcharcoal preserved in a deep-sea core located off Namibia reveals changes of fire activity on orbital timescales in the precession band. In particular, increase in fire is observed during glacial periods, and reduction of fire during interglacials such as the Eemian and the Holocene. The Holocene was characterized by even lower level of fire activity than Eemian. Those results suggest the alternance of grass-fueled fires during glacials driven by increase in moisture and the development of limited fueled ecosystems during interglacials characterized by dryness. Those results question the simulated increase in the fire risk probability projected for this region under a warming and drying climate obtained by Pechony and Schindell (2010). To explore the validity of the hypotheses we conducted a data-model comparison for both interglacials from 126.000 to 115.000 BP for the Eemian and from 8.000 to 2.000 BP for the Holocene. Data out of a transient, global modeling study with a Vegetation-Fire model of full complexity (JSBACH) is used, driven by a Climate model of intermediate complexity (CLIMBER). Climate data like precipitation and temperature as well as vegetation data like soil moisture, productivity (NPP) on plant functional type level are used to explain trends in fire activity. The comparison of trends in fire activity during the Eemian (126.000 to 120.000 BP) and the Holocene (8.000 to 200 BP) shows an increase in fire data and in simulated fire. Lower level of fire during the Holocene than Eemian can be explained by differences due to unequal trends in vegetation as a result of climate forcing due to orbital changes: while woody type vegetation plays a major role during the Eemian, the Holocene is influenced by grass land. From the modelling perspective changes in the seasonal precipitation drives the vegetation pattern.

Strengthening community participation in reducing GHG emission from forest and peatland fire

NASA Astrophysics Data System (ADS)

Thoha, A. S.; Saharjo, B. H.; Boer, R.; Ardiansyah, M.

2018-02-01

Strengthening community participation is needed to find solutions to encourage community more participate in reducing Green House Gas (GHG) from forest and peatland fire. This research aimed to identify stakeholders that have the role in forest and peatland fire control and to formulate strengthening model of community participation through community-based early warning fire. Stakeholder mapping and action research were used to determine stakeholders that had potential influence and interest and to formulate strengthening model of community participation in reducing GHG from forest and peatland fire. There was found that position of key players in the mapping of stakeholders came from the government institution. The existence of community-based fire control group can strengthen government institution through collaborating with stakeholders having strong interest and influence. Moreover, it was found several local knowledge in Kapuas District about how communities predict drought that have potential value for developing the community-based early warning fire system. Formulated institutional model in this research also can be further developed as a model institution in the preservation of natural resources based on local knowledge. In conclusion, local knowledge and community-based fire groups can be integrated within strengthening model of community participation in reducing GHG from forest and peatland fire.

Avian response to fire in pine–oak forests of Great Smoky Mountains National Park following decades of fire suppression

USGS Publications Warehouse

Rose, Eli T.; Simons, Theodore R.

2016-01-01

Fire suppression in southern Appalachian pine–oak forests during the past century dramatically altered the bird community. Fire return intervals decreased, resulting in local extirpation or population declines of many bird species adapted to post-fire plant communities. Within Great Smoky Mountains National Park, declines have been strongest for birds inhabiting xeric pine–oak forests that depend on frequent fire. The buildup of fuels after decades of fire suppression led to changes in the 1996 Great Smoky Mountains Fire Management Plan. Although fire return intervals remain well below historic levels, management changes have helped increase the amount of fire within the park over the past 20 years, providing an opportunity to study patterns of fire severity, time since burn, and bird occurrence. We combined avian point counts in burned and unburned areas with remote sensing indices of fire severity to infer temporal changes in bird occurrence for up to 28 years following fire. Using hierarchical linear models that account for the possibility of a species presence at a site when no individuals are detected, we developed occurrence models for 24 species: 13 occurred more frequently in burned areas, 2 occurred less frequently, and 9 showed no significant difference between burned and unburned areas. Within burned areas, the top models for each species included fire severity, time since burn, or both, suggesting that fire influenced patterns of species occurrence for all 24 species. Our findings suggest that no single fire management strategy will suit all species. To capture peak occupancy for the entire bird community within xeric pine–oak forests, at least 3 fire regimes may be necessary; one applying frequent low severity fire, another using infrequent low severity fire, and a third using infrequently applied high severity fire.

Southwestern Oregon's Biscuit Fire: An Analysis of Forest Resources, Fire Severity, and Fire Hazard

Treesearch

David L. Azuma; Glenn A. Christensen

2005-01-01

This study compares pre-fire field inventory data (collected from 1993 to 1997) in relation to post-fire mapped fire severity classes and the Fire and Fuels Extension of the Forest Vegetation Simulator growth and yield model measures of fire hazard for the portion of the Siskiyou National Forest in the 2002 Biscuit fire perimeter of southwestern Oregon. Post-fire...

Bifurcations of large networks of two-dimensional integrate and fire neurons.

PubMed

Nicola, Wilten; Campbell, Sue Ann

2013-08-01

Recently, a class of two-dimensional integrate and fire models has been used to faithfully model spiking neurons. This class includes the Izhikevich model, the adaptive exponential integrate and fire model, and the quartic integrate and fire model. The bifurcation types for the individual neurons have been thoroughly analyzed by Touboul (SIAM J Appl Math 68(4):1045-1079, 2008). However, when the models are coupled together to form networks, the networks can display bifurcations that an uncoupled oscillator cannot. For example, the networks can transition from firing with a constant rate to burst firing. This paper introduces a technique to reduce a full network of this class of neurons to a mean field model, in the form of a system of switching ordinary differential equations. The reduction uses population density methods and a quasi-steady state approximation to arrive at the mean field system. Reduced models are derived for networks with different topologies and different model neurons with biologically derived parameters. The mean field equations are able to qualitatively and quantitatively describe the bifurcations that the full networks display. Extensions and higher order approximations are discussed.

Evaluating the coupled vegetation-fire model, LPJ-GUESS-SPITFIRE, against observed tropical forest biomass

NASA Astrophysics Data System (ADS)

Spessa, Allan; Forrest, Matthew; Werner, Christian; Steinkamp, Joerg; Hickler, Thomas

2013-04-01

Wildfire is a fundamental Earth System process. It is the most important disturbance worldwide in terms of area and variety of biomes affected; a major mechanism by which carbon is transferred from the land to the atmosphere (2-4 Pg per annum, equiv. 20-30% of global fossil fuel emissions over the last decade); and globally a significant source of particulate aerosols and trace greenhouse gases. Fire is also potentially important as a feedback in the climate system. If climate change favours more intense fire regimes, this would result in a net transfer of carbon from ecosystems to the atmosphere, as well as higher emissions, and under certain circumstances, increased troposphere ozone production- all contributing to positive climate-land surface feedbacks. Quantitative analysis of fire-vegetation-climate interactions has been held back until recently by a lack of consistent global data sets on fire, and by the underdeveloped state of dynamic vegetation-fire modelling. Dynamic vegetation-fire modelling is an essential part of our forecasting armory for examining the possible impacts of climate, fire regimes and land-use on ecosystems and emissions from biomass burning beyond the observation period, as part of future climate or paleo-climate studies. LPJ-GUESS is a process-based model of vegetation dynamics designed for regional to global applications. It combines features of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) with those of the General Ecosystem Simulator (GUESS) in a single, flexible modelling framework. The models have identical representations of eco-physiological and biogeochemical processes, including the hydrological cycle. However, they differ in the detail with which vegetation dynamics and canopy structure are simulated. Simplified, computationally efficient representations are used in the LPJ-DGVM, while LPJ-GUESS employs a gap-model approach, which better captures ecological succession and hence ecosystem changes due to disturbance such as fire. SPITFIRE (SPread and InTensity of FIRe and Emissions) mechanistically simulates the number of fires, area burnt, fire intensity, crown fires, fire-induced plant mortality, and emissions of carbon, trace gases and aerosols from biomass burning. Originally developed as an embedded model within LPJ-DGVM, SPITFIRE has since been coupled to LPJ-GUESS. However, neither LPJ-DGVM-SPITFIRE nor LPJ-GUESS-SPITFIRE has been fully benchmarked, especially in terms of how well each model simulates vegetation patterns and biomass in areas where fire is known to be important. This information is crucial if we are to have confidence in the models in forecasting fire, emissions from biomass burning and fire-climate impacts on ecosystems. Here we report on the benchmarking of the LPJ-GUESS-SPITFIRE model. We benchmarked LPJ-GUESS-SPITFIRE driven by a combination of daily reanalysis climate data (Sheffield 2012), monthly GFEDv3 burnt area data (1997-2009) (van der Werf et al. 2010) and long-term annual fire statistics (1901 to 2000) (Mouillot and Field 2005) against new Lidar-based biomass data for tropical forests and savannas (Saatchi et al. 2011; Baccini et al., 2012). Our new work has focused on revising the way GUESS simulates tree allometry, light penetration through the tree canopy and sapling recruitment, and how GUESS-SPITFIRE simulates fire-induced mortality, all based on recent literature, as well as a more explicit accounting of land cover change (JRC's GLC 2009). We present how these combined changes result in a much improved simulation of tree carbon across the tropics, including the Americas, Africa, Asia and Australia. Our results are compared with respect to more empirical-based approaches to calculating emissions from biomass burning. We discuss our findings in terms of improved forecasting of fire, emissions from biomass burning and fire-climate impacts on ecosystems.

Using the Large Fire Simulator System to map wildland fire potential for the conterminous United States

Treesearch

LaWen Hollingsworth; James Menakis

2010-01-01

This project mapped wildland fire potential (WFP) for the conterminous United States by using the large fire simulation system developed for Fire Program Analysis (FPA) System. The large fire simulation system, referred to here as LFSim, consists of modules for weather generation, fire occurrence, fire suppression, and fire growth modeling. Weather was generated with...

Big data integration shows Australian bush-fire frequency is increasing significantly.

PubMed

Dutta, Ritaban; Das, Aruneema; Aryal, Jagannath

2016-02-01

Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift.

Big data integration shows Australian bush-fire frequency is increasing significantly

PubMed Central

Dutta, Ritaban; Das, Aruneema; Aryal, Jagannath

2016-01-01

Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift. PMID:26998312

Model of large pool fires.

PubMed

Fay, J A

2006-08-21

A two zone entrainment model of pool fires is proposed to depict the fluid flow and flame properties of the fire. Consisting of combustion and plume zones, it provides a consistent scheme for developing non-dimensional scaling parameters for correlating and extrapolating pool fire visible flame length, flame tilt, surface emissive power, and fuel evaporation rate. The model is extended to include grey gas thermal radiation from soot particles in the flame zone, accounting for emission and absorption in both optically thin and thick regions. A model of convective heat transfer from the combustion zone to the liquid fuel pool, and from a water substrate to cryogenic fuel pools spreading on water, provides evaporation rates for both adiabatic and non-adiabatic fires. The model is tested against field measurements of large scale pool fires, principally of LNG, and is generally in agreement with experimental values of all variables.

Rapid response tools and datasets for post-fire modeling: Linking Earth Observations and process-based hydrological models to support post-fire remediation

Treesearch

M. E. Miller; M. Billmire; W. J. Elliot; K. A. Endsley; P. R. Robichaud

2015-01-01

Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation...

Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels

Treesearch

David R. Weise; Eunmo Koo; Xiangyang Zhou; Shankar Mahalingam; Frédéric Morandini; Jacques-Henri Balbi

2016-01-01

Fire behaviour data from 240 laboratory fires in high-density live chaparral fuel beds were compared with model predictions. Logistic regression was used to develop a model to predict fire spread success in the fuel beds and linear regression was used to predict rate of spread. Predictions from the Rothermel equation and three proposed changes as well as two physically...

Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

USGS Publications Warehouse

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquin; Gutierrez, Jose M.; San Miguel-Ayanz, Jesus; Camia, Andrea; Keeley, Jon E.; Moreno, Jose M.

2015-01-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Forest fire effects on transpiration: process modeling of sapwood area reduction

NASA Astrophysics Data System (ADS)

Michaletz, Sean; Johnson, Edward

2010-05-01

Transpiration is a hydrological process that is strongly affected by forest fires. In crown fires, canopy fine fuels (foliage, buds, and small branches) combust, which kills individual trees and stops transpiration of the entire stand. In surface fires (intensities ≤ 2500 kW m-1), however, effects on transpiration are less predictable becuase heat transfer from the passing fireline can injure or kill fine roots, leaves, and sapwood; post-fire transpiration of forest stands is thus governed by fire effects on individual tree water budgets. Here, we consider fire effects on cross-sectional sapwood area. A two-dimensional model of transient bole heating is used to estimate radial isotherms for a range of fireline intensities typical of surface fires. Isotherms are then used to drive three processes by which heat may reduce sapwood area: 1) necrosis of living cells in contact with xylem conduits, which prevents repair of natural embolism; 2) relaxation of viscoelastic conduit wall polymers (cellulose, hemicelloluse, and lignin), which reduces cross-sectional conduit area; and 3) boiling of metastable water under tension, which causes conduit embolism. Results show that these processes operate on different time scales, suggesting that fire effects on transpiration vary with time since fire. The model can be linked with a three-dimensional physical fire spread model to predict size-dependent effects on individual trees, which can be used to estimate scaling of individual tree and stand-level transpiration.

Event-driven simulations of nonlinear integrate-and-fire neurons.

PubMed

Tonnelier, Arnaud; Belmabrouk, Hana; Martinez, Dominique

2007-12-01

Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.

Assessing the value of increased model resolution in forecasting fire danger

Treesearch

Jeanne Hoadley; Miriam Rorig; Ken Westrick; Larry Bradshaw; Sue Ferguson; Scott Goodrick; Paul Werth

2003-01-01

The fire season of 2000 was used as a case study to assess the value of increasing mesoscale model resolution for fire weather and fire danger forecasting. With a domain centered on Western Montana and Northern Idaho, MM5 simulations were run at 36, 12, and 4-km resolutions for a 30 day period at the height of the fire season. Verification analyses for meteorological...

Comparing fire severity models from post-fire and pre/post-fire differenced imagery

USDA-ARS?s Scientific Manuscript database

Wildland fires are common in rangelands worldwide. The potential for high severity fires to affect long-term changes in rangelands is considerable, and for this reason assessing fire severity shortly after the fire is critical. Such assessments are typically carried out following Burned Area Emergen...

Human and biophysical influences on fire occurrence in the United States

USGS Publications Warehouse

Hawbaker, Todd J.; Radeloff, Volker C.; Stewart, Susan I.; Hammer, Roger B.; Keuler, Nicholas S.; Clayton, Murray K.

2013-01-01

National-scale analyses of fire occurrence are needed to prioritize fire policy and management activities across the United States. However, the drivers of national-scale patterns of fire occurrence are not well understood, and how the relative importance of human or biophysical factors varies across the country is unclear. Our research goal was to model the drivers of fire occurrence within ecoregions across the conterminous United States. We used generalized linear models to compare the relative influence of human, vegetation, climate, and topographic variables on fire occurrence in the United States, as measured by MODIS active fire detections collected between 2000 and 2006. We constructed models for all fires and for large fires only and generated predictive maps to quantify fire occurrence probabilities. Areas with high fire occurrence probabilities were widespread in the Southeast, and localized in the Mountain West, particularly in southern California, Arizona, and New Mexico. Probabilities for large-fire occurrence were generally lower, but hot spots existed in the western and south-central United States The probability of fire occurrence is a critical component of fire risk assessments, in addition to vegetation type, fire behavior, and the values at risk. Many of the hot spots we identified have extensive development in the wildland–urban interface and are near large metropolitan areas. Our results demonstrated that human variables were important predictors of both all fires and large fires and frequently exhibited nonlinear relationships. However, vegetation, climate, and topography were also significant variables in most ecoregions. If recent housing growth trends and fire occurrence patterns continue, these areas will continue to challenge policies and management efforts seeking to balance the risks generated by wildfires with the ecological benefits of fire.

Color model and method for video fire flame and smoke detection using Fisher linear discriminant

NASA Astrophysics Data System (ADS)

Wei, Yuan; Jie, Li; Jun, Fang; Yongming, Zhang

2013-02-01

Video fire detection is playing an increasingly important role in our life. But recent research is often based on a traditional RGB color model used to analyze the flame, which may be not the optimal color space for fire recognition. It is worse when we research smoke simply using gray images instead of color ones. We clarify the importance of color information for fire detection. We present a fire discriminant color (FDC) model for flame or smoke recognition based on color images. The FDC models aim to unify fire color image representation and fire recognition task into one framework. With the definition of between-class scatter matrices and within-class scatter matrices of Fisher linear discriminant, the proposed models seek to obtain one color-space-transform matrix and a discriminate projection basis vector by maximizing the ratio of these two scatter matrices. First, an iterative basic algorithm is designed to get one-component color space transformed from RGB. Then, a general algorithm is extended to generate three-component color space for further improvement. Moreover, we propose a method for video fire detection based on the models using the kNN classifier. To evaluate the recognition performance, we create a database including flame, smoke, and nonfire images for training and testing. The test experiments show that the proposed model achieves a flame verification rate receiver operating characteristic (ROC I) of 97.5% at a false alarm rate (FAR) of 1.06% and a smoke verification rate (ROC II) of 91.5% at a FAR of 1.2%, and lots of fire video experiments demonstrate that our method reaches a high accuracy for fire recognition.

Fire in the Brazilian Amazon: A Spatially Explicit Model for Policy Impact Analysis

NASA Technical Reports Server (NTRS)

Arima, Eugenio Y.; Simmons, Cynthia S.; Walker, Robert T.; Cochrane, Mark A.

2007-01-01

This article implements a spatially explicit model to estimate the probability of forest and agricultural fires in the Brazilian Amazon. We innovate by using variables that reflect farmgate prices of beef and soy, and also provide a conceptual model of managed and unmanaged fires in order to simulate the impact of road paving, cattle exports, and conservation area designation on the occurrence of fire. Our analysis shows that fire is positively correlated with the price of beef and soy, and that the creation of new conservation units may offset the negative environmental impacts caused by the increasing number of fire events associated with early stages of frontier development.

Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

2009-12-01

The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

Simulations of Forest Fires by the Cellular Automata Model "ABBAMPAU"

NASA Astrophysics Data System (ADS)

di Gregorio, S.; Bendicenti, E.

2003-04-01

Forest fires represent a serious environmental problem, whose negative impact is becoming day by day more worrisome. Forest fires are very complex phenomena; that need an interdisciplinary approach. The adopted method to modelling involves the definition of local rules, from which the global behaviour of the system can emerge. The paradigm of Cellular Automata was applied and the model ABBAMPAU was projected to simulate the evolution of forest fires. Cellular Automata features (parallelism and a-centrism) seem to match the system "forest fire"; the parameters, describing globally a forest fire, i.e. propagation rate, flame length and direction, fireline intensity, fire duration time et c. are mainly depending on some local characteristics i.e. vegetation type (live and dead fuel), relative humidity, fuel moisture, heat, territory morphology (altitude, slope), et c.. The only global characteristic is given by wind velocity and direction, but wind velocity and direction is locally altered according to the morphology; therefore wind has also to be considered at local level. ABBAMPAU accounts for the following aspects of the phenomenon: effects of combustion in surface and crown fire inside the cell, crown fire triggering off; surface and crown fire spread, determination of the local wind rate and direction. A validation of ABBAMPAU was tested on a real case of forest fire, in the territory of Villaputzu, Sardinia island, August 22nd, 1998. First simulations account for the main characteristics of the phenomenon and agree with the observations. The results show that the model could be applied for the forest fire preventions, the productions of risk scenarios and the evaluation of the forest fire environmental impact.

Simulating wildfire spread behavior between two NASA Active Fire data timeframes

NASA Astrophysics Data System (ADS)

Adhikari, B.; Hodza, P.; Xu, C.; Minckley, T. A.

2017-12-01

Although NASA's Active Fire dataset is considered valuable in mapping the spatial distribution and extent of wildfires across the world, the data is only available at approximately 12-hour time intervals, creating uncertainties and risks associated with fire spread and behavior between the two Visible Infrared Imaging Radiometer Satellite (VIIRS) data collection timeframes. Our study seeks to close the information gap for the United States by using the latest Active Fire data collected for instance around 0130 hours as an ignition source and critical inputs to a wildfire model by uniquely incorporating forecasted and real-time weather conditions for predicting fire perimeter at the next 12 hour reporting time (i.e. around 1330 hours). The model ingests highly dynamic variables such as fuel moisture, temperature, relative humidity, wind among others, and prompts a Monte Carlo simulation exercise that uses a varying range of possible values for evaluating all possible wildfire behaviors. The Monte Carlo simulation implemented in this model provides a measure of the relative wildfire risk levels at various locations based on the number of times those sites are intersected by simulated fire perimeters. Model calibration is achieved using data at next reporting time (i.e. after 12 hours) to enhance the predictive quality at further time steps. While initial results indicate that the calibrated model can predict the overall geometry and direction of wildland fire spread, the model seems to over-predict the sizes of most fire perimeters possibly due to unaccounted fire suppression activities. Nonetheless, the results of this study show great promise in aiding wildland fire tracking, fighting and risk management.

Assessing the risk of ignition in the Russian far east within a modeling framework of fire threat.

PubMed

Loboda, Tatiana V; Csiszar, Ivan A

2007-04-01

The forests of high biological importance in the Russian Far East (RFE) have been experiencing increasing pressure from growing demands for natural resources under the changing economy of post-Soviet Russia. This pressure is further amplified by the rising threat of large and catastrophic fire occurrence, which threatens both the resources and the economic potential of the region. In this paper we introduce a conceptual Fire Threat Model (FTM) and use it to provide quantitative assessment of the risk of ignition in the Russian Far East. The remotely sensed data driven FTM is aimed at evaluating potential wildland fire occurrence and its impact and recovery potential for a given resource. This model is intended for use by resource managers to assist in assessing current levels of fire threat to a given resource, projecting the changes in fire threat under changing climate and land use, and evaluating the efficiency of various management approaches aimed at minimizing the fire impact. Risk of ignition (one of the major uncertainties within fire threat modeling) was analyzed using the MODIS active fire product. The risk of ignition in the RFE is shown to be highly variable in spatial and temporal domains. However, the number of ignition points is not directly proportional to the amount of fire occurrence in the area. Fire ignitions in the RFE are strongly linked to anthropogenic activity (transportation routes, settlements, and land use). An increase in the number of fire ignitions during summer months could be attributed to (1) disruption of the summer monsoons and subsequent changes in fire weather and (2) an increase in natural sources of fire ignitions.

Self-organization, the cascade model, and natural hazards.

PubMed

Turcotte, Donald L; Malamud, Bruce D; Guzzetti, Fausto; Reichenbach, Paola

2002-02-19

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions.

Self-organization, the cascade model, and natural hazards

PubMed Central

Turcotte, Donald L.; Malamud, Bruce D.; Guzzetti, Fausto; Reichenbach, Paola

2002-01-01

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions. PMID:11875206

EVALUATION OF UTILITY BOILER RADIANT FURNACE RESIDENCE TIME/TEMPERATURE CHARACTERISTICS: FIELD TESTS AND HEAT TRANSFER MODELING

EPA Science Inventory

The report describes an investigation of the adequacy of a modeling approach in predicting the thermal environment and flow field of pulverized-coal-fired utility boilers. Two 420 MWe coal-fired boilers were evaluated: a single-wall-fired unit and a tangentially fired unit, repre...

On the need for a theory of wildland fire spread

Treesearch

Mark A. Finney; Jack D. Cohen; Sara S. McAllister; W. Matt Jolly

2012-01-01

We explore the basis of understanding wildland fire behaviour with the intention of stimulating curiosity and promoting fundamental investigations of fire spread problems that persist even in the presence of tremendous modelling advances. Internationally, many fire models have been developed based on a variety of assumptions and expressions for the fundamental heat...

Retrospective fire modeling: Quantifying the impacts of fire suppression

Treesearch

Brett H. Davis; Carol Miller; Sean A. Parks

2010-01-01

Land management agencies need to understand and monitor the consequences of their fire suppression decisions. We developed a framework for retrospective fire behavior modeling and impact assessment to determine where ignitions would have spread had they not been suppressed and to assess the cumulative effects that would have resulted. This document is a general...

Spatially explicit modeling of mixed-severity fire regimes and landscape dynamics

Treesearch

Michael C. Wimberly; Rebecca S.H. Kennedy

2008-01-01

Simulation models of disturbance and succession are being increasingly applied to characterize landscape composition and dynamics under natural fire regimes, and to evaluate alternative management strategies for ecological restoration and fire hazard reduction. However, we have a limited understanding of how landscapes respond to changes in fire frequency, and about...

Fire Modeling Institute 2011 Annual Report

Treesearch

Robin J. Innes

2012-01-01

The Fire Modeling Institute (FMI), a part of the Rocky Mountain Research Station, Fire, Fuel, and Smoke Science Program, provides a bridge between scientists and managers. The mission of FMI is to bring the best available science and technology developed throughout the research community to bear on fire-related management issues across the nation. Resource management...

Reformulation of Rothermel's wildland fire behaviour model for heterogeneous fuelbeds.

Treesearch

David V. Sandberg; Cynthia L. Riccardi; Mark D. Schaaf

2007-01-01

Abstract: The Fuel Characteristic Classification System (FCCS) includes equations that calculate energy release and one-dimensional spread rate in quasi-steady-state fires in heterogeneous but spatially uniform wildland fuelbeds, using a reformulation of the widely used Rothermel fire spread model. This reformulation provides an automated means to predict fire behavior...

Impacts of prescribed fires on air quality over the Southeastern United States in spring based on modeling and ground/satellite measurements.

PubMed

Zeng, Tao; Wang, Yuhang; Yoshida, Yasuko; Tian, Di; Russell, Amistead G; Barnard, William R

2008-11-15

Prescribed burning is a large aerosol source in the southeastern United States. Its air quality impact is investigated using 3-D model simulations and analysis of ground and satellite observations. Fire emissions for 2002 are calculated based on a recently developed VISTAS emission inventory. March was selected for the investigation because it is the most active prescribed fire month. Inclusion of fire emissions significantly improved model performance. Model results show that prescribed fire emissions lead to approximately 50% enhancements of mean OC and EC concentrations in the Southeast and a daily increase of PM2.5 up to 25 microg m(-3), indicating that fire emissions can lead to PM2.5 nonattainment in affected regions. Surface enhancements of CO up to 200 ppbv are found. Fire count measurements from the moderate resolution imaging spectroradiometer (MODIS) onboard the NASA Terra satellite show large springtime burning in most states, which is consistent with the emission inventory. These measurements also indicate that the inventory may underestimate fire emissions in the summer.

The Rothermel surface fire spread model and associated developments: A comprehensive explanation

Treesearch

Patricia L. Andrews

2018-01-01

The Rothermel surface fire spread model, with some adjustments by Frank A. Albini in 1976, has been used in fire and fuels management systems since 1972. It is generally used with other models including fireline intensity and flame length. Fuel models are often used to define fuel input parameters. Dynamic fuel models use equations for live fuel curing. Models have...

Real time forest fire warning and forest fire risk zoning: a Vietnamese case study

NASA Astrophysics Data System (ADS)

Chu, T.; Pham, D.; Phung, T.; Ha, A.; Paschke, M.

2016-12-01

Forest fire occurs seriously in Vietnam and has been considered as one of the major causes of forest lost and degradation. Several studies of forest fire risk warning were conducted using Modified Nesterov Index (MNI) but remaining shortcomings and inaccurate predictions that needs to be urgently improved. In our study, several important topographic and social factors such as aspect, slope, elevation, distance to residential areas and road system were considered as "permanent" factors while meteorological data were updated hourly using near-real-time (NRT) remotely sensed data (i.e. MODIS Terra/Aqua and TRMM) for the prediction and warning of fire. Due to the limited number of weather stations in Vietnam, data from all active stations (i.e. 178) were used with the satellite data to calibrate and upscale meteorological variables. These data with finer resolution were then used to generate MNI. The only significant "permanent" factors were selected as input variables based on the correlation coefficients that computed from multi-variable regression among true fire-burning (collected from 1/2007) and its spatial characteristics. These coefficients also used to suggest appropriate weight for computing forest fire risk (FR) model. Forest fire risk model was calculated from the MNI and the selected factors using fuzzy regression models (FRMs) and GIS based multi-criteria analysis. By this approach, the FR was slightly modified from MNI by the integrated use of various factors in our fire warning and prediction model. Multifactor-based maps of forest fire risk zone were generated from classifying FR into three potential danger levels. Fire risk maps were displayed using webgis technology that is easy for managing data and extracting reports. Reported fire-burnings thereafter have been used as true values for validating the forest fire risk. Fire probability has strong relationship with potential danger levels (varied from 5.3% to 53.8%) indicating that the higher potential risk, the more chance of fire happen. By adding spatial factors to continuous daily updated remote sensing based meteo-data, results are valuable for both mapping forest fire risk zones in short and long-term and real time fire warning in Vietnam. Key words: Near-real-time, forest fire warning, fuzzy regression model, remote sensing.

Risk for large-scale fires in boreal forests of Finland under changing climate

NASA Astrophysics Data System (ADS)

Lehtonen, I.; Venäläinen, A.; Kämäräinen, M.; Peltola, H.; Gregow, H.

2015-08-01

The target of this work was to assess the impact of projected climate change on the number of large forest fires (over 10 ha fires) and burned area in Finland. For this purpose, we utilized a strong relationship between fire occurrence and the Canadian fire weather index (FWI) during 1996-2014. We used daily data from five global climate models under representative concentration pathway RCP4.5 and RCP8.5 scenarios. The model data were statistically downscaled onto a high-resolution grid using the quantile-mapping method before performing the analysis. Our results suggest that the number of large forest fires may double or even triple during the present century. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to active and efficient fire suppression. Our results also reveal substantial inter-model variability in the rate of the projected increase in forest-fire danger. We moreover showed that the majority of large fires occur within a relatively short period in May and June due to human activities and that FWI correlates poorer with the fire activity during this time of year than later in summer when lightning is more important cause of fires.

Error associated with model predictions of wildland fire rate of spread

Treesearch

Miguel G. Cruz; Martin E. Alexander

2015-01-01

How well can we expect to predict the spread rate of wildfires and prescribed fires? The degree of accuracy in model predictions of wildland fire behaviour characteristics are dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data (Alexander and Cruz 2013b#. We...

Rapid Response Tools and Datasets for Post-fire Erosion Modeling: Lessons Learned from the Rock House and High Park Fires

NASA Astrophysics Data System (ADS)

Miller, Mary Ellen; Elliot, William E.; MacDonald, Lee H.

2013-04-01

Once the danger posed by an active wildfire has passed, land managers must rapidly assess the threat from post-fire runoff and erosion due to the loss of surface cover and fire-induced changes in soil properties. Increased runoff and sediment delivery are of great concern to both the pubic and resource managers. Post-fire assessments and proposals to mitigate these threats are typically undertaken by interdisciplinary Burned Area Emergency Response (BAER) teams. These teams are under very tight deadlines, so they often begin their analysis while the fire is still burning and typically must complete their plans within a couple of weeks. Many modeling tools and datasets have been developed over the years to assist BAER teams, but process-based, spatially explicit models are currently under-utilized relative to simpler, lumped models because they are more difficult to set up and require the preparation of spatially-explicit data layers such as digital elevation models, soils, and land cover. The difficulty of acquiring and utilizing these data layers in spatially-explicit models increases with increasing fire size. Spatially-explicit post-fire erosion modeling was attempted for a small watershed in the 1270 km2 Rock House fire in Texas, but the erosion modeling work could not be completed in time. The biggest limitation was the time required to extract the spatially explicit soils data needed to run the preferred post-fire erosion model (GeoWEPP with Disturbed WEPP parameters). The solution is to have the spatial soil, land cover, and DEM data layers prepared ahead of time, and to have a clear methodology for the BAER teams to incorporate these layers in spatially-explicit modeling interfaces like GeoWEPP. After a fire occurs the data layers can quickly be clipped to the fire perimeter. The soil and land cover parameters can then be adjusted according to the burn severity map, which is one of the first products generated for the BAER teams. Under a previous project for the U.S. Environmental Protection Agency this preparatory work was done for much of Colorado, and in June 2012 the High Park wildfire in north central Colorado burned over 340 km2. The data layers for the entire burn area were quickly assembled and the spatially explicit runoff and erosion modeling was completed in less than three days. The resulting predictions were then used by the BAER team to quantify downstream risks and delineate priority areas for different post-fire treatments. These two contrasting case studies demonstrate the feasibility and the value of preparing datasets and modeling tools ahead of time. In recognition of this, the U.S. National Aeronautic and Space Administration has agreed to fund a pilot project to demonstrate the utility of acquiring and preparing the necessary data layers for fire-prone wildlands across the western U.S. A similar modeling and data acquisition approach could be followed

Stem mortality in surface fires: Part II, experimental methods for characterizing the thermal response of tree stems to heating by fires

Treesearch

D. M. Jimenez; B. W. Butler; J. Reardon

2003-01-01

Current methods for predicting fire-induced plant mortality in shrubs and trees are largely empirical. These methods are not readily linked to duff burning, soil heating, and surface fire behavior models. In response to the need for a physics-based model of this process, a detailed model for predicting the temperature distribution through a tree stem as a function of...

Effects of wildland fire smoke on a tree-roosting bat: integrating a plume model, field measurements, and mammalian dose-response relationships

Treesearch

M.B. Dickinson; J.C. Norris; A.S. Bova; R.L. Kremens; V. Young; M.J. Lacki

2010-01-01

Faunal injury and mortality in wildland fires is a concern for wildlife and fire management although little work has been done on the mechanisms by which exposures cause their effects. In this paper, we use an integral plume model, field measurements, and models of carbon monoxide and heat effects to explore risk to tree-roosting bats during prescribed fires in mixed-...

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

Modelling the ecological vulnerability to forest fires in mediterranean ecosystems using geographic information technologies.

PubMed

Duguy, Beatriz; Alloza, José Antonio; Baeza, M Jaime; De la Riva, Juan; Echeverría, Maite; Ibarra, Paloma; Llovet, Juan; Cabello, Fernando Pérez; Rovira, Pere; Vallejo, Ramon V

2012-12-01

Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model's predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model's predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model's performance is satisfactory when applied to the three selected vegetation types.

Modelling Variable Fire Severity in Boreal Forests: Effects of Fire Intensity and Stand Structure

PubMed Central

Miquelajauregui, Yosune; Cumming, Steven G.; Gauthier, Sylvie

2016-01-01

It is becoming clear that fires in boreal forests are not uniformly stand-replacing. On the contrary, marked variation in fire severity, measured as tree mortality, has been found both within and among individual fires. It is important to understand the conditions under which this variation can arise. We integrated forest sample plot data, tree allometries and historical forest fire records within a diameter class-structured model of 1.0 ha patches of mono-specific black spruce and jack pine stands in northern Québec, Canada. The model accounts for crown fire initiation and vertical spread into the canopy. It uses empirical relations between fire intensity, scorch height, the percent of crown scorched and tree mortality to simulate fire severity, specifically the percent reduction in patch basal area due to fire-caused mortality. A random forest and a regression tree analysis of a large random sample of simulated fires were used to test for an effect of fireline intensity, stand structure, species composition and pyrogeographic regions on resultant severity. Severity increased with intensity and was lower for jack pine stands. The proportion of simulated fires that burned at high severity (e.g. >75% reduction in patch basal area) was 0.80 for black spruce and 0.11 for jack pine. We identified thresholds in intensity below which there was a marked sensitivity of simulated fire severity to stand structure, and to interactions between intensity and structure. We found no evidence for a residual effect of pyrogeographic region on simulated severity, after the effects of stand structure and species composition were accounted for. The model presented here was able to produce variation in fire severity under a range of fire intensity conditions. This suggests that variation in stand structure is one of the factors causing the observed variation in boreal fire severity. PMID:26919456

Critical wind velocity for arresting upwind gas and smoke dispersion induced by near-wall fire in a road tunnel.

PubMed

Hu, L H; Peng, W; Huo, R

2008-01-15

In case of a tunnel fire, toxic gas and smoke particles released are the most fatal contaminations. It is important to supply fresh air from the upwind side to provide a clean and safe environment upstream from the fire source for people evacuation. Thus, the critical longitudinal wind velocity for arresting fire induced upwind gas and smoke dispersion is a key criteria for tunnel safety design. Former studies and thus, the models built for estimating the critical wind velocity are all arbitrarily assuming that the fire takes place at the centre of the tunnel. However, in many real cases in road tunnels, the fire originates near the sidewall. The critical velocity of a near-wall fire should be different with that of a free-standing central fire due to their different plume entrainment process. Theoretical analysis and CFD simulation were performed in this paper to estimate the critical velocity for the fire near the sidewall. Results showed that when fire originates near the sidewall, it needs larger critical velocity to arrest the upwind gas and smoke dispersion than when fire at the centre. The ratio of critical velocity of a near-wall fire to that of a central fire was ideally estimated to be 1.26 by theoretical analysis. Results by CFD modelling showed that the ratio decreased with the increase of the fire size till near to unity. The ratio by CFD modelling was about 1.18 for a 500kW small fire, being near to and a bit lower than the theoretically estimated value of 1.26. However, the former models, including those of Thomas (1958, 1968), Dangizer and Kenndey (1982), Oka and Atkinson (1995), Wu and Barker (2000) and Kunsch (1999, 2002), underestimated the critical velocity needed for a fire near the tunnel sidewall.

Modelling Variable Fire Severity in Boreal Forests: Effects of Fire Intensity and Stand Structure.

PubMed

Miquelajauregui, Yosune; Cumming, Steven G; Gauthier, Sylvie

2016-01-01

It is becoming clear that fires in boreal forests are not uniformly stand-replacing. On the contrary, marked variation in fire severity, measured as tree mortality, has been found both within and among individual fires. It is important to understand the conditions under which this variation can arise. We integrated forest sample plot data, tree allometries and historical forest fire records within a diameter class-structured model of 1.0 ha patches of mono-specific black spruce and jack pine stands in northern Québec, Canada. The model accounts for crown fire initiation and vertical spread into the canopy. It uses empirical relations between fire intensity, scorch height, the percent of crown scorched and tree mortality to simulate fire severity, specifically the percent reduction in patch basal area due to fire-caused mortality. A random forest and a regression tree analysis of a large random sample of simulated fires were used to test for an effect of fireline intensity, stand structure, species composition and pyrogeographic regions on resultant severity. Severity increased with intensity and was lower for jack pine stands. The proportion of simulated fires that burned at high severity (e.g. >75% reduction in patch basal area) was 0.80 for black spruce and 0.11 for jack pine. We identified thresholds in intensity below which there was a marked sensitivity of simulated fire severity to stand structure, and to interactions between intensity and structure. We found no evidence for a residual effect of pyrogeographic region on simulated severity, after the effects of stand structure and species composition were accounted for. The model presented here was able to produce variation in fire severity under a range of fire intensity conditions. This suggests that variation in stand structure is one of the factors causing the observed variation in boreal fire severity.

An organizational process for promoting home fire safety in two community settings.

PubMed

Lehna, Carlee; Twyman, Stephanie; Fahey, Erin; Coty, Mary-Beth; Williams, Joe; Scrivener, Drane; Wishnia, Gracie; Myers, John

2017-02-01

The purpose of this study was to describe the home fire safety quality improvement model designed to aid organizations in achieving institutional program goals. The home fire safety model was developed from community-based participatory research (CBPR) applying training-the-trainer methods and is illustrated by an institutional case study. The model is applicable to other types of organizations to improve home fire safety in vulnerable populations. Utilizing the education model leaves trained employees with guided experience to build upon, adapt, and modify the home fire safety intervention to more effectively serve their clientele, promote safety, and meet organizational objectives. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

Models for predicting fuel consumption in sagebrush-dominated ecosystems

Treesearch

Clinton S. Wright

2013-01-01

Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

BEHAVE: fire behavior prediction and fuel modeling system-BURN Subsystem, part 1

Treesearch

Patricia L. Andrews

1986-01-01

Describes BURN Subsystem, Part 1, the operational fire behavior prediction subsystem of the BEHAVE fire behavior prediction and fuel modeling system. The manual covers operation of the computer program, assumptions of the mathematical models used in the calculations, and application of the predictions.

Simulating the Effects of Fire on Forests in the Russian Far East: Integrating a Fire Danger Model and the FAREAST Forest Growth Model Across a Complex Landscape

NASA Astrophysics Data System (ADS)

Sherman, N. J.; Loboda, T.; Sun, G.; Shugart, H. H.; Csiszar, I.

2008-12-01

The remaining natural habitat of the critically endangered Amur tiger (Panthera tigris altaica) and Amur leopard (Panthera pardus orientalis) is a vast, biologically and topographically diverse area in the Russian Far East (RFE). Although wildland fire is a natural component of ecosystem functioning in the RFE, severe or repeated fires frequently re-set the process of forest succession, which may take centuries to return the affected forests to the pre-fire state and thus significantly alters habitat quality and long-term availability. The frequency of severe fire events has increased over the last 25 years, leading to irreversible modifications of some parts of the species' habitats. Moreover, fire regimes are expected to continue to change toward more frequent and severe events under the influence of climate change. Here we present an approach to developing capabilities for a comprehensive assessment of potential Amur tiger and leopard habitat availability throughout the 21st century by integrating regionally parameterized fire danger and forest growth models. The FAREAST model is an individual, gap-based model that simulates forest growth in a single location and demonstrates temporally explicit forest succession leading to mature forests. Including spatially explicit information on probabilities of fire occurrence at 1 km resolution developed from the regionally specific remotely -sensed data-driven fire danger model improves our ability to provide realistic long-term projections of potential forest composition in the RFE. This work presents the first attempt to merge the FAREAST model with a fire disturbance model, to validate its outputs across a large region, and to compare it to remotely-sensed data products as well as in situ assessments of forest structure. We ran the FAREAST model at 1,000 randomly selected points within forested areas in the RFE. At each point, the model was calibrated for temperature, precipitation, slope, elevation, and fire probability. The output of the model includes biomass estimates for 44 tree species that occur in the RFE, grouped by genus. We compared the model outputs with land cover classifications derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data and LIDAR-based estimates of biomass across the entire region, and Russian forest inventory records at selected sites. Overall, we find that the FAREAST estimates of forest biomass and general composition are consistent with the observed distribution of forest types.

Overview of the 2013 FireFlux II grass fire field experiment

Treesearch

C.B. Clements; B. Davis; D. Seto; J. Contezac; A. Kochanski; J.-B. Fillipi; N. Lareau; B. Barboni; B. Butler; S. Krueger; R. Ottmar; R. Vihnanek; W.E. Heilman; J. Flynn; M.A. Jenkins; J. Mandel; C. Teske; D. Jimenez; J. O' Brien; B. Lefer

2014-01-01

In order to better understand the dynamics of fire-atmosphere interactions and the role of micrometeorology on fire behaviour the FireFlux campaign was conducted in 2006 on a coastal tall-grass prairie in southeast Texas, USA. The FireFlux campaign dataset has become the international standard for evaluating coupled fire-atmosphere model systems. While FireFlux is one...

Numerical modeling of water spray suppression of conveyor belt fires in a large-scale tunnel.

PubMed

Yuan, Liming; Smith, Alex C

2015-05-01

Conveyor belt fires in an underground mine pose a serious life threat to miners. Water sprinkler systems are usually used to extinguish underground conveyor belt fires, but because of the complex interaction between conveyor belt fires and mine ventilation airflow, more effective engineering designs are needed for the installation of water sprinkler systems. A computational fluid dynamics (CFD) model was developed to simulate the interaction between the ventilation airflow, the belt flame spread, and the water spray system in a mine entry. The CFD model was calibrated using test results from a large-scale conveyor belt fire suppression experiment. Simulations were conducted using the calibrated CFD model to investigate the effects of sprinkler location, water flow rate, and sprinkler activation temperature on the suppression of conveyor belt fires. The sprinkler location and the activation temperature were found to have a major effect on the suppression of the belt fire, while the water flow rate had a minor effect.

Numerical modeling of water spray suppression of conveyor belt fires in a large-scale tunnel

PubMed Central

Yuan, Liming; Smith, Alex C.

2015-01-01

Conveyor belt fires in an underground mine pose a serious life threat to miners. Water sprinkler systems are usually used to extinguish underground conveyor belt fires, but because of the complex interaction between conveyor belt fires and mine ventilation airflow, more effective engineering designs are needed for the installation of water sprinkler systems. A computational fluid dynamics (CFD) model was developed to simulate the interaction between the ventilation airflow, the belt flame spread, and the water spray system in a mine entry. The CFD model was calibrated using test results from a large-scale conveyor belt fire suppression experiment. Simulations were conducted using the calibrated CFD model to investigate the effects of sprinkler location, water flow rate, and sprinkler activation temperature on the suppression of conveyor belt fires. The sprinkler location and the activation temperature were found to have a major effect on the suppression of the belt fire, while the water flow rate had a minor effect. PMID:26190905

Linear Modeling and Evaluation of Controls on Flow Response in Western Post-Fire Watersheds

NASA Astrophysics Data System (ADS)

Saxe, S.; Hogue, T. S.; Hay, L.

2015-12-01

This research investigates the impact of wildfires on watershed flow regimes throughout the western United States, specifically focusing on evaluation of fire events within specified subregions and determination of the impact of climate and geophysical variables in post-fire flow response. Fire events were collected through federal and state-level databases and streamflow data were collected from U.S. Geological Survey stream gages. 263 watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. For each watershed, percent changes in runoff ratio (RO), annual seven day low-flows (7Q2) and annual seven day high-flows (7Q10) were calculated from pre- to post-fire. Numerous independent variables were identified for each watershed and fire event, including topographic, land cover, climate, burn severity, and soils data. The national watersheds were divided into five regions through K-clustering and a lasso linear regression model, applying the Leave-One-Out calibration method, was calculated for each region. Nash-Sutcliffe Efficiency (NSE) was used to determine the accuracy of the resulting models. The regions encompassing the United States along and west of the Rocky Mountains, excluding the coastal watersheds, produced the most accurate linear models. The Pacific coast region models produced poor and inconsistent results, indicating that the regions need to be further subdivided. Presently, RO and HF response variables appear to be more easily modeled than LF. Results of linear regression modeling showed varying importance of watershed and fire event variables, with conflicting correlation between land cover types and soil types by region. The addition of further independent variables and constriction of current variables based on correlation indicators is ongoing and should allow for more accurate linear regression modeling.

Visualization and modeling of smoke transport over landscape scales

Treesearch

Glenn P. Forney; William Mell

2007-01-01

Computational tools have been developed at the National Institute of Standards and Technology (NIST) for modeling fire spread and smoke transport. These tools have been adapted to address fire scenarios that occur in the wildland urban interface (WUI) over kilometer-scale distances. These models include the smoke plume transport model ALOFT (A Large Open Fire plume...

State of Fire Behavior Models and their Application to Ecosystem and Smoke Management Issues: Special Session Summary Report

DTIC Science & Technology

2013-10-24

advance fire science: (1) fire behavior, (2) ecological effects of fire, (3) carbon accounting , (4) emissions characterization, and (5) fire plume...relates to smoke management. 3) Carbon accounting in forest management and prescribed fire programs (including tradeoffs such as prescribed burning...carbon accounting , 4) emissions characterization and 5) fire plume dispersion. 1) Fire behavior. Better characterization of wildland fire behavior is

Fire modeling in the Brazilian arc of deforestation through nested coupling of atmosphere, dynamic vegetation, LUCC and fire spread models

NASA Astrophysics Data System (ADS)

Tourigny, E.; Nobre, C.; Cardoso, M. F.

2012-12-01

Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.

From Spiking Neuron Models to Linear-Nonlinear Models

PubMed Central

Ostojic, Srdjan; Brunel, Nicolas

2011-01-01

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777

From spiking neuron models to linear-nonlinear models.

PubMed

Ostojic, Srdjan; Brunel, Nicolas

2011-01-20

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

Assessing accuracy of point fire intervals across landscapes with simulation modelling

Treesearch

Russell A. Parsons; Emily K. Heyerdahl; Robert E. Keane; Brigitte Dorner; Joseph Fall

2007-01-01

We assessed accuracy in point fire intervals using a simulation model that sampled four spatially explicit simulated fire histories. These histories varied in fire frequency and size and were simulated on a flat landscape with two forest types (dry versus mesic). We used three sampling designs (random, systematic grids, and stratified). We assessed the sensitivity of...

Seasonal predictions for wildland fire severity

Treesearch

Shyh-Chin Chen; Haiganoush Preisler; Francis Fujioka; John W. Benoit; John O. Roads

2009-01-01

The National Fire Danger Rating System (NFDRS) indices deduced from the monthly to seasonal predictions of a meteorological climate model at 50-km grid space from January 1998 through December 2003 were used in conjunction with a probability model to predict the expected number of fire occurrences and large fires over the U.S. West. The short-term climate forecasts are...

A conceptual framework for ranking crown fire potential in wildland fuelbeds.

Treesearch

Mark D. Schaaf; David V. Sandberg; Maarten D. Schreuder; Cynthia L. Riccardi

2007-01-01

This paper presents a conceptual framework for ranking the crown fire potential of wildland fuelbeds with forest canopies. This approach extends the work by Van Wagner and Rothermel, and introduces several new physical concepts to the modeling of crown fire behavior derived from the reformulated Rothemel surface fire modeling concepts proposed by Sandberg et al. This...

The wildfire experiment (WIFE): observations with airborne remote sensors

Treesearch

L.F. Radke; T.L. Clark; J.L. Coen; C.A. Walther; R.N. Lockwood; P.J. Riggan; J.A. Brass; R.G. Higgins

2000-01-01

Airborne remote sensors have long been a cornerstone of wildland fire research, and recently three-dimensional fire behaviour models fully coupled to the atmosphere have begun to show a convincing level of verisimilitude. The WildFire Experiment (WiFE) attempted the marriage of airborne remote sensors, multi-sensor observations together with fire model development and...

Burn severity mapping using simulation modeling and satellite imagery

Treesearch

Eva C. Karau; Robert E. Keane

2010-01-01

Although burn severity maps derived from satellite imagery provide a landscape view of fire impacts, fire effects simulation models can provide spatial fire severity estimates and add a biotic context in which to interpret severity. In this project, we evaluated two methods of mapping burn severity in the context of rapid post-fire assessment for four wildfires in...

A foundation for initial attack simulation: the Fried and Fried fire containment model

Treesearch

Jeremy S. Fried; Burton D. Fried

2010-01-01

The Fried and Fried containment algorithm, which models the effect of suppression efforts on fire growth, allows simulation of any mathematically representable fire shape, provides for "head" and "tail" attack tactics as well as parallel attack (building fireline parallel to but at some offset distance from the free-burning fire perimeter, alone and...

An integer programming model to optimize resource allocation for wildfire containment.

Treesearch

Geoffrey H. Donovan; Douglas B. Rideout

2003-01-01

Determining the specific mix of fire-fighting resources for a given fire is a necessary condition for identifying the minimum of the Cost Plus Net Value Change (C+NVC) function. Current wildland fire management models may not reliably do so. The problem of identifying the most efficient wildland fire organization is characterized mathematically using integer-...

Fire spread in chaparral -"go or no-go?"

Treesearch

D.R. Weise; Xiangyang Zhou; Lulu Sun; Shankar Mahalingam

2005-01-01

Current fire models are designed to model the spread of a linear fire front in dead, small-diameter fuels. Fires in predominantly living vegetation account for a large proportion of annual burned area nationally. Prescribed burning is used to manage living fuels; however, prescribed burning is currently conducted under conditions that result in marginal burning. We do...

Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750-2015)

NASA Astrophysics Data System (ADS)

van Marle, Margreet J. E.; Kloster, Silvia; Magi, Brian I.; Marlon, Jennifer R.; Daniau, Anne-Laure; Field, Robert D.; Arneth, Almut; Forrest, Matthew; Hantson, Stijn; Kehrwald, Natalie M.; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stéphane; Yue, Chao; Kaiser, Johannes W.; van der Werf, Guido R.

2017-09-01

Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data have shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently, there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emission estimates back in time based on satellite data starting in 1997, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant, with 10-year averages varying between 1.8 and 2.3 Pg C yr-1. Carbon emissions increased only slightly over the full time period and peaked during the 1990s after which they decreased gradually. There is substantial uncertainty in these estimates, and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 % of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emission estimates are mostly suited for global analyses and will be used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.

Modelling Middle Infrared Thermal Imagery from Observed or Simulated Active Fire

NASA Astrophysics Data System (ADS)

Paugam, R.; Gastellu-Etchegorry, J. P.; Mell, W.; Johnston, J.; Filippi, J. B.

2016-12-01

The Fire Radiative Power (FRP) is used in the atmospheric and fire communities to estimate fire emission. For example, the current version of the emission inventory GFAS is using FRP observation from the MODIS sensors to derive daily global distribution of fire emissions. Although the FRP product is widely accepted, most of its theoretical justifications are still based on small scale burns. When up-scaling to large fires effects of view angle, canopy cover, or smoke absorption are still unknown. To cover those questions, we are building a system based on the DART radiative transfer model to simulate the middle infrared radiance emitted by a propagating fire front and propagating in the surrounding scene made of ambient vegetation and plume aerosols. The current version of the system was applied to fire ranging from a 1m2 to 7ha. The 3D fire scene used as input in DART is made of the flame, the vegetation (burnt and unburnt), and the plume. It can be either set up from [i] 3D physical based model scene (ie WFDS, mainly applicable for small scale burn), [ii] coupled 2D fire spread - atmospheric models outputs (eg ForeFire-MesoNH) or [iii] derived from thermal imageries observations (here plume effects are not considered). In the last two cases, as the complexity of physical processes occurring in the flame (in particular soot formation and emission) is not to solved, the flames structures are parameterized with (a) temperature and soot concentration based on empirical derived profiles and (b) 3D triangular shape hull interpolated at the fire front location. Once the 3D fire scene is set up, DART is then used to render thermal imageries in the middle infrared. Using data collected from burns conducted at different scale, the modelled thermal imageries are compared against observations, and effects of view angle are discussed.

Fire dynamics during the 20th century simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kloster, Silvia; Mahowald, Natalie; Randerson, Jim

2011-01-01

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we foundmore » the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997 2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000 2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.« less

Use of spatially refined satellite remote sensing fire detection data to initialize and evaluate coupled weather-wildfire growth model simulations

NASA Astrophysics Data System (ADS)

Schroeder, W.; Coen, J.; Oliva, P.

2013-12-01

Availability of spatially refined satellite active fire detection data is gradually increasing. For example, the new 375 m Visible Infrared Imaging Radiometer Suite (VIIRS) data show improved active fire detection performance for both small and large size fires. The VIIRS data have proved superior to MODIS for mapping of wildfires events spanning several days to weeks of either continued or intermittent activity, delivering 12-h active fire data of improved spatial fidelity. The VIIRS active fire data are complemented by other satellite active fire data sets of similar or higher spatial resolution, including the new 30 m Landsat-8. Additional assets should include the upcoming 20 m Sentinel-2 Landsat-class satellite program by the European Space Agency to be launched in 2014-15. These improved active fire data sets are fostering new applications that rely on higher resolution input fire data. In this study, we describe the characteristics of the new VIIRS and Landsat-8 data and demonstrate one such new application of satellite active fire data in support of fire behavior modeling. We present results for a wildfire observed in June 2012 in New Mexico using an innovative approach to improving the simulation of large, long-duration wildfires, either for retrospective studies or forecasting in a number of geophysical applications. The approach uses (1) the Coupled Atmosphere-Wildland Fire Environment (CAWFE) Model, a numerical weather prediction model two-way coupled with a module representing the rate of spread of a wildfire's flaming front, its rate of consumption of different wildland fuels, and the feedback of this heat release upon the atmosphere - i.e. 'how a fire creates its own weather', combined with (2) spatially refined 375 m VIIRS active fire data, which is used for initialization of a wildfire already in progress in the model and evaluation of its simulated progression at the time of the next pass. Results show that initializing a fire that is 'in progress' with VIIRS data and a weather simulation based on more recent atmospheric analyses can overcome several issues and improve the simulation of late-developing fires and of later periods (particularly those with growth periods separated by lulls) in a long-lived fire.

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE - Part 2: Carbon emissions and the role of fires in the global carbon balance

NASA Astrophysics Data System (ADS)

Yue, C.; Ciais, P.; Cadule, P.; Thonicke, K.; van Leeuwen, T. T.

2015-05-01

Carbon dioxide emissions from wild and anthropogenic fires return the carbon absorbed by plants to the atmosphere, and decrease the sequestration of carbon by land ecosystems. Future climate warming will likely increase the frequency of fire-triggering drought, so that the future terrestrial carbon uptake will depend on how fires respond to altered climate variation. In this study, we modelled the role of fires in the global terrestrial carbon balance for 1901-2012, using the ORCHIDEE global vegetation model equipped with the SPITFIRE model. We conducted two simulations with and without the fire module being activated, using a static land cover. The simulated global fire carbon emissions for 1997-2009 are 2.1 Pg C yr-1, which is close to the 2.0 Pg C yr-1 as estimated by GFED3.1. The simulated land carbon uptake after accounting for emissions for 2003-2012 is 3.1 Pg C yr-1, which is within the uncertainty of the residual carbon sink estimation (2.8 ± 0.8 Pg C yr-1). Fires are found to reduce the terrestrial carbon uptake by 0.32 Pg C yr-1 over 1901-2012, or 20% of the total carbon sink in a world without fire. The fire-induced land sink reduction (SRfire) is significantly correlated with climate variability, with larger sink reduction occurring in warm and dry years, in particular during El Niño events. Our results suggest a "fire respiration partial compensation". During the 10 lowest SRfire years (SRfire = 0.17 Pg C yr-1), fires mainly compensate for the heterotrophic respiration that would occur in a world without fire. By contrast, during the 10 highest SRfire fire years (SRfire = 0.49 Pg C yr-1), fire emissions far exceed their respiration partial compensation and create a larger reduction in terrestrial carbon uptake. Our findings have important implications for the future role of fires in the terrestrial carbon balance, because the capacity of terrestrial ecosystems to sequester carbon will be diminished by future climate change characterized by increased frequency of droughts and extreme El Niño events.

Continued warming could transform Greater Yellowstone fire regimes by mid-21st century

PubMed Central

Westerling, Anthony L.; Turner, Monica G.; Smithwick, Erica A. H.; Romme, William H.; Ryan, Michael G.

2011-01-01

Climate change is likely to alter wildfire regimes, but the magnitude and timing of potential climate-driven changes in regional fire regimes are not well understood. We considered how the occurrence, size, and spatial location of large fires might respond to climate projections in the Greater Yellowstone ecosystem (GYE) (Wyoming), a large wildland ecosystem dominated by conifer forests and characterized by infrequent, high-severity fire. We developed a suite of statistical models that related monthly climate data (1972–1999) to the occurrence and size of fires >200 ha in the northern Rocky Mountains; these models were cross-validated and then used with downscaled (∼12 km × 12 km) climate projections from three global climate models to predict fire occurrence and area burned in the GYE through 2099. All models predicted substantial increases in fire by midcentury, with fire rotation (the time to burn an area equal to the landscape area) reduced to <30 y from the historical 100–300 y for most of the GYE. Years without large fires were common historically but are expected to become rare as annual area burned and the frequency of regionally synchronous fires increase. Our findings suggest a shift to novel fire–climate–vegetation relationships in Greater Yellowstone by midcentury because fire frequency and extent would be inconsistent with persistence of the current suite of conifer species. The predicted new fire regime would transform the flora, fauna, and ecosystem processes in this landscape and may indicate similar changes for other subalpine forests. PMID:21788495

Investigating dynamic underground coal fires by means of numerical simulation

NASA Astrophysics Data System (ADS)

Wessling, S.; Kessels, W.; Schmidt, M.; Krause, U.

2008-01-01

Uncontrolled burning or smoldering of coal seams, otherwise known as coal fires, represents a worldwide natural hazard. Efficient application of fire-fighting strategies and prevention of mining hazards require that the temporal evolution of fire propagation can be sufficiently precise predicted. A promising approach for the investigation of the temporal evolution is the numerical simulation of involved physical and chemical processes. In the context of the Sino-German Research Initiative `Innovative Technologies for Detection, Extinction and Prevention of Coal Fires in North China,' a numerical model has been developed for simulating underground coal fires at large scales. The objective of such modelling is to investigate observables, like the fire propagation rate, with respect to the thermal and hydraulic parameters of adjacent rock. In the model, hydraulic, thermal and chemical processes are accounted for, with the last process complemented by laboratory experiments. Numerically, one key challenge in modelling coal fires is to circumvent the small time steps resulting from the resolution of fast reaction kinetics at high temperatures. In our model, this problem is solved by means of an `operator-splitting' approach, in which transport and reactive processes of oxygen are independently calculated. At high temperatures, operator-splitting has the decisive advantage of allowing the global time step to be chosen according to oxygen transport, so that time-consuming simulation through the calculation of fast reaction kinetics is avoided. Also in this model, because oxygen distribution within a coal fire has been shown to remain constant over long periods, an additional extrapolation algorithm for the coal concentration has been applied. In this paper, we demonstrate that the operator-splitting approach is particularly suitable for investigating the influence of hydraulic parameters of adjacent rocks on coal fire propagation. A study shows that dynamic propagation strongly depends on permeability variations. For the assumed model, no fire exists for permeabilities k < 10-10m2, whereas the fire propagation velocity ranges between 340ma-1 for k = 10-8m2, and drops to lower than 3ma-1 for k = 5 × 10-10m2. Additionally, strong temperature variations are observed for the permeability range 5 × 10-10m2 < k < 10-8m2.

Landslides, forest fires, and earthquakes: examples of self-organized critical behavior

NASA Astrophysics Data System (ADS)

Turcotte, Donald L.; Malamud, Bruce D.

2004-09-01

Per Bak conceived self-organized criticality as an explanation for the behavior of the sandpile model. Subsequently, many cellular automata models were found to exhibit similar behavior. Two examples are the forest-fire and slider-block models. Each of these models can be associated with a serious natural hazard: the sandpile model with landslides, the forest-fire model with actual forest fires, and the slider-block model with earthquakes. We examine the noncumulative frequency-area statistics for each natural hazard, and show that each has a robust power-law (fractal) distribution. We propose an inverse-cascade model as a general explanation for the power-law frequency-area statistics of the three cellular-automata models and their ‘associated’ natural hazards.

PyrE, an interactive fire module within the NASA-GISS Earth System Model

NASA Astrophysics Data System (ADS)

Mezuman, K.; Bauer, S. E.; Tsigaridis, K.

2017-12-01

Fires directly affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. Having an interactive fire module in an Earth System Model allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of biomass burning in different time periods. To do so we have developed PyrE, the NASA-GISS interactive fire emissions model. PyrE uses the flammability, ignition, and suppression parameterization proposed by Pechony and Shindell (2009), and is coupled to a burned area and surface recovery parameterization. The burned area calculation follows CLM's approach (Li et al., 2012), paired with an offline recovery scheme based on Ent's Terrestrial Biosphere Model (Ent TBM) carbon pool turnover time. PyrE is driven by environmental variables calculated by climate simulations, population density data, MODIS fire counts and LAI retrievals, as well as GFED4s emissions. Since the model development required extensive use of reference datasets, in addition to comparing it to GFED4s BA, we evaluate it by studying the effect of fires on atmospheric composition and climate. Our results show good agreement globally, with some regional differences. Finally, we quantify the present day fire radiative forcing. The development of PyrE allowed us for the first time to interactively simulate climate and fire activity with GISS-ModelE3

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

NASA Technical Reports Server (NTRS)

Barrett, K.; Kasischke, E. S.; McGuire, A. D.; Turetsky, M. R.; Kane, E. S.

2010-01-01

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data

USGS Publications Warehouse

Barrett, Kirsten M.; Kasischke, E.S.; McGuire, A.D.; Turetsky, M.R.; Kane, E.S.

2010-01-01

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Fire and Smoke Model Evaluation Experiment: Coordination of a study to improve smoke modeling for fire operations within the United States

NASA Astrophysics Data System (ADS)

French, N. H. F.; Ottmar, R. D.; Brown, T. J.; Larkin, N. K.

2017-12-01

The Fire and Smoke Model Evaluation Experiment (FASMEE) is an integrative research effort to identify and collect critical measurements to improve operational wildland fire and smoke prediction systems. FASMEE has two active phases and one suggested phase. Phase 1 is the analysis and planning process to assess the current state of fire-plume-smoke modeling and to determine the critical measurements required to evaluate and improve these operational fire and smoke models. As the major deliverable for Phase 1, a study plan has been completed that describes the measurement needs, field campaigns, and command, safety and air space de-confliction plans necessary to complete the FASMEE project. Phase 2 is a set of field campaigns to collect data during 2019-2022. Future Improvements would be a set of analyses and model improvements based on the data collected within Phase 2 that is dependent on identifying future funding sources. In this presentation, we will review the FASMEE Study Plan and detailed measurements and conditions expected for the four to five proposed research burns. The recommended measurements during Phase 2 span the four interrelated disciplines of FASMEE: fuels and consumption, fire behavior and energy, plume dynamics and meteorology, and smoke emissions, chemistry, and transport. Fuel type, condition, and consumption during wildland fire relates to several fire impacts including radiative heating, which provides the energy that drives fire dynamics. Local-scale meteorology is an important factor which relates to atmospheric chemistry, dispersion, and transport. Plume dynamics provide the connection between fire behavior and far-field smoke dispersion, because it determines the vertical distribution of the emissions. Guided by the data needs and science questions generated during Phase 1, three wildland fire campaigns were selected. These included the western wildfire campaign (rapid deployment aimed at western wildfires supporting NOAA, NASA, and NSF smoke flights), southwestern campaign (targeting high intensity prescribed fires), and southeastern campaign (targeting large and higher than average fuel loadings with important smoke management relevancy).

A high-resolution modelling approach on spatial wildfire distribution in the Tyrolean Alps

NASA Astrophysics Data System (ADS)

Malowerschnig, Bodo; Sass, Oliver

2013-04-01

Global warming will cause increasing danger of wildfires in Austria, which can have long-lasting consequences on woodland ecosystems. The protective effect of forest can be severely diminished, leading to natural hazards like avalanches and rockfall. However, data on wildfire frequency and distribution have been sparse and incomplete for Austria. Long-lasting postfire degradation under adverse preconditions (steep slopes, limestone) was a common phenomenon in parts of the Tyrolean Alps several decades ago and should become relevant again under a changing fire frequency. The FIRIA project compiles historical wildfire data, information on fuel loads, fire weather indices (FWI) and vegetation recovery patterns. The governing climatic, topographic and socio-economic factors of forest fire distribution were assessed to trigger a distribution model of currently fire-prone areas in Tyrol. By collecting data from different sources like old newspapers archives and fire-fighter databases, we were able to build up a fire database of wildfire occurrences containing more than 1400 forest fires since the 15th century in Tyrol. For the period from 1993 to 2011, the database is widely complete and covers 482 fires. Using a non-parametrical statistical method it was possible to select the best suited fire weather index (FWI) for the prediction. The testing of 19 FWI's shows that it is necessary to use two discriminative indices to differentiate between summer and winter season. Together with compiled topographic, socio-economic, infrastructure and forest maps, the dataset was the base for a multifactorial analysis, performed by comparing the maximum entropy approach (Maxent) with an ensemble classifier (Random Forests). Both approaches have their background in the spatial habitat distribution and are easy to adapt to the requirements of a wildfire ignition model. The aim of this modelling approach was to determine areas which are particularly prone to wildfire. Due to the pronounced relief curvature we based our model on 100 x 100 m cells to identify individual slopes and their topography. The first provisional result is a map of fire probability under current climate conditions (fire hot-spots). Our modelling approach indicates the fire weather index as the main driver, which is followed closely by socioeconomic (population density) and infrastructure factors (roads density, aerial railways, building density). The leverage of the forest community or its management is rather low; the same applies to topographic influences like aspect or sea level. The derived fire hot-spots are either placed close to the valley ground or around touristic infrastructure, with an overall preference for inner alpine areas and south-facing slopes. In the next step, the impact of climate change on the distribution and frequency of fires will be assessed by calculating a climate change model adapted to the 1x1km INCA dataset and based on different regional climate change models. Finally, a selection of fire-hot-spots from the previous modelling steps will be used for enhanced 3D-modelling approaches of natural hazards after wildfire-driven deforestation.

Research on Influence and Prediction Model of Urban Traffic Link Tunnel curvature on Fire Temperature Based on Pyrosim--SPSS Multiple Regression Analysis

NASA Astrophysics Data System (ADS)

Li, Xiao Ju; Yao, Kun; Dai, Jun Yu; Song, Yun Long

2018-05-01

The underground space, also known as the “fourth dimension” of the city, reflects the efficient use of urban development intensive. Urban traffic link tunnel is a typical underground limited-length space. Due to the geographical location, the special structure of space and the curvature of the tunnel, high-temperature smoke can easily form the phenomenon of “smoke turning” and the fire risk is extremely high. This paper takes an urban traffic link tunnel as an example to focus on the relationship between curvature and the temperature near the fire source, and use the pyrosim built different curvature fire model to analyze the influence of curvature on the temperature of the fire, then using SPSS Multivariate regression analysis simulate curvature of the tunnel and fire temperature data. Finally, a prediction model of urban traffic link tunnel curvature on fire temperature was proposed. The regression model analysis and test show that the curvature is negatively correlated with the tunnel temperature. This model is feasible and can provide a theoretical reference for the urban traffic link tunnel fire protection design and the preparation of the evacuation plan. And also, it provides some reference for other related curved tunnel curvature design and smoke control measures.

Fire Technology Abstracts, volume 4, issue 1, August, 1981

NASA Astrophysics Data System (ADS)

Holtschlag, L. J.; Kuvshinoff, B. W.; Jernigan, J. B.

This bibliography contains over 400 citations with abstracts addressing various aspects of fire technology. Subjects cover the dynamics of fire, behavior and properties of materials, fire modeling and test burns, fire protection, fire safety, fire service organization, apparatus and equipment, fire prevention, suppression, planning, human behavior, medical problems, codes and standards, hazard identification, safe handling of materials, insurance, economics of loss and prevention, and more.

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

Inhibitory neurons promote robust critical firing dynamics in networks of integrate-and-fire neurons.

PubMed

Lu, Zhixin; Squires, Shane; Ott, Edward; Girvan, Michelle

2016-12-01

We study the firing dynamics of a discrete-state and discrete-time version of an integrate-and-fire neuronal network model with both excitatory and inhibitory neurons. When the integer-valued state of a neuron exceeds a threshold value, the neuron fires, sends out state-changing signals to its connected neurons, and returns to the resting state. In this model, a continuous phase transition from non-ceaseless firing to ceaseless firing is observed. At criticality, power-law distributions of avalanche size and duration with the previously derived exponents, -3/2 and -2, respectively, are observed. Using a mean-field approach, we show analytically how the critical point depends on model parameters. Our main result is that the combined presence of both inhibitory neurons and integrate-and-fire dynamics greatly enhances the robustness of critical power-law behavior (i.e., there is an increased range of parameters, including both sub- and supercritical values, for which several decades of power-law behavior occurs).

Fire risk in California

NASA Astrophysics Data System (ADS)

Peterson, Seth Howard

Fire is an integral part of ecosystems in the western United States. Decades of fire suppression have led to (unnaturally) large accumulations of fuel in some forest communities, such as the lower elevation forests of the Sierra Nevada. Urban sprawl into fire prone chaparral vegetation in southern California has put human lives at risk and the decreased fire return intervals have put the vegetation community at risk of type conversion. This research examines the factors affecting fire risk in two of the dominant landscapes in the state of California, chaparral and inland coniferous forests. Live fuel moisture (LFM) is important for fire ignition, spread rate, and intensity in chaparral. LFM maps were generated for Los Angeles County by developing and then inverting robust cross-validated regression equations from time series field data and vegetation indices (VIs) and phenological metrics from MODIS data. Fire fuels, including understory fuels which are not visible to remote sensing instruments, were mapped in Yosemite National Park using the random forests decision tree algorithm and climatic, topographic, remotely sensed, and fire history variables. Combining the disparate data sources served to improve classification accuracies. The models were inverted to produce maps of fuel models and fuel amounts, and these showed that fire fuel amounts are highest in the low elevation forests that have been most affected by fire suppression impacting the natural fire regime. Wildland fires in chaparral commonly burn in late summer or fall when LFM is near its annual low, however, the Jesusita Fire burned in early May of 2009, when LFM was still relatively high. The HFire fire spread model was used to simulate the growth of the Jesusita Fire using LFM maps derived from imagery acquired at the time of the fire and imagery acquired in late August to determine how much different the fire would have been if it had occurred later in the year. Simulated fires were 1.5 times larger, and the fire reached the wildland urban interface three hours earlier, when using August LFM.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

PubMed

Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

2013-11-05

A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

Modeling post-fire hydro-geomorphic recovery in the Waldo Canyon Fire

NASA Astrophysics Data System (ADS)

Kinoshita, Alicia; Nourbakhshbeidokhti, Samira; Chin, Anne

2016-04-01

Wildfire can have significant impacts on watershed hydrology and geomorphology by changing soil properties and removing vegetation, often increasing runoff and soil erosion and deposition, debris flows, and flooding. Watershed systems may take several years or longer to recover. During this time, post-fire channel changes have the potential to alter hydraulics that influence characteristics such as time of concentration and increase time to peak flow, flow capacity, and velocity. Using the case of the 2012 Waldo Canyon Fire in Colorado (USA), this research will leverage field-based surveys and terrestrial Light Detection and Ranging (LiDAR) data to parameterize KINEROS2 (KINematic runoff and EROSion), an event oriented, physically-based watershed runoff and erosion model. We will use the Automated Geospatial Watershed Assessment (AGWA) tool, which is a GIS-based hydrologic modeling tool that uses commonly available GIS data layers to parameterize, execute, and spatially visualize runoff and sediment yield for watersheds impacted by the Waldo Canyon Fire. Specifically, two models are developed, an unburned (Bear Creek) and burned (Williams) watershed. The models will simulate burn severity and treatment conditions. Field data will be used to validate the burned watersheds for pre- and post-fire changes in infiltration, runoff, peak flow, sediment yield, and sediment discharge. Spatial modeling will provide insight into post-fire patterns for varying treatment, burn severity, and climate scenarios. Results will also provide post-fire managers with improved hydro-geomorphic modeling and prediction tools for water resources management and mitigation efforts.

Quantifying soil burn severity for hydrologic modeling to assess post-fire effects on sediment delivery

NASA Astrophysics Data System (ADS)

Dobre, Mariana; Brooks, Erin; Lew, Roger; Kolden, Crystal; Quinn, Dylan; Elliot, William; Robichaud, Pete

2017-04-01

Soil erosion is a secondary fire effect with great implications for many ecosystem resources. Depending on the burn severity, topography, and the weather immediately after the fire, soil erosion can impact municipal water supplies, degrade water quality, and reduce reservoirs' storage capacity. Scientists and managers use field and remotely sensed data to quickly assess post-fire burn severity in ecologically-sensitive areas. From these assessments, mitigation activities are implemented to minimize post-fire flood and soil erosion and to facilitate post-fire vegetation recovery. Alternatively, land managers can use fire behavior and spread models (e.g. FlamMap, FARSITE, FOFEM, or CONSUME) to identify sensitive areas a priori, and apply strategies such as fuel reduction treatments to proactively minimize the risk of wildfire spread and increased burn severity. There is a growing interest in linking fire behavior and spread models with hydrology-based soil erosion models to provide site-specific assessment of mitigation treatments on post-fire runoff and erosion. The challenge remains, however, that many burn severity mapping and modeling products quantify vegetation loss rather than measuring soil burn severity. Wildfire burn severity is spatially heterogeneous and depends on the pre-fire vegetation cover, fuel load, topography, and weather. Severities also differ depending on the variable of interest (e.g. soil, vegetation). In the United States, Burned Area Reflectance Classification (BARC) maps, derived from Landsat satellite images, are used as an initial burn severity assessment. BARC maps are classified from either a Normalized Burn Ratio (NBR) or differenced Normalized Burned Ratio (dNBR) scene into four classes (Unburned, Low, Moderate, and High severity). The development of soil burn severity maps requires further manual field validation efforts to transform the BARC maps into a product more applicable for post-fire soil rehabilitation activities. Alternative spectral indices and modeled output approaches may prove better predictors of soil burn severity and hydrologic effects, but these have not yet been assessed in a model framework. In this project we compare field-verified soil burn severity maps to satellite-derived and modeled burn severity maps. We quantify the extent to which there are systematic differences in these mapping products. We then use the Water Erosion Prediction Project (WEPP) hydrologic soil erosion model to assess sediment delivery from these fires using the predicted and observed soil burn severity maps. Finally, we discuss differences in observed and predicted soil burn severity maps and application to watersheds in the Pacific Northwest to estimate post-fire sediment delivery.

Determination of Realistic Fire Scenarios in Spacecraft

NASA Technical Reports Server (NTRS)

Dietrich, Daniel L.; Ruff, Gary A.; Urban, David

2013-01-01

This paper expands on previous work that examined how large a fire a crew member could successfully survive and extinguish in the confines of a spacecraft. The hazards to the crew and equipment during an accidental fire include excessive pressure rise resulting in a catastrophic rupture of the vehicle skin, excessive temperatures that burn or incapacitate the crew (due to hyperthermia), carbon dioxide build-up or accumulation of other combustion products (e.g. carbon monoxide). The previous work introduced a simplified model that treated the fire primarily as a source of heat and combustion products and sink for oxygen prescribed (input to the model) based on terrestrial standards. The model further treated the spacecraft as a closed system with no capability to vent to the vacuum of space. The model in the present work extends this analysis to more realistically treat the pressure relief system(s) of the spacecraft, include more combustion products (e.g. HF) in the analysis and attempt to predict the fire spread and limiting fire size (based on knowledge of terrestrial fires and the known characteristics of microgravity fires) rather than prescribe them in the analysis. Including the characteristics of vehicle pressure relief systems has a dramatic mitigating effect by eliminating vehicle overpressure for all but very large fires and reducing average gas-phase temperatures.

Fire-danger rating and observed wildfire behavior in the Northeastern United States.

Treesearch

Donald A. Haines; William A. Main; Albert J. Simard

1986-01-01

Compares the 1978 National Fire-Danger Rating System and its 20 fuel models, along with other danger rating systems, with observed fire behavior and rates the strengths and weaknesses of models and systems.

SPITFIRE within the MPI Earth system model: Model development and evaluation

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Thonicke, Kirsten; Kloster, Silvia

2014-09-01

Quantification of the role of fire within the Earth system requires an adequate representation of fire as a climate-controlled process within an Earth system model. To be able to address questions on the interaction between fire and the Earth system, we implemented the mechanistic fire model SPITFIRE, in JSBACH, the land surface model of the MPI Earth system model. Here, we document the model implementation as well as model modifications. We evaluate our model results by comparing the simulation to the GFED version 3 satellite-based data set. In addition, we assess the sensitivity of the model to the meteorological forcing and to the spatial variability of a number of fire relevant model parameters. A first comparison of model results with burned area observations showed a strong correlation of the residuals with wind speed. Further analysis revealed that the response of the fire spread to wind speed was too strong for the application on global scale. Therefore, we developed an improved parametrization to account for this effect. The evaluation of the improved model shows that the model is able to capture the global gradients and the seasonality of burned area. Some areas of model-data mismatch can be explained by differences in vegetation cover compared to observations. We achieve benchmarking scores comparable to other state-of-the-art fire models. The global total burned area is sensitive to the meteorological forcing. Adjustment of parameters leads to similar model results for both forcing data sets with respect to spatial and seasonal patterns. This article was corrected on 29 SEP 2014. See the end of the full text for details.

Data for Room Fire Model Comparisons

PubMed Central

Peacock, Richard D.; Davis, Sanford; Babrauskas, Vytenis

1991-01-01

With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system. PMID:28184121

Data for Room Fire Model Comparisons.

PubMed

Peacock, Richard D; Davis, Sanford; Babrauskas, Vytenis

1991-01-01

With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system.

Fire regime in Mediterranean ecosystem

NASA Astrophysics Data System (ADS)

Biondi, Guido; Casula, Paolo; D'Andrea, Mirko; Fiorucci, Paolo

2010-05-01

The analysis of burnt areas time series in Mediterranean regions suggests that ecosystems characterising this area consist primarily of species highly vulnerable to the fire but highly resilient, as characterized by a significant regenerative capacity after the fire spreading. In a few years the area burnt may once again be covered by the same vegetation present before the fire. Similarly, Mediterranean conifer forests, which often refers to plantations made in order to reforest the areas most severely degraded with high erosion risk, regenerate from seed after the fire resulting in high resilience to the fire as well. Only rarely, and usually with negligible damages, fire affects the areas covered by climax species in relation with altitude and soil types (i.e, quercus, fagus, abies). On the basis of these results, this paper shows how the simple Drossel-Schwabl forest fire model is able to reproduce the forest fire regime in terms of number of fires and burned area, describing whit good accuracy the actual fire perimeters. The original Drossel-Schwabl model has been slightly modified in this work by introducing two parameters (probability of propagation and regrowth) specific for each different class of vegetation cover. Using model selection methods based on AIC, the model with the optimal number of classes with different fire behaviour was selected. Two different case studies are presented in this work: Regione Liguria and Regione Sardegna (Italy). Both regions are situated in the center of the Mediterranean and are characterized by a high number of fires and burned area. However, the two regions have very different fire regimes. Sardinia is affected by the fire phenomenon only in summer whilst Liguria is affected by fires also in winter, with higher number of fires and larger burned area. In addition, the two region are very different in vegetation cover. The presence of Mediterranean conifers, (Pinus Pinaster, Pinus Nigra, Pinus halepensis) is quite spread in Liguria and is limited in Sardinia. What is common in the two regions is the widespread presence of shrub species frequently spread by fire. The analysis in the two regions thus allows in a rather limited area to study almost all the species that characterize the Mediterranean region. This work shows that the fire regime in Mediterranean area is strongly related with vegetation patterns, is almost totally independent by the cause of ignition, and only partially dependent by fire extinguishing actions.

Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest

USGS Publications Warehouse

Barrett, Kirsten; Loboda, Tatiana; McGuire, A. David; Genet, Hélène; Hoy, Elizabeth; Kasischke, Eric

2016-01-01

Wildfire, a dominant disturbance in boreal forests, is highly variable in occurrence and behavior at multiple spatiotemporal scales. New data sets provide more detailed spatial and temporal observations of active fires and the post-burn environment in Alaska. In this study, we employ some of these new data to analyze variations in fire activity by developing three explanatory models to examine the occurrence of (1) seasonal periods of elevated fire activity using the number of MODIS active fire detections data set (MCD14DL) within an 11-day moving window, (2) unburned patches within a burned area using the Monitoring Trends in Burn Severity fire severity product, and (3) short-to-moderate interval (<60 yr) fires using areas of burned area overlap in the Alaska Large Fire Database. Explanatory variables for these three models included dynamic variables that can change over the course of the fire season, such as weather and burn date, as well as static variables that remain constant over a fire season, such as topography, drainage, vegetation cover, and fire history. We found that seasonal periods of high fire activity are associated with both seasonal timing and aggregated weather conditions, as well as the landscape composition of areas that are burning. Important static inputs to the model of seasonal fire activity indicate that when fire weather conditions are suitable, areas that typically resist fire (e.g., deciduous stands) may become more vulnerable to burning and therefore less effective as fire breaks. The occurrence of short-to-moderate interval fires appears to be primarily driven by weather conditions, as these were the only relevant explanatory variables in the model. The unique importance of weather in explaining short-to-moderate interval fires implies that fire return intervals (FRIs) will be sensitive to projected climate changes in the region. Unburned patches occur most often in younger stands, which may be related to a greater deciduous fraction of vegetation as well as lower fuel loads compared with mature stands. The fraction of unburned patches may therefore increase in response to decreasing FRIs and increased deciduousness in the region, or these may decrease if fire weather conditions become more severe.

Deriving forest fire ignition risk with biogeochemical process modelling.

PubMed

Eastaugh, C S; Hasenauer, H

2014-05-01

Climate impacts the growth of trees and also affects disturbance regimes such as wildfire frequency. The European Alps have warmed considerably over the past half-century, but incomplete records make it difficult to definitively link alpine wildfire to climate change. Complicating this is the influence of forest composition and fuel loading on fire ignition risk, which is not considered by purely meteorological risk indices. Biogeochemical forest growth models track several variables that may be used as proxies for fire ignition risk. This study assesses the usefulness of the ecophysiological model BIOME-BGC's 'soil water' and 'labile litter carbon' variables in predicting fire ignition. A brief application case examines historic fire occurrence trends over pre-defined regions of Austria from 1960 to 2008. Results show that summer fire ignition risk is largely a function of low soil moisture, while winter fire ignitions are linked to the mass of volatile litter and atmospheric dryness.

Validation of smoke plume rise models using ground based lidar

Treesearch

Cyle E. Wold; Shawn Urbanski; Vladimir Kovalev; Alexander Petkov; Wei Min Hao

2010-01-01

Biomass fires can significantly degrade regional air quality. Plume rise height is one of the critical factors determining the impact of fire emissions on air quality. Plume rise models are used to prescribe the vertical distribution of fire emissions which are critical input for smoke dispersion and air quality models. The poor state of model evaluation is due in...

Forest Fire Danger Rating (FFDR) Prediction over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Song, B.; Won, M.; Jang, K.; Yoon, S.; Lim, J.

2016-12-01

Approximately five hundred forest fires occur and inflict the losses of both life and property each year in Korea during the forest fire seasons in the spring and autumn. Thus, an accurate prediction of forest fire is essential for effective forest fire prevention. The meteorology is one of important factors to predict and understand the fire occurrence as well as its behaviors and spread. In this study, we present the Forest Fire Danger Rating Systems (FFDRS) on the Korean Peninsula based on the Daily Weather Index (DWI) which represents the meteorological characteristics related to forest fire. The thematic maps including temperature, humidity, and wind speed produced from Korea Meteorology Administration (KMA) were applied to the forest fire occurrence probability model by logistic regression to analyze the DWI over the Korean Peninsula. The regional data assimilation and prediction system (RDAPS) and the improved digital forecast model were used to verify the sensitivity of DWI. The result of verification test revealed that the improved digital forecast model dataset showed better agreements with the real-time weather data. The forest fire danger rating index (FFDRI) calculated by the improved digital forecast model dataset showed a good agreement with the real-time weather dataset at the 233 administrative districts (R2=0.854). In addition, FFDRI were compared with observation-based FFDRI at 76 national weather stations. The mean difference was 0.5 at the site-level. The results produced in this study indicate that the improved digital forecast model dataset can be useful to predict the FFDRI in the Korean Peninsula successfully.

A generalized linear integrate-and-fire neural model produces diverse spiking behaviors.

PubMed

Mihalaş, Stefan; Niebur, Ernst

2009-03-01

For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model's rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation.

Climatic and socio-economic fire drivers in the Mediterranean basin at a century scale: Analysis and modelling based on historical fire statistics and dynamic global vegetation models (DGVMs)

NASA Astrophysics Data System (ADS)

Mouillot, F.; Koutsias, N.; Conedera, M.; Pezzatti, B.; Madoui, A.; Belhadj Kheder, C.

2017-12-01

Wildfire is the main disturbance affecting Mediterranean ecosystems, with implications on biogeochemical cycles, biosphere/atmosphere interactions, air quality, biodiversity, and socio-ecosystems sustainability. The fire/climate relationship is time-scale dependent and may additionally vary according to concurrent changes climatic, environmental (e.g. land use), and fire management processes (e.g. fire prevention and control strategies). To date, however, most studies focus on a decadal scale only, being fire statistics ore remote sensing data usually available for a few decades only. Long-term fire data may allow for a better caption of the slow-varying human and climate constrains and for testing the consistency of the fire/climate relationship on the mid-time to better apprehend global change effects on fire risks. Dynamic Global Vegetation Models (DGVMs) associated with process-based fire models have been recently developed to capture both the direct role of climate on fire hazard and the indirect role of changes in vegetation and human population, to simulate biosphere/atmosphere interactions including fire emissions. Their ability to accurately reproduce observed fire patterns is still under investigation regarding seasonality, extreme events or temporal trend to identify potential misrepresentations of processes. We used a unique long-term fire reconstruction (from 1880 to 2016) of yearly burned area along a North/South and East/West environmental gradient across the Mediterranean Basin (southern Switzerland, Greece, Algeria, Tunisia) to capture the climatic and socio economic drivers of extreme fire years by linking yearly burned area with selected climate indices derived from historical climate databases and socio-economic variables. We additionally compared the actual historical reconstructed fire history with the yearly burned area simulated by a panel of DGVMS (FIREMIP initiative) driven by daily CRU climate data at 0.5° resolution across the Mediterranean basin. We will present and discuss the key processes driving interannual fire hazard along the 20th century, and analysed how DGVMs capture this interannual variability.

FireMap: A Web Tool for Dynamic Data-Driven Predictive Wildfire Modeling Powered by the WIFIRE Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Block, J.; Crawl, D.; Artes, T.; Cowart, C.; de Callafon, R.; DeFanti, T.; Graham, J.; Smarr, L.; Srivas, T.; Altintas, I.

2016-12-01

The NSF-funded WIFIRE project has designed a web-based wildfire modeling simulation and visualization tool called FireMap. The tool executes FARSITE to model fire propagation using dynamic weather and fire data, configuration settings provided by the user, and static topography and fuel datasets already built-in. Using GIS capabilities combined with scalable big data integration and processing, FireMap enables simple execution of the model with options for running ensembles by taking the information uncertainty into account. The results are easily viewable, sharable, repeatable, and can be animated as a time series. From these capabilities, users can model real-time fire behavior, analyze what-if scenarios, and keep a history of model runs over time for sharing with collaborators. Firemap runs FARSITE with national and local sensor networks for real-time weather data ingestion and High-Resolution Rapid Refresh (HRRR) weather for forecasted weather. The HRRR is a NOAA/NCEP operational weather prediction system comprised of a numerical forecast model and an analysis/assimilation system to initialize the model. It is run with a horizontal resolution of 3 km, has 50 vertical levels, and has a temporal resolution of 15 minutes. The HRRR requires an Environmental Data Exchange (EDEX) server to receive the feed and generate secondary products out of it for the modeling. UCSD's EDEX server, funded by NSF, makes high-resolution weather data available to researchers worldwide and enables visualization of weather systems and weather events lasting months or even years. The high-speed server aggregates weather data from the University Consortium for Atmospheric Research by way of a subscription service from the Consortium called the Internet Data Distribution system. These features are part of WIFIRE's long term goals to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. Although Firemap is a research product of WIFIRE, developed in collaboration with a number of fire departments, the tool is operational in pilot form for providing big data-driven predictive fire spread modeling. Most recently, FireMap was used for situational awareness in the July 2016 Sand Fire by LA City and LA County Fire Departments.

Fires and fuels: Vegetation change over time in the Zuni Mountains, New Mexico

NASA Astrophysics Data System (ADS)

Wylie, Luke Anthony

The Zuni Mountains are a region that has been dramatically changed by human interference. Anthropogenically, fire suppression practices have allowed a buildup of fuels and caused a change in the fire-adapted ponderosa pine ecosystem such that the new ecosystem now incorporates many fire-intolerant species. As a result, the low-severity fires that the ecosystem once depended on to regenerate the forest are much reduced, and these low-severity fires are now replaced by crown-level infernos that threaten the forest and nearby towns. In order to combat these effects, land managers are implementing fuel reduction practices and are striving to better understand the local ecosystem. In this study, a predictive fire spread model (FARSITE) was implemented to predict spatio-temporal distribution of fire in the Zuni Mountains based on change in vegetation types that are most prone to fire. Using Landsat imagery and historical fire spread data from 2001 to 2014, the following research questions were investigated: (1) What variables are responsible for fire spread in the Zuni Mountains, New Mexico? (2) Which areas are prone to destructive and canopy level fires? and (3) How have the fuel model types that are most conducive to fire spread changed in the past twenty years? The utilization of spatial modeling and remote sensing to understand the interaction of meteorological variables and vegetation in predicting fire spread in this region is a novel approach. This study showed that (i) fires are more likely to occur in the valleys and high elevation grassland areas of the Zuni Mountains, (ii) certain vegetation types including grass and shrub lands in the area present a greater danger to canopy fire than others, and (iii) that these vegetation types have changed in the past sixteen years.

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

NASA Technical Reports Server (NTRS)

Brooker, J. E.; Dietrich, D. L.; Gokoglu, S. A.; Urban, D. L.; Ruff, G. A.

2015-01-01

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

Modeling the effects of fire severity and climate warming on active layer and soil carbon dynamics of black spruce forests across the landscape in interior Alaska

USGS Publications Warehouse

Genet, H.; McGuire, Anthony David; Barrett, K.; Breen, A.; Euskirchen, E.S.; Johnstone, J.F.; Kasischke, E.S.; Melvin, A.M.; Bennett, A.; Mack, M.C.; Rupp, T.S.; Schuur, A.E.G.; Turetsky, M.R.; Yuan, F.

2013-01-01

There is a substantial amount of carbon stored in the permafrost soils of boreal forest ecosystems, where it is currently protected from decomposition. The surface organic horizons insulate the deeper soil from variations in atmospheric temperature. The removal of these insulating horizons through consumption by fire increases the vulnerability of permafrost to thaw, and the carbon stored in permafrost to decomposition. In this study we ask how warming and fire regime may influence spatial and temporal changes in active layer and carbon dynamics across a boreal forest landscape in interior Alaska. To address this question, we (1) developed and tested a predictive model of the effect of fire severity on soil organic horizons that depends on landscape-level conditions and (2) used this model to evaluate the long-term consequences of warming and changes in fire regime on active layer and soil carbon dynamics of black spruce forests across interior Alaska. The predictive model of fire severity, designed from the analysis of field observations, reproduces the effect of local topography (landform category, the slope angle and aspect and flow accumulation), weather conditions (drought index, soil moisture) and fire characteristics (day of year and size of the fire) on the reduction of the organic layer caused by fire. The integration of the fire severity model into an ecosystem process-based model allowed us to document the relative importance and interactions among local topography, fire regime and climate warming on active layer and soil carbon dynamics. Lowlands were more resistant to severe fires and climate warming, showing smaller increases in active layer thickness and soil carbon loss compared to drier flat uplands and slopes. In simulations that included the effects of both warming and fire at the regional scale, fire was primarily responsible for a reduction in organic layer thickness of 0.06 m on average by 2100 that led to an increase in active layer thickness of 1.1 m on average by 2100. The combination of warming and fire led to a simulated cumulative loss of 9.6 kgC m−2 on average by 2100. Our analysis suggests that ecosystem carbon storage in boreal forests in interior Alaska is particularly vulnerable, primarily due to the combustion of organic layer thickness in fire and the related increase in active layer thickness that exposes previously protected permafrost soil carbon to decomposition.

Allocating resources to large wildland fires: a model with stochastic production rates

Treesearch

Romain Mees; David Strauss

1992-01-01

Wildland fires that grow out of the initial attack phase are responsible for most of the damage and burned area. We model the allocation of fire suppression resources (ground crews, engines, bulldozers, and airdrops) to these large fires. The fireline at a given future time is partitioned into homogeneous segments on the basis of fuel type, available resources, risk,...

Burning rates of wood cribs with implications for wildland fires

Treesearch

Sara McAllister; Mark Finney

2016-01-01

Wood cribs are often used as ignition sources for room fire tests and the well characterized burning rates may also have applications to wildland fires. The burning rate of wildland fuel structures, whether the needle layer on the ground or trees and shrubs themselves, is not addressed in any operational fire model and no simple model exists. Several relations...

Challenges of assessing fire and burn severity using field measures, remote sensing and modelling

Treesearch

Penelope Morgan; Robert E. Keane; Gregory K. Dillon; Theresa B. Jain; Andrew T. Hudak; Eva C. Karau; Pamela G. Sikkink; Zachery A. Holden; Eva K. Strand

2014-01-01

Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models. We draw on diverse recent research for guidance on assessing...

A GIS-based approach for comparative analysis of potential fire risk assessment

NASA Astrophysics Data System (ADS)

Sun, Ying; Hu, Lieqiu; Liu, Huiping

2007-06-01

Urban fires are one of the most important sources of property loss and human casualty and therefore it is necessary to assess the potential fire risk with consideration of urban community safety. Two evaluation models are proposed, both of which are integrated with GIS. One is the single factor model concerning the accessibility of fire passage and the other is grey clustering approach based on the multifactor system. In the latter model, fourteen factors are introduced and divided into four categories involving security management, evacuation facility, construction resistance and fire fighting capability. A case study on campus of Beijing Normal University is presented to express the potential risk assessment models in details. A comparative analysis of the two models is carried out to validate the accuracy. The results are approximately consistent with each other. Moreover, modeling with GIS promotes the efficiency the potential risk assessment.

Numerical Field Model Simulation of Full Scale Fire Tests in a Closed Spherical/Cylindrical Vessel.

DTIC Science & Technology

1987-12-01

the behavior of an actual fire on board a ship. The computer model will be verified by the experimental data obtained in Fire-l. It is important to... behavior in simulations where convection is important. The upwind differencing scheme takes into account the unsymmetrical phenomenon of convection by using...TANK CELL ON THE NORTH SIDE) FOR A * * PARTICULAR FIRE CELL * * COSUMS (I,J) = THE ARRAY TO STORE THE SIMILIAR VALUE FOR THE FIRE * * CELL TO THE SOUTH

A sub-grid, mixture-fraction-based thermodynamic equilibrium model for gas phase combustion in FIRETEC: development and results

Treesearch

M. M. Clark; T. H. Fletcher; R. R. Linn

2010-01-01

The chemical processes of gas phase combustion in wildland fires are complex and occur at length-scales that are not resolved in computational fluid dynamics (CFD) models of landscape-scale wildland fire. A new approach for modelling fire chemistry in HIGRAD/FIRETEC (a landscape-scale CFD wildfire model) applies a mixture– fraction model relying on thermodynamic...

Fuel consumption models for pine flatwoods fuel types in the southeastern United States

Treesearch

Clinton S. Wright

2013-01-01

Modeling fire effects, including terrestrial and atmospheric carbon fluxes and pollutant emissions during wildland fires, requires accurate predictions of fuel consumption. Empirical models were developed for predicting fuel consumption from fuel and environmental measurements on a series of operational prescribed fires in pine flatwoods ecosystems in the southeastern...

Environmental drivers and spatial dependency in wildfire ignition patterns of northwestern Patagonia.

PubMed

Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas

2013-07-15

Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Laboratory fire behavior measurements of chaparral crown fire

Treesearch

C. Sanpakit; S. Omodan; D. Weise; M Princevac

2015-01-01

In 2013, there was an estimated 9,900 wildland fires that claimed more than 577,000 acres of land. That same year, about 542 prescribed fires were used to treat 48,554 acres by several agencies in California. Being able to understand fires using laboratory models can better prepare individuals to combat or use fires. Our research focused on chaparral crown fires....

Fire danger and fire behavior modeling systems in Australia, Europe, and North America

Treesearch

Francis M. Fujioka; A. Malcolm Gill; Domingos X. Viegas; B. Mike Wotton

2009-01-01

Wildland fire occurrence and behavior are complex phenomena involving essentially fuel (vegetation), topography, and weather. Fire managers around the world use a variety of systems to track and predict fire danger and fire behavior, at spatial scales that span from local to global extents, and temporal scales ranging from minutes to seasons. The fire management...

How to generate and interpret fire characteristics charts for surface and crown fire behavior

Treesearch

Patricia L. Andrews; Faith Ann Heinsch; Luke Schelvan

2011-01-01

A fire characteristics chart is a graph that presents primary related fire behavior characteristics-rate of spread, flame length, fireline intensity, and heat per unit area. It helps communicate and interpret modeled or observed fire behavior. The Fire Characteristics Chart computer program plots either observed fire behavior or values that have been calculated by...

Development of wildfires in Australia over the last century

NASA Astrophysics Data System (ADS)

Nieradzik, Lars Peter; Haverd, Vanessa; Briggs, Peter; Canadell, Josep G.; Smith, Ben

2017-04-01

Wildfires and their emissions are key biospheric processes in the modeling of the carbon cycle that still are insufficiently understood. In Australia, fire emissions constitute a large flux of carbon from the biosphere to the atmosphere of approximately 1.3 times larger than the annual fossil fuel emissions. In addition, fire plays a big role in determining the composition of vegetation which in turn affects land-atmosphere fluxes. Annualy, up to 4% of the vegetated land-surface area is burned which amounts to up to 3% of global NPP and results in the reslease of about 2 Pg carbon into the atmosphere. There are indications that burned area has decreased globally over recent decades but so far there is not a clear trend in the development in fire-intensity and fuel availability. Net emissions from wildfires are not generally included in global and regional carbon budgets, because it is assumed that gross fire emissions are in balance with post-fire carbon uptake by recovering vegetation. This is a valid assumption as long as climate and fire regimes are in equilibrium, but not when the climate and other drivers are changing. We present a study on the behaviour of wildfires on the Australian continent over the last century (1911 - 2012) introducing the novel fire model BLAZE (BLAZe induced biosphere-atmosphere flux Estimator) that has been designed to address the feedbacks between climate, fuel loads, and fires. BLAZE is used within the Australian land-surface model CABLE (Community Atmophere-Biosphere-Land Exchange model). The study shows two significant outcomes: A regional shift in fire patterns shift during this century due to fire suppression and greening effects as well as an increase of potential fire-line intensity (the risk that a fire becomes more intense), especially in regions where most of Australia's population resides. This strongly emphasises the need to further investigate fire dynamics under future climate scenarios. The fire model BLAZE has been developed at the CSIRO Oceans and Atmosphere, Canberra, Australia and will be part of the upcoming release of the dynamic global vegetation model LPJ-GUESS version 4.1 within the MERGE project at Lund University, Sweden. It will also be included in the EC-Earth ESM within the EU Horizon 2020 project CRESCENDO.

Understanding coupled natural and human systems on fire prone landscapes: integrating wildfire simulation into an agent based planning system.

NASA Astrophysics Data System (ADS)

Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John

2015-04-01

Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and surface fuels are modeled in a state and transition framework that accounts for succession, fire effects, and fuels management. Fire effects are modeled using simulated fire intensity (flame length) to calculate expected vegetation impacts for each vegetation state. This talk will describe the mechanics of the simulation system along with initial results of Envision simulations for the Central Oregon study area that explore the dynamics of wildfire, fuel management, and succession over time.

Optimal firing rate estimation

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

Human impact on wildfires varies between regions and with vegetation productivity

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Kloster, Silvia

2017-11-01

We assess the influence of humans on burned area simulated with a dynamic global vegetation model. The human impact in the model is based on population density and cropland fraction, which were identified as important drivers of burned area in analyses of global datasets, and are commonly used in global models. After an evaluation of the sensitivity to these two variables we extend the model by including an additional effect of the cropland fraction on the fire duration. The general pattern of human influence is similar in both model versions: the strongest human impact is found in regions with intermediate productivity, where fire occurrence is not limited by fuel load or climatic conditions. Human effects in the model increases burned area in the tropics, while in temperate regions burned area is reduced. While the population density is similar on average for the tropical and temperate regions, the cropland fraction is higher in temperate regions, and leads to a strong suppression of fire. The model shows a low human impact in the boreal region, where both population density and cropland fraction is very low and the climatic conditions, as well as the vegetation productivity limit fire. Previous studies attributed a decrease in fire activity found in global charcoal datasets to human activity. This is confirmed by our simulations, which only show a decrease in burned area when the human influence on fire is accounted for, and not with only natural effects on fires. We assess how the vegetation-fire feedback influences the results, by comparing simulations with dynamic vegetation biogeography to simulations with prescribed vegetation. The vegetation-fire feedback increases the human impact on burned area by 10% for present day conditions. These results emphasize that projections of burned area need to account for the interactions between fire, climate, vegetation and humans.

Estimating fire behavior with FIRECAST: user's manual

Treesearch

Jack D. Cohen

1986-01-01

FIRECAST is a computer program that estimates fire behavior in terms of six fire parameters. Required inputs vary depending on the outputs desired by the fire manager. Fuel model options available to users are these: Northern Forest Fire Laboratory (NFFL), National Fire Danger Rating System (NFDRS), and southern California brushland (SCAL). The program has been...

Development of a model to predict ash transport and water pollution risk in fire-affected environments

NASA Astrophysics Data System (ADS)

Neris, Jonay; Elliot, William J.; Doerr, Stefan H.; Robichaud, Peter R.

2017-04-01

An estimated that 15% of the world's population lives in volcanic areas. Recent catastrophic erosion events following wildfires in volcanic terrain have highlighted the geomorphological instability of this soil type under disturbed conditions and steep slopes. Predicting the hydrological and erosional response of this soils in the post-fire period is the first step to design and develop adequate actions to minimize risks in the post-fire period. In this work we apply, for the first time, the Water Erosion Prediction Project model for predicting erosion and runoff events in fire-affected volcanic soils in Europe. Two areas affected by wildfires in 2015 were selected in Tenerife (Spain) representative of different fire behaviour (downhill surface fire with long residence time vs uphill crown fire with short residence time), severity (moderate soil burn severity vs light soil burn severity) and climatic conditions (average annual precipitation of 750 and 210 mm respectively). The actual erosion processes were monitored in the field using silt fences. Rainfall and rill simulations were conducted to determine hydrologic, interrill and rill erosion parameters. The soils were sampled and key properties used as model input, evaluated. During the first 18 months after the fire 7 storms produced runoff and erosion in the selected areas. Sediment delivery reached 5.4 and 2.5 Mg ha-1 respectively in the first rainfall event monitored after the fire, figures comparable to those reported for fire-affected areas of the western USA with similar climatic conditions but lower than those showed by wetter environments. The validation of the WEPP model using field data showed reasonable estimates of hillslope sediment delivery in the post-fire period and, therefore, it is suggested that this model can support land managers in volcanic areas in Europe in predicting post-fire hydrological and erosional risks and designing suitable mitigation treatments.

First application of the WEPP model to predict runoff and erosion risk in fire-affected volcanic areas in Europe

NASA Astrophysics Data System (ADS)

Neris, Jonay; Robichaud, Peter R.; Elliot, William J.; Doerr, Stefan H.; Notario del Pino, Jesús S.; Lado, Marcos

2017-04-01

An estimated that 15% of the world's population lives in volcanic areas. Recent catastrophic erosion events following wildfires in volcanic terrain have highlighted the geomorphological instability of this soil type under disturbed conditions and steep slopes. Predicting the hydrological and erosional response of this soils in the post-fire period is the first step to design and develop adequate actions to minimize risks in the post-fire period. In this work we apply, for the first time, the Water Erosion Prediction Project model for predicting erosion and runoff events in fire-affected volcanic soils in Europe. Two areas affected by wildfires in 2015 were selected in Tenerife (Spain) representative of different fire behaviour (downhill surface fire with long residence time vs uphill crown fire with short residence time), severity (moderate soil burn severity vs light soil burn severity) and climatic conditions (average annual precipitation of 750 and 210 mm respectively). The actual erosion processes were monitored in the field using silt fences. Rainfall and rill simulations were conducted to determine hydrologic, interrill and rill erosion parameters. The soils were sampled and key properties used as model input, evaluated. During the first 18 months after the fire 7 storms produced runoff and erosion in the selected areas. Sediment delivery reached 5.4 and 2.5 Mg ha-1 respectively in the first rainfall event monitored after the fire, figures comparable to those reported for fire-affected areas of the western USA with similar climatic conditions but lower than those showed by wetter environments. The validation of the WEPP model using field data showed reasonable estimates of hillslope sediment delivery in the post-fire period and, therefore, it is suggested that this model can support land managers in volcanic areas in Europe in predicting post-fire hydrological and erosional risks and designing suitable mitigation treatments.

An Accurate Fire-Spread Algorithm in the Weather Research and Forecasting Model Using the Level-Set Method

NASA Astrophysics Data System (ADS)

Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.

2018-04-01

The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

Global Pyrogeography: the Current and Future Distribution of Wildfire

PubMed Central

Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine

2009-01-01

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494

Local and global pyrogeographic evidence that indigenous fire management creates pyrodiversity.

PubMed

Trauernicht, Clay; Brook, Barry W; Murphy, Brett P; Williamson, Grant J; Bowman, David M J S

2015-05-01

Despite the challenges wildland fire poses to contemporary resource management, many fire-prone ecosystems have adapted over centuries to millennia to intentional landscape burning by people to maintain resources. We combine fieldwork, modeling, and a literature survey to examine the extent and mechanism by which anthropogenic burning alters the spatial grain of habitat mosaics in fire-prone ecosystems. We survey the distribution of Callitris intratropica, a conifer requiring long fire-free intervals for establishment, as an indicator of long-unburned habitat availability under Aboriginal burning in the savannas of Arnhem Land. We then use cellular automata to simulate the effects of burning identical proportions of the landscape under different fire sizes on the emergent patterns of habitat heterogeneity. Finally, we examine the global extent of intentional burning and diversity of objectives using the scientific literature. The current distribution of Callitris across multiple field sites suggested long-unburnt patches are common and occur at fine scales (<0.5 ha), while modeling revealed smaller, patchy disturbances maximize patch age diversity, creating a favorable habitat matrix for Callitris. The literature search provided evidence for intentional landscape burning across multiple ecosystems on six continents, with the number of identified objectives ranging from two to thirteen per study. The fieldwork and modeling results imply that the occurrence of long-unburnt habitat in fire-prone ecosystems may be an emergent property of patch scaling under fire regimes dominated by smaller fires. These findings provide a model for understanding how anthropogenic burning alters spatial and temporal aspects of habitat heterogeneity, which, as the literature survey strongly suggests, warrant consideration across a diversity of geographies and cultures. Our results clarify how traditional fire management shapes fire-prone ecosystems, which despite diverse objectives, has allowed human societies to cope with fire as a recurrent disturbance.

Local and global pyrogeographic evidence that indigenous fire management creates pyrodiversity

PubMed Central

Trauernicht, Clay; Brook, Barry W; Murphy, Brett P; Williamson, Grant J; Bowman, David M J S

2015-01-01

Despite the challenges wildland fire poses to contemporary resource management, many fire-prone ecosystems have adapted over centuries to millennia to intentional landscape burning by people to maintain resources. We combine fieldwork, modeling, and a literature survey to examine the extent and mechanism by which anthropogenic burning alters the spatial grain of habitat mosaics in fire-prone ecosystems. We survey the distribution of Callitris intratropica, a conifer requiring long fire-free intervals for establishment, as an indicator of long-unburned habitat availability under Aboriginal burning in the savannas of Arnhem Land. We then use cellular automata to simulate the effects of burning identical proportions of the landscape under different fire sizes on the emergent patterns of habitat heterogeneity. Finally, we examine the global extent of intentional burning and diversity of objectives using the scientific literature. The current distribution of Callitris across multiple field sites suggested long-unburnt patches are common and occur at fine scales (<0.5 ha), while modeling revealed smaller, patchy disturbances maximize patch age diversity, creating a favorable habitat matrix for Callitris. The literature search provided evidence for intentional landscape burning across multiple ecosystems on six continents, with the number of identified objectives ranging from two to thirteen per study. The fieldwork and modeling results imply that the occurrence of long-unburnt habitat in fire-prone ecosystems may be an emergent property of patch scaling under fire regimes dominated by smaller fires. These findings provide a model for understanding how anthropogenic burning alters spatial and temporal aspects of habitat heterogeneity, which, as the literature survey strongly suggests, warrant consideration across a diversity of geographies and cultures. Our results clarify how traditional fire management shapes fire-prone ecosystems, which despite diverse objectives, has allowed human societies to cope with fire as a recurrent disturbance. PMID:26140206

Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.

PubMed

Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Xu, Chong

2018-07-15

The main objective of the present study was to utilize Genetic Algorithms (GA) in order to obtain the optimal combination of forest fire related variables and apply data mining methods for constructing a forest fire susceptibility map. In the proposed approach, a Random Forest (RF) and a Support Vector Machine (SVM) was used to produce a forest fire susceptibility map for the Dayu County which is located in southwest of Jiangxi Province, China. For this purpose, historic forest fires and thirteen forest fire related variables were analyzed, namely: elevation, slope angle, aspect, curvature, land use, soil cover, heat load index, normalized difference vegetation index, mean annual temperature, mean annual wind speed, mean annual rainfall, distance to river network and distance to road network. The Natural Break and the Certainty Factor method were used to classify and weight the thirteen variables, while a multicollinearity analysis was performed to determine the correlation among the variables and decide about their usability. The optimal set of variables, determined by the GA limited the number of variables into eight excluding from the analysis, aspect, land use, heat load index, distance to river network and mean annual rainfall. The performance of the forest fire models was evaluated by using the area under the Receiver Operating Characteristic curve (ROC-AUC) based on the validation dataset. Overall, the RF models gave higher AUC values. Also the results showed that the proposed optimized models outperform the original models. Specifically, the optimized RF model gave the best results (0.8495), followed by the original RF (0.8169), while the optimized SVM gave lower values (0.7456) than the RF, however higher than the original SVM (0.7148) model. The study highlights the significance of feature selection techniques in forest fire susceptibility, whereas data mining methods could be considered as a valid approach for forest fire susceptibility modeling. Copyright © 2018 Elsevier B.V. All rights reserved.

History of Fire Events in the U.S. Commercial Nuclear Industry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bijan Najafi; Joglar-Biloch, Francisco; Kassawara, Robert P.

2002-07-01

Over the past decade, interest in performance-based fire protection has increased within the nuclear industry. In support of this growing interest, in 1997 the Electric Power Research Institute (EPRI) developed a long-range plan to develop/improve data and tools needed to support Risk-Informed/Performance-Based fire protection. This plan calls for continued improvement in collection and use of information obtained from fire events at nuclear plants. The data collection process has the objectives of improving the insights gained from such data and reducing the uncertainty in fire risk and fire modeling methods in order to make them a more reliable basis for performancemore » based fire protection programs. In keeping with these objectives, EPRI continues to collect, review and analyze fire events in support of the nuclear industry. EPRI collects these records in cooperation with the Nuclear Electric Insurance Limited (NEIL), by compiling public fire event reports and by direct solicitation of U.S. nuclear facilities. EPRI fire data collection project is based on the principle that the understanding of history is one of the cornerstones of improving fire protection technology and practice. Therefore, the goal has been to develop and maintain a comprehensive database of fire events with flexibility to support various aspects of fire protection engineering. With more than 1850 fire records over a period of three decades and 2400 reactor years, this is the most comprehensive database of nuclear power industry fire events in existence today. In general, the frequency of fires in the U.S. commercial nuclear industry remains constant. In few cases, e.g., transient fires and fires in BWR offgas/recombiner systems, where either increasing or decreasing trends are observed, these trends tend to slow after 1980. The key issues in improving quality of the data remain to be consistency of the recording and reporting of fire events and difficulties in collection of records. EPRI has made significant progress towards improving the quality of the fire events data through use of multiple collection methods as well as its review and verification. To date EPRI has used this data to develop a generic fire ignition frequency model for U.S. nuclear power industry (Ref. 1, 4 and 5) as well as to support other models in support of EPRI Fire Risk Methods such as a cable fire manual suppression model. EPRI will continue its effort to collect and analyze operating data to support risk informed/performance based fire safety engineering, including collection and analysis of impairment data for fire protection systems and features. This paper provides details on the collection and application of fire events to risk informed/performance based fire protection. The paper also provides valuable insights into improving both collection and use of fire events data. (authors)« less

Species-abundance distribution patterns of soil fungi: contribution to the ecological understanding of their response to experimental fire in Mediterranean maquis (southern Italy).

PubMed

Persiani, Anna Maria; Maggi, Oriana

2013-01-01

Experimental fires, of both low and high intensity, were lit during summer 2000 and the following 2 y in the Castel Volturno Nature Reserve, southern Italy. Soil samples were collected Jul 2000-Jul 2002 to analyze the soil fungal community dynamics. Species abundance distribution patterns (geometric, logarithmic, log normal, broken-stick) were compared. We plotted datasets with information both on species richness and abundance for total, xerotolerant and heat-stimulated soil microfungi. The xerotolerant fungi conformed to a broken-stick model for both the low- and high intensity fires at 7 and 84 d after the fire; their distribution subsequently followed logarithmic models in the 2 y following the fire. The distribution of the heat-stimulated fungi changed from broken-stick to logarithmic models and eventually to a log-normal model during the post-fire recovery. Xerotolerant and, to a far greater extent, heat-stimulated soil fungi acquire an important functional role following soil water stress and/or fire disturbance; these disturbances let them occupy unsaturated habitats and become increasingly abundant over time.

Evaluation of MM5 model resolution when applied to prediction of national fire danger rating indexes

Treesearch

Jeanne L. Hoadley; Miriam L. Rorig; Larry Bradshaw; Sue A. Ferguson; Kenneth J. Westrick; Scott L. Goodrick; Paul Werth

2006-01-01

Weather predictions from the MM5 mesoscale model were used to compute gridded predictions of National Fire Danger Rating System (NFDRS) indexes. The model output was applied to a case study of the 2000 fire season in Northern Idaho and Western Montana to simulate an extreme event. To determine the preferred resolution for automating NFD RS predictions, model...

Considerations in the use of models available for fuel treatment analysis

Treesearch

Charles W. McHugh

2006-01-01

Fire managers are required to evaluate and justify the effectiveness of planned fuel treatments in modifying fire growth, behavior and effects on resources and assets. With the number of models currently available, today’s fire manager can become overwhelmed when deciding which model to use. Each model has a required level of expertise in order to develop the necessary...

A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors

PubMed Central

Mihalaş, Ştefan; Niebur, Ernst

2010-01-01

For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model’s rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation. PMID:18928368

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

NASA Technical Reports Server (NTRS)

Mu, M.; Randerson, J. T.; vanderWerf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.;

Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA

NASA Astrophysics Data System (ADS)

Kennedy, R. S.

2010-12-01

Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.

Local and regional smoke impacts from prescribed fires

NASA Astrophysics Data System (ADS)

Price, Owen F.; Horsey, Bronwyn; Jiang, Ningbo

2016-10-01

Smoke from wildfires poses a significant threat to affected communities. Prescribed burning is conducted to reduce the extent and potential damage of wildfires, but produces its own smoke threat. Planners of prescribed fires model the likely dispersion of smoke to help manage the impacts on local communities. Significant uncertainty remains about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models. To address this uncertainty, a detailed study of smoke dispersal was conducted for one small (52 ha) and one large (700 ha) prescribed fire near Appin in New South Wales, Australia, through the use of stationary and handheld pollution monitors, visual observations and rain radar data, and by comparing observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM2.5) reached very high peak values (> 400 µg m-3) and high 24 h average values (> 100 µg m-3) at several locations next to or within ˜ 500 m downwind from the fire, but low levels elsewhere. The 700 ha fire produced a much larger plume, peaking at ˜ 2000 m altitude and affecting downwind areas up to 14 km away. Both peak and 24 h average PM2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further away from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations. Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (˜ 1200 km2). PM2.5 concentrations up to 169 µg m-3 were recorded on the morning following the fire. The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate concentrations (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night-time collapse of the plume from the 700 ha fire. This study provides a preliminary insight into the potential for large impacts from prescribed fire smoke to NSW communities and the need for increased accuracy in smoke dispersion modelling. More research is needed to better understand when and why such impacts might occur and provide better predictions of pollution risk.

Advancements in Hydrology and Erosion Process Understanding and Post-Fire Hydrologic and Erosion Model Development for Semi-Arid Landscapes

NASA Astrophysics Data System (ADS)

Williams, C. Jason; Pierson, Frederick B.; Al-Hamdan, Osama Z.; Robichaud, Peter R.; Nearing, Mark A.; Hernandez, Mariano; Weltz, Mark A.; Spaeth, Kenneth E.; Goodrich, David C.

2017-04-01

Fire activity continues to increase in semi-arid regions around the globe. Private and governmental land management entities are challenged with predicting and mitigating post-fire hydrologic and erosion responses on these landscapes. For more than a decade, a team of scientists with the US Department of Agriculture has collaborated on extensive post-fire hydrologic field research and the application of field research to development of post-fire hydrology and erosion predictive technologies. Experiments funded through this research investigated the impacts of fire on vegetation and soils and the effects of these fire-induced changes on infiltration, runoff generation, erodibility, and soil erosion processes. The distribution of study sites spans diverse topography across grassland, shrubland, and woodland landscapes throughout the western United States. Knowledge gleaned from the extensive field experiments was applied to develop and enhance physically-based models for hillslope- to watershed-scale runoff and erosion prediction. Our field research and subsequent data syntheses have identified key knowledge gaps and challenges regarding post-fire hydrology and erosion modeling. Our presentation details some consistent trends across a diverse domain and varying landscape conditions based on our extensive field campaigns. We demonstrate how field data have advanced our understanding of post-fire hydrology and erosion for semi-arid landscapes and highlight remaining key knowledge gaps. Lastly, we briefly show how our well-replicated experimental methodologies have contributed to advancements in hydrologic and erosion model development for the post-fire environment.

Modeling very large-fire occurrences over the continental United States from weather and climate forcing

Treesearch

R Barbero; J T Abatzoglou; E A Steel

2014-01-01

Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡­60 km spatial and weekly temporal resolutions using solely atmospheric...

Validating the Malheur model for predicting ponderosa pine post-fire mortality using 24 fires in the Pacific Northwest, USA

Treesearch

Walter G. Thies; Douglas J. Westlind

2012-01-01

Fires, whether intentionally or accidentally set, commonly occur in western interior forests of the US. Following fire, managers need the ability to predict mortality of individual trees based on easily observed characteristics. Previously, a two-factor model using crown scorch and bole scorch proportions was developed with data from 3415 trees for predicting the...

Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA

Treesearch

Thomas A. Spies; Eric White; Alan Ager; Jeffrey D. Kline; John P. Bolte; Emily K. Platt; Keith A. Olsen; Robert J. Pabst; Ana M. G. Barros; John D. Bailey; Susan Charnley; Anita T. Morzillo; Jennifer Koch; Michelle M. Steen-Adams; Peter H. Singleton; James Sulzman; Cynthia Schwartz; Blair Csuti

2017-01-01

Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern...

Simulated western spruce budworm defoliation reduces torching and crowning potential: A sensitivity analysis using a physics-based fire model

Treesearch

Gregory M. Cohn; Russell A. Parsons; Emily K. Heyerdahl; Daniel G. Gavin; Aquila Flower

2014-01-01

The widespread, native defoliator western spruce budworm (Choristoneura occidentalis Freeman) reduces canopy fuels, which might affect the potential for surface fires to torch (ignite the crowns of individual trees) or crown (spread between tree crowns). However, the effects of defoliation on fire behaviour are poorly understood. We used a physics-based fire model to...

Linking sediment-charcoal records and ecological modeling to understand causes of fire-regime change in boreal forests

Treesearch

Linda B. Brubaker; Philip E. Higuera; T. Scott Rupp; Mark A. Olson; Patricia M. Anderson; Feng Sheng. Hu

2009-01-01

Interactions between vegetation and fire have the potential to overshadow direct effects of climate change on fire regimes in boreal forests of North America. We develop methods to compare sediment-charcoal records with fire regimes simulated by an ecological model, ALFRESCO (Alaskan Frame-based Ecosystem Code) and apply these methods to evaluate potential causes of a...

Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning

Treesearch

Alan A. Ager; Nicole M. Vaillant; Mark A. Finney

2011-01-01

Wildland fire risk assessment and fuel management planning on federal lands in the US are complex problems that require state-of-the-art fire behavior modeling and intensive geospatial analyses. Fuel management is a particularly complicated process where the benefits and potential impacts of fuel treatments must be demonstrated in the context of land management goals...

EcoSmart Fire as structure ignition model in wildland urban interface: predictions and validations

Treesearch

Mark A. Dietenberger; Charles R. Boardman

2016-01-01

EcoSmartFire is a Windows program that models heat damage and piloted ignition of structures from radiant exposure to discrete landscaped tree fires. It calculates the radiant heat transfer from cylindrical shaped fires to the walls and roof of the structure while accounting for radiation shadowing, attenuation, and ground reflections. Tests of litter burn, a 0.6 m...

Sensitivity analysis of a FMC model for improving forecasting forest fires: Comparison with real fires in Spain

NASA Astrophysics Data System (ADS)

San Jose, Roberto; Perez, Juan Luis; Gonzalez-Barras, Rosa M.; Pecci, Julia; Palacios, Marino

2014-05-01

Forest fires continue to be a very dangerous and extreme violent episode jeopardizing the human lives and owns. Spain is plagued by forest and brush fires every summer, when extremely dry weather sets in along with high temperatures. The use of fire behavior models requires the availability of high resolution environmental and fuel data; in absence of realistic data, errors on the simulated fire spread con be compounded to produce o decrease of the spatial and temporal accuracy of predicted data. In this work we have carried out a sensitivity analysis of different components of the fire model and particularly the fuel moisture content (FMC) such as microphysics and solar radiation model. Three different real fire models have been used: Murcia (September, 7, 2010 19h09 and 9 hours duration), Gabiel (March, 7, 2007, 22h15 and 38 hours duration) and Culla (Marzo, 7, 2007, 23h36 and 37 hours duration). We use the 100 m European Corine Land Cover map. We use the WRF-Fire model developed by NCAR (USA). The WRF mode is run using the GFS global data and over the Iberian Peninsula with 15 km spatial resolution. We apply the nesting approach over the fires areas (located in the South East of the Iberian Peninsula) with 3 km, 1 km and 200 m spatial resolution. The Fire module included into WRF is run with 20 m spatial resolution and the landuse is interpolated from the Corine 100 m land use map. The results show that the Thompson et al. microphysics scheme and the RRTM solar radiation scheme are those with the best combination using a specific counting score to classify the goodness of the results compare with the real burned area. Those pixels not burned by the simulations but burned by the observational data sets are penalized double compare with the vice versa process. The NDVI obtained by satellite on the day of starting the fire is included in the simulations and a substantial improving in the final score is obtained.

Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

NASA Astrophysics Data System (ADS)

Yue, C.; Ciais, P.; Luyssaert, S.; Cadule, P.; Harden, J.; Randerson, J.; Bellassen, V.; Wang, T.; Piao, S. L.; Poulter, B.; Viovy, N.

2013-04-01

Stand-replacing fires are the dominant fire type in North American boreal forest and leave a historical legacy of a mosaic landscape of different aged forest cohorts. To accurately quantify the role of fire in historical and current regional forest carbon balance using models, one needs to explicitly simulate the new forest cohort that is established after fire. The present study adapted the global process-based vegetation model ORCHIDEE to simulate boreal forest fire CO2 emissions and follow-up recovery after a stand-replacing fire, with representation of postfire new cohort establishment, forest stand structure and the following self-thinning process. Simulation results are evaluated against three clusters of postfire forest chronosequence observations in Canada and Alaska. Evaluation variables for simulated postfire carbon dynamics include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index (LAI), and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). The model simulation results, when forced by local climate and the atmospheric CO2 history on each chronosequence site, generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with measurement accuracy (for CO2 flux ~100 g C m-2 yr-1, for biomass carbon ~1000 g C m-2 and for soil carbon ~2000 g C m-2). We find that current postfire forest carbon sink on evaluation sites observed by chronosequence methods is mainly driven by historical atmospheric CO2 increase when forests recover from fire disturbance. Historical climate generally exerts a negative effect, probably due to increasing water stress caused by significant temperature increase without sufficient increase in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon stocks evolution after fire, making it suitable for regional simulations in boreal regions where fire regimes play a key role on ecosystem carbon balance.

Analysis of weather condition influencing fire regime in Italy

NASA Astrophysics Data System (ADS)

Bacciu, Valentina; Masala, Francesco; Salis, Michele; Sirca, Costantino; Spano, Donatella

2014-05-01

Fires have a crucial role within Mediterranean ecosystems, with both negative and positive impacts on all biosphere components and with reverberations on different scales. Fire determines the landscape structure and plant composition, but it is also the cause of enormous economic and ecological damages, beside the loss of human life. In addition, several authors are in agreement suggesting that, during the past decades, changes on fire patterns have occurred, especially in terms of fire-prone areas expansion and fire season lengthening. Climate and weather are two of the main controlling agents, directly and indirectly, of fire regime influencing vegetation productivity, causing water stress, igniting fires through lightning, or modulating fire behavior through wind. On the other hand, these relationships could be not warranted in areas where most ignitions are caused by people (Moreno et al. 2009). Specific analyses of the driving forces of fire regime across countries and scales are thus still required in order to better anticipate fire seasons and also to advance our knowledge of future fire regimes. The objective of this work was to improve our knowledge of the relative effects of several weather variables on forest fires in Italy for the period 1985-2008. Meteorological data were obtained through the MARS (Monitoring Agricultural Resources) database, interpolated at 25x25 km scale. Fire data were provided by the JRC (Join Research Center) and the CFVA (Corpo Forestale e di Vigilanza Ambientale, Sardinia). A hierarchical cluster analysis, based on fire and weather data, allowed the identification of six homogeneous areas in terms of fire occurrence and climate (pyro-climatic areas). Two statistical techniques (linear and non-parametric models) were applied in order to assess if inter-annual variability in weather pattern and fire events had a significant trend. Then, through correlation analysis and multi-linear regression modeling, we investigated the influence of weather variables on fire activity across a range of time- and spatial-scales. The analysis revealed a general decrease of both number of fires and burned area, although not everywhere with the same magnitude. Overall, regression models where highly significant (p<0.001), and the explained variance ranged from 36% to 80% for fire number and from 37% to 76% for burned area, depending on pyro-climatic area. Moreover, our results contributed in determining the relative importance of climate variables acting at different timescales as control on intrinsic (i.e. flammability and moisture) and extrinsic (i.e. fuel amount and structure) characteristics of vegetation, thus strongly influencing fire occurrence. The good performance of our models, especially in the most fire affected pyro-climatic areas of Italy, and the better understanding of the main driver of fire variability gained through this work could be of great help for fire management among the different pyro-climatic areas.

Wild Fire Emissions for the NOAA Operational HYSPLIT Smoke Model

NASA Astrophysics Data System (ADS)

Huang, H. C.; ONeill, S. M.; Ruminski, M.; Shafran, P.; McQueen, J.; DiMego, G.; Kondragunta, S.; Gorline, J.; Huang, J. P.; Stunder, B.; Stein, A. F.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

2015-12-01

Particulate Matter (PM) generated from forest fires often lead to degraded visibility and unhealthy air quality in nearby and downstream areas. To provide near-real time PM information to the state and local agencies, the NOAA/National Weather Service (NWS) operational HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) smoke modeling system (NWS/HYSPLIT smoke) provides the forecast of smoke concentration resulting from fire emissions driven by the NWS North American Model 12 km weather predictions. The NWS/HYSPLIT smoke incorporates the U.S. Forest Service BlueSky Smoke Modeling Framework (BlueSky) to provide smoke fire emissions along with the input fire locations from the NOAA National Environmental Satellite, Data, and Information Service (NESDIS)'s Hazard Mapping System fire and smoke detection system. Experienced analysts inspect satellite imagery from multiple sensors onboard geostationary and orbital satellites to identify the location, size and duration of smoke emissions for the model. NWS/HYSPLIT smoke is being updated to use a newer version of USFS BlueSky. The updated BlueSky incorporates the Fuel Characteristic Classification System version 2 (FCCS2) over the continental U.S. and Alaska. FCCS2 includes a more detailed description of fuel loadings with additional plant type categories. The updated BlueSky also utilizes an improved fuel consumption model and fire emission production system. For the period of August 2014 and June 2015, NWS/HYSPLIT smoke simulations show that fire smoke emissions with updated BlueSky are stronger than the current operational BlueSky in the Northwest U.S. For the same comparisons, weaker fire smoke emissions from the updated BlueSky were observed over the middle and eastern part of the U.S. A statistical evaluation of NWS/HYSPLIT smoke predicted total column concentration compared to NOAA NESDIS GOES EAST Aerosol Smoke Product retrievals is underway. Preliminary results show that using the newer version of BlueSky leads to improved performance of NWS/HYSPLIT-smoke for June 2015. These results are partially due to the default fuel loading selected for Canadian fires that lead to stronger fire emissions there. The use of more realistic Canadian fuel loading may improve NWS/HYSPLIT smoke forecast.

Mitigating Large Fires in Drossel-Schwabl Forest Fire Models

NASA Astrophysics Data System (ADS)

Yoder, M.; Turcotte, D.; Rundle, J.; Morein, G.

2008-12-01

We employ variations of the traditional Drossel-Schwabl cellular automata Forest Fire Models (FFM) to study wildfire dynamics. The traditional FFM produces a very robust power law distribution of events, as a function of size, with frequency-size slope very close to -1. Observed data from Australia, the US and northern Mexico suggest that real wild fires closely follow power laws in frequency size with slopes ranging from close to -2 to -1.3 (B.D. Malamud et al. 2005). We suggest two models that, by fracturing and trimming large clusters, reduce the number of large fires while maintaining scale invariance. These fracturing and trimming processes can be justified in terms of real physical processes. For each model, we achieve slopes in the frequency-size relation ranging from approximately -1.77 to -1.06.

Tree injury and mortality in fires: developing process-based models

Treesearch

Bret W. Butler; Matthew B. Dickinson

2010-01-01

Wildland fire managers are often required to predict tree injury and mortality when planning a prescribed burn or when considering wildfire management options; and, currently, statistical models based on post-fire observations are the only tools available for this purpose. Implicit in the derivation of statistical models is the assumption that they are strictly...

A way forward for fire-caused tree mortality prediction: Modeling a physiological consequence of fire

Treesearch

Kathleen L. Kavanaugh; Matthew B. Dickinson; Anthony S. Bova

2010-01-01

Current operational methods for predicting tree mortality from fire injury are regression-based models that only indirectly consider underlying causes and, thus, have limited generality. A better understanding of the physiological consequences of tree heating and injury are needed to develop biophysical process models that can make predictions under changing or novel...

Modeling fire and other disturbance processes using LANDIS

Treesearch

Stephen R. Shifley; Jian Yang; Hong He

2009-01-01

LANDIS is a landscape decision support tool that models spatial relationships to help managers and planners examine the large-scale, long-term, cumulative effects of succession, harvesting, wildfire, prescribed fire, insects, and disease. It can operate on forest landscapes from a few thousand to a few million acres in extent. Fire modeling capabilities in LANDIS are...

Evaluating crown fire rate of spread predictions from physics-based models

Treesearch

C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont

2015-01-01

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...

Integrating models to predict regional haze from wildland fire.

Treesearch

D. McKenzie; S.M. O' Neill; N. Larkin; R.A. Norheim

2006-01-01

Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling...

Space-Based Sensorweb Monitoring of Wildfires in Thailand

NASA Technical Reports Server (NTRS)

Chien, Steve; Doubleday, Joshua; Mclaren, David; Davies, Ashley; Tran, Daniel; Tanpipat, Veerachai; Akaakara, Siri; Ratanasuwan, Anuchit; Mandl, Daniel

2011-01-01

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties.We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

Long-term temporal changes in the occurrence of a high forest fire danger in Finland

NASA Astrophysics Data System (ADS)

Mäkelä, H. M.; Laapas, M.; Venäläinen, A.

2012-08-01

Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June-August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908-2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

Modeling Payload Stowage Impacts on Fire Risks On-Board the International Space Station

NASA Technical Reports Server (NTRS)

Anton, Kellie e.; Brown, Patrick F.

2010-01-01

The purpose of this presentation is to determine the risks of fire on-board the ISS due to non-standard stowage. ISS stowage is constantly being reexamined for optimality. Non-standard stowage involves stowing items outside of rack drawers, and fire risk is a key concern and is heavily mitigated. A Methodology is needed to account for fire risk due to non-standard stowage to capture the risk. The contents include: 1) Fire Risk Background; 2) General Assumptions; 3) Modeling Techniques; 4) Event Sequence Diagram (ESD); 5) Qualitative Fire Analysis; 6) Sample Qualitative Results for Fire Risk; 7) Qualitative Stowage Analysis; 8) Sample Qualitative Results for Non-Standard Stowage; and 9) Quantitative Analysis Basic Event Data.

Linking Wildfire and Climate as Drivers of Plant Species and Community-level Change

NASA Astrophysics Data System (ADS)

Newingham, B. A.; Hudak, A. T.; Bright, B. C.

2015-12-01

Plant species distributions and community shifts after fire are affected by burn severity, elevation, aspect, and climate. However, little empirical data exists on long-term (decadal) recovery after fire across these interacting factors, limiting understanding of fire regime characteristics and climate in post-fire community trajectories. We examined plant species and community responses a decade after fire across five fires in ponderosa pine, dry mixed coniferous, and moist mixed coniferous forests across the western USA. Using field data, we determined changes in plant communities one and ten years post-fire across gradients of burn severity, elevation, and aspect. Existing published work has shown that plant species distributions can be accurately predicted from physiologically relevant climate variables using non-parametric Random Forests models; such models have also been linked to projected climate profiles in 2030, 2060, and 2090 generated from three commonly used general circulation models (GCMs). We explore the possibility that fire and climate are coupled drivers affecting plant species distributions. Climate change may not manifest as a slow shift in plant species distributions, but as sudden, localized events tied to changing fire and other disturbance regimes.

Climatic and anthropogenic drivers of northern Amazon fires during the 2015-2016 El Niño event.

PubMed

Fonseca, Marisa G; Anderson, Liana O; Arai, Egidio; Shimabukuro, Yosio E; Xaud, Haron A M; Xaud, Maristela R; Madani, Nima; Wagner, Fabien H; Aragão, Luiz E O C

2017-12-01

The strong El Niño Southern Oscillation (ENSO) event that occurred in 2015-2016 caused extreme drought in the northern Brazilian Amazon, especially in the state of Roraima, increasing fire occurrence. Here we map the extent of precipitation and fire anomalies and quantify the effects of climatic and anthropogenic drivers on fire occurrence during the 2015-2016 dry season (from December 2015 to March 2016) in the state of Roraima. To achieve these objectives we first estimated the spatial pattern of precipitation anomalies, based on long-term data from the TRMM (Tropical Rainfall Measuring Mission), and the fire anomaly, based on MODIS (Moderate Resolution Imaging Spectroradiometer) active fire detections during the referred period. Then, we integrated climatic and anthropogenic drivers in a Maximum Entropy (MaxEnt) model to quantify fire probability, assessing (1) the model accuracy during the 2015-2016 and the 2016-2017 dry seasons; (2) the relative importance of each predictor variable on the model predictive performance; and (3) the response curves, showing how each environmental variable affects the fire probability. Approximately 59% (132,900 km 2 ) of the study area was exposed to precipitation anomalies ≤-1 standard deviation (SD) in January and ~48% (~106,800 km 2 ) in March. About 38% (86,200 km 2 ) of the study area experienced fire anomalies ≥1 SD in at least one month between December 2015 and March 2016. The distance to roads and the direct ENSO effect on fire occurrence were the two most influential variables on model predictive performance. Despite the improvement of governmental actions of fire prevention and firefighting in Roraima since the last intense ENSO event (1997-1998), we show that fire still gets out of control in the state during extreme drought events. Our results indicate that if no prevention actions are undertaken, future road network expansion and a climate-induced increase in water stress will amplify fire occurrence in the northern Amazon, even in its humid dense forests. As an additional outcome of our analysis, we conclude that the model and the data we used may help to guide on-the-ground fire-prevention actions and firefighting planning and therefore minimize fire-related ecosystems degradation, economic losses and carbon emissions in Roraima. © 2017 by the Ecological Society of America.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Genet, Helene; McGuire, A. David; Barrett, K.

There is a substantial amount of carbon stored in the permafrost soils of boreal forest ecosystems, where it is currently protected from decomposition. The surface organic horizons insulate the deeper soil from variations in atmospheric temperature. The removal of these insulating horizons through consumption by fire increases the vulnerability of permafrost to thaw, and the carbon stored in permafrost to decomposition. In this study we ask how warming and fire regime may influence spatial and temporal changes in active layer and carbon dynamics across a boreal forest landscape in interior Alaska. To address this question, we (1) developed and testedmore » a predictive model of the effect of fire severity on soil organic horizons that depends on landscape-level conditions and (2) used this model to evaluate the long-term consequences of warming and changes in fire regime on active layer and soil carbon dynamics of black spruce forests across interior Alaska. The predictive model of fire severity, designed from the analysis of field observations, reproduces the effect of local topography (landform category, the slope angle and aspect and flow accumulation), weather conditions (drought index, soil moisture) and fire characteristics (day of year and size of the fire) on the reduction of the organic layercaused by fire. The integration of the fire severity model into an ecosystem process-based model allowed us to document the relative importance and interactions among local topography, fire regime and climate warming on active layer and soil carbon dynamics. Lowlands were more resistant to severe fires and climate warming, showing smaller increases in active layer thickness and soil carbon loss compared to drier flat uplands and slopes. In simulations that included the effects of both warming and fire at the regional scale, fire was primarily responsible for a reduction in organic layer thickness of 0.06 m on average by 2100 that led to an increase in active layer thickness of 1.1 m on average by 2100. The combination of warming and fire led to a simulated cumulative loss of 9.6 kgC m 2 on average by 2100. Our analysis suggests that ecosystem carbon storage in boreal forests in interior Alaska is particularly vulnerable, primarily due to the combustion of organic layer thickness in fire and the related increase in active layer thickness that exposes previously protected permafrost soil carbon to decomposition.« less

Predicting Fire Severity and Hydrogeomorphic Effects for Wildland Fire Decision Support

NASA Astrophysics Data System (ADS)

Hyde, K.; Woods, S. W.; Calkin, D.; Ryan, K.; Keane, R.

2007-12-01

The Wildland Fire Decision Support System (WFDSS) uses the Fire Spread Probability (FSPro) model to predict the spatial extent of fire, and to assess values-at-risk within probable spread zones. This information is used to support Appropriate Management Response (AMR), which involves decision making regarding fire-fighter deployment, fire suppression requirements, and identification of areas where fire may be safely permitted to take its course. Current WFDSS assessments are generally limited to a binary prediction of whether or not a fire will reach a given location and an assessment of the infrastructure which may be damaged or destroyed by fire. However, an emerging challenge is to expand the capabilities of WFDSS so that it also estimates the probable fire severity, and hence the effect on soil, vegetation and on hydrologic and geomorphic processes such as runoff and soil erosion. We present a conceptual framework within which derivatives of predictive fire modelling are used to predict impacts upon vegetation and soil, from which fire severity and probable post-fire watershed response can be inferred, before a fire actually occurs. Fire severity predictions are validated using Burned Area Reflectance Classification imagery. Recent tests indicate that satellite derived BARC images are a simple and effective means to predict post-fire erosion response based on relative vegetation disturbance. A fire severity prediction which reasonably approximates a BARC image may therefore be used to assess post-fire erosion and flood potential before fire reaches an area. This information may provide a new avenue of reliable support for fire management decisions.

Fire occurrence prediction in the Mediterranean: Application to Southern France

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Öster, Jan; Scherb, Anke; Straub, Daniel

2013-04-01

The areas that extend in the Mediterranean basin have a long fire history. The climatic conditions of wet winters and long hot drying summers support seasonal fire events, mainly ignited by humans. Extended land fragmentation hinders fire spread, but seasonal winds (e.g. Mistral in South France or Meltemia in Greece) can drive fire events to become uncontrollable fires with severe impacts to humans and the environment [1]. Prediction models in these areas should incorporate both natural and anthropogenic factors. Several indices have been developed worldwide to express fire weather conditions. The Canadian Fire Weather Index (FWI) is currently adapted by many countries in Europe due to the easily observable input weather parameters (temperature, wind speed, relative humidity, precipitation) and the easy-to-implement algorithms of the Canadian formulation describing fuel moisture relations [2],[3]. Human influence can be expressed directly by human presence (e.g. population density) or indirectly by proxy indicators (e.g. street density [4], land cover type). The random nature of fire occurrences and the uncertainties associated with the influencing factors motivate probabilistic prediction models. The aim of this study is to develop a prediction model of fire occurrence probability under natural and anthropogenic influence in Southern France and to compare it with earlier developed predictions in other Mediterranean areas [5]. Fire occurrence is modeled as a Poisson process. Two interpolation methods (Kriging and Inverse Distance Weighting) are used to interpolate daily weather observations from weather stations to a 1 km² spatial grid and their results are compared. Poisson regression estimates the parameters of the model and the resulting daily predictions are provided in terms of maps displaying fire occurrence rates. The model is applied to the regions Provence-Alpes-Côtes D'Azur und Languedoc-Roussillon in the South of France. Weather data are obtained from the German and French Weather Services (Deutscher Wetterdienst and Météo-France). Historical fire events are taken from Prométhée database. Time series 2000-2010 are used as learning data and data from 2011 is used as the validation data. The resulting model can support real-time fire risk estimation for improved allocation of firefighting resources and planning of other mitigation actions. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA, pp.515 [2] Lawson, B.D.; Armitage, O.B. (2008): Weather Guide for the Canadian Forest Fire Danger Rating System. Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, Alberta, Canada. [3] Van Wagner, C.E.; Pickett, T.L. (1985): Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System. Forestry Technical Report 33. Canadian Forestry Service, Government of Canada, Ottawa, Ontario, Canada [4] Syphard, A.D.; Radeloff, V.C.; Keuler, N.S.; Taylor, R.S.; Hawbaker, T.J.; Stewart, S.I.; Clayton, M.K. (2008): Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire, 17, pp.602-613 [5] Papakosta, P.; Klein, F.; König, S.; Straub, D. (2012): Linking spatio-temporal data to the Fire Weather Index to estimate the probability of wildfire in the Mediterranean. Geophysical Research Abstracts, Vol.14, EGU2012-12737, EGU General Assembly 2012

Modeling heat and moisture transport in firefighter protective clothing during flash fire exposure

NASA Astrophysics Data System (ADS)

Chitrphiromsri, Patirop; Kuznetsov, Andrey V.

2005-01-01

In this paper, a model of heat and moisture transport in firefighter protective clothing during a flash fire exposure is presented. The aim of this study is to investigate the effect of coupled heat and moisture transport on the protective performance of the garment. Computational results show the distribution of temperature and moisture content in the fabric during the exposure to the flash fire as well as during the cool-down period. Moreover, the duration of the exposure during which the garment protects the firefighter from getting second and third degree burns from the flash fire exposure is numerically predicted. A complete model for the fire-fabric-air gap-skin system is presented.

Simulating dynamic and mixed-severity fire regimes: a process-based fire extension for LANDIS-II

Treesearch

Brian R. Sturtevant; Robert M. Scheller; Brian R. Miranda; Douglas Shinneman; Alexandra Syphard

2009-01-01

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and...

Fire danger rating over Mediterranean Europe based on fire radiative power derived from Meteosat

NASA Astrophysics Data System (ADS)

Pinto, Miguel M.; DaCamara, Carlos C.; Trigo, Isabel F.; Trigo, Ricardo M.; Feridun Turkman, K.

2018-02-01

We present a procedure that allows the operational generation of daily forecasts of fire danger over Mediterranean Europe. The procedure combines historical information about radiative energy released by fire events with daily meteorological forecasts, as provided by the Satellite Application Facility for Land Surface Analysis (LSA SAF) and the European Centre for Medium-Range Weather Forecasts (ECMWF). Fire danger is estimated based on daily probabilities of exceedance of daily energy released by fires occurring at the pixel level. Daily probability considers meteorological factors by means of the Canadian Fire Weather Index (FWI) and is estimated using a daily model based on a generalized Pareto distribution. Five classes of fire danger are then associated with daily probability estimated by the daily model. The model is calibrated using 13 years of data (2004-2016) and validated against the period of January-September 2017. Results obtained show that about 72 % of events releasing daily energy above 10 000 GJ belong to the extreme class of fire danger, a considerably high fraction that is more than 1.5 times the values obtained when using the currently operational Fire Danger Forecast module of the European Forest Fire Information System (EFFIS) or the Fire Risk Map (FRM) product disseminated by the LSA SAF. Besides assisting in wildfire management, the procedure is expected to help in decision making on prescribed burning within the framework of agricultural and forest management practices.

Land cover, more than monthly fire weather, drives fire-size distribution in Southern Québec forests: Implications for fire risk management.

PubMed

Marchal, Jean; Cumming, Steve G; McIntire, Eliot J B

2017-01-01

Fire activity in North American forests is expected to increase substantially with climate change. This would represent a growing risk to human settlements and industrial infrastructure proximal to forests, and to the forest products industry. We modelled fire size distributions in southern Québec as functions of fire weather and land cover, thus explicitly integrating some of the biotic interactions and feedbacks in a forest-wildfire system. We found that, contrary to expectations, land-cover and not fire weather was the primary driver of fire size in our study region. Fires were highly selective on fuel-type under a wide range of fire weather conditions: specifically, deciduous forest, lakes and to a lesser extent recently burned areas decreased the expected fire size in their vicinity compared to conifer forest. This has large implications for fire risk management in that fuels management could reduce fire risk over the long term. Our results imply, for example, that if 30% of a conifer-dominated landscape were converted to hardwoods, the probability of a given fire, occurring in that landscape under mean fire weather conditions, exceeding 100,000 ha would be reduced by a factor of 21. A similarly marked but slightly smaller effect size would be expected under extreme fire weather conditions. We attribute the decrease in expected fire size that occurs in recently burned areas to fuel availability limitations on fires spread. Because regenerating burned conifer stands often pass through a deciduous stage, this would also act as a negative biotic feedback whereby the occurrence of fires limits the size of nearby future for some period of time. Our parameter estimates imply that changes in vegetation flammability or fuel availability after fires would tend to counteract shifts in the fire size distribution favoring larger fires that are expected under climate warming. Ecological forecasts from models neglecting these feedbacks may markedly overestimate the consequences of climate warming on fire activity, and could be misleading. Assessments of vulnerability to climate change, and subsequent adaptation strategies, are directly dependent on integrated ecological forecasts. Thus, we stress the need to explicitly incorporate land-cover's direct effects and feedbacks in simulation models of coupled climate-fire-fuels systems.

Fire and Heat Spreading Model Based on Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Samartsev, A. A.; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Fominykh, D. S.

2018-05-01

The distinctive feature of the proposed fire and heat spreading model in premises is the reduction of the computational complexity due to the use of the theory of cellular automata with probability rules of behavior. The possibilities and prospects of using this model in practice are noted. The proposed model has a simple mechanism of integration with agent-based evacuation models. The joint use of these models could improve floor plans and reduce the time of evacuation from premises during fires.

A review of the main driving factors of forest fire ignition over Europe.

PubMed

Ganteaume, Anne; Camia, Andrea; Jappiot, Marielle; San-Miguel-Ayanz, Jesus; Long-Fournel, Marlène; Lampin, Corinne

2013-03-01

Knowledge of the causes of forest fires, and of the main driving factors of ignition, is an indispensable step towards effective fire prevention policies. This study analyses the factors driving forest fire ignition in the Mediterranean region including the most common human and environmental factors used for modelling in the European context. Fire ignition factors are compared to spatial and temporal variations of fire occurrence in the region, then are compared to results obtained in other areas of the world, with a special focus on North America (US and Canada) where a significant number of studies has been carried out on this topic. The causes of forest fires are varied and their distribution differs among countries, but may also differ spatially and temporally within the same country. In Europe, and especially in the Mediterranean basin, fires are mostly human-caused mainly due arson. The distance to transport networks and the distance to urban or recreation areas are among the most frequently used human factors in modelling exercises and the Wildland-Urban Interface is increasingly taken into account in the modelling of fire occurrence. Depending on the socio-economic context of the region concerned, factors such as the unemployment rate or variables linked to agricultural activity can explain the ignition of intentional and unintentional fires. Regarding environmental factors, those related to weather, fuel and topography are the most significant drivers of ignition of forest fires, especially in Mediterranean-type regions. For both human and lightning-caused fires, there is a geographical gradient of fire ignition, mainly due to variations in climate and fuel composition but also to population density for instance. The timing of fires depends on their causes. In populated areas, the timing of human-caused fires is closely linked to human activities and peaks in the afternoon whereas, in remote areas, the timing of lightning-caused fires is more linked to weather conditions and the season, with most such fires occurring in summer.

A Review of the Main Driving Factors of Forest Fire Ignition Over Europe

NASA Astrophysics Data System (ADS)

Ganteaume, Anne; Camia, Andrea; Jappiot, Marielle; San-Miguel-Ayanz, Jesus; Long-Fournel, Marlène; Lampin, Corinne

2013-03-01

Knowledge of the causes of forest fires, and of the main driving factors of ignition, is an indispensable step towards effective fire prevention policies. This study analyses the factors driving forest fire ignition in the Mediterranean region including the most common human and environmental factors used for modelling in the European context. Fire ignition factors are compared to spatial and temporal variations of fire occurrence in the region, then are compared to results obtained in other areas of the world, with a special focus on North America (US and Canada) where a significant number of studies has been carried out on this topic. The causes of forest fires are varied and their distribution differs among countries, but may also differ spatially and temporally within the same country. In Europe, and especially in the Mediterranean basin, fires are mostly human-caused mainly due arson. The distance to transport networks and the distance to urban or recreation areas are among the most frequently used human factors in modelling exercises and the Wildland-Urban Interface is increasingly taken into account in the modelling of fire occurrence. Depending on the socio-economic context of the region concerned, factors such as the unemployment rate or variables linked to agricultural activity can explain the ignition of intentional and unintentional fires. Regarding environmental factors, those related to weather, fuel and topography are the most significant drivers of ignition of forest fires, especially in Mediterranean-type regions. For both human and lightning-caused fires, there is a geographical gradient of fire ignition, mainly due to variations in climate and fuel composition but also to population density for instance. The timing of fires depends on their causes. In populated areas, the timing of human-caused fires is closely linked to human activities and peaks in the afternoon whereas, in remote areas, the timing of lightning-caused fires is more linked to weather conditions and the season, with most such fires occurring in summer.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling

PubMed Central

2013-01-01

Background A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Methods Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. Results The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. Conclusions The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data. PMID:24192051

The study of soils and vegetation transformation due fire disturbances in remote areas through scenario modelling of observed hydrological response to fire impact

NASA Astrophysics Data System (ADS)

Nesterova, Natalia; Semenova, Olga; Lebedeva, Luidmila

2015-04-01

Large territories of Siberia and Russian Far East are the subject to frequent forest fires. Often there is no information available about fire impact except its timing, areal distribution and qualitative characteristics of fire severity. Observed changes of hydrological response in burnt watersheds can be considered as indirect evidence of soil and vegetation transformation due to fire impact. In our study we used MODIS Fire products to detect spatial distribution of fires in Transbaikal and Far East regions of Russia in 2000 - 2012 period. Small and middle-size watersheds (with area up to 10000 km2) affected by extensive (burn area not less than 20 %) fires were chosen. We analyzed available hydrological data (measured discharges in watersheds outlets) for chosen basins. In several cases apparent hydrological response to fire was detected. To investigate main factors causing the change of hydrologic regime after fire several scenarios of soil and vegetation transformation were developed for each watershed under consideration. Corresponding sets of hydrological model parameters describing those transformations were elaborated based on data analysis and post-fire landscape changes as derived from a literature review. We implied different factors such as removal of organic layer, albedo changes, intensification of soil thaw (in presence of permafrost and seasonal soil freezing), reduction of infiltration rate and evapotranspiration, increase of upper subsurface flow fraction in summer flood events following the fire and others. We applied Hydrograph model (Russia) to conduct simulation experiments aiming to reveal which landscape changes scenarios were more plausible. The advantages of chosen hydrological model for this study are 1) that it takes into consideration thermal processes in soils which in case of permafrost and seasonal soil freezing presence can play leading role in runoff formation and 2) that observable vegetation and soil properties are used as its parameters allowing minimal resort to calibration. The model can use dynamic set of parameters performing preassigned abrupt and/or gradual changes of landscape characteristics. Interestingly, based on modelling results it can be concluded that depending on dominant landscape different aspects of soil and vegetation cover changes may influence runoff formation in contrasting way. The results of the study will be reported.

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting thosemore » into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.« less

A numerical study of atmospheric perturbations induced by heat from a wildland fire: sensitivity to vertical canopy structure and heat source strength

Treesearch

Michael T. Kiefer; Shiyuan Zhong; Warren E. Heilman; Joseph J. Charney; Xindi Bian

2018-01-01

An improved understanding of atmospheric perturbations within and above a forest during a wildland fire has relevance to many aspects of wildland fires including fire spread, smoke transport and dispersion, and tree mortality. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization, is...

A case study comparison of landfire fuel loading and emissions generation on a mixed conifer forest in northern Idaho, USA

Treesearch

Josh Hyde; Eva K. Strand; Andrew T. Hudak; Dale Hamilton

2015-01-01

The use of fire as a land management tool is well recognized for its ecological benefits in many natural systems. To continue to use fire while complying with air quality regulations, land managers are often tasked with modeling emissions from fire during the planning process. To populate such models, the Landscape Fire and Resource Management Planning Tools (...

Fuels planning: science synthesis and integration; environmental consequences fact sheet 09: Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS)

Treesearch

Elizabeth Reinhardt

2005-01-01

FFE-FVS is a model linking stand development, fuel dynamics, fire behavior and fire effects. It allows comparison of mid- to long-term effects of management alternatives including harvest, mechanical fuel treatment, prescribed fire, salvage, and no action. This fact sheet identifies the intended users and uses, required inputs, what the model does, and tells the user...

Modelling global CO2 emissions into the atmosphere from crown, ground, and peat fires

NASA Astrophysics Data System (ADS)

Eliseev, Alexey V.; Mokhov, Igor I.; Chernokulsky, Alexander V.

2015-04-01

The scheme for natural fires implemented in the climate model (CM) developed at the A.M. Obukhov Institute of Atmospheric Physics (IAP RAS) is extended by a module accounting for ground and peat fires. With the IAP RAS CM, the simulations are performed for 1700-2300 in accordance with the CMIP5 (Coupled Models Intercomparison Project, phase 5) protocol. The modelled present-day burnt area, BA, and the corresponding CO2 emissions into the atmosphere E agree with the GFED-3.1 estimates at most regions. In the 21st century, under the RCP (Representative Concentration Pathways) scenarios, the global BA increases by 10-41% depending on scenario, and E increases by 11-39%. Under the mitigation scenario RCP 2.6, both BA and E slightly decrease in the 22nd-23rd centuries. For scenarios RCP 4.5, RCP 6.0, and RCP 8.5, they continue to increase in these two centuries. All these changes are mostly due to changes in natural fires activity in the boreal regions. Ground and peat fires contribute significantly to the total emissions of CO2 from natural fires (20-25% at the global scale depending on scenario and calendar year). Peat fires markedly intensify interannual variability of regional CO2 emissions from natural fires.

Pyro-eco-hydrologic feedbacks and catchment co-evolution in fire-prone forested uplands

NASA Astrophysics Data System (ADS)

Sheridan, Gary; Inbar, Assaf; Lane, Patrick; Nyman, Petter

2017-04-01

The south east Australian forested uplands are characterized by complex and inter-correlated spatial patterns in standing biomass, soil depth/quality, and fire regimes, even within areas with similar rainfall, geology and catenary position. These system properties have traditionally been investigated independently, however recent research in the areas of post fire hydrology and erosion, and new insights into forest structure, fuel moisture, and flammability, suggest the presence of critical co-evolutionary feedbacks between fire, soils and vegetation that may explain the observed system states. To test this hypothesis we started with a published ecohydrologic model, modifying and extending the algorithms to capture feedbacks between hyrology and fire, and between fire, vegetation and soil production and erosion. The model was parameterized and calibrated with new data from instrumented forested hillslopes across energy and rainfall gradients generated by selecting sites with a range of aspect (energy) and elevation (rainall). The calibrated model was able to reasonably replicate the observed patterns of standing biomass, water balance, fire interval, and soil depth. The catchment co-evolution/feedback modelling approach to understanding patterns of vegetation, soils and fire regimes provides a promising new paradigm for predicting the response of forested se Australian catchments to declining rainfall and increasing temperatures under climate change.

Fire technology abstracts, volume 4. Cumulative indexes

NASA Astrophysics Data System (ADS)

1982-03-01

Cumulative subject, author, publisher, and report number indexes referencing articles, books, reports, and patents are provided. The dynamics of fire, behavior and properties of materials, fire modeling and test burns, fire protection, fire safety, fire service organization, apparatus and equipment, fire prevention suppression, planning, human behavior, medical problems, codes and standards, hazard identification, safe handling of materials, and insurance economics of loss and prevention are among the subjects covered.

NEW IMPROVEMENTS TO MFIRE TO ENHANCE FIRE MODELING CAPABILITIES.

PubMed

Zhou, L; Smith, A C; Yuan, L

2016-06-01

NIOSH's mine fire simulation program, MFIRE, is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines, which has been used by U.S. and international companies to simulate fires for planning and response purposes. MFIRE is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence such as changes in ventilation parameters, external influences such as changes in temperature, and internal influences such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the Bureau of Mines in the 1970s, several updates have been released over the years. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE's outdated FORTRAN programming language was replaced with an object-oriented C++ language and packaged into a dynamic link library (DLL). However, the MFIRE 3.0 release made no attempt to change or improve the fire modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of fire source models of the t-squared fire and heat release rate curve data file, the addition of a moving fire source for conveyor belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke rollback phenomena. All the improvements discussed in this paper will be termed as MFIRE 3.1 and released by NIOSH in the near future.

Sensitivity of ALOS/PALSAR imagery to forest degradation by fire in northern Amazon

NASA Astrophysics Data System (ADS)

Martins, Flora da Silva Ramos Vieira; dos Santos, João Roberto; Galvão, Lênio Soares; Xaud, Haron Abrahim Magalhães

2016-07-01

We evaluated the sensitivity of the full polarimetric Phased Array type L-band Synthetic Aperture Radar (PALSAR), onboard the Advanced Land Observing Satellite (ALOS), to forest degradation caused by fires in northern Amazon, Brazil. We searched for changes in PALSAR signal and tri-dimensional polarimetric responses for different classes of fire disturbance defined by fire frequency and severity. Since the aboveground biomass (AGB) is affected by fire, multiple regression models to estimate AGB were obtained for the whole set of coherent and incoherent attributes (general model) and for each set separately (specific models). The results showed that the polarimetric L-band PALSAR attributes were sensitive to variations in canopy structure and AGB caused by forest fire. However, except for the unburned and thrice burned classes, no single PALSAR attribute was able to discriminate between the intermediate classes of forest degradation by fire. Both the coherent and incoherent polarimetric attributes were important to explain AGB variations in tropical forests affected by fire. The HV backscattering coefficient, anisotropy, double-bounce component, orientation angle, volume index and HH-VV phase difference were PALSAR attributes selected from multiple regression analysis to estimate AGB. The general regression model, combining phase and power radar metrics, presented better results than specific models using coherent or incoherent attributes. The polarimetric responses indicated the dominance of VV-oriented backscattering in primary forest and lightly burned forests. The HH-oriented backscattering predominated in heavily and frequently burned forests. The results suggested a greater contribution of horizontally arranged constituents such as fallen trunks or branches in areas severely affected by fire.

Implications of emission inventory choice for modeling fire-related pollution in the U.S.

NASA Astrophysics Data System (ADS)

Koplitz, S. N.; Nolte, C. G.; Pouliot, G.

2017-12-01

Wildland fires are a major source of fine particulate matter (PM2.5), one of the most harmful ambient pollutants for human health globally. Within the U.S., wildland fires can account for more than 30% of total annual PM2.5 emissions. In order to represent the influence of fire emissions on atmospheric composition, regional and global chemical transport models (CTMs) rely on fire emission inventories developed from estimates of burned area (i.e. fire size and location). Burned area can be estimated using a range of top-down and bottom-up approaches, including satellite-derived remote sensing and on-the-ground incident reports. While burned area estimates agree with each other reasonably well in the western U.S. (within 20-30% for most years during 2002-2014), estimates for the southern U.S. vary by more than a factor of 3. Differences in burned area estimation methods lead to significant variability in the spatial and temporal allocation of emissions across fire emission inventory platforms. In this work, we implement fire emission estimates for 2011 from three different products - the USEPA National Emission Inventory (NEI), the Fire INventory of NCAR (FINN), and the Global Fire Emission Database (GFED4s) - into the Community Multiscale Air Quality (CMAQ) model to quantify and characterize differences in simulated fire-related PM2.5 and ozone concentrations across the contiguous U.S. due solely to the emission inventory used. Preliminary results indicate that the estimated contribution to national annual average PM2.5 from wildland fire in 2011 is highest using GFED4s emissions (1.0 µg m-3) followed by NEI (0.7 µg m-3) and FINN (0.3 µg m-3), with comparisons varying significantly by region and season. Understanding the sensitivity of modeling fire-related PM2.5 and ozone in the U.S. to fire emission inventory choice will inform future efforts to assess the implications of present and future fire activity for air quality and human health at national and global scales.

Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular

NASA Astrophysics Data System (ADS)

Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.

2015-12-01

The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had meaningful result with artificial and natural effect. It is expected to predict future forest fire risk with future climate variables as the climate changes.

Fire modeling in a nonventilated corridor

NASA Astrophysics Data System (ADS)

Lulea, Marius Dorin; Iordache, Vlad; Năstase, Ilinca

2018-02-01

The main objective of this study was to determine the effect of fire in a nonventilated corridor. A real-scale model of a corridor has been modeled in Fire Dynamics Simulator(F.D.S.) in order to determine the evolution of indoor temperatures, the visibility and the oxygen quantities during a fire. The start time of a sprinkler has also been determined. The use of sprinklers in buildings has become a necessity and a requirement imposed by technical norms. The provision of this type of installation has become a common feature in buildings with a high fire risk, with two main effects: fire extinction and protection of structural and partition elements from high temperatures[15]. The ultimate goal is to ensure optimal conditions for saving the building users, intervention teams and maintaining the stability of the building. Low temperatures and good visibility on the escape routes during a fire are the basic conditions to ensure the optimal evacuation of users.

Simulation of the FRP Product

NASA Astrophysics Data System (ADS)

Paugam, Ronan; Wooster, Martin; Johnston, Joshua; Gastellu-Etchegorry, Jean-Philippe

2014-05-01

Among the different alternative of remote sensing technologies for estimating global fire carbon emission, the thermally-based measures of fire radiative power (FRP; and its temporal integration, fire radiative energy or FRE) has the potential to capture the spatial and temporal variability of fire occurrence. It was shown that a strong linear relationship exists between the total amount of thermal radiant energy emitted by a fire over its lifetime (the FRE) and the amount of fuel burned. Since all vegetation is 50(±5)% carbon, it is therefore in theory a potentially simple matter to measure the FRE and estimate the carbon release. In a fire inventory like the Global Fire Assimilation System (GFAS), the total carbon emission is derived from a gridded FRE product forced by the MODIS observation, using Ct = β x FRE x Ef, where β is a conversion factor initially estimated from small scale experiment as β=0.368 and later derived for different bio dome by comparison with the Global Fire Emission Database (GFED). The sensitivities of the above equation to (i) different types of fire activity (ie, flaming, smoldering, torching), (ii) sensor view angles or (iii) soot/smoke absorption have not yet been well studied. The investigation of these types of sensitivity, and of the information content of thermal IR observations of actively burning fires in general, is one of the primary subjects of this study. Our approach is based on a combination of observational work and simulations conducted via the linkage of different fire models and the 3D radiative transfer (RT) model DART operating in the thermal domain. The radiation properties of a fire as seen from above its plume (e.g. space/air borne sensor) depend on the temperature distribution, the gas concentration (mainly CO2, H2O), and the amount, shape, distribution and optical properties of the soot particles in the flame (where they are emitting) and in the cooling plume (where they are mainly absorbing). While gas and soot radiative properties can be estimated from the literature, their concentration and temperature are calculated from output of fire models. Due to the large range of length scale involved in fire dynamics, a twofold approach is use to model the fire scene with (i) first the multi-phases model WFDS which can handle fire size ranging from a 1m2 to 1ha with a particular focus on flame-plume interaction, (ii) and then the meso scale model WRF-fire which can handle larger fires and the interaction plume-atmosphere (e.g. pyroconvection). In the former case, as the Radiative Transfer is WFDS is based on a Gray Body assumption (WFDS only focuses on fire dynamics) the main challenge is to derive the radiative properties of the different component of the fire scene (soot and gas) for the different bands (optical and IR) solved in DART to re-process a multispectral RT. In the later case, because WRF-fire is running at a resolution of tens of meters, pyrolysis and combustion processes cannot be resolved and to predict the fire front dynamics, the use of an empirical model based on the Rothermel equation and the level set method is required. In this later case, it is therefore necessary to use empirical relationship to determine: (i) the 3D structure of the flame defined by: flame length, flame height and fire front depth derived from Rate of Spread and residence time, (ii) the gas and soot concentration profile within the flame, and (iii) the convective flux generated by the flame. The development of these empirical relationships presents one of the main challenges of this work. Thought this work is still undergoing, first results show the potential impact of view angle on the evaluation of FRP.

Land cover, more than monthly fire weather, drives fire-size distribution in Southern Québec forests: Implications for fire risk management

PubMed Central

Marchal, Jean; Cumming, Steve G.; McIntire, Eliot J. B.

2017-01-01

Fire activity in North American forests is expected to increase substantially with climate change. This would represent a growing risk to human settlements and industrial infrastructure proximal to forests, and to the forest products industry. We modelled fire size distributions in southern Québec as functions of fire weather and land cover, thus explicitly integrating some of the biotic interactions and feedbacks in a forest-wildfire system. We found that, contrary to expectations, land-cover and not fire weather was the primary driver of fire size in our study region. Fires were highly selective on fuel-type under a wide range of fire weather conditions: specifically, deciduous forest, lakes and to a lesser extent recently burned areas decreased the expected fire size in their vicinity compared to conifer forest. This has large implications for fire risk management in that fuels management could reduce fire risk over the long term. Our results imply, for example, that if 30% of a conifer-dominated landscape were converted to hardwoods, the probability of a given fire, occurring in that landscape under mean fire weather conditions, exceeding 100,000 ha would be reduced by a factor of 21. A similarly marked but slightly smaller effect size would be expected under extreme fire weather conditions. We attribute the decrease in expected fire size that occurs in recently burned areas to fuel availability limitations on fires spread. Because regenerating burned conifer stands often pass through a deciduous stage, this would also act as a negative biotic feedback whereby the occurrence of fires limits the size of nearby future for some period of time. Our parameter estimates imply that changes in vegetation flammability or fuel availability after fires would tend to counteract shifts in the fire size distribution favoring larger fires that are expected under climate warming. Ecological forecasts from models neglecting these feedbacks may markedly overestimate the consequences of climate warming on fire activity, and could be misleading. Assessments of vulnerability to climate change, and subsequent adaptation strategies, are directly dependent on integrated ecological forecasts. Thus, we stress the need to explicitly incorporate land-cover’s direct effects and feedbacks in simulation models of coupled climate–fire–fuels systems. PMID:28609467

Influence of Fire Mosaics, Habitat Characteristics and Cattle Disturbance on Mammals in Fire-Prone Savanna Landscapes of the Northern Kimberley.

PubMed

Radford, Ian J; Gibson, Lesley A; Corey, Ben; Carnes, Karin; Fairman, Richard

2015-01-01

Patch mosaic burning, in which fire is used to produce a mosaic of habitat patches representative of a range of fire histories ('pyrodiversity'), has been widely advocated to promote greater biodiversity. However, the details of desired fire mosaics for prescribed burning programs are often unspecified. Threatened small to medium-sized mammals (35 g to 5.5 kg) in the fire-prone tropical savannas of Australia appear to be particularly fire-sensitive. Consequently, a clear understanding of which properties of fire mosaics are most instrumental in influencing savanna mammal populations is critical. Here we use mammal capture data, remotely sensed fire information (i.e. time since last fire, fire frequency, frequency of late dry season fires, diversity of post-fire ages in 3 km radius, and spatial extent of recently burnt, intermediate and long unburnt habitat) and structural habitat attributes (including an index of cattle disturbance) to examine which characteristics of fire mosaics most influence mammals in the north-west Kimberley. We used general linear models to examine the relationship between fire mosaic and habitat attributes on total mammal abundance and richness, and the abundance of the most commonly detected species. Strong negative associations of mammal abundance and richness with frequency of late dry season fires, the spatial extent of recently burnt habitat (post-fire age <1 year within 3 km radius) and level of cattle disturbance were observed. Shrub cover was positively related to both mammal abundance and richness, and availability of rock crevices, ground vegetation cover and spatial extent of ≥4 years unburnt habitat were all positively associated with at least some of the mammal species modelled. We found little support for diversity of post-fire age classes in the models. Our results indicate that both a high frequency of intense late dry season fires and extensive, recently burnt vegetation are likely to be detrimental to mammals in the north Kimberley. A managed fire mosaic that reduces large scale and intense fires, including the retention of ≥4 years unburnt patches, will clearly benefit savanna mammals. We also highlighted the importance of fire mosaics that retain sufficient shelter for mammals. Along with fire, it is clear that grazing by introduced herbivores also needs to be reduced so that habitat quality is maintained.

WRF-based fire risk modelling and evaluation for years 2010 and 2012 in Poland

NASA Astrophysics Data System (ADS)

Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej

2016-04-01

Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The year 2010 was characterized by the smallest number of wildfires and burnt area whereas 2012 - by the biggest number of fires and the largest area of conflagration. The data about time, localization, scale and causes of individual wildfire occurrence in given years are taken from the National Forest Fire Information System (KSIPL), administered by Forest Fire Protection Department of Polish Forest Research Institute. The database is a part of European Forest Fire Information System (EFFIS). Basing on this data and on the WRF-based fire risk modelling we intend to achieve the second goal of the study, which is the evaluation of the forecasted fire risk with an occurrence of wildfires. Special attention is paid here to the number, time and the spatial distribution of wildfires occurred in cases of low-level predicted fire risk. Results obtained reveals the effectiveness of the new forecasting method. The outcome of our investigation allows to draw a conclusion that some adjustments are possible to improve the efficiency on the fire-risk estimation method.

Consequence modeling using the fire dynamics simulator.

PubMed

Ryder, Noah L; Sutula, Jason A; Schemel, Christopher F; Hamer, Andrew J; Van Brunt, Vincent

2004-11-11

The use of Computational Fluid Dynamics (CFD) and in particular Large Eddy Simulation (LES) codes to model fires provides an efficient tool for the prediction of large-scale effects that include plume characteristics, combustion product dispersion, and heat effects to adjacent objects. This paper illustrates the strengths of the Fire Dynamics Simulator (FDS), an LES code developed by the National Institute of Standards and Technology (NIST), through several small and large-scale validation runs and process safety applications. The paper presents two fire experiments--a small room fire and a large (15 m diameter) pool fire. The model results are compared to experimental data and demonstrate good agreement between the models and data. The validation work is then extended to demonstrate applicability to process safety concerns by detailing a model of a tank farm fire and a model of the ignition of a gaseous fuel in a confined space. In this simulation, a room was filled with propane, given time to disperse, and was then ignited. The model yields accurate results of the dispersion of the gas throughout the space. This information can be used to determine flammability and explosive limits in a space and can be used in subsequent models to determine the pressure and temperature waves that would result from an explosion. The model dispersion results were compared to an experiment performed by Factory Mutual. Using the above examples, this paper will demonstrate that FDS is ideally suited to build realistic models of process geometries in which large scale explosion and fire failure risks can be evaluated with several distinct advantages over more traditional CFD codes. Namely transient solutions to fire and explosion growth can be produced with less sophisticated hardware (lower cost) than needed for traditional CFD codes (PC type computer verses UNIX workstation) and can be solved for longer time histories (on the order of hundreds of seconds of computed time) with minimal computer resources and length of model run. Additionally results that are produced can be analyzed, viewed, and tabulated during and following a model run within a PC environment. There are some tradeoffs, however, as rapid computations in PC's may require a sacrifice in the grid resolution or in the sub-grid modeling, depending on the size of the geometry modeled.

Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooke, William H.; Mostovoy, Georgy; Anantharaj, Valentine G

2012-01-01

Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year meanmore » (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence probability over this region.« less

A model of gas mixing into single-entrance tree cavities during wildland fires

Treesearch

A.S. Bova; G. Bohrer; Matthew Dickinson

2011-01-01

The level of protection to fauna provided by tree cavities during wildland fires is not well understood. Here we present a model for estimating the transport of combustion gases into cylindrical, single-entrance cavities during exposures caused by different wildland fire scenarios. In these shelters, the entrance occurs near the top of the cavity. This empirical model...

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

Comparison of Fire Model Predictions with Experiments Conducted in a Hangar With a 15 Meter Ceiling

NASA Technical Reports Server (NTRS)

Davis, W. D.; Notarianni, K. A.; McGrattan, K. B.

1996-01-01

The purpose of this study is to examine the predictive capabilities of fire models using the results of a series of fire experiments conducted in an aircraft hangar with a ceiling height of about 15 m. This study is designed to investigate model applicability at a ceiling height where only a limited amount of experimental data is available. This analysis deals primarily with temperature comparisons as a function of distance from the fire center and depth beneath the ceiling. Only limited velocity measurements in the ceiling jet were available but these are also compared with those models with a velocity predictive capability.

A combustion model of vegetation burning in "Tiger" fire propagation tool

NASA Astrophysics Data System (ADS)

Giannino, F.; Ascoli, D.; Sirignano, M.; Mazzoleni, S.; Russo, L.; Rego, F.

2017-11-01

In this paper, we propose a semi-physical model for the burning of vegetation in a wildland fire. The main physical-chemical processes involved in fire spreading are modelled through a set of ordinary differential equations, which describe the combustion process as linearly related to the consumption of fuel. The water evaporation process from leaves and wood is also considered. Mass and energy balance equations are written for fuel (leaves and wood) assuming that combustion process is homogeneous in space. The model is developed with the final aim of simulating large-scale wildland fires which spread on heterogeneous landscape while keeping the computation cost very low.

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

USGS Publications Warehouse

Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

2013-01-01

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Modeling of fire smoke movement in multizone garments building using two open source platforms

NASA Astrophysics Data System (ADS)

Khandoker, Md. Arifur Rahman; Galib, Musanna; Islam, Adnan; Rahman, Md. Ashiqur

2017-06-01

Casualty of garment factory workers from factory fire in Bangladesh is a recurring tragedy. Smoke, which is more fatal than fire itself, often propagates through different pathways from lower to upper floors during building fire. Among the toxic gases produced from a building fire, carbon monoxide (CO) can be deadly, even in small amounts. This paper models the propagation and transportation of fire induced smoke (CO) that resulted from the burning of synthetic polyester fibers using two open source platforms, CONTAM and Fire Dynamics Simulator (FDS). Smoke migration in a generic multistoried garment factory building in Bangladesh is modeled using CONTAM where each floor is compartmentalized by different zones. The elevator and stairway shafts are modeled by phantom zones to simulate contaminant (CO) transport from one floor to upper floors. FDS analysis involves burning of two different stacks of polyester jacket of six feet height and with a maximum heat release rate per unit area of 1500kw/m2 over a storage area 50m2 and 150m2, respectively. The resulting CO generation and removal rates from FDS are used in CONTAM to predict fire-borne CO propagation in different zones of the garment building. Findings of the study exhibit that the contaminant flow rate is a strong function of the position of building geometry, location of initiation of fire, amount of burnt material, presence of AHU and contaminant generation and removal rate of CO from the source location etc. The transport of fire-smoke in the building Hallways, stairways and lifts are also investigated in detail to examine the safe egress of the occupants in case of fire.

Impact of air quality in Mexico City due to particles smaller than ten microns (PM10) by wildland fire in "Cumbres del Ajusco Park" for the year 2013

NASA Astrophysics Data System (ADS)

Mendoza, A.; Garcia-Reynoso, J. A.; Ruiz-Suárez, L. G.; Torres, R.; Castro, T.; Peralta, O.; Padilla Barrera, Z. V.; Mar, B.; Carbajal, J. N.

2014-12-01

A forest fire is a natural process of combustion in a specific geographical area, its occurrence depends on meteorological variables, topography and vegetation type, the wildland fires are potential sources of large amounts of pollutants. The main air pollutants are in a wildland fires particles (PM10 and PM2.5) Carbon Monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOC's) and a negligible amount of sulfur dioxide (SO2) (Chow 1995), Was performed a study of the environmental impact on air quality in Mexico city for a wildland fire. The fire was presented in Cumbres del Ajusco Park on April 14 for the year 2013, with a duration of 26 hours and consuming an extension 150 ha of pasture, WRF-Chem and WRF-fire model were used to conduct the study, two modeling scenarios were made, one including emissions from wildfire and other without emission-fire, comparison is made between the two modeling scenarios in order to calculate on air quality in Mexico cityPM10 concentrations have a larger impact on the air quality of Mexico city, when fire emission were included, a plume of PM10 coming from fire increase ambient concentration up to 350ug/m3 and it was obtained by modeling similar to the concentration measured by a monitoring station (320ug/m3).The current limit is 120ug/m3 24 hours average. (Mexican standard NOM-025-SSA1-1993)This system for setting emissions from fire is working properly whoever further development is required.

Spatial probability models of fire in the desert grasslands of the southwestern USA

USDA-ARS?s Scientific Manuscript database

Fire is an important driver of ecological processes in semiarid environments; however, the role of fire in desert grasslands of the Southwestern US is controversial and the regional fire distribution is largely unknown. We characterized the spatial distribution of fire in the desert grassland region...

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

The drivers of wildfire enlargement do not exhibit scale thresholds in southeastern Australian forests.

PubMed

Price, Owen F; Penman, Trent; Bradstock, Ross; Borah, Rittick

2016-10-01

Wildfires are complex adaptive systems, and have been hypothesized to exhibit scale-dependent transitions in the drivers of fire spread. Among other things, this makes the prediction of final fire size from conditions at the ignition difficult. We test this hypothesis by conducting a multi-scale statistical modelling of the factors determining whether fires reached 10 ha, then 100 ha then 1000 ha and the final size of fires >1000 ha. At each stage, the predictors were measures of weather, fuels, topography and fire suppression. The objectives were to identify differences among the models indicative of scale transitions, assess the accuracy of the multi-step method for predicting fire size (compared to predicting final size from initial conditions) and to quantify the importance of the predictors. The data were 1116 fires that occurred in the eucalypt forests of New South Wales between 1985 and 2010. The models were similar at the different scales, though there were subtle differences. For example, the presence of roads affected whether fires reached 10 ha but not larger scales. Weather was the most important predictor overall, though fuel load, topography and ease of suppression all showed effects. Overall, there was no evidence that fires have scale-dependent transitions in behaviour. The models had a predictive accuracy of 73%, 66%, 72% and 53% accuracy at 10 ha, 100 ha, 1000 ha and final size scales. When these steps were combined, the overall accuracy for predicting the size of fires was 62%, while the accuracy of the one step model was only 20%. Thus, the multi-scale approach was an improvement on the single scale approach, even though the predictive accuracy was probably insufficient for use as an operational tool. The analysis has also provided further evidence of the important role of weather, compared to fuel, suppression and topography in driving fire behaviour. Copyright © 2016. Published by Elsevier Ltd.

Fires in storages of LFO: Analysis of hazard of structural collapse of steel-aluminium containers.

PubMed

Rebec, A; Kolšek, J; Plešec, P

2016-04-05

Pool fires of light fuel oil (LFO) in above-ground storages with steel-aluminium containers are discussed. A model is developed for assessments of risks of between-tank fire spread. Radiative effects of the flame body are accounted for by a solid flame radiation model. Thermal profiles evolved due to fire in the adjacent tanks and their consequential structural response is pursued in an exact (materially and geometrically non-linear) manner. The model's derivation is demonstrated on the LFO tank storage located near the Port of Koper (Slovenia). In support of the model, data from literature are adopted where appropriate. Analytical expressions are derived correspondingly for calculations of emissive characteristics of LFO pool fires. Additional data are collected from experiments. Fire experiments conducted on 300cm diameter LFO pans and at different wind speeds and high-temperature uniaxial tension tests of the analysed aluminium alloys types 3xxx and 6xxx are presented. The model is of an immediate fire engineering practical value (risk analyses) or can be used for further research purposes (e.g. sensitivity and parametric studies). The latter use is demonstrated in the final part of the paper discussing possible effects of high-temperature creep of 3xxx aluminium. Copyright © 2015 Elsevier B.V. All rights reserved.

Computational properties of networks of synchronous groups of spiking neurons.

PubMed

Dayhoff, Judith E

2007-09-01

We demonstrate a model in which synchronously firing ensembles of neurons are networked to produce computational results. Each ensemble is a group of biological integrate-and-fire spiking neurons, with probabilistic interconnections between groups. An analogy is drawn in which each individual processing unit of an artificial neural network corresponds to a neuronal group in a biological model. The activation value of a unit in the artificial neural network corresponds to the fraction of active neurons, synchronously firing, in a biological neuronal group. Weights of the artificial neural network correspond to the product of the interconnection density between groups, the group size of the presynaptic group, and the postsynaptic potential heights in the synchronous group model. All three of these parameters can modulate connection strengths between neuronal groups in the synchronous group models. We give an example of nonlinear classification (XOR) and a function approximation example in which the capability of the artificial neural network can be captured by a neural network model with biological integrate-and-fire neurons configured as a network of synchronously firing ensembles of such neurons. We point out that the general function approximation capability proven for feedforward artificial neural networks appears to be approximated by networks of neuronal groups that fire in synchrony, where the groups comprise integrate-and-fire neurons. We discuss the advantages of this type of model for biological systems, its possible learning mechanisms, and the associated timing relationships.

Effectiveness of Prescribed Fire as a Fuel Treatment in Californian Coniferous Forests

Treesearch

Nicole M. Vaillant; JoAnn Fites-Kaufman; Scott L. Stephens

2006-01-01

Effective fire suppression for the past century has altered forest structure and increased fuel loads. Prescribed fire as a fuels treatment can reduce wildfire size and severity. This study investigates how prescribed fire affects fuel loads, forest structure, potential fire behavior, and modeled tree mortality at 80th, 90th, and 97.5th percentile fire weather...

Continental-scale simulation of burn probabilities, flame lengths, and fire size distribution for the United States

Treesearch

Mark A. Finney; Charles W. McHugh; Isaac Grenfell; Karin L. Riley

2010-01-01

Components of a quantitative risk assessment were produced by simulation of burn probabilities and fire behavior variation for 134 fire planning units (FPUs) across the continental U.S. The system uses fire growth simulation of ignitions modeled from relationships between large fire occurrence and the fire danger index Energy Release Component (ERC). Simulations of 10,...

Value and challenges of conducting rapid response research on wildland fires

Treesearch

L. Lentile; P. Morgan; C. Hardy; A. Hudak; R. Means; R. Ottmar; P. Robichaud; E. Kennedy Sutherland; J. Szymoniak; F. Way; J. Fites-Kaufman; S. Lewis; E. Mathews; H. Shovik; K. Ryan

2007-01-01

Rapid Response Research is conducted during and immediately after wildland fires, in coordination with fire management teams, in order to collect information that can best be garnered in situ and in real-time. This information often includes fire behavior and fire effects data, which can be used to generate practical tools such as predictive fire models for managers....

A two-step combination of top-down and bottom-up fire emission estimates at regional and global scales: strengths and main uncertainties

NASA Astrophysics Data System (ADS)

Sofiev, Mikhail; Soares, Joana; Kouznetsov, Rostislav; Vira, Julius; Prank, Marje

2016-04-01

Top-down emission estimation via inverse dispersion modelling is used for various problems, where bottom-up approaches are difficult or highly uncertain. One of such areas is the estimation of emission from wild-land fires. In combination with dispersion modelling, satellite and/or in-situ observations can, in principle, be used to efficiently constrain the emission values. This is the main strength of the approach: the a-priori values of the emission factors (based on laboratory studies) are refined for real-life situations using the inverse-modelling technique. However, the approach also has major uncertainties, which are illustrated here with a few examples of the Integrated System for wild-land Fires (IS4FIRES). IS4FIRES generates the smoke emission and injection profile from MODIS and SEVIRI active-fire radiative energy observations. The emission calculation includes two steps: (i) initial top-down calibration of emission factors via inverse dispersion problem solution that is made once using training dataset from the past, (ii) application of the obtained emission coefficients to individual-fire radiative energy observations, thus leading to bottom-up emission compilation. For such a procedure, the major classes of uncertainties include: (i) imperfect information on fires, (ii) simplifications in the fire description, (iii) inaccuracies in the smoke observations and modelling, (iv) inaccuracies of the inverse problem solution. Using examples of the fire seasons 2010 in Russia, 2012 in Eurasia, 2007 in Australia, etc, it is pointed out that the top-down system calibration performed for a limited number of comparatively moderate cases (often the best-observed ones) may lead to errors in application to extreme events. For instance, the total emission of 2010 Russian fires is likely to be over-estimated by up to 50% if the calibration is based on the season 2006 and fire description is simplified. Longer calibration period and more sophisticated parameterization (including the smoke injection model and distinguishing all relevant vegetation types) can improve the predictions. The other significant parameter, so far weakly addressed in fire emission inventories, is the size spectrum of the emitted aerosols. Direct size-resolving measurements showed, for instance, that smoke from smouldering fires has smaller particles as compares with smoke from flaming fires. Due to dependence of the smoke optical thickness on the size distribution, such variability can lead to significant changes in the top-down calibration step. Experiments with IS4FIRES-SILAM system manifested up to a factor of two difference in AOD, depending on the assumption on particle spectrum.

Uncertainties of wild-land fires emission in AQMEII phase 2 case study

NASA Astrophysics Data System (ADS)

Soares, J.; Sofiev, M.; Hakkarainen, J.

2015-08-01

The paper discusses the main uncertainties of wild-land fire emission estimates used in the AQMEII-II case study. The wild-land fire emission of particulate matter for the summer fire season of 2010 in Eurasia was generated by the Integrated System for wild-land Fires (IS4FIRES). The emission calculation procedure included two steps: bottom-up emission compilation from radiative energy of individual fires observed by MODIS instrument on-board of Terra and Aqua satellites; and top-down calibration of emission factors based on the comparison between observations and modelled results. The approach inherits various uncertainties originating from imperfect information on fires, inaccuracies of the inverse problem solution, and simplifications in the fire description. These are analysed in regard to the Eurasian fires in 2010. It is concluded that the total emission is likely to be over-estimated by up to 50% with individual-fire emission accuracy likely to vary in a wide range. The first results of the new IS4FIRESv2 products and fire-resolving modelling are discussed in application to the 2010 events. It is shown that the new emission estimates have similar patterns but are lower than the IS4FIRESv1 values.

Surface Dimming by the 2013 Rim Fire Simulated by a Sectional Aerosol Model

NASA Technical Reports Server (NTRS)

Yu, Pengfei; Toon, Owen B.; Bardeen, Charles G; Bucholtz, Anthony; Rosenlof, Karen; Saide, Pablo E.; Da Silva, Arlindo M.; Ziemba, Luke D.; Thornhill, Kenneth L.; Jimenez, Jose-Luis;

Surface dimming by the 2013 Rim Fire simulated by a sectional aerosol model.

PubMed

Yu, Pengfei; Toon, Owen B; Bardeen, Charles G; Bucholtz, Anthony; Rosenlof, Karen H; Saide, Pablo E; Da Silva, Arlindo; Ziemba, Luke D; Thornhill, Kenneth L; Jimenez, Jose-Luis; Campuzano-Jost, Pedro; Schwarz, Joshua P; Perring, Anne E; Froyd, Karl D; Wagner, N L; Mills, Michael J; Reid, Jeffrey S

2016-06-27

The Rim Fire of 2013, the third largest area burned by fire recorded in California history, is simulated by a climate model coupled with a size-resolved aerosol model. Modeled aerosol mass, number, and particle size distribution are within variability of data obtained from multiple-airborne in situ measurements. Simulations suggest that Rim Fire smoke may block 4-6% of sunlight energy reaching the surface, with a dimming efficiency around 120-150 W m -2 per unit aerosol optical depth in the midvisible at 13:00-15:00 local time. Underestimation of simulated smoke single scattering albedo at midvisible by 0.04 suggests that the model overestimates either the particle size or the absorption due to black carbon. This study shows that exceptional events like the 2013 Rim Fire can be simulated by a climate model with 1° resolution with overall good skill, although that resolution is still not sufficient to resolve the smoke peak near the source region.

Validation of coupled atmosphere-fire behavior models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bossert, J.E.; Reisner, J.M.; Linn, R.R.

1998-12-31

Recent advances in numerical modeling and computer power have made it feasible to simulate the dynamical interaction and feedback between the heat and turbulence induced by wildfires and the local atmospheric wind and temperature fields. At Los Alamos National Laboratory, the authors have developed a modeling system that includes this interaction by coupling a high resolution atmospheric dynamics model, HIGRAD, with a fire behavior model, BEHAVE, to predict the spread of wildfires. The HIGRAD/BEHAVE model is run at very high resolution to properly resolve the fire/atmosphere interaction. At present, these coupled wildfire model simulations are computationally intensive. The additional complexitymore » of these models require sophisticated methods for assuring their reliability in real world applications. With this in mind, a substantial part of the research effort is directed at model validation. Several instrumented prescribed fires have been conducted with multi-agency support and participation from chaparral, marsh, and scrub environments in coastal areas of Florida and inland California. In this paper, the authors first describe the data required to initialize the components of the wildfire modeling system. Then they present results from one of the Florida fires, and discuss a strategy for further testing and improvement of coupled weather/wildfire models.« less

A Five-Year CMAQ PM2.5 Model Performance for Wildfires and Prescribed Fires

NASA Astrophysics Data System (ADS)

Wilkins, J. L.; Pouliot, G.; Foley, K.; Rappold, A.; Pierce, T. E.

2016-12-01

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. We will also review plume rise to see how it affects model bias and compare CMAQ current fire emissions input to an hourly dataset from FLAMBE.

EARTH, WIND AND FIRE: BUILDING METEOROLOGICALLY-SENSITIVE BIOGENIC AND WILDLAND FIRE EMISSION ESTIMATES FOR AIR QUALITY MODELS

EPA Science Inventory

Emission estimates are important for ensuring the accuracy of atmospheric chemical transport models. Estimates of biogenic and wildland fire emissions, because of their sensitivity to meteorological conditions, need to be carefully constructed and closely linked with a meteorolo...

High-severity fire: evaluating its key drivers and mapping its probability across western US forests

NASA Astrophysics Data System (ADS)

Parks, Sean A.; Holsinger, Lisa M.; Panunto, Matthew H.; Jolly, W. Matt; Dobrowski, Solomon Z.; Dillon, Gregory K.

2018-04-01

Wildland fire is a critical process in forests of the western United States (US). Variation in fire behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type, leads to heterogeneity in fire severity across landscapes. The relative influence of these factors in driving fire severity, however, is poorly understood. Here, we explore the drivers of high-severity fire for forested ecoregions in the western US over the period 2002–2015. Fire severity was quantified using a satellite-inferred index of severity, the relativized burn ratio. For each ecoregion, we used boosted regression trees to model high-severity fire as a function of live fuel, topography, climate, and fire weather. We found that live fuel, on average, was the most important factor driving high-severity fire among ecoregions (average relative influence = 53.1%) and was the most important factor in 14 of 19 ecoregions. Fire weather was the second most important factor among ecoregions (average relative influence = 22.9%) and was the most important factor in five ecoregions. Climate (13.7%) and topography (10.3%) were less influential. We also predicted the probability of high-severity fire, were a fire to occur, using recent (2016) satellite imagery to characterize live fuel for a subset of ecoregions in which the model skill was deemed acceptable (n = 13). These ‘wall-to-wall’ gridded ecoregional maps provide relevant and up-to-date information for scientists and managers who are tasked with managing fuel and wildland fire. Lastly, we provide an example of the predicted likelihood of high-severity fire under moderate and extreme fire weather before and after fuel reduction treatments, thereby demonstrating how our framework and model predictions can potentially serve as a performance metric for land management agencies tasked with reducing hazardous fuel across large landscapes.

[Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].

PubMed

Sun, Yu; Shi, Ming-Chang; Peng, Huan; Zhu, Pei-Lin; Liu, Si-Lin; Wu, Shi-Lei; He, Cheng; Chen, Feng

2014-04-01

Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains.

Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada: BC DEPOSITION FROM FOREST FIRES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, J. L.; Polashenski, C. M.; Soja, A. J.

We identify an important Black Carbon (BC) aerosol deposition event that was observed in snow stratigraphy and dated to between 27 July 2013 – 2 August 2013. This event comprises a significant portion (~60%) of total deposition over a 10 month period (July 2013 – April 2014). Here we link this event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the CALIOP and MODIS instruments during transport between Canada and Greenland, confirming that this event involved emissions from forest fires in Canada. We use high-resolution regional chemical transportmore » mod-eling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model accurately captures the timing of the BC deposition event and shows that the major contribution to deposition during this event is emissions originating from fires in Canada. However, the model under-predicts aerosol deposition compared to measurements at all sites by a factor of 2–100. Under-prediction of modeled BC deposition originates from uncertainties in fire emissions combined with uncertainties in aerosol scavenging by clouds. This study suggests that it is possible to describe the transport of an exceptional smoke event on regional and continental scales. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.« less

Colored noise and a stochastic fractional model for correlated inputs and adaptation in neuronal firing.

PubMed

Pirozzi, Enrica

2018-04-01

High variability in the neuronal response to stimulations and the adaptation phenomenon cannot be explained by the standard stochastic leaky integrate-and-fire model. The main reason is that the uncorrelated inputs involved in the model are not realistic. There exists some form of dependency between the inputs, and it can be interpreted as memory effects. In order to include these physiological features in the standard model, we reconsider it with time-dependent coefficients and correlated inputs. Due to its hard mathematical tractability, we perform simulations of it for a wide investigation of its output. A Gauss-Markov process is constructed for approximating its non-Markovian dynamics. The first passage time probability density of such a process can be numerically evaluated, and it can be used to fit the histograms of simulated firing times. Some estimates of the moments of firing times are also provided. The effect of the correlation time of the inputs on firing densities and on firing rates is shown. An exponential probability density of the first firing time is estimated for low values of input current and high values of correlation time. For comparison, a simulation-based investigation is also carried out for a fractional stochastic model that allows to preserve the memory of the time evolution of the neuronal membrane potential. In this case, the memory parameter that affects the firing activity is the fractional derivative order. In both models an adaptation level of spike frequency is attained, even if along different modalities. Comparisons and discussion of the obtained results are provided.

Using a prescribed fire to test custom and standard fuel models for fire behaviour prediction in a non-native, grass-invaded tropical dry shrubland

Treesearch

Andrew D. Pierce; Sierra McDaniel; Mark Wasser; Alison Ainsworth; Creighton M. Litton; Christian P. Giardina; Susan Cordell; Ralf Ohlemuller

2014-01-01

Questions: Do fuel models developed for North American fuel types accurately represent fuel beds found in grass-invaded tropical shrublands? Do standard or custom fuel models for firebehavior models with in situ or RAWS measured fuel moistures affect the accuracy of predicted fire behavior in grass-invaded tropical shrublands? Location: Hawai’i Volcanoes National...

Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau

USGS Publications Warehouse

van Mantgem, Phillip J.; Lalemand, Laura; Keifer, MaryBeth; Kane, Jeffrey M.

2016-01-01

Prescribed fire is a widely used forest management tool, yet the long-term effectiveness of prescribed fire in reducing fuels and fire hazards in many vegetation types is not well documented. We assessed the magnitude and duration of reductions in surface fuels and modeled fire hazards in coniferous forests across nine U.S. national parks in California and the Colorado Plateau. We used observations from a prescribed fire effects monitoring program that feature standard forest and surface fuels inventories conducted pre-fire, immediately following an initial (first-entry) prescribed fire and at varying intervals up to >20 years post-fire. A subset of these plots was subjected to prescribed fire again (second-entry) with continued monitoring. Prescribed fire effects were highly variable among plots, but we found on average first-entry fires resulted in a significant post-fire reduction in surface fuels, with litter and duff fuels not returning to pre-fire levels over the length of our observations. Fine and coarse woody fuels often took a decade or longer to return to pre-fire levels. For second-entry fires we found continued fuels reductions, without strong evidence of fuel loads returning to levels observed immediately prior to second-entry fire. Following both first- and second-entry fire there were increases in estimated canopy base heights, along with reductions in estimated canopy bulk density and modeled flame lengths. We did not find evidence of return to pre-fire conditions during our observation intervals for these measures of fire hazard. Our results show that prescribed fire can be a valuable tool to reduce fire hazards and, depending on forest conditions and the measurement used, reductions in fire hazard can last for decades. Second-entry prescribed fire appeared to reinforce the reduction in fuels and fire hazard from first-entry fires.

How Fire History, Fire Suppression Practices and Climate Change Affect Wildfire Regimes in Mediterranean Landscapes

PubMed Central

Brotons, Lluís; Aquilué, Núria; de Cáceres, Miquel; Fortin, Marie-Josée; Fall, Andrew

2013-01-01

Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies. PMID:23658726

How fire history, fire suppression practices and climate change affect wildfire regimes in Mediterranean landscapes.

PubMed

Brotons, Lluís; Aquilué, Núria; de Cáceres, Miquel; Fortin, Marie-Josée; Fall, Andrew

2013-01-01

Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies.

A hydroclimatic model of global fire patterns

NASA Astrophysics Data System (ADS)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F (i.e. F_0.99 ) was explained by two terms of the climatic water balance: i) mean annual actual evapotranspiration (AET), which is a proxy for fuel productivity, and ii) mean annual water deficit (D=PET-AET, where PET is mean annual potential evapotranspiration), which is a measure of fuel drying potential. As expected, F_0.99 was close to zero in environments of low AET (e.g. deserts) or low D (e.g. wet forests), due to strong fuel productivity or fuel dryness constraints, and maximum for environments of intermediate AET and D (e.g. tropical savannas). The topography of the F_0.99 response surface was analysed to explore how the relative importance of fuel productivity and fuel dryness constraints varied with the climatic water balance, and geographically across the continents. Consistent with current understanding of global pyrogeography, the hydroclimatic fire model predicted that fire activity is mostly constrained by fuel productivity in arid environments with grassy fuels and by fuel dryness in humid environments with litter fuels derived from woody shrubs and trees. The model provides a simple, yet biophysically-based, approach to evaluating potential for incremental change in fire activity or transformational change in fire types under future climate conditions.

Complex systems approach to fire dynamics and climate change impacts

NASA Astrophysics Data System (ADS)

Pueyo, S.

2012-04-01

I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire sizes are also well fitted by a power law. A possible interpretation is that the spatial structure of fire in savannas is strongly constrained by the spatial structure of their environment. Instead of resulting from ecosystem self-organization as in the model, in this case the scale invariance in fire events would be just a reflection of scale invariance in the environment in which the ecosystem lives. These results suggest at least three major types of fire dynamics: endogenous scaling, percolating, and exogenous scaling, in addition to intermediate options. The world's biomes can be classified based on the type of dynamics that is most likely to apply in each of them, and forecasts can be carried out with the tools developed for each of these types.

Modelling public support for wildland fire policy

Treesearch

J.D. Absher; J.J. Vaske

2007-01-01

Theoretically grounded explanations of wildland fire policy can be improved by empirically documenting the causal influences of support for (or opposition to) management alternatives. This chapter proposes a model based on the specificity principle (i.e. correspondence between measured variables to empirically examine four common wildland fire policies in relation to...

Isotopic composition of carbon dioxide from a boreal forest fire: Inferring carbon loss from measurements and modeling

USGS Publications Warehouse

Schuur, E.A.G.; Trumbore, S.E.; Mack, M.C.; Harden, J.W.

2003-01-01

Fire is an important pathway for carbon (C) loss from boreal forest ecosystems and has a strong effect on ecosystem C balance. Fires can range widely in severity, defined as the amount of vegetation and forest floor consumed by fire, depending on local fuel and climatic conditions. Here we explore a novel method for estimating fire severity and loss of C from fire using the atmosphere to integrate ecosystem heterogeneity at the watershed scale. We measured the ??13C and ??14C isotopic values of CO2 emitted from an experimental forest fire at the Caribou-Poker Creek Research Watershed (CPCRW), near Fairbanks, Alaska. We used inverse modeling combined with dual isotope near measurements of C contained in aboveground black spruce biomass and soil organic horizons to estimate the amount of C released by this fire. The experimental burn was a medium to severe intensity fire that released, on average, about 2.5 kg Cm-2, more than half of the C contained in vegetation and soil organic horizon pools. For vegetation, the model predicted that approximately 70-75% of pools such as needles, fine branches, and bark were consumed by fire, whereas only 20-30% of pools such as coarse branches and cones were consumed. The fire was predicted to have almost completely consumed surface soil organic horizons and burned about half of the deepest humic horizon. The ability to estimate the amount of biomass combusted and C emission from fires at the watershed scale provides an extensive approach that can complement more limited intensive ground-based measurements.

Fire-mediated disruptive selection can explain the reseeder-resprouter dichotomy in Mediterranean-type vegetation.

PubMed

Altwegg, Res; De Klerk, Helen M; Midgley, Guy F

2015-02-01

Crown fire is a key selective pressure in Mediterranean-type plant communities. Adaptive responses to fire regimes involve trade-offs between investment for persistence (fire survival and resprouting) and reproduction (fire mortality, fast growth to reproductive maturity, and reseeding) as investments that enhance adult survival lower growth and reproductive rates. Southern hemisphere Mediterranean-type ecosystems are dominated by species with either endogenous regeneration from adult resprouting or fire-triggered seedling recruitment. Specifically, on nutrient-poor soils, these are either resprouting or reseeding life histories, with few intermediate forms, despite the fact that the transition between strategies is evolutionarily labile. How did this strong dichotomy evolve? We address this question by developing a stochastic demographic model to assess determinants of relative fitness of reseeders, resprouters and hypothetical intermediate forms. The model was parameterised using published demographic data from South African protea species and run over various relevant fire regime parameters facets. At intermediate fire return intervals, trade-offs between investment in growth versus fire resilience can cause fitness to peak at either of the extremes of the reseeder-resprouter continuum, especially when assuming realistic non-linear shapes for these trade-offs. Under these circumstances, the fitness landscape exhibits a saddle which could lead to disruptive selection. The fitness gradient between the peaks was shallow, which may explain why this life-history trait is phylogenetically labile. Resprouters had maximum fitness at shorter fire-return intervals than reseeders. The model suggests that a strong dichotomy in fire survival strategy depends on a non-linear trade-off between growth and fire persistence traits.

A laboratory-scale comparison of rate of spread model predictions using chaparral fuel beds – preliminary results

Treesearch

D.R. Weise; E. Koo; X. Zhou; S. Mahalingam

2011-01-01

Observed fire spread rates from 240 laboratory fires in horizontally-oriented single-species live fuel beds were compared to predictions from various implementations and modifications of the Rothermel rate of spread model and a physical fire spread model developed by Pagni and Koo. Packing ratio of the laboratory fuel beds was generally greater than that observed in...

A robust scientific workflow for assessing fire danger levels using open-source software

NASA Astrophysics Data System (ADS)

Vitolo, Claudia; Di Giuseppe, Francesca; Smith, Paul

2017-04-01

Modelling forest fires is theoretically and computationally challenging because it involves the use of a wide variety of information, in large volumes and affected by high uncertainties. In-situ observations of wildfire, for instance, are highly sparse and need to be complemented by remotely sensed data measuring biomass burning to achieve homogeneous coverage at global scale. Fire models use weather reanalysis products to measure energy release and rate of spread but can only assess the potential predictability of fire danger as the actual ignition is due to human behaviour and, therefore, very unpredictable. Lastly, fire forecasting systems rely on weather forecasts to extend the advance warning but are currently calibrated using fire danger thresholds that are defined at global scale and do not take into account the spatial variability of fuel availability. As a consequence, uncertainties sharply increase cascading from the observational to the modelling stage and they might be further inflated by non-reproducible analyses. Although uncertainties in observations will only decrease with technological advances over the next decades, the other uncertainties (i.e. generated during modelling and post-processing) can already be addressed by developing transparent and reproducible analysis workflows, even more if implemented within open-source initiatives. This is because reproducible workflows aim to streamline the processing task as they present ready-made solutions to handle and manipulate complex and heterogeneous datasets. Also, opening the code to the scrutiny of other experts increases the chances to implement more robust solutions and avoids duplication of efforts. In this work we present our contribution to the forest fire modelling community: an open-source tool called "caliver" for the calibration and verification of forest fire model results. This tool is developed in the R programming language and publicly available under an open license. We will present the caliver R package, illustrate the main functionalities and show the results of our preliminary experiments calculating fire danger thresholds for various regions on Earth. We will compare these with the existing global thresholds and, lastly, demonstrate how these newly-calculated regional thresholds can lead to improved calibration of fire forecast models in an operational setting.

Probabilistic models to estimate fire-induced cable damage at nuclear power plants

NASA Astrophysics Data System (ADS)

Valbuena, Genebelin R.

Even though numerous PRAs have shown that fire can be a major contributor to nuclear power plant risk, there are some specific areas of knowledge related to this issue, such as the prediction of fire-induced damage to electrical cables and circuits, and their potential effects in the safety of the nuclear power plant, that still constitute a practical enigma, particularly for the lack of approaches/models to perform consistent and objective assessments. This report contains a discussion of three different models to estimate fire-induced cable damage likelihood given a specified fire profile: the kinetic, the heat transfer and the IR "K Factor" model. These models not only are based on statistical analysis of data available in the open literature, but to the greatest extent possible they use physics based principles to describe the underlying mechanism of failures that take place among the electrical cables upon heating due to external fires. The characterization of cable damage, and consequently the loss of functionality of electrical cables in fire is a complex phenomenon that depends on a variety of intrinsic factors such as cable materials and dimensions, and extrinsic factors such as electrical and mechanical loads on the cables, heat flux severity, and exposure time. Some of these factors are difficult to estimate even in a well-characterized fire, not only for the variability related to the unknown material composition and physical arrangements, but also for the lack of objective frameworks and theoretical models to study the behavior of polymeric wire cable insulation under dynamic external thermal insults. The results of this research will (1) help to develop a consistent framework to predict fire-induced cable failure modes likelihood, and (2) develop some guidance to evaluate and/or reduce the risk associated with these failure modes in existing and new power plant facilities. Among the models evaluated, the physics-based heat transfer model takes into account the properties and characteristics of the cables and cable materials, and the characteristics of the thermal insult. This model can be used to estimate the probability of cable damage under different thermal conditions.

[Relationships of forest fire with lightning in Daxing' anling Mountains, Northeast China].

PubMed

Lei, Xiao-Li; Zhou, Guang-Sheng; Jia, Bing-Rui; Li, Shuai

2012-07-01

Forest fire is an important factor affecting forest ecosystem succession. Recently, forest fire, especially forest lightning fire, shows an increasing trend under global warming. To study the relationships of forest fire with lightning is essential to accurately predict the forest fire in time. Daxing' anling Mountains is a region with high frequency of forest lightning fire in China, and an important experiment site to study the relationships of forest fire with lightning. Based on the forest fire records and the corresponding lightning and meteorological observation data in the Mountains from 1966 to 2007, this paper analyzed the relationships of forest fire with lightning in this region. In the period of 1966-2007, both the lightning fire number and the fired forest area in this region increased significantly. The meteorological factors affecting the forest lighting fire were related to temporal scales. At yearly scale, the forest lightning fire was significantly correlated with precipitation, with a correlation coefficient of -0.489; at monthly scale, it had a significant correlation with air temperature, the correlation coefficient being 0.18. The relationship of the forest lightning fire with lightning was also related to temporal scales. At yearly scale, there was no significant correlation between them; at monthly scale, the forest lightning fire was strongly correlated with lightning and affected by precipitation; at daily scale, a positive correlation was observed between forest lightning fire and lightning when the precipitation was less than 5 mm. According to these findings, a fire danger index based on ADTD lightning detection data was established, and a forest lightning fire forecast model was developed. The prediction accuracy of this model for the forest lightning fire in Daxing' anling Mountains in 2005-2007 was > 80%.

Challenges and a checklist for biodiversity conservation in fire-prone forests: perspecitves from the Pacific Northwest of USA and Southeastern Australia

Treesearch

Thomas A. Spies; David B. Lindenmayer; A. Malcolm Gill; Scott L. Stephens; James K. Agee

2012-01-01

Conserving biodiversity in fire-prone forest ecosystems is challenging for several reasons including differing and incomplete conceptual models of fire-related ecological processes, major gaps in ecological and management knowledge, high variability in fire behavior and ecological responses to fires, altered fire regimes as a result of land-use history and climate...

FOCUS: a fire management planning system -- final report

Treesearch

Frederick W. Bratten; James B. Davis; George T. Flatman; Jerold W. Keith; Stanley R. Rapp; Theodore G. Storey

1981-01-01

FOCUS (Fire Operational Characteristics Using Simulation) is a computer simulation model for evaluating alternative fire management plans. This final report provides a broad overview of the FOCUS system, describes two major modules-fire suppression and cost, explains the role in the system of gaming large fires, and outlines the support programs and ways of...

FEES: design of a Fire Economics Evaluation System

Treesearch

Thomas J. Mills; Frederick W. Bratten

1982-01-01

The Fire Economics Evaluation System (FEES)--a simulation model--is being designed for long-term planning application by all public agencies with wildland fire management responsibilities. A fully operational version of FEES will be capable of estimating the economic efficiency, fire-induced changes in resource outputs, and risk characteristics of a range of fire...

Crown fuel spatial variability and predictability of fire spread

Treesearch

Russell A. Parsons; Jeremy Sauer; Rodman R. Linn

2010-01-01

Fire behavior predictions, as well as measures of uncertainty in those predictions, are essential in operational and strategic fire management decisions. While it is becoming common practice to assess uncertainty in fire behavior predictions arising from variability in weather inputs, uncertainty arising from the fire models themselves is difficult to assess. This is...

Implications of the spatial dynamics of fire spread for the bistability of savanna and forest.

PubMed

Schertzer, E; Staver, A C; Levin, S A

2015-01-01

The role of fire in expanding the global distribution of savanna is well recognized. Empirical observations and modeling suggest that fire spread has a threshold response to fuel-layer continuity, which sets up a positive feedback that maintains savanna-forest bistability. However, modeling has so far failed to examine fire spread as a spatial process that interacts with vegetation. Here, we use simple, well-supported assumptions about fire spread as an infection process and its effects on trees to ask whether spatial dynamics qualitatively change the potential for savanna-forest bistability. We show that the spatial effects of fire spread are the fundamental reason that bistability is possible: because fire spread is an infection process, it exhibits a threshold response to fuel continuity followed by a rapid increase in fire size. Other ecological processes affecting fire spread may also contribute including temporal variability in demography or fire spread. Finally, including the potential for spatial aggregation increases the potential both for savanna-forest bistability and for savanna and forest to coexist in a landscape mosaic.

Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca; Rémy, Samuel; Pappenberger, Florian; Wetterhall, Fredrik

2018-04-01

The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

Modeling of Electrical Cable Failure in a Dynamic Assessment of Fire Risk

NASA Astrophysics Data System (ADS)

Bucknor, Matthew D.

Fires at a nuclear power plant are a safety concern because of their potential to defeat the redundant safety features that provide a high level of assurance of the ability to safely shutdown the plant. One of the added complexities of providing protection against fires is the need to determine the likelihood of electrical cable failure which can lead to the loss of the ability to control or spurious actuation of equipment that is required for safe shutdown. A number of plants are now transitioning from their deterministic fire protection programs to a risk-informed, performance based fire protection program according to the requirements of National Fire Protection Association (NFPA) 805. Within a risk-informed framework, credit can be taken for the analysis of fire progression within a fire zone that was not permissible within the deterministic framework of a 10 CFR 50.48 Appendix R safe shutdown analysis. To perform the analyses required for the transition, plants need to be able to demonstrate with some level of assurance that cables related to safe shutdown equipment will not be compromised during postulated fire scenarios. This research contains the development of new cable failure models that have the potential to more accurately predict electrical cable failure in common cable bundle configurations. Methods to determine the thermal properties of the new models from empirical data are presented along with comparisons between the new models and existing techniques used in the nuclear industry today. A Dynamic Event Tree (DET) methodology is also presented which allows for the proper treatment of uncertainties associated with fire brigade intervention and its effects on cable failure analysis. Finally a shielding analysis is performed to determine the effects on the temperature response of a cable bundle that is shielded from a fire source by an intervening object such as another cable tray. The results from the analyses demonstrate that models of similar complexity to existing cable failure techniques and tuned to empirical data can better approximate the temperature response of a cables located in tightly packed cable bundles. The new models also provide a way to determine the conditions insides a cable bundle which allows for separate treatment of cables on the interior of the bundle from cables on the exterior of the bundle. The results from the DET analysis show that the overall assessed probability of cable failure can be significantly reduced by more realistically accounting for the influence that the fire brigade has on a fire progression scenario. The shielding analysis results demonstrate a significant reduction in the temperature response of a shielded versus a non-shielded cable bundle; however the computational cost of using a fire progression model that can capture these effects may be prohibitive for performing DET analyses with currently available computational fluid dynamics models and computational resources.

Fuel model selection for BEHAVE in midwestern oak savannas

USGS Publications Warehouse

Grabner, K.W.; Dwyer, J.P.; Cutter, B.E.

2001-01-01

BEHAVE, a fire behavior prediction system, can be a useful tool for managing areas with prescribed fire. However, the proper choice of fuel models can be critical in developing management scenarios. BEHAVE predictions were evaluated using four standardized fuel models that partially described oak savanna fuel conditions: Fuel Model 1 (Short Grass), 2 (Timber and Grass), 3 (Tall Grass), and 9 (Hardwood Litter). Although all four models yielded regressions with R2 in excess of 0.8, Fuel Model 2 produced the most reliable fire behavior predictions.

Effects of fire suppression under a changing climate in Pacific Northwest mixed-pine forests

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Bart, R. R.; Kennedy, M. C.; Abatzoglou, J. T.; Kolden, C.; Adam, J. C.

2017-12-01

The frequency of large and severe wildfires has increased over recent decades in many regions across the Western U.S., including the Pacific and Inland Northwest. This increase is likely driven in large part by wildfire suppression, which has promoted fuel accumulation in western landscapes. Recent studies also suggest that anthropogenic climate change intensifies wildfire activity by increasing fuel aridity. However, the contribution of these drivers to observed changes in fire regime is not well quantified at regional scales. Understanding the relative influence of climate and fire suppression is crucial for both projecting the effects of climate change on future fire spread, and for developing site-specific fuel management strategies under a new climate paradigm. To quantify the extent to which fire suppression and climate change have contributed to increases in wildfire activity in the Pacific Northwest, we conduct a modeling experiment using the ecohydrologic model RHESSys and the coupled stochastic fire spread model WMFire. Specifically, we use historical climate inputs from GCMs, combined with fire suppression scenarios to gauge the extent to which these drivers promote the spread of severe wildfires in Johnson Creek, a large (565-km2) mixed-pine dominated subcatchment of the Southfork Salmon River; part of the larger Columbia River Basin. We run 500 model iterations for suppressed, intermediate, and unsuppressed fire management scenarios, both with and without climate change in a factorial design, focusing on fire spread surrounding two extreme fire years in Johnson Creek (1998 and 2007). After deriving fire spread "fingerprints" for each combination of possible drivers, we evaluate the extent to which these fingerprints match observations in the fire record. We expect that climate change plays a role in the spread of large and severe wildfires in Johnson Creek, but the magnitude of this effect is mediated by prior suppression. Preliminary results suggest that management strategies aimed at reducing the extent of contiguous even-aged fuels may help curtail climate-driven increases in wildfire severity in Pacific Northwest watersheds.

Fire and deforestation dynamics in Amazonia (1973-2014).

PubMed

van Marle, Margreet J E; Field, Robert D; van der Werf, Guido R; Estrada de Wagt, Ivan A; Houghton, Richard A; Rizzo, Luciana V; Artaxo, Paulo; Tsigaridis, Kostas

2017-01-01

Consistent long-term estimates of fire emissions are important to understand the changing role of fire in the global carbon cycle and to assess the relative importance of humans and climate in shaping fire regimes. However, there is limited information on fire emissions from before the satellite era. We show that in the Amazon region, including the Arc of Deforestation and Bolivia, visibility observations derived from weather stations could explain 61% of the variability in satellite-based estimates of bottom-up fire emissions since 1997 and 42% of the variability in satellite-based estimates of total column carbon monoxide concentrations since 2001. This enabled us to reconstruct the fire history of this region since 1973 when visibility information became available. Our estimates indicate that until 1987 relatively few fires occurred in this region and that fire emissions increased rapidly over the 1990s. We found that this pattern agreed reasonably well with forest loss data sets, indicating that although natural fires may occur here, deforestation and degradation were the main cause of fires. Compared to fire emissions estimates based on Food and Agricultural Organization's Global Forest and Resources Assessment data, our estimates were substantially lower up to the 1990s, after which they were more in line. These visibility-based fire emissions data set can help constrain dynamic global vegetation models and atmospheric models with a better representation of the complex fire regime in this region.

Control effects of stimulus paradigms on characteristic firings of parkinsonism

NASA Astrophysics Data System (ADS)

Zhang, Honghui; Wang, Qingyun; Chen, Guanrong

2014-09-01

Experimental studies have shown that neuron population located in the basal ganglia of parkinsonian primates can exhibit characteristic firings with certain firing rates differing from normal brain activities. Motivated by recent experimental findings, we investigate the effects of various stimulation paradigms on the firing rates of parkinsonism based on the proposed dynamical models. Our results show that the closed-loop deep brain stimulation is superior in ameliorating the firing behaviors of the parkinsonism, and other control strategies have similar effects according to the observation of electrophysiological experiments. In addition, in conformity to physiological experiments, we found that there exists optimal delay of input in the closed-loop GPtrain|M1 paradigm, where more normal behaviors can be obtained. More interestingly, we observed that W-shaped curves of the firing rates always appear as stimulus delay varies. We furthermore verify the robustness of the obtained results by studying three pallidal discharge rates of the parkinsonism based on the conductance-based model, as well as the integrate-and-fire-or-burst model. Finally, we show that short-term plasticity can improve the firing rates and optimize the control effects on parkinsonism. Our conclusions may give more theoretical insight into Parkinson's disease studies.

Evaluation of NOx emissions from U.S. wildfires occurring during August-October 2006 using WRF-Chem model simulations and satellite observations

NASA Astrophysics Data System (ADS)

Kim, S.; Brioude, J.; Hilboll, A.; Richter, A.; Gleason, J. F.; Burrows, J. P.; Ryerson, T. B.; Peischl, J. W.; Holloway, J.; Lee, S.; Frost, G. J.; McKeen, S. A.; Trainer, M.

2009-12-01

During August-October 2006, there were many fire events in the U.S., including a month-long fire in Los Padres National Forest in California and numerous fires in the southeastern U.S. The OMI instrument onboard NASA's Aura satellite, the MODIS instrument on NASA's Terra satellite, and instruments on the NOAA GOES satellites clearly detected fire plumes during this period, opening the possibility of using trace gas and aerosol measurements from satellites to improve bottom-up emission estimates from wildfires. WRF-Chem model simulations of U.S. air quality without bottom-up fire emissions underestimated satellite-observed nitrogen dioxide columns substantially over fire-impacted regions during this time period. In this presentation, nitrogen dioxide columns simulated from the model including the wildfire emissions will be compared with the satellite retrievals and uncertainties in the bottom-up fire NOx emissions will be discussed. In addition, the sensitivities of satellite retrievals to aerosols resulting from these fires will be shown. The satellite NO2 columns will also be tested with aircraft observations made over the Texas region during September-October 2006 as part of the TexAQS/GoMACCS field campaign.

Ion channel mechanisms underlying frequency-firing patterns of the avian nucleus magnocellularis: A computational model

PubMed Central

Lu, Ting; Wade, Kirstie; Sanchez, Jason Tait

2017-01-01

ABSTRACT We have previously shown that late-developing avian nucleus magnocellularis (NM) neurons (embryonic [E] days 19–21) fire action potentials (APs) that resembles a band-pass filter in response to sinusoidal current injections of varying frequencies. NM neurons located in the mid- to high-frequency regions of the nucleus fire preferentially at 75 Hz, but only fire a single onset AP to frequency inputs greater than 200 Hz. Surprisingly, NM neurons do not fire APs to sinusoidal inputs less than 20 Hz regardless of the strength of the current injection. In the present study we evaluated intrinsic mechanisms that prevent AP generation to low frequency inputs. We constructed a computational model to simulate the frequency-firing patterns of NM neurons based on experimental data at both room and near physiologic temperatures. The results from our model confirm that the interaction among low- and high-voltage activated potassium channels (KLVA and KHVA, respectively) and voltage dependent sodium channels (NaV) give rise to the frequency-firing patterns observed in vitro. In particular, we evaluated the regulatory role of KLVA during low frequency sinusoidal stimulation. The model shows that, in response to low frequency stimuli, activation of large KLVA current counterbalances the slow-depolarizing current injection, likely permitting NaV closed-state inactivation and preventing the generation of APs. When the KLVA current density was reduced, the model neuron fired multiple APs per sinusoidal cycle, indicating that KLVA channels regulate low frequency AP firing of NM neurons. This intrinsic property of NM neurons may assist in optimizing response to different rates of synaptic inputs. PMID:28481659

Using simulated historical time series to prioritize fuel treatments on landscapes across the United States: The LANDFIRE prototype project

USGS Publications Warehouse

Keane, Robert E.; Rollins, Matthew; Zhu, Zhi-Liang

2007-01-01

Canopy and surface fuels in many fire-prone forests of the United States have increased over the last 70 years as a result of modern fire exclusion policies, grazing, and other land management activities. The Healthy Forest Restoration Act and National Fire Plan establish a national commitment to reduce fire hazard and restore fire-adapted ecosystems across the USA. The primary index used to prioritize treatment areas across the nation is Fire Regime Condition Class (FRCC) computed as departures of current conditions from the historical fire and landscape conditions. This paper describes a process that uses an extensive set of ecological models to map FRCC from a departure statistic computed from simulated time series of historical landscape composition. This mapping process uses a data-driven, biophysical approach where georeferenced field data, biogeochemical simulation models, and spatial data libraries are integrated using spatial statistical modeling to map environmental gradients that are then used to predict vegetation and fuels characteristics over space. These characteristics are then fed into a landscape fire and succession simulation model to simulate a time series of historical landscape compositions that are then compared to the composition of current landscapes to compute departure, and the FRCC values. Intermediate products from this process are then used to create ancillary vegetation, fuels, and fire regime layers that are useful in the eventual planning and implementation of fuel and restoration treatments at local scales. The complex integration of varied ecological models at different scales is described and problems encountered during the implementation of this process in the LANDFIRE prototype project are addressed.

Numerical study of fire whirlwind taking into account radiative heat transfer

NASA Astrophysics Data System (ADS)

Sakai, S.; Miyagi, N.

2010-06-01

The fire whirlwind is a strong swirling flow with flame and spark, which may occur in the case of, widespread fire in the urban region by an earthquake disaster or an air raid, and a large-scale fire such as a forest fire. Fire whirlwind moves and promotes spread of fire and may extend serious damage rapidly. In this study, performing the numerical analysis of fire whirlwind with respect to scale effect, it is examined whether a relationship exists between a real phenomenon and the phenomenon in the reduction model with taking into account radiative heat transfer. Three dimensional analyses are performed to investigate the thermal and flow fields by using the analytical software FLUENT6.3. It is analyzed that those swirling flow in original scale, 1/10 scale, 1/50 scale, 1/100 scale from the original brake out to vanish. As an analytical condition, parameter calculation is repeated to get the velocity of a parallel flow which is the easiest to occur the swirling flow for each reduction model, and then scale effect is discussed by comparing the velocity of the natural convection, the velocity of the parallel flow, the center pressure of the whirlwind and the continuance time of the swirling flow. The analysis model of C-character heat source model is performed as well as the analysis in L-character model, which is one of the representative example of the fire whirlwind occurred at Tokyo in the Great Kanto Earthquake (1923). The result of the numerical analysis shows that there is a scale effect to the speed of the parallel flow to generate the swirling flow.

A multi-scale conceptual model of fire and disease interactions in North American forests

NASA Astrophysics Data System (ADS)

Varner, J. M.; Kreye, J. K.; Sherriff, R.; Metz, M.

2013-12-01

One aspect of global change with increasing attention is the interactions between irruptive pests and diseases and wildland fire behavior and effects. These pests and diseases affect fire behavior and effects in spatially and temporally complex ways. Models of fire and pathogen interactions have been constructed for individual pests or diseases, but to date, no synthesis of this complexity has been attempted. Here we synthesize North American fire-pathogen interactions into syndromes with similarities in spatial extent and temporal duration. We base our models on fire interactions with three examples: sudden oak death (caused by the pathogen Phytopthora ramorum) and the native tree tanoak (Notholithocarpus densiflorus); mountain pine beetle (Dendroctonus ponderosae) and western Pinus spp.; and hemlock woolly adelgid (Adelges tsugae) on Tsuga spp. We evaluate each across spatial (severity of attack from branch to landscape scale) and temporal scales (from attack to decades after) and link each change to its coincident effects on fuels and potential fire behavior. These syndromes differ in their spatial and temporal severity, differentially affecting windows of increased or decreased community flammability. We evaluate these models with two examples: the recently emergent ambrosia beetle-vectored laurel wilt (caused by the pathogen Raffaelea lauricola) in native members of the Lauraceae and the early 20th century chestnut blight (caused by the pathogen Cryphonectria parasitica) that led to the decline of American chestnut (Castanea dentata). Some changes (e.g., reduced foliar moisture content) have short-term consequences for potential fire behavior while others (functional extirpation) have more complex indirect effects on community flammability. As non-native emergent diseases and pests continue, synthetic models that aid in prediction of fire behavior and effects will enable the research and management community to prioritize mitigation efforts to realized effects.

Quantifying the role of fire in the Earth system - Part 2: Impact on the net carbon balance of global terrestrial ecosystems for the 20th century

NASA Astrophysics Data System (ADS)

Li, F.; Bond-Lamberty, B.; Levis, S.

2014-03-01

Fire is the primary form of terrestrial ecosystem disturbance on a global scale. It affects the net carbon balance of terrestrial ecosystems by emitting carbon directly and immediately into the atmosphere from biomass burning (the fire direct effect), and by changing net ecosystem productivity and land-use carbon loss in post-fire regions due to biomass burning and fire-induced vegetation mortality (the fire indirect effect). Here, we provide the first quantitative assessment of the impact of fire on the net carbon balance of global terrestrial ecosystems during the 20th century, and investigate the roles of fire's direct and indirect effects. This is done by quantifying the difference between the 20th century fire-on and fire-off simulations with the NCAR Community Land Model CLM4.5 (prescribed vegetation cover and uncoupled from the atmospheric model) as a model platform. Results show that fire decreases the net carbon gain of global terrestrial ecosystems by 1.0 Pg C yr-1 averaged across the 20th century, as a result of the fire direct effect (1.9 Pg C yr-1) partly offset by the indirect effect (-0.9 Pg C yr-1). Post-fire regions generally experience decreased carbon gains, which is significant over tropical savannas and some North American and East Asian forests. This decrease is due to the direct effect usually exceeding the indirect effect, while they have similar spatial patterns and opposite sign. The effect of fire on the net carbon balance significantly declines until ∼1970 with a trend of 8 Tg C yr-1 due to an increasing indirect effect, and increases subsequently with a trend of 18 Tg C yr-1 due to an increasing direct effect. These results help constrain the global-scale dynamics of fire and the terrestrial carbon cycle.

Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region

PubMed Central

Callister, Kate E.; Griffioen, Peter A.; Avitabile, Sarah C.; Haslem, Angie; Kelly, Luke T.; Kenny, Sally A.; Nimmo, Dale G.; Farnsworth, Lisa M.; Taylor, Rick S.; Watson, Simon J.; Bennett, Andrew F.; Clarke, Michael F.

2016-01-01

Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (~1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km2 study region in semi-arid Australia to create a spatial model of vegetation age structure, which is primarily the result of stand-replacing fires which occurred before 1972. An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (rs = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery. PMID:27029046

Wildfire and drought dynamics destabilize carbon stores of fire-suppressed forests.

PubMed

Earles, J Mason; North, Malcolm P; Hurteau, Matthew D

2014-06-01

Widespread fire suppression and thinning have altered the structure and composition of many forests in the western United States, making them more susceptible to the synergy of large-scale drought and fire events. We examine how these changes affect carbon storage and stability compared to historic fire-adapted conditions. We modeled carbon dynamics under possible drought and fire conditions over a 300-year simulation period in two mixed-conifer conditions common in the western United States: (1) pine-dominated with an active fire regime and (2) fir-dominated, fire suppressed forests. Fir-dominated stands, with higher live- and dead-wood density, had much lower carbon stability as drought and fire frequency increased compared to pine-dominated forest. Carbon instability resulted from species (i.e., fir's greater susceptibility to drought and fire) and stand (i.e., high density of smaller trees) conditions that develop in the absence of active management. Our modeling suggests restoring historic species composition and active fire regimes can significantly increase carbon stability in fire-suppressed, mixed-conifer forests. Long-term management of forest carbon should consider the relative resilience of stand structure and composition to possible increases in disturbance frequency and intensity under changing climate.

Numerical simulation on behaviour of timber-concrete composite beams in fire

NASA Astrophysics Data System (ADS)

Du, Hao; Hu, Xiamin; Zhang, Bing; Minli, Yao

2017-08-01

This paper established sequentially coupled thermal-mechanical models of timber--concrete composite (TCC) beams by finite element software ANSYS to investigate the fire resistance of TCC beam. Existing experimental results were used to verify the coupled thermal-mechanical model. The influencing parameters consisted of the width of timber beam, the thickness of the concrete slab and the timber board. Based on the numerical results, the effects of these parameters on fire resistance of TCC beams were investigated in detail. The results showed that modeling results agreed well with test results, and verified the reliability of the finite element model. The width of the timber beam had a significant influence on the fire resistance of TCC beams. The fire resistance of TCC beams would be enhanced by increasing the width of timber beam, the thickness of concrete slab and the timber board.

Four-component numerical simulation model of radiative convective interactions in large-scale oxygen-hydrogen turbulent fire balls

DOE Office of Scientific and Technical Information (OSTI.GOV)

Surzhikov, S.T.

1996-12-31

Two-dimensional radiative gas dynamics model for numerical simulation of oxygen-hydrogen fire ball which may be generated by an explosion of a launch vehicle with cryogenic (LO{sub 2}-LH{sub 2}) fuel components is presented. The following physical-chemical processes are taken into account in the numerical model: and effective chemical reaction between the gaseous components (O{sub 2}-H{sub 2}) of the propellant, turbulent mixing and diffusion of the components, and radiative heat transfer. The results of numerical investigations of the following problems are presented: The influence of radiative heat transfer on fire ball gas dynamics during the first 13 sec after explosion, the effectmore » of the fuel gaseous components afterburning on fire ball gas dynamics, and the effect of turbulence on fire ball gas dynamics (in a framework of algebraic model of turbulent mixing).« less

Presynaptic learning and memory with a persistent firing neuron and a habituating synapse: a model of short term persistent habituation.

PubMed

Ramanathan, Kiruthika; Ning, Ning; Dhanasekar, Dhiviya; Li, Guoqi; Shi, Luping; Vadakkepat, Prahlad

2012-08-01

Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show that, depending on the amount of synaptic resources, persistent firing either results in continued habituation or maintains the response, both leading to longer recovery times. The effectiveness of the model as an element in a bio-inspired memory system is discussed.

Data Filtering of Western Hemisphere GOES Wildfire ABBA Products

NASA Astrophysics Data System (ADS)

Theisen, M.; Prins, E.; Schmidt, C.; Reid, J. S.; Hunter, J.; Westphal, D.

2002-05-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE') project was developed to model biomass burning emissions, transport, and radiative effects in real time. The model relies on data from the Geostationary Operational Environment Satellites (GOES-8, GOES-10), that is generated by the Wildfire Automated Biomass Burning Algorithm (WF ABBA). In an attempt to develop the most accurate modeling system the data set needs to be filtered to distinguish the true fire pixels from false alarms. False alarms occur due to reflection of solar radiation off of standing water, surface structure variances, and heat anomalies. The Reoccurring Fire Filtering algorithm (ReFF) was developed to address such false alarms by filtering data dependent on reoccurrence, location in relation to region and satellite, as well as heat intensity. WF ABBA data for the year 2000 during the peak of the burning season were analyzed using ReFF. The analysis resulted in a 45% decrease in North America and only a 15% decrease in South America, respectively, in total fire pixel occurrence. The lower percentage decrease in South America is a result of fires burning for longer periods of time, less surface variance, as well as an increase in heat intensity of fires for that region. Also fires are so prevalent in the region that multiple fires may coexist in the same 4-kilometer pixel.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane.

PubMed

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-03-05

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m² and 16.39 kW/m² for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m². The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane

PubMed Central

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-01-01

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m2 and 16.39 kW/m2 for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m2. The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation. PMID:28773295

Factors in adoption of a fire department wellness program: champ-and-chief model.

PubMed

Kuehl, Hannah; Mabry, Linda; Elliot, Diane L; Kuehl, Kerry S; Favorite, Kim C

2013-04-01

To identify and evaluate determinants of fire departments' wellness program adoption. The Promoting Healthy Lifestyles: Alternative Models' Effects fire service wellness program was offered for free to all medium-sized fire departments in Oregon and Washington. An invitation to participate was mailed to key fire department decision makers (chief, union president, and wellness officer). These key decision makers from 12 sites that adopted the program and 24 matched nonadopting sites were interviewed and results were analyzed to define adoption determinants. Three adoption requirements were identified: (1) mailer connection, (2) local firefighter wellness champion, and (3) willing fire chief, whereas a fourth set of organizational factors had little or no impact on adoption including previous and ongoing wellness activities, financial pressures, and resistance to change. Findings identified determinants of medium-sized fire service wellness program adoption.

Active fire detection using a peat fire radiance model

NASA Astrophysics Data System (ADS)

Kushida, K.; Honma, T.; Kaku, K.; Fukuda, M.

2011-12-01

The fire fractional area and radiances at 4 and 11 μm of active fires in Indonesia were estimated using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. Based on these fire information, a stochastic fire model was used for evaluating two fire detection algorithms of Moderate Resolution Imaging Spectroradiometer (MODIS). One is single-image stochastic fire detection, and the other is multitemporal stochastic fire detection (Kushida, 2010 - IEEE Geosci. Remote Sens. Lett.). The average fire fractional area per one 1 km2 ×1 km2 pixel was 1.7%; this value corresponds to 32% of that of Siberian and Mongolian boreal forest fires. The average radiances at 4 and 11 μm of active fires were 7.2 W/(m2.sr.μm) and 11.1 W/(m2.sr.μm); these values correspond to 47% and 91% of those of Siberian and Mongolian boreal forest fires, respectively. In order to get false alarms less than 20 points per 106 km2 area, for the Siberian and Mongolian boreal forest fires, omission errors (OE) of 50-60% and about 40% were expected for the detections by using the single and multitemporal images, respectively. For Indonesian peat fires, OE of 80-90% was expected for the detections by using the single images. For the peat-fire detections by using the multitemporal images, OE of about 40% was expected, provided that the background radiances were estimated from past multitemporal images with less than the standard deviation of 1K. The analyses indicated that it was difficult to obtain sufficient active-fire information of Indonesian peat fires from single MODIS images for the fire fighting, and that the use of the multitemporal images was important.

Supporting FIRE-suppression strategies combining fire spread MODelling and SATellite data in an operational context in Portugal: the FIRE-MODSAT project

NASA Astrophysics Data System (ADS)

Sá, Ana C. L.; Benali, Akli; Pinto, Renata M. S.; Pereira, José M. C.; Trigo, Ricardo M.; DaCamara, Carlos C.

2014-05-01

Large wildfires are infrequent but account for the most severe environmental, ecological and socio-economic impacts. In recent years Portugal has suffered the impact of major heat waves that fuelled records of burnt area exceeding 400.000ha and 300.000ha in 2003 and 2005, respectively. According to the latest IPCC reports, the frequency and amplitude of summer heat waves over Iberia will very likely increase in the future. Therefore, most climate change studies point to an increase in the number and extent of wildfires. Thus, an increase in both wildfire impacts and fire suppression difficulties is expected. The spread of large wildfires results from a complex interaction between topography, meteorology and fuel properties. Wildfire spread models (e.g. FARSITE) are commonly used to simulate fire growth and behaviour and are an essential tool to understand their main drivers. Additionally, satellite active-fire data have been used to monitor the occurrence, extent, and spread of wildfires. Both satellite data and fire spread models provide different types of information about the spatial and temporal distribution of large wildfires and can potentially be used to support strategic decisions regarding fire suppression resource allocation. However, they have not been combined in a manner that fully exploits their potential and minimizes their limitations. A knowledge gap still exists in understanding how to minimize the impacts of large wildfires, leading to the following research question: What can we learn from past large wildfires in order to mitigate future fire impacts? FIRE-MODSAT is a one-year funded project by the Portuguese Foundation for the Science and Technology (FCT) that is founded on this research question, with the main goal of improving our understanding on the interactions between fire spread and its environmental drivers, to support fire management decisions in an operational context and generate valuable information to improve the efficiency of the fire suppression system. This project proposes to explore an innovative combination of remote sensing and fire spread models in order to 1) better understand the interactions of fire spread drivers that lead to large wildfires; 2) identify the spatio-temporal frames in which large wildfires can be suppressed more efficiently, and 3) explore the essential steps towards an operational use of both tools to assist fire suppression decisions. Preliminary results combine MODIS active-fire data and burn scar perimeters, to derive the main fire spread paths for the 10 largest wildfires that occurred in Portugal between 2001 and 2012. Fire growth and behavior simulations of some of those wildfires are assessed using the active fires data. Results are also compared with the major fire paths to understand the main drivers of fire propagation, through their interactions with topography, vegetation and meteorology. These combined results are also used for spatial and temporal identification of opportunity windows for a more efficient suppression intervention for each fire event. The approach shows promising results, providing a valuable reconstruction of the fire events and retrieval of important parameters related to the complex spread patterns of individual fire events.

Simulating modern-day cropland and pasture burning in an Earth system model

NASA Astrophysics Data System (ADS)

Rabin, Sam; Malyshev, Sergey; Shevliakova, Elena; Magi, Brian; Pacala, Steve

2015-04-01

Throughout the Holocene, humans have extended our influence across a larger and larger fraction of ecosystems, even creating some new ones in the process. Herds of livestock grazing either native vegetation (rangeland) or specially planted species (pasture) have modified huge areas of land. We have even developed new plant species and cultivated them as crops. The extent of our ecosystem modification intensified dramatically with the advent of industrialized agriculture, to the point where cropland and pasture (which will henceforth encompass rangeland as well) now cover over a third of the Earth's land area. One way we have altered the terrestrial biosphere is by intentionally and unintentionally altering fire's frequency, intensity, and seasonal timing. This is especially true for agricultural ecosystems. Because their maintenance and use require a level of human control, cropland and pasture often experience fire regimes substantially different from those of the ecosystems they replaced or what would occur in the absence of active fire management. For example, farmers might burn to prepare land for planting or to dispose of crop residues, and pastoralists often use fire to prevent encroachment of unpalatable woody plants. Due to the vast global extent of agriculture, and considering the myriad ways fire affects the Earth system, it is critical that we understand (a) the ways people manage fire on cropland and pasture and (b) the effects of this management on the Earth system. Earth system models are an ideal tool for examining this kind of question. By simulating the processes within and interactions among the atmosphere, oceans, land, and terrestrial ecosystems, Earth system models allow phenomena such as fire to be examined in their global context. However, while the past fifteen years have seen great progress in the simulation of vegetation fire within Earth system models, the direct human influence via cropland and pasture management burning has been mostly ignored. Instead, indirect functions are usually used to incorporate human influence based on population density and economic factors. This paper describes a global fire model that incorporates knowledge from new estimates of cropland and pasture burning to explicitly simulate fire on those lands across the world. After briefly describing some of the agricultural fire patterns observed in Eurasia, we detail the structure of the model and context in which it was developed. We then use the model to investigate the contribution of cropland and pasture fire to emissions of greenhouse gases and aerosols, as well as net carbon cycling across the globe.

Integrate-and-fire models with an almost periodic input function

NASA Astrophysics Data System (ADS)

Kasprzak, Piotr; Nawrocki, Adam; Signerska-Rynkowska, Justyna

2018-02-01

We investigate leaky integrate-and-fire models (LIF models for short) driven by Stepanov and μ-almost periodic functions. Special attention is paid to the properties of the firing map and its displacement, which give information about the spiking behavior of the considered system. We provide conditions under which such maps are well-defined and are uniformly continuous. We show that the LIF models with Stepanov almost periodic inputs have uniformly almost periodic displacements. We also show that in the case of μ-almost periodic drives it may happen that the displacement map is uniformly continuous, but is not μ-almost periodic (and thus cannot be Stepanov or uniformly almost periodic). By allowing discontinuous inputs, we extend some previous results, showing, for example, that the firing rate for the LIF models with Stepanov almost periodic input exists and is unique. This is a starting point for the investigation of the dynamics of almost-periodically driven integrate-and-fire systems.

Carbon loss and greenhouse gas emission from extreme fire events occurred in Sardinia, Italy

NASA Astrophysics Data System (ADS)

Bacciu, V. M.; Salis, M.; Pellizzaro, G.; Arca, B.; Duce, P.; Spano, D.

2011-12-01

It is widely recognized that biomass burning is a significant driver of CO2 cycling and a source of greenhouse gases, aerosol particles, and other chemically reactive atmospheric gases. The large amounts of carbon that fires release into the atmosphere could approach levels of anthropogenic carbon emissions, especially in years of extreme fire activity. CO2 emissions from 2007 forest fires in Greece were in the range of 4.5 Mt, representing about the 4% of the total annual CO2 emissions of that country (http://effis.jrc.it/). Barbosa et al. (2006) reported a similar percentage of fire emissions to total emissions of CO2 in Portugal during the extreme fire seasons of 2003 and 2005. Currently, inventory methods for biomass burning emission use the equation first proposed by Seiler and Crutzen (1980), taking into account the area burned, the amount of biomass burned, and the emission factors associated with each specific chemical species. However, several errors and uncertainties can affect the emission assessment, due to the estimate consistency of the various parameters involved in the equation, including flaming and smoldering combustion periods, appropriate fuel load evaluations and gaseous emission factors for different fuel fractions and fire types. In this context, model approaching can contribute to better appraise fuel consumption and the resultant emissions. In addition, more comprehensive and accurate data inputs would be of valuable help for predicting and quantifying the source and the composition of fire emissions. The purpose of this work is to explore the impacts of extreme fire events occurred in Sardinia Island (Italy) using an integrated approach combining modelling fire emissions, field observations and remotely-sensed data. In order to achieve realistic fire emission estimates, we used the FOFEM model, due to the necessity to use a consistent modeling methodology across source categories, the input required, and its ability to estimate flaming and smoldering emissions. FOFEM input fuel load data were surveyed to represent those combusted, and fuel availability was obtained from supervised classification of remotely-sensed images. Data relative to fire perimeters, fire weather data, and fire behaviour were gathered by the Sardinian Forestry Corps (CFVA). Consumptions and emissions for each fuel types were estimated through FOFEM. Finally, all the data were assembled into a Geographical Information System (GIS) to facilitate manipulation and display of the data. The results showed the crucial role of appropriate fuel, fire, and weather data and maps to attain reasonable simulations of fuel consumption and smoke emissions. Carbon emission estimates are sensitive to pre-fire fuel loads, so the method used to establish initial fuel conditions is crucial. The FOFEM outputs and the derived smoke emission maps are useful for several applications including emissions inventories, air quality management plans, and emission source models coupled with dispersion models and decision support systems.

Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductance-based synaptic drive.

PubMed

Richardson, Magnus J E

2007-08-01

Integrate-and-fire models are mainstays of the study of single-neuron response properties and emergent states of recurrent networks of spiking neurons. They also provide an analytical base for perturbative approaches that treat important biological details, such as synaptic filtering, synaptic conductance increase, and voltage-activated currents. Steady-state firing rates of both linear and nonlinear integrate-and-fire models, receiving fluctuating synaptic drive, can be calculated from the time-independent Fokker-Planck equation. The dynamic firing-rate response is less easy to extract, even at the first-order level of a weak modulation of the model parameters, but is an important determinant of neuronal response and network stability. For the linear integrate-and-fire model the response to modulations of current-based synaptic drive can be written in terms of hypergeometric functions. For the nonlinear exponential and quadratic models no such analytical forms for the response are available. Here it is demonstrated that a rather simple numerical method can be used to obtain the steady-state and dynamic response for both linear and nonlinear models to parameter modulation in the presence of current-based or conductance-based synaptic fluctuations. To complement the full numerical solution, generalized analytical forms for the high-frequency response are provided. A special case is also identified--time-constant modulation--for which the response to an arbitrarily strong modulation can be calculated exactly.

A population model of chaparral vegetation response to frequent wildfires.

PubMed

Lucas, Timothy A; Johns, Garrett; Jiang, Wancen; Yang, Lucie

2013-12-01

The recent increase in wildfire frequency in the Santa Monica Mountains (SMM) may substantially impact plant community structure. Species of Chaparral shrubs represent the dominant vegetation type in the SMM. These species can be divided into three life history types according to their response to wildfires. Nonsprouting species are completely killed by fire and reproduce by seeds that germinate in response to a fire cue, obligate sprouting species survive by resprouting from dormant buds in a root crown because their seeds are destroyed by fire, and facultative sprouting species recover after fire both by seeds and resprouts. Based on these assumptions, we developed a set of nonlinear difference equations to model each life history type. These models can be used to predict species survivorship under varying fire return intervals. For example, frequent fires can lead to localized extinction of nonsprouting species such as Ceanothus megacarpus while several facultative sprouting species such as Ceanothus spinosus and Malosma (Rhus) laurina will persist as documented by a longitudinal study in a biological preserve in the SMM. We estimated appropriate parameter values for several chaparral species using 25 years of data and explored parameter relationships that lead to equilibrium populations. We conclude by looking at the survival strategies of these three species of chaparral shrubs under varying fire return intervals and predict changes in plant community structure under fire intervals of short return. In particular, our model predicts that an average fire return interval of greater than 12 years is required for 50 % of the initial Ceanothus megacarpus population and 25 % of the initial Ceanothus spinosus population to survive. In contrast, we predict that the Malosma laurina population will have 90 % survivorship for an average fire return interval of at least 6 years.

Uncertainty quantification and propagation in a complex human-environment system driven by fire and climate

NASA Astrophysics Data System (ADS)

Terando, A. J.; Reich, B. J.; Pacifici, K.

2013-12-01

Fire is an important disturbance process in many coupled natural-human systems. Changes in the frequency and severity of fires due to anthropogenic climate change could have significant costs to society and the plant and animal communities that are adapted to a particular fire regime Planning for these changes requires a robust model of the relationship between climate and fire that accounts for multiple sources of uncertainty that are present when simulating ecological and climatological processes. Here we model how anthropogenic climate change could affect the wildfire regime for a region in the Southeast US whose natural ecosystems are dependent on frequent, low-intensity fires while humans are at risk from large catastrophic fires. We develop a modeling framework that incorporates three major sources of uncertainty: (1) uncertainty in the ecological drivers of expected monthly area burned, (2) uncertainty in the environmental drivers influencing the probability of an extreme fire event, and (3) structural uncertainty in different downscaled climate models. In addition we use two policy-relevant emission scenarios (climate stabilization and 'business-as-usual') to characterize the uncertainty in future greenhouse gas forcings. We use a Bayesian framework to incorporate different sources of uncertainty including simulation of predictive errors and Stochastic Search Variable Selection. Our results suggest that although the mean process remains stationary, the probability of extreme fires declines through time, owing to the persistence of high atmospheric moisture content during the peak fire season that dampens the effect of increasing temperatures. Including multiple sources of uncertainty leads to wide prediction intervals, but is potentially more useful for decision-makers that will require adaptation strategies that are robust to rapid but uncertain climate and ecological change.

Variability of fire emissions on interannual to multi-decadal timescales in two Earth System models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ward, D. S.; Shevliakova, E.; Malyshev, S.

Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. HBut, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDLmore » ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. In addition, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.« less