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.

An Implementing Strategy for Improving Wildland Fire Environmental Literacy

NASA Astrophysics Data System (ADS)

McCalla, M. R.; Andrus, D.; Barnett, K.

2007-12-01

Wildland fire is any planned or unplanned fire which occurs in wildland ecosystems. Wildland fires affect millions of acres annually in the U.S. An average of 5.4 million acres a year were burned in the U.S. between 1995 and 2004, approximately 142 percent of the average burned area between 1984 and 1994. In 2005 alone, Federal agencies spent nearly $1 billion on fire suppression and state and local agencies contributed millions more. Many Americans prefer to live and vacation in relatively remote surroundings, (i.e., woods and rangelands). These choices offer many benefits, but they also present significant risks. Most of North America is fire-prone and every day developed areas and home sites are extending further into natural wildlands, which increases the chances of catastrophic fire. In addition, an abundance of accumulated biomass in forests and rangelands and persistent drought conditions are contributing to larger, costlier wildland fires. To effectively prevent, manage, suppress, respond to, and recover from wildland fires, fire managers, and other communities which are impacted by wildland fires (e.g., the business community; healthcare providers; federal, state, and local policymakers; the media; the public, etc.) need timely, accurate, and detailed wildland fire weather and climate information to support their decision-making activities. But what are the wildland fire weather and climate data, products, and information, as well as information dissemination technologies, needed to reach out and promote wildland fire environmental literacy in these communities? The Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) conducted a comprehensive review and assessment of weather and climate needs of providers and users in their wildland fire and fuels management activities. The assessment has nine focus areas, one of which is environmental literacy (e.g., education, training, outreach, partnering, and collaboration). The OFCM model for promoting wildland fire environmental literacy, the model's component parts, as well as an implementing strategy to execute the model will be presented. That is, the presentation will lay out the framework and methodology which the OFCM used to systematically define the wildland fire weather and climate education and outreach needs through interdepartmental collaboration within the OFCM coordinating infrastructure. A key element of the methodology is to improve the overall understanding and use of wildland fire forecast and warning climate and weather products and to exploit current and emerging technologies to improve the dissemination of customer-tailored forecast and warning information and products to stakeholders and users. Thus, the framework and methodology define the method used to determine the target public, private, and academic sector audiences. The methodology also identifies the means for determining the optimal channels, formats, and content for informing end users in time for effective action to be taken.

Fission in R-processes Elements (FIRE) - Annual Report: Fiscal Year 2017

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

Schunck, Nicolas

The goal of the FIRE topical collaboration in nuclear theory is to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This will be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, beta-delayed) that have been developed at LLNL and LANL. The collaboration is composed of LLNL (lead) and LANL for work on nuclear data (ground-state properties, fission, beta-decay), BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r-process simulations. Under DOE/NNSA agreement, both universitiesmore » receive funds from the DOE Office of Science, while national laboratories receive funds directly from NA221.« less

The Making of National Seasonal Wildfire Outlooks

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Brown, T. J.

2015-12-01

Bridging the gap between research-based experiments and fully operational products has been likened to crossing the valley of death. In this talk, we document the development of pre-season fire potential outlooks, informed by seasonal climate predictions, through a long-term collaboration between NOAA RISA teams, the Program for Climate, Ecosystem and Fire Applications (Desert Research Institute), the National Interagency Fire Center's Predictive Services program and multiple collaborators. To transition experimental outlooks into a sustained, monthly operational product, we co-developed a temporary institution, the National Seasonal Assessment Workshops, as a platform for cross-disciplinary knowledge exchange, training, and experimentation in consensus forecast processes and product development. In our retrospective evaluation of the process, we identified several factors that supported the transition from research to operations. These include: the development of new institutions; focus on a geographic scale commensurate with the needs of federal and state land management agencies; participatory and deliberative engagements; cooperation by many partners with perspectives on the connections between climate and wildland fire management; and iterative engagement sustained by funding and human resource commitments from the key partners. Through co-production of the outlooks and the institution, we created a cross-disciplinary community of practice, thus, increasing the capacity of fire management practitioners to use climate information in decision making. This experiment in developing a collaborative climate service was not an unqualified success. For example, while practitioners almost always *consult* official probabilistic climate forecasts, based on the output from dynamical and statistical models, they sometimes *act* on information from self-constructed forecasts, based on analysis of analogue years. We recommend research to further examine the distribution and use of the outlooks, further dialogue with practitioners, and research to develop forecast evaluation metrics and practices to improve the use of official forecasts. (The figure shows partnerships, information and communication flows for the development of seasonal fire potential outlooks).

Collaborative planning to reduce risk

Treesearch

Victoria Sturtevant; Pamela Jakes

2008-01-01

Wildland fire knows no political boundaries, nor should efforts to address its risk. Collaboration is not a new idea; many examples of natural resource managers and community groups working together can be found in forest management planning, watershed restoration, and wildland fire suppression (Sturtevant et al. 2005). Direction from a number of sources has urged...

Large-Scale Spacecraft Fire Safety Tests

NASA Technical Reports Server (NTRS)

Urban, David; Ruff, Gary A.; Ferkul, Paul V.; Olson, Sandra; Fernandez-Pello, A. Carlos; T'ien, James S.; Torero, Jose L.; Cowlard, Adam J.; Rouvreau, Sebastien; Minster, Olivier;

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.

A new North American fire scar network for reconstructing historical pyrogeography, 1600-1900 AD

Treesearch

Donald A. Falk; Thomas Swetnam; Thomas Kitzberger; Elaine Sutherland; Peter Brown; Erica Bigio; Matthew Hall

2013-01-01

The Fire and Climate Synthesis (FACS) project is a collaboration of about 50 fire ecologists to compile and synthesize fire and climate data for western North America. We have compiled nearly 900 multi-century fire-scar based fire histories from the western United States, Canada, and Mexico. The resulting tree-ring based fire history is the largest and most spatially...

Perspectives on Fire Research Collaboration in Siberia: What Have We Learned; Why Does It Matter; and Where Do We Go from Here?

NASA Astrophysics Data System (ADS)

Conard, S. G.

2010-12-01

My first experience of the vast taiga forests of Russia, and my first chance to meet and work with Russian fire researchers, was at a 1993 conference and field experiment planned jointly by Johann G. Goldammer from Germany and Valentin V. Furyaev from Russia. This meeting was the beginning of a long and fruitful collaboration among US, Canadian, and Russian fire scientists. We all became increasingly aware of the global signifiance of the circumpolar boreal zone, and of the need for better information on the extent and effects of boreal fires. Wildfires are the dominant disturbance regime in the Russian boreal zone, burning 10 to 20 million hectares per year. These fires are a significant source of CO2 and other greenhouse gases and aerosols. Our research team published some of the first remote-sensing based estimates of the extent of fire in Russia and of the potential variability in emissions that could result from different burning conditions. Through a series of 20 prescribed burns we were able to mimic a wide range of burning conditions and obtain information on the impacts on soils, vegetation, and fuel consumption. Based on these experimental fires, we have modeled the effects of weather and fuels on fuel consumption and other factors, and related fire characteristics to emissions, carbon stocks, and soil and vegetation processes. For the past 10 years, we have focused on the ecosystem effects of fires of varying severity in the Scots pine and mixed larch forests of central Siberia, on improved remote-sensing based estimates of burned area and fire effects, and on relating fire weather indices to fire potential and fuel consumption. Logging is an increasingly important disturbance in Russia’s forests, and logged sites, with their high fuel loads seem particularly susceptible to fire. We are currently studying interactions between logging and fire, with an emphasis on the differences in fuel consumption, emissions, and carbon stocks when fires burn in logged and unlogged areas. Fire activity and emissions are projected to increase substantially in the boreal zone as climate warms. We are currently working to develop a 30-yr fire record for Siberia based on satellite data. We will integrate these data with historic fire weather, emissions, and vegetation data to estimate fuel consumption and emissions from fires in Siberia from 1980 to 2010. We will reconstruct past fire regimes using dendrochronology data for selected sub-regions. The relationships derived through this work will provide a basis for projecting the future effects of changing climate on fire patterns, emissions and carbon cycle in Siberia. This project will provide critical information for input to global change models and for analysis of the regional and global impacts of changing fire regimes in the boreal zone.

Strategic Help in User Interfaces for Information Retrieval.

ERIC Educational Resources Information Center

Brajnik, Giorgio; Mizzaro, Stefano; Tasso, Carlo; Venuti, Fabio

2002-01-01

Discussion of search strategy in information retrieval by end users focuses on the role played by strategic reasoning and design principles for user interfaces. Highlights include strategic help based on collaborative coaching; a conceptual model for strategic help; and a prototype knowledge-based system named FIRE. (Author/LRW)

Economic opportunities and trade-offs in collaborative forest landscape restoration

Treesearch

Alan A. Ager; Kevin C. Vogler; Michelle A. Day; John D. Bailey

2017-01-01

We modeled forest restoration scenarios to examine socioeconomic and ecological trade-offs associated with alternative prioritization scenarios. The study examined four US national forests designated as priorities for investments to restore fire resiliency and generate economic opportunities to support local industry. We were particularly interested in economic trade-...

OptFuels: Fuel treatment optimization

Treesearch

Greg Jones

2011-01-01

Scientists at the USDA Forest Service, Rocky Mountain Research Station, in Missoula, MT, in collaboration with scientists at the University of Montana, are developing a tool to help forest managers prioritize forest fuel reduction treatments. Although several computer models analyze fuels and fire behavior, stand-level effects of fuel treatments, and priority planning...

Collaborative capacity, problem framing, and mutual trust in addressing the wildland fire social problem: An annotated reading list

Treesearch

Jeffrey J. Brooks; Alexander N. Bujak; Joseph G. Champ; Daniel R. Williams

2006-01-01

We reviewed, annotated, and organized recent social science research and developed a framework for addressing the wildland fire social problem. We annotated articles related to three topic areas or factors, which are critical for understanding collective action, particularly in the wildland-urban interface. These factors are collaborative capacity, problem framing, and...

The Fire Locating and Modeling of Burning Emissions (FLAMBE) Project

NASA Astrophysics Data System (ADS)

Reid, J. S.; Prins, E. M.; Westphal, D.; Richardson, K.; Christopher, S.; Schmidt, C.; Theisen, M.; Eck, T.; Reid, E. A.

2001-12-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE) project was initiated by NASA, the US Navy and NOAA to monitor biomass burning and burning emissions on a global scale. The idea behind the mission is to integrate remote sensing data with global and regional transport models in real time for the purpose of providing the scientific community with smoke and fire products for planning and research purposes. FLAMBE is currently utilizing real time satellite data from GOES satellites, fire products based on the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) are generated for the Western Hemisphere every 30 minutes with only a 90 minute processing delay. We are currently collaborating with other investigators to gain global coverage. Once generated, the fire products are used to input smoke fluxes into the NRL Aerosol Analysis and Prediction System, where advection forecasts are performed for up to 6 days. Subsequent radiative transfer calculations are used to estimate top of atmosphere and surface radiative forcing as well as surface layer visibility. Near real time validation is performed using field data collected by Aerosol Robotic Network (AERONET) Sun photometers. In this paper we fully describe the FLAMBE project and data availability. Preliminary result from the previous year will also be presented, with an emphasis on the development of algorithms to determine smoke emission fluxes from individual fire products. Comparisons to AERONET Sun photometer data will be made.

SNL/JAEA Collaborations on Sodium Fire Benchmarking.

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

Clark, Andrew Jordan; Denman, Matthew R; Takata, Takashi

Two sodium spray fire experiments performed by Sandia National Laboratories (SNL) were used for a code - to - code comparison between CONTAIN - LMR and SPHINCS. Both computer codes are used for modeling sodium accidents in sodium fast reactors. The comparison between the two codes provides insights into the ability of both codes to model sodium spray fires. The SNL T3 and T4 experiments are 20 kg sodium spray fires with sodium spray temperature s of 200 deg C and 500 deg C, respe ctively. Given the relatively low sodium temperature in the SNL T3 experiment, the sodium spraymore » experienced a period of non - combustion. The vessel in the SNL T4 experiment experienced a rapid pressurization that caused of the instrumentation ports to fail during the sodium spray. Despite these unforeseen difficulties, both codes were shown in good agreement with the experiment s . The subsequent pool fire that develops from the unburned sodium spray is a significant characteristic of the T3 experiment. SPHIN CS showed better long - term agreement with the SNL T3 experiment than CONTAIN - LMR. The unexpected port failure during the SNL T4 experiment presented modelling challenges. The time at which the port failure occurred is unknown, but is believed to have occur red at about 11 seconds into the sodium spray fire. The sensitivity analysis for the SNL T4 experiment shows that with a port failure, the sodium spray fire can still maintain elevated pressures during the spray.« less

Bulgarian fuel models developed for implementation in FARSITE simulations for test cases in Zlatograd area

Treesearch

Nina Dobrinkova; LaWen Hollingsworth; Faith Ann Heinsch; Greg Dillon; Georgi Dobrinkov

2014-01-01

As a key component of the cross-border project between Bulgaria and Greece known as OUTLAND, a team from the Bulgarian Academy of Sciences and Rocky Mountain Research Station started a collaborative project to identify and describe various fuel types for a test area in Bulgaria in order to model fire behavior for recent wildfires. Although there have been various...

Advancing Fire Weather Research via Interagency Collaboration: The NOAA/USFS MOU

NASA Astrophysics Data System (ADS)

Schranz, S.; Pouyat, R.

2012-12-01

In 2005, the Western Governors' Association (WGA) first articulated the need for closer collaboration between NOAA and the land management agencies to improve our services - and to ensure the best new technology and scientific advances are infused into fire weather information and services. NOAA has taken the WGA advice very seriously and, over the past few years, have followed up by polling users of our fire weather information. This was done both by our Office of the Federal Coordinator for Meteorology, and via an examination of internal and collaborative research activities as conducted by NOAA's Science Advisory Board. Through these processes, and given the tight budget environment, it's become clear we can't make needed progress alone. We need to call upon our joint expertise, along with the expertise of partners across the federal, state, academic, and research communities. This talk will outline the NOAA/USFS MOU signed in August, 2012 and the collaborative research already begun with the USFS and other partners.

Fire Process Research Natural Areas: Managing research and restoration of dynamic ecosystem processes

Treesearch

Timothy Ingalsbee

2001-01-01

Since 1992 a collaborative group of fire scientists, forest conservationists, and Federal resource specialists have been developing proposals for a Research Natural Area (RNA) in the Warner Creek Fire area on the Willamette National Forest in Oregon. Inspired by these proposals, the Oregon Natural Heritage Plan created the new category of "Fire Process RNAs"...

Hospital collaboration with public safety organizations on bioterrorism response.

PubMed

Niska, Richard W

2008-01-01

To identify hospital characteristics that predict collaboration with public safety organizations on bioterrorism response plans and mass casualty drills. The 2003 and 2004 Bioterrorism and Mass Casualty Supplements to the National Hospital Ambulatory Medical Care Survey examined collaboration with emergency medical services (EMS), hazardous materials teams (HAZMAT), fire departments, and law enforcement. The sample included 112 geographic primary sampling units and 1,110 hospitals. Data were weighted by inverse selection probability, to yield nationally representative estimates. Characteristics included residency and medical school affiliation, bed capacity, ownership, urbanicity and Joint Commission accreditation. The response rate was 84.6%. Chi-square analysis was performed with alpha set at p < 0.05. Logistic regression modeling yielded odds ratios with 95% confidence intervals. During a bioterrorism incident, 68.9% of hospitals would contact EMS, 68.7% percent law enforcement, 61.6% fire departments, 58.1% HAZMAT, and 42.8% all four. About 74.2% had staged mass casualty drills with EMS, 70.4% with fire departments, 67.4% with law enforcement, 43.3% with HAZMAT, and 37.0% with all four. Predictors of drilling with some or all of these public safety organizations included larger bed capacity, nonprofit and proprietary ownership, and JCAHO accreditation. Medical school affiliation was a negative predictor of drilling with EMS. The majority of hospitals involve public safety organizations in their emergency plans or drills. Bed capacity was most predictive of drilling with these organizations. Medical school affiliation was the only characteristic negatively associated with drilling.

Coexisting with fire: Ecosystems, people, and collaboration

Treesearch

Merrill R. Kaufmann; Ayn Shlisky; Jeffrey J. Brooks; Brian Kent

2009-01-01

We are in a "fire crisis." Many regions of the world are experiencing larger, more frequent, and more severe fires that threaten people's lives, livelihoods, and properties, and the health of ecosystems. Regardless of the causes of this crisis - a common threat that crosses cultural and geographical boundaries - societies need informed and...

Wildfire risk reduction in the United States: Leadership staff perceptions of local fire department roles and responsibilities

Treesearch

Rachel S. Madsen; Hylton J. G. Haynes; Sarah M. McCaffrey

2018-01-01

As wildland fires have had increasing negative impacts on a range of human values, in many parts of the United States (U.S.) and around the world, collaborative risk reduction efforts among agencies, homeowners, and fire departments are needed to improve wildfire safety and mitigate risk. Using interview data from 46 senior officers from local fire departments around...

43 CFR 46.210 - Listing of Departmental categorical exclusions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... using prescribed fire not to exceed 4,500 acres, and mechanical methods for crushing, piling, thinning... limited to areas— (i) In wildland-urban interface; and (ii) Condition Classes 2 or 3 in Fire Regime Groups... framework as described in “A Collaborative Approach for Reducing Wildland Fire Risks to Communities and the...

43 CFR 46.210 - Listing of Departmental categorical exclusions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... using prescribed fire not to exceed 4,500 acres, and mechanical methods for crushing, piling, thinning... limited to areas— (i) In wildland-urban interface; and (ii) Condition Classes 2 or 3 in Fire Regime Groups... framework as described in “A Collaborative Approach for Reducing Wildland Fire Risks to Communities and the...

43 CFR 46.210 - Listing of Departmental categorical exclusions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... using prescribed fire not to exceed 4,500 acres, and mechanical methods for crushing, piling, thinning... limited to areas— (i) In wildland-urban interface; and (ii) Condition Classes 2 or 3 in Fire Regime Groups... framework as described in “A Collaborative Approach for Reducing Wildland Fire Risks to Communities and the...

Terrestrial-based lidar beach topography of Fire Island, New York, June 2014

USGS Publications Warehouse

Brenner, Owen T.; Hapke, Cheryl J.; Lee, Kathryn G.; Kimbrow, Dustin R.

2016-02-19

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

Social science to improve fuels management: a synthesis of research on collaboration.

Treesearch

Victoria Sturtevant; Margaret Ann Moote; Pamela Jakes; Anthony S. Cheng

2005-01-01

A series of syntheses were commissioned by the USDA Forest Service to aid in fuels mitigation project planning. This synthesis focuses on collaboration research, and offers knowledge and tools to improve collaboration in the planning and implementation of wildland fire and fuels management projects. It covers a variety of topics including benefits of collaboration,...

New Approach in Modelling Indonesian Peat Fire Emission

NASA Astrophysics Data System (ADS)

Putra, E. I.; Cochrane, M. A.; Saharjo, B.; Yokelson, R. J.; Stockwell, C.; Vetrita, Y.; Zhang, X.; Hagen, S. C.; Nurhayati, A. D.; Graham, L.

2017-12-01

Peat fires are a serious problem for Indonesia, producing devastating environmental effects and making the country the 3rd largest emitter of CO2. Extensive fires ravaged vast areas of peatlands in Sumatra, Kalimantan and Papua during the pronounced El-Nino of 2015, causing international concern when the resultant haze blanketed Indonesia and neighboring countries, severely impacting the health of millions of people. Our recent unprecedented in-situ studies of aerosol and gas emissions from 35 peat fires of varying depths near Palangka Raya, Central Kalimantan have documented the range and variability of emissions from these major fires. We strongly suggest revisions to previously recommended IPPC's emission factors (EFs) from peat fires, notably: CO2 (-8%), CH4 (-55%), NH3 (-86%), and CO (+39%). Our findings clearly showed that Indonesian carbon equivalent measurements (100 years) might have been 19% less than what current IPCC emission factors indicate. The results also demonstrate the toxic air quality in the area with HCN, which is almost only emitted by biomass burning, accounting for 0.28% and the carcinogenic compound formaldehyde 0.04% of emissions. However, considerable variation in emissions may exist between peat fires of different Indonesian peat formations, illustrating the need for additional regional field emissions measurements for parameterizing peatland emissions models for all of Indonesia's major peatland areas. Through the continuous mutual research collaboration between the Indonesian and USA scientists, we will implement our standardized field-based analyses of fuels, hydrology, peat burning characteristics and fire emissions to characterize the three major Indonesian peatland formations across four study provinces (Central Kalimantan, Riau, Jambi and West Papua). We will provide spatial and temporal drivers of the modeled emissions and validate them at a national level using biomass burning emissions estimations derived from Visible/Infrared Imager and Radiometer Suite (VIIRS). Multiple LiDAR datasets (2014, 2011, 2007) for Kalimantan will be used to quantify model accuracy, and new work will be undertaken to quantify uncertainty in our most recent LiDAR-based digital terrain model (DTM), further improving assessments of modelling errors.

Fuels planning: science synthesis and integration; social issues fact sheet 09: Benefits of collaboration

Treesearch

Christine Esposito

2006-01-01

Wildland fire professionals at the Federal, State, and local levels have a long tradition of collaborating across agencies and jurisdictions to achieve goals that they could not achieve independently. This fact sheet discusses the reasons and resources for collaboration.Other...

LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment

USGS Publications Warehouse

Rollins, Matthew G.

2009-01-01

LANDFIRE is a 5-year, multipartner project producing consistent and comprehensive maps and data describing vegetation, wildland fuel, fire regimes and ecological departure from historical conditions across the United States. It is a shared project between the wildland fire management and research and development programs of the US Department of Agriculture Forest Service and US Department of the Interior. LANDFIRE meets agency and partner needs for comprehensive, integrated data to support landscape-level fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. The LANDFIRE data production framework is interdisciplinary, science-based and fully repeatable, and integrates many geospatial technologies including biophysical gradient analyses, remote sensing, vegetation modelling, ecological simulation, and landscape disturbance and successional modelling. LANDFIRE data products are created as 30-m raster grids and are available over the internet at www.landfire.gov, accessed 22 April 2009. The data products are produced at scales that may be useful for prioritizing and planning individual hazardous fuel reduction and ecosystem restoration projects; however, the applicability of data products varies by location and specific use, and products may need to be adjusted by local users.

Wildfire risk to residential structures in the Island Park Sustainable Fire Community: Caribou-Targhee National Forest

Treesearch

Don Helmbrecht; Julie Gilbertson-Day; Joe H. Scott; LaWen Hollingsworth

2016-01-01

The Island Park Sustainable Fire Community (IPSFC) Project is a collaborative working group of citizens, businesses, non-profit organizations, and local, state, and federal government agencies (www.islandparkfirecommunity.com) working to create fire-resilient ecosystems in and around the human communities of West Yellowstone, Montana and Island Park, Idaho....

Using ArcObjects for automating fireshed assessments and analyzing wildfire risk

Treesearch

Alan A. Ager; Bernhard Bahro; Mark Finney

2006-01-01

Firesheds are geographic units used by the Forest Service to delineate areas with similar fire regimes, fire history, and wildland fire risk issues. Fireshed assessment is a collaborative process where specialists design fuel treatments to mitigate wildfire risk. Fireshed assessments are an iterative process where fuel treatments are proposed for specific stands based...

Fuels planning: science synthesis and integration; social issues fact sheet 12: Keys to successful collaboration

Treesearch

Christine Esposito

2006-01-01

Collaborating on fire and fuels management with a host of public and private partners may seem like an impossible undertaking, and presents many challenges. This fact sheet reviews tips for what to focus on as you embark on a collaborative fuels management project.Other...

Gaps in Data and Modeling Tools for Understanding Fire and Fire Effects in Tundra Ecosystems

NASA Astrophysics Data System (ADS)

French, N. H.; Miller, M. E.; Loboda, T. V.; Jenkins, L. K.; Bourgeau-Chavez, L. L.; Suiter, A.; Hawkins, S. M.

2013-12-01

As the ecosystem science community learns more about tundra ecosystems and disturbance in tundra, a review of base data sets and ecological field data for the region shows there are many gaps that need to be filled. In this paper we will review efforts to improve our knowledge of the occurrence and impacts of fire in the North American tundra region completed under a NASA Terrestrial Ecology grant. Our main source of information is remote sensing data from satellite sensors and ecological data from past and recent field data collections by our team, collaborators, and others. Past fire occurrence is not well known for this region compared with other North American biomes. In this presentation we review an effort to use a semi-automated detection algorithm to identify past fire occurrence using the Landsat TM/ETM+ archives, pointing out some of the still-unaddressed issues for a full understanding of fire regime for the region. For this task, fires in Landsat scenes were mapped using the Random Forest classifier (Breiman 2001) to automatically detect potential burn scars. Random Forests is an ensemble classifier that employs machine learning to build a large collection of decision trees that are grown from a random selection of user supplied training data. A pixel's classification is then determined by which class receives the most 'votes' from each tree. We also review the use fire location records and existing modeling methods to quantify emissions from these fires. Based on existing maps of vegetation fuels, we used the approach developed for the Wildland Fire Emissions Information System (WFEIS; French et al. 2011) to estimate emissions across the tundra region. WFEIS employs the Consume model (http://www.fs.fed.us/pnw/fera/research/smoke/consume/index.shtml) to estimate emissions by applying empirically developed relationships between fuels, fire conditions (weather-based fire indexes), and emissions. Here again, we will review the gaps in data and modeling capability for accurate estimation of fire emissions in this region. Initial evaluation of Landsat for tundra fire characterization (Loboda et al. 2013) and successful use of the rich archive of Synthetic Aperture Radar imagery for many fire-disturbed sites in the region will be additional topics covered in this poster presentation. References: Breiman, L. 2001. Random forests. Machine Learning, 45:5-32. French, N.H.F., W.J. de Groot, L.K. Jenkins, B.. Rogers, et al. 2011. Model comparisons for estimating carbon emissions from North American wildland fire. J. Geophys. Res. 116:G00K05, doi:10.1029/2010JG001469. Loboda, T L, N H F French, C. Hight-Harf, L. Jenkins, M.E. Miller. 2013. Mapping fire extent and burn severity in Alaskan tussock tundra: An analysis of the spectral response of tundra vegetation to wildland fire. Remote Sens. Enviro. 134:194-209.

Visions of Restoration in Fire-Adapted Forest Landscapes: Lessons from the Collaborative Forest Landscape Restoration Program.

PubMed

Urgenson, Lauren S; Ryan, Clare M; Halpern, Charles B; Bakker, Jonathan D; Belote, R Travis; Franklin, Jerry F; Haugo, Ryan D; Nelson, Cara R; Waltz, Amy E M

2017-02-01

Collaborative approaches to natural resource management are becoming increasingly common on public lands. Negotiating a shared vision for desired conditions is a fundamental task of collaboration and serves as a foundation for developing management objectives and monitoring strategies. We explore the complex socio-ecological processes involved in developing a shared vision for collaborative restoration of fire-adapted forest landscapes. To understand participant perspectives and experiences, we analyzed interviews with 86 respondents from six collaboratives in the western U.S., part of the Collaborative Forest Landscape Restoration Program established to encourage collaborative, science-based restoration on U.S. Forest Service lands. Although forest landscapes and group characteristics vary considerably, collaboratives faced common challenges to developing a shared vision for desired conditions. Three broad categories of challenges emerged: meeting multiple objectives, collaborative capacity and trust, and integrating ecological science and social values in decision-making. Collaborative groups also used common strategies to address these challenges, including some that addressed multiple challenges. These included use of issue-based recommendations, field visits, and landscape-level analysis; obtaining support from local agency leadership, engaging facilitators, and working in smaller groups (sub-groups); and science engagement. Increased understanding of the challenges to, and strategies for, developing a shared vision of desired conditions is critical if other collaboratives are to learn from these efforts.

Visions of Restoration in Fire-Adapted Forest Landscapes: Lessons from the Collaborative Forest Landscape Restoration Program

NASA Astrophysics Data System (ADS)

Urgenson, Lauren S.; Ryan, Clare M.; Halpern, Charles B.; Bakker, Jonathan D.; Belote, R. Travis; Franklin, Jerry F.; Haugo, Ryan D.; Nelson, Cara R.; Waltz, Amy E. M.

2017-02-01

Collaborative approaches to natural resource management are becoming increasingly common on public lands. Negotiating a shared vision for desired conditions is a fundamental task of collaboration and serves as a foundation for developing management objectives and monitoring strategies. We explore the complex socio-ecological processes involved in developing a shared vision for collaborative restoration of fire-adapted forest landscapes. To understand participant perspectives and experiences, we analyzed interviews with 86 respondents from six collaboratives in the western U.S., part of the Collaborative Forest Landscape Restoration Program established to encourage collaborative, science-based restoration on U.S. Forest Service lands. Although forest landscapes and group characteristics vary considerably, collaboratives faced common challenges to developing a shared vision for desired conditions. Three broad categories of challenges emerged: meeting multiple objectives, collaborative capacity and trust, and integrating ecological science and social values in decision-making. Collaborative groups also used common strategies to address these challenges, including some that addressed multiple challenges. These included use of issue-based recommendations, field visits, and landscape-level analysis; obtaining support from local agency leadership, engaging facilitators, and working in smaller groups (sub-groups); and science engagement. Increased understanding of the challenges to, and strategies for, developing a shared vision of desired conditions is critical if other collaboratives are to learn from these efforts.

Private-public collaboration to reintroduce fire into the changing ecosystems of the Southwestern Borderlands region

Treesearch

Gerald J. Gottfried; Larry S. Allen; Peter L. Warren; Bill McDonald; Ronald J. Bemis; Carleton B. Edminster

2009-01-01

Fires caused by lightning or Native Americans were the major ecological factor in the borderlands region of Arizona, New Mexico, and Mexico prior to European settlement. Historical overgrazing and aggressive fire suppression have led to the encroachment of woody vegetation and accumulations of woody fuels in these grasslands. Ranchers associated with the Malpai...

Ground-based lidar beach topography of Fire Island, New York, April 2013

USGS Publications Warehouse

Brenner, Owen T.; Hapke, Cheryl J.; Spore, Nicholas J.; Brodie, Katherine L.; McNinch, Jesse E.

2015-01-01

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, strong winter storms. The ongoing beach monitoring is part of the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

Bathymetry of the Wilderness breach at Fire Island, New York, June 2013

USGS Publications Warehouse

Brownell, Andrew T.; Hapke, Cheryl J.; Spore, Nicholas J.; McNinch, Jesse E.

2015-01-01

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, collaborated with the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, to collect shallow water bathymetric data of the Wilderness breach on Fire Island, New York, in June 2013. The breach formed in October 2012 during Hurricane Sandy, and the USGS is involved in a post-Sandy effort to map, monitor, and model the morphologic evolution of the breach as part of Hurricane Sandy Supplemental Project GS2-2B: Linking Coastal Vulnerability and Process, Fire Island. This publication includes a bathymetric dataset of the breach and the adjacent nearshore on the ocean side of the island. The objective of the data collection and analysis is to map the bathymetry of the primary breach channel, ebb shoal, and nearshore bar system.

Unmanned Vehicle Material Flammability Test

NASA Technical Reports Server (NTRS)

Urban, David; Ruff, Gary A.; Fernandez-Pello, A. Carlos; T’ien, James S.; Torero, Jose L.; Cowlard, Adam; Rouvreau, Sebastian; Minster, Olivier; Toth, Balazs; Legros, Guillaume;

Web-of-Objects (WoO)-Based Context Aware Emergency Fire Management Systems for the Internet of Things

PubMed Central

Shamszaman, Zia Ush; Ara, Safina Showkat; Chong, Ilyoung; Jeong, Youn Kwae

2014-01-01

Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository. PMID:24531299

Web-of-Objects (WoO)-based context aware emergency fire management systems for the Internet of Things.

PubMed

Shamszaman, Zia Ush; Ara, Safina Showkat; Chong, Ilyoung; Jeong, Youn Kwae

2014-02-13

Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository.

Electrostatic atomization--Experiment, theory and industrial applications

NASA Astrophysics Data System (ADS)

Okuda, H.; Kelly, Arnold J.

1996-05-01

Experimental and theoretical research has been initiated at the Princeton Plasma Physics Laboratory on the electrostatic atomization process in collaboration with Charged Injection Corporation. The goal of this collaboration is to set up a comprehensive research and development program on the electrostatic atomization at the Princeton Plasma Physics Laboratory so that both institutions can benefit from the collaboration. Experimental, theoretical and numerical simulation approaches are used for this purpose. An experiment consisting of a capillary sprayer combined with a quadrupole mass filter and a charge detector was installed at the Electrostatic Atomization Laboratory to study fundamental properties of the charged droplets such as the distribution of charges with respect to the droplet radius. In addition, a numerical simulation model is used to study interaction of beam electrons with atmospheric pressure water vapor, supporting an effort to develop an electrostatic water mist fire-fighting nozzle.

Measurement and Characterization of Space Shuttle Solid Rocket Motor Plume Acoustics

NASA Technical Reports Server (NTRS)

Kenny, Robert Jeremy

2009-01-01

NASA's current models to predict lift-off acoustics for launch vehicles are currently being updated using several numerical and empirical inputs. One empirical input comes from free-field acoustic data measured at three Space Shuttle Reusable Solid Rocket Motor (RSRM) static firings. The measurements were collected by a joint collaboration between NASA - Marshall Space Flight Center, Wyle Labs, and ATK Launch Systems. For the first time NASA measured large-thrust solid rocket motor plume acoustics for evaluation of both noise sources and acoustic radiation properties. Over sixty acoustic free-field measurements were taken over the three static firings to support evaluation of acoustic radiation near the rocket plume, far-field acoustic radiation patterns, plume acoustic power efficiencies, and apparent noise source locations within the plume. At approximately 67 m off nozzle centerline and 70 m downstream of the nozzle exit plan, the measured overall sound pressure level of the RSRM was 155 dB. Peak overall levels in the far field were over 140 dB at 300 m and 50-deg off of the RSRM thrust centerline. The successful collaboration has yielded valuable data that are being implemented into NASA's lift-off acoustic models, which will then be used to update predictions for Ares I and Ares V liftoff acoustic environments.

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

Brouillette, Greg A.

These are slides for various presentations on C41SR and urban disasters disasters response and recovery tools. These are all mainly charts and images of disaster response and recovery tools. Slides included have headings such as the following: vignette of a disaster response, situational awareness and common operating picture available to EOC, plume modeling capability, Program ASPECT Chemical Response Products, EPA ASPECT - Hurricane RITA Response 9/25/2005, Angel Fire Imagery, incident commander's view/police chief's view/ EMS' view, common situational awareness and collaborative planning, exercise, training capability, systems diagram, Austere Challenge 06 Sim/C4 Requirements, common situational awareness and collaborative planning, exercise, trainingmore » environment, common situational awareness, real world, crisis response, and consequence management.« less

Fire and tribal cultural resources

Treesearch

Frank K. Lake; Jonathan W. Long

2014-01-01

Native American tribes regard plants that have evolved with frequent fire and other natural resources as living cultural resources that provide, water, food, medicines, and other material goods while also sustaining tribal cultural traditions. Collaborations between management agencies and tribes and other Native American groups can incorporate traditional ecological...

Collaborative restoration effects on forest structure in ponderosa pine-dominated forests of Colorado

Treesearch

Jeffery B. Cannon; Kevin J. Barrett; Benjamin M. Gannon; Robert N. Addington; Mike A. Battaglia; Paula J. Fornwalt; Gregory H. Aplet; Antony S. Cheng; Jeffrey L. Underhill; Jennifer S. Briggs; Peter M. Brown

2018-01-01

In response to large, severe wildfires in historically fire-adapted forests in the western US, policy initiatives, such as the USDA Forest Service’s Collaborative Forest Landscape Restoration Program (CFLRP), seek to increase the pace and scale of ecological restoration. One required component of this program is collaborative adaptive management, in which monitoring...

Collaboration in Action: Office of Research and Development ...

EPA Pesticide Factsheets

The "Collaboration in Action: US EPA's Office of Research and Develop - Current Wildfire Research Program" was invited by the USDA's US Forest Service's Scientific Executive Committee to provide USFS scientific leadership active and potential future opportunities for cooperation/collaboration. Health impacts of wildfire smoke merit the attention and action of the US EPA and current research is supported in the ACE and SHC Research Programs. Wildland fire smoke research has taken on greater importance because the 1) contribution of wildland fire PM emissions relative to total US PM emissions is increasing, 2) the population health impacts are measurable and costly, 3) vulnerable and sensitive populations at-risk are increasing attendant to our aging U.S. population and the increasing area of the wildland-urban interface, and 4) health impacts of smoke could be minimized by identifying at-risk individuals and reducing their exposures. Examples are provided. The "Collaboration in Action: US EPA's Office of Research and Develop - Current Wildfire Research Program" was invited by the USDA's US Forest Service's Scientific Executive Committee to provide USFS scientific leadership active and potential future opportunities for cooperation/collaboration.

75 FR 10204 - Collaborative Forest Landscape Restoration Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-05

... Restoration, 2. Fire Ecology, 3. Fire Management, 4. Rural Economic Development, 5. Strategies for Ecological Adaptation to Climate Change, 6. Fish and Wildlife Ecology, and 7. Woody Biomass and Small-Diameter Tree... will be subject to appropriate conflict of interest statutes and standards of ethical conduct. All SGE...

Fuels Products of the LANDFIRE Project

Treesearch

Matthew C. Reeves; Jay R. Kost; Kevin C. Ryan

2006-01-01

The LANDFIRE project is a collaborative interagency effort designed to provide seamless, nationally consistent, locally relevant geographic information systems (GIS) data layers depicting wildland fuels, vegetation and fire regime characteristics. The LANDFIRE project is the first of its kind and offers new opportunity for fire management and research activities. Here...

Identifying Best Practices in the Dissemination of Intelligence to First Responders in the Fire and EMS Services

DTIC Science & Technology

2010-09-01

claim that a daily brief may tend to desensitize the average first responder and they may not read it regularly. The consensus was that a weekly...they risked becoming ineffective and could lead to desensitization to the information provided. 41 Figure 6. Responses to Question 5...information sharing between fire service organizations. State fire chiefs associations, in collaboration with the FSIE, should advertise the benefits of

Cloud Microphysics and Absorption Validation

NASA Technical Reports Server (NTRS)

Ackerman, Steven

2002-01-01

Vertical distributions of particle size and habit were developed from in-situ data collected from three midlatitude cirrus field campaigns (FIRE-1, FIRE-2, and ARM IOP). These new midlatitude microphysical models were used to develop new cirrus scattering models at a number of wavelengths appropriate for use with the MODIS imager (Nasiri et al. 2002). This was the first successful collaborative effort between all the investigators on this proposal. Recent efforts have extended the midlatitude cirrus cloud analyses to tropical cirrus, using in-situ data collected during the Tropical Rainfall Measurement Mission (TRMM) Kwajalein field campaign in 1999. We note that there are critical aspects to the work: a) Improvement in computing the scattering and radiative properties of ice crystals; b) Requirement for copious amounts of cirrus in-situ data, presented in terms of both particle size and habit distributions; c) Development of cirrus microphysical and optical models for various satellite, aircraft, and ground-based instruments based on the theoretical calculations and in-situ measurements; d) Application to satellite data.

Determinants of National Fire Plan Fuels Treatment Expenditures: A Revealed Preference Analysis for Northern New Mexico

NASA Astrophysics Data System (ADS)

Shepherd, Curt; Grimsrud, Kristine; Berrens, Robert P.

2009-10-01

The accumulation of fire fuels in forests throughout the world contributes significantly to the severity of wildfires. To combat the threat of wildfire, especially in the wildland-urban interface (WUI), US federal land management agencies have implemented a number of forest restoration and wildfire risk reduction programs. In the spirit of revealed preference analyses, the objective of this study is to investigate the pattern and determinants of National Fire Plan (NFP) expenditures for fuel reduction treatments in northern New Mexico (USA). Estimation results from a set of Generalized Estimating Equations models are mixed with respect to risk reduction hypotheses, and also raise issues regarding how risk reduction should be defined for a region characterized by both pockets of urban sprawl into the WUI and large areas of chronic rural poverty. Program preferences for project funding under the federal Collaborative Forest Restoration Program in New Mexico are shown to be distinctly different (e.g., exhibiting greater concern for social equity) than for other NFP-funded projects.

Variations in high reliability practices in the federal fire community: Relative contributions of agency affiliation, years of experience, and position hierarchy and function

Treesearch

Brooke Baldauf McBride; Anne E. Black

2012-01-01

While several studies have examined the relevance of the HRO paradigm for fire management, no known empirical studies exist. In late 2007, in collaboration with researchers at the University of Michigan, we embarked on an exploration of the nature and extent of HRO practices in the US fire community. One of the primary questions was: How do HRO practices vary across...

Collaboration and Interconnectivity: Nottinghamshire Fire and Rescue Services and Higher Education Institutions in Nottingham

ERIC Educational Resources Information Center

Murphy, Peter; Greenhalgh, Kirsten; Parkin, Craig

2013-01-01

This article will describe the developing relationship between Nottinghamshire Fire and Rescue Services and the two higher education institutions in Nottingham. It will chronicle how a very traditional relationship has been transformed, initially by a simple consultancy project, into a much closer working relationship characterised by a much…

Preliminary analysis of University of North Dakota aircraft data from the FIRE Cirrus IFO-2

NASA Technical Reports Server (NTRS)

Poellot, Michael R.

1995-01-01

The stated goals of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) are 'to promote the development of improved cloud and radiation parameterization for use in climate models, and to provide for assessment and improvement of ISCCP projects'. FIRE Phase 2 has focused on the formation, maintenance and dissipation of cirrus and marine stratocumulus cloud systems. These objectives have been approached through a combination of modeling, extended-time observations and intensive field observation (IFO) periods. The work under this grant was associated with the FIRE Cirrus IFO 2. This field measurement program was conducted to obtain observations of cirrus cloud systems on a range of scales from the synoptic to the microscale, utilizing simultaneous measurements from a variety of ground-based, satellite and airborne platforms. By combining these remote and in situ measurements a more complete picture of cirrus systems can be obtained. The role of the University of North Dakota in Phase 2 was three-fold: to collect in situ microphysical data during the Cirrus IFO 2; to process and archive these data; and to collaborate in analyses of IFO data. This report will summarize the activities and findings of the work performed under this grant; detailed description of the data sets available and of the analyses are contained in the Semi-annual Status Reports submitted to NASA.

WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

NASA Astrophysics Data System (ADS)

Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

2013-12-01

Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before, during and after a wildfire. Scalability of the WIFIRE approach allows many sensors to be subjected to user-specified data processing algorithms to generate threshold alerts within seconds. Integration of this sensor data into both rapidly available fire image data and models will better enable situational awareness, responses and decision support at local, state, national, and international levels. The products of WIFIRE will be initially disseminated to our collaborators (SDG&E, CAL FIRE, USFS), covering academic, private, and government laboratories while generating values to emergency officials, and consequently to the general public. WIFIRE may be used by government agencies in the future to save lives and property during wildfire events, test the effectiveness of response and evacuation scenarios before they occur and assess the effectiveness of high-density sensor networks in improving fire and weather predictions. WIFIRE's high-density network, therefore, will serve as a testbed for future applications worldwide.

Examining the social acceptability of forest biomass harvesting and utilization from collaborative forest landscape restoration: A case study from western Colorado, USA

Treesearch

Jessica M. Western; Antony S. Cheng; Nathaniel M. Anderson; Pamela Motley

2017-01-01

Collaborative efforts have expanded in recent years to reduce fuel loads and restore the resilience of forest landscapes to future fires. The social acceptability of harvesting and using forest biomass associated with these programs are a hot topic, with questions about the extent to which collaboration can generate unified acceptance. We present results from a Q-...

Evidence of Human Health Impacts from Uncontrolled Coal Fires in Jharia, India

NASA Astrophysics Data System (ADS)

Dhar, U.; Balogun, A. H.; Finkelman, R.; Chakraborty, S.; Olanipekun, O.; Shaikh, W. A.

2017-12-01

Uncontrolled coal fires and burning coal waste piles have been reported from dozens of countries. These fires can be caused by spontaneous combustion, sparks from machinery, lightning strikes, grass or forest fires, or intentionally. Both underground and surface coal fires mobilize potentially toxic elements such as sulfur, arsenic, selenium, fluorine, lead, and mercury as well as dangerous organic compounds such as benzene, toluene, xylene, ethylbenzene and deadly gases such as CO2 and CO. Despite the serious health problems that can be caused by uncontrolled coal fires it is rather surprising that there has been so little research and documentation of their health impacts. Underground coal fires in the Jharia region of India where more than a million people reside, have been burning for 100 years. Numerous villages exist above the underground fires exposing the residents daily to dangerous emissions. Local residents near the fire affected areas do their daily chores without concern about the intensity of nearby fires. During winter children enjoy the heat of the coal fires oblivious to the potentially harmful emissions. To determine if these uncontrolled coal fires have caused health problems we developed a brief questionnaire on general health indices and administered it to residents of the Jharia region. Sixty responses were obtained from residents of two villages, one proximal to the coal fires and one about 5 miles away from the fires. The responses were statistically analyzed using SAS 9.4. It was observed that at a significance level of 5%, villagers who lived more than 5 miles away from the fires had a 98.3% decreased odds of having undesirable health outcomes. This brief survey indicates the risk posed by underground coal fires and how it contributes to the undesirable health impacts. What remains is to determine the specific health issues, what components of the emissions cause the health problems, and what can be done to minimize these problems. Collaboration between geoscientists and public health researchers are essential to assess complex geohealth issues such as those that may be caused by uncontrolled coal fires. This type of multidisciplinary collaboration must be maintained and expanded to include engineers, social scientists, and others to help minimize or avoid these problems.

Automated system for smoke dispersion prediction due to wild fires in Alaska

NASA Astrophysics Data System (ADS)

Kulchitsky, A.; Stuefer, M.; Higbie, L.; Newby, G.

2007-12-01

Community climate models have enabled development of specific environmental forecast systems. The University of Alaska (UAF) smoke group was created to adapt a smoke forecast system to the Alaska region. The US Forest Service (USFS) Missoula Fire Science Lab had developed a smoke forecast system based on the Weather Research and Forecasting (WRF) Model including chemistry (WRF/Chem). Following the successful experience of USFS, which runs their model operationally for the contiguous U.S., we develop a similar system for Alaska in collaboration with scientists from the USFS Missoula Fire Science Lab. Wildfires are a significant source of air pollution in Alaska because the climate and vegetation favor annual summer fires that burn huge areas. Extreme cases occurred in 2004, when an area larger than Maryland (more than 25000~km2) burned. Small smoke particles with a diameter less than 10~μm can penetrate deep into lungs causing health problems. Smoke also creates a severe restriction to air transport and has tremendous economical effect. The smoke dispersion and forecast system for Alaska was developed at the Geophysical Institute (GI) and the Arctic Region Supercomputing Center (ARSC), both at University of Alaska Fairbanks (UAF). They will help the public and plan activities a few days in advance to avoid dangerous smoke exposure. The availability of modern high performance supercomputers at ARSC allows us to create and run high-resolution, WRF-based smoke dispersion forecast for the entire State of Alaska. The core of the system is a Python program that manages the independent pieces. Our adapted Alaska system performs the following steps \\begin{itemize} Calculate the medium-resolution weather forecast using WRF/Met. Adapt the near real-time satellite-derived wildfire location and extent data that are received via direct broadcast from UAF's "Geographic Information Network of Alaska" (GINA) Calculate fuel moisture using WRF forecasts and National Fire Danger Rating System (NFDRS) fuel maps Calculate smoke emission components using a first order fire emission model Model the smoke plume rise yielding a vertically distribution that accounts for one-dimensional (vertical) concentrations of smoke constituents in the atmosphere above the fire Run WRF/Chem at high resolution for the forecast Use standard graphical tools to provide accessible smoke dispersion The system run twice each day at ARSC. The results will be freely available from a dedicated wildfire smoke web portal at ARSC.

Exploring how alternative mapping approaches influence fireshed assessment and human community exposure to wildfire

Treesearch

Joe H. Scott; Matthew P. Thompson; Julie W. Gilbertson-Day

2015-01-01

Attaining fire-adapted human communities has become a key focus of collaborative planning on landscapes across the western United States and elsewhere. The coupling of fire simulation with GIS has expanded the analytical base to support such planning efforts, particularly through the "fireside" concept that identifies areas where wildfires could ignite and...

Talking with the "Enemy": Firing Enthusiasm for History through International Conversation and Collaboration

ERIC Educational Resources Information Center

Kerridge, Richard; Cinnamond, Sacha

2012-01-01

Richard Kerridge and Sacha Cinnamond explain how their history department built a culture of international dialogue and collaboration that enriches their students' historical learning. Video-conferencing is at the centre of these activities. Their story begins with an initial, moving encounter with the First World War battlefields that soon turned…

Climate change and California: potential implications for vegetation, carbon, and fire.

Treesearch

Jonathan Thompson

2005-01-01

Nineteen scientists from leading research institutes in the United States collaborated to estimate how California’s environment and economy would respond to global climate change. A scientist from the PNW Research Station led efforts to estimate effects on vegetation, carbon, and fire.To quantify the range of the possible effects of climate change over the...

Behavior of Mercury Emissions from a Commercial Coal-Fired Utility Boiler: TheRelationship Between Stack Speciation and Near-Field Plume Measurements

EPA Science Inventory

The reduction of divalent gaseous mercury (Hg^II) to elemental gaseous mercury (Hg⁰) in a commercial coal-fired power plant (CFPP)exhaust plume was investigated by simultaneous measurement in-stack and in-plume as part of a collaborative study among the U.S....

Landscape-scale fire restoration on the big piney ranger district in the Ozark highlands of Arkansas

Treesearch

John Andre; McRee Anderson; Douglas Zollner; Marie Melnechuk; Theo Witsell

2009-01-01

The Ozark-St. Francis National Forest, The Nature Conservancy (TNC), the Arkansas Natural Heritage Commission, Arkansas Forestry Commission, private landowners, and others are currently engaged in a collaborative project to restore the oak-hickory and pine-oak ecosystems of the Ozark Highlands on 60,000 acres of the Big Piney Ranger District. Frequent historical fires...

Reduction of Potential Fire Behavior in Wildland-urban Interface Communities in Southern California: A Collaborative Approach

Treesearch

Christopher A. Dicus; Michael E. Scott

2006-01-01

This manuscript details a collaborative effort that reduced the risk of wildfire in an affluent, wildland-urban interface community in southern California while simultaneously minimizing the environmental impact to the site. FARSITE simulations illustrated the potential threat to the community of Rancho Santa Fe in San Diego County, California, where multimillion-...

Collaboration via E-Mail and Internet Relay Chat: Understanding Time and Technology.

ERIC Educational Resources Information Center

Duin, Ann Hill; Archee, Ray

1996-01-01

Examines how college students working across distances used e-mail and Internet Relay Chat (IRC) to facilitate their collaboration and decision-making processes. Finds that students came to a decision more quickly using e-mail than with IRC, and when IRC was slow, students reverted to a series of rapid-fire e-mail messages. (RS)

2017 Fire Protection Informational Exchange Meeting

DTIC Science & Technology

documents the results of an information exchange meeting held May 1011, 2017 at the US Army Research Laboratory, which brought together interested...parties across the armed services to outline, as a community, the current state of the art in fire protection research and engineering and determine...where future efforts would be most advantageous. The forum provided the opportunity to strengthen old collaborations, begin new partnerships, and serve

Strength in Numbers: Data-Driven Collaboration May Not Sound Sexy, But it Could Save Your Job

ERIC Educational Resources Information Center

Buzzeo, Toni

2010-01-01

This article describes a practical, sure-fire way for media specialists to boost student achievement. The method is called data-driven collaboration, and it's a practical, easy-to-use technique in which media specialists and teachers work together to pinpoint kids' instructional needs and improve their essential skills. The author discusses the…

Development of Large-Scale Spacecraft Fire Safety Experiments

NASA Technical Reports Server (NTRS)

Ruff, Gary A.; Urban, David; Fernandez-Pello, A. Carlos; T'ien, James S.; Torero, Jose L.; Legros, Guillaume; Eigenbrod, Christian; Smirnov, Nickolay; Fujita, Osamu; Cowlard, Adam J.;

Principles of effective USA federal fire management plans

USGS Publications Warehouse

Meyer, Marc D.; Roberts, Susan L.; Wills, Robin; Brooks, Matthew L.; Winford, Eric M.

2015-01-01

Federal fire management plans are essential implementation guides for the management of wildland fire on federal lands. Recent changes in federal fire policy implementation guidance and fire science information suggest the need for substantial changes in federal fire management plans of the United States. Federal land management agencies are also undergoing land management planning efforts that will initiate revision of fire management plans across the country. Using the southern Sierra Nevada as a case study, we briefly describe the underlying framework of fire management plans, assess their consistency with guiding principles based on current science information and federal policy guidance, and provide recommendations for the development of future fire management plans. Based on our review, we recommend that future fire management plans be: (1) consistent and compatible, (2) collaborative, (3) clear and comprehensive, (4) spatially and temporally scalable, (5) informed by the best available science, and (6) flexible and adaptive. In addition, we identify and describe several strategic guides or “tools” that can enhance these core principles and benefit future fire management plans in the following areas: planning and prioritization, science integration, climate change adaptation, partnerships, monitoring, education and communication, and applied fire management. These principles and tools are essential to successfully realize fire management goals and objectives in a rapidly changing world.

Burn Education Awareness Recognition and Support (BEARS): a community-based juvenile firesetters assessment and treatment program.

PubMed

Bennett, B K; Gamelli, R L; Duchene, R C; Atkocaitis, D; Plunkett, J A

2004-01-01

In response to the continued staggering statistics of fires set by juveniles and the devastating personal and property costs that are associated with these fires, the Burn and Shock Trauma Institute of Loyola University Medical Center, in collaboration with the State Fire Marshal's Office; the Illinois Fire Safety Alliance; and representatives from the firefighting community, law enforcement, emergency medicine and mental health, came together to create the Burn Education Awareness Recognition and Support Program. Through financial grant support from the International Association of Firefighters, the Illinois Fire Safety Alliance, and other private donations, the Burn Education Awareness Recognition and Support Program is able to provide a free resource to anyone who is concerned about a child playing with fire. Specially trained firefighters assess each child using the tool developed by the Federal Emergency Management Agency. In 2002, we assessed 42 children; 29 of those children were referred through the courts. So far, none of the children treated in our program have returned to fire-setting behaviors.

Contribution of Earth Observation and meteorological datasets for the design and development of a national fire risk assessment system (NFOFRAS)

NASA Astrophysics Data System (ADS)

Katagis, Thomas; Bliziotis, Dimitris; Liantinioti, Chrysa; Gitas, Ioannis Z.; Charalampopoulou, Betty

2016-08-01

During the past decades, forest fires have increased both in frequency and severity thus, increasing the life threats for people and environment and leading countries to spend vast amounts of resources in fighting forest fires. Besides anthropogenic activities, climatic and environmental changes are considered as driving factors affecting fire occurrence and vegetation succession. Especially in the Mediterranean region, the development and existence of effective tools and services is crucial for assisting pre-fire planning and preparedness. The collaborative project NFOFRAS aims at introducing an innovative and effective system for rating forest fire risk, and is based on existing technology and standards that have been developed by countries with a long and a very successful involvement in this field. During the first phase of the project a detailed documentation of the proposed methodology was composed. In addition, Earth Observation (EO) and meteorological datasets were utilized for producing accurate pre-fire measurements over a selected study area in Greece.

Upping The Emergency Management Ante: The Role Of Private Sector Collaboration In Emergency Management And Whether State Procurement And Emergency Management Laws Are Built To Collaborate

DTIC Science & Technology

2016-03-01

welfare, or safety such as may arise by reason of fires, floods, tornadoes , other natural or man-caused disasters, epidemics, riots, enemy attack...West, Westlaw through end of the 2015 First Regular and First Extraordinary Sessions of the 63rd Legislature). 267 Ibid. ( Texas law contains an

Forest-fire models

Treesearch

Haiganoush Preisler; Alan Ager

2013-01-01

For applied mathematicians forest fire models refer mainly to a non-linear dynamic system often used to simulate spread of fire. For forest managers forest fire models may pertain to any of the three phases of fire management: prefire planning (fire risk models), fire suppression (fire behavior models), and postfire evaluation (fire effects and economic models). In...

Bulletin of Forest Fire risk in Albania- The experience of the Albania National Centre for forecast and Monitoring of Natural Risks

NASA Astrophysics Data System (ADS)

Berdufi, I.; Jaupaj, O.; Marku, M.; Deda, M.; Fiori, E.; D'Andrea, M.; Biondi, G.; Fioruci, P.; Massabò, M.; Zorba, P.; Gjonaj, M.

2012-04-01

In the territory of Albania usually every year around 1000 ha are affected by forest fires, from which about 500 ha are completely destroyed. The number of forest fires (nf), with the burning surface (bs) in years has been like this: during the years 1988-1998: nf / bs = 2.19, 1998-2001: nf / bs = 5.66, year 2002 -2005: nf / bs = 8.2, and during the years 2005-2006: nf / bs = 11.9, while economic losses in a year by forest fires is about 2 million of Euro. The increase in years of these figures and the last floods which happened in the last two years in Shkoder, led to an international cooperation, that between the Italian Civil Protection Department and the Albania General Directorate of Civil Emergency. The focus of this cooperation was the building capacity of the Albanian National System of Civil Protection in forecasting, monitoring and prevention forest fires and floods risks. As a result of this collaboration the "National Center for the Forecast and Monitoring of Natural Risks", was set up at the Institute of Geosciences, Energy, Water and Environment. The Center is the first of its kind in Albania. The mission of the Center is the prediction and monitoring of the forest fire and flood risk in the Albanian territory, as a tools for risk reduction and mitigation. The first step to achieve this strategy was the implementation of the forest fires risk forecast model "RISICO". RISICO was adapted for whole Albania territory by CIMA Research Foundation. The Center, in the summer season, issues a daily bulletin. The bulletin reports the potential risk scenarios related with the ignition and propagation of fires in Albania. The bulletin is broadcasted through email or fax within 12.00 AM of each working day. It highlights where and when severe risk conditions may occur within the next 48 hours

An ecosystem services framework for multidisciplinary research in the Colorado River headwaters

USGS Publications Warehouse

Semmens, D.J.; Briggs, J.S.; Martin, D.A.

2009-01-01

A rapidly spreading Mountain Pine Beetle epidemic is killing lodgepole pine forest in the Rocky Mountains, causing landscape change on a massive scale. Approximately 1.5 million acres of lodgepoledominated forest is already dead or dying in Colorado, the infestation is still spreading rapidly, and it is expected that in excess of 90 percent of all lodgepole forest will ultimately be killed. Drought conditions combined with dramatically reduced foliar moisture content due to stress or mortality from Mountain Pine Beetle have combined to elevate the probability of large fires throughout the Colorado River headwaters. Large numbers of homes in the wildland-urban interface, an extensive water supply infrastructure, and a local economy driven largely by recreational tourism make the potential costs associated with such a fire very large. Any assessment of fire risk for strategic planning of pre-fire management actions must consider these and a host of other important socioeconomic benefits derived from the Rocky Mountain Lodgepole Pine Forest ecosystem. This paper presents a plan to focus U.S. Geological Survey (USGS) multidisciplinary fire/beetle-related research in the Colorado River headwaters within a framework that integrates a wide variety of discipline-specific research to assess and value the full range of ecosystem services provided by the Rocky Mountain Lodgepole Pine Forest ecosystem. Baseline, unburned conditions will be compared with a hypothetical, fully burned scenario to (a) identify where services would be most severely impacted, and (b) quantify potential economic losses. Collaboration with the U.S. Forest Service will further yield a distributed model of fire probability that can be used in combination with the ecosystem service valuation to develop comprehensive, distributed maps of fire risk in the Upper Colorado River Basin. These maps will be intended for use by stakeholders as a strategic planning tool for pre-fire management activities and can be updated and improved adaptively on an annual basis as tree mortality, climatic conditions, and management actions unfold. 

In situ Micrometeorological Measurements during RxCADRE

NASA Astrophysics Data System (ADS)

Clements, C. B.; Hiers, J. K.; Strenfel, S. J.

2009-12-01

The Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment (RxCADRE) was a collaborative research project designed to fully instrument prescribed fires in the Southeastern United States. Data were collected on pre-burn fuel loads, post burn consumption, ambient weather, in situ atmospheric dynamics, plume dynamics, radiant heat release (both from in-situ and remote sensors), in-situ fire behavior, and select fire effects. The sampling was conducted at Eglin Air Force Base, Florida, and the Joseph W. Jones Ecological Research Center in Newton, Georgia, from February 29 to March 6, 2008. Data were collected on 5 prescribed burns, totaling 4458 acres. The largest aerial ignition totaled 2,290 acres and the smallest ground ignition totaled 104 acres. Quantifying fire-atmospheric interactions is critical for understanding wildland fire dynamics and enhancing modeling of smoke plumes. During Rx-CADRE, atmospheric soundings using radiosondes were made at each burn prior to ignition. In situ micrometeorological measurements were made within each burn unit using five portable, 10-m towers equipped with sonic and prop anemometers, fine-wire thermocouples, and a carbon dioxide probes. The towers were arranged within the burn units to capture the wind and temperature fields as the fire front and plume passed the towers. Due to the interaction of fire lines following ignition, several of the fire fronts that passed the towers were backing fires and thus less intense. Preliminary results indicate that the average vertical velocities associated with the fire front passage were on the order of 3-5 m s-1 and average plume temperatures were on the order of 30-50 °C above ambient. During two of the experimental burns, radiosondes were released into the fire plumes to determine the vertical structure of the plume temperature, humidity, and winds. A radiosonde released into the plume during the burn conducted on 3 March 2008 indicated a definite plume boundary in the potential temperature and dew point temperature structure. The plume height immediately downwind of the fire front was approximately 150 m AGL and heating within this layer was on the order of 3 K. One interesting feature of the plume was the enhanced wind velocity at the top of the plume. Winds increased by 2 m s-1 in a shallow layer at the very top of the plume boundary indicating enhanced acceleration due to the increase in buoyancy. This experience highlights the dynamism of interacting fire lines within prescribed burns as well as the difficulty of measuring fire-atmospheric interactions on large prescribed fire ignitions.

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Development and Application of Version 2.1 of the Fire INventory from NCAR (FINN)

NASA Astrophysics Data System (ADS)

McDonald-Buller, E.; Wiedinmyer, C.; Kimura, Y.

2016-12-01

The Fire INventory from the National Center for Atmospheric Research (FINN) generates global daily emissions estimates of trace gases and particles from open biomass burning, including wildfires, agricultural fires, and prescribed burning. FINN has been widely used for global and regional air quality studies, offering high spatial and temporal resolution necessary for capturing daily variations in emissions and chemistry, consistency across geopolitical boundaries, and chemical speciation profiles for volatile organic compound (VOC) emissions for the GEOS-Chem, SAPRC99, MOZART-4, and Carbon Bond mechanisms. FINN v.1 was first released in 2010 and updated in 2011. FINN v. 1.5 was released in 2014. The work presented here focuses on a collaborative effort between NCAR and the University of Texas at Austin to develop the next generation of the public release of the model, FINN v.2.1, to benefit air quality management and research initiatives within the U.S. and internationally. Specific objectives have included developing a new algorithm for estimating area burned from satellite-derived fire detections, distinguishing major crop types typically found in the U.S., improving the spatial resolution of fuel loading in the United States, and providing flexibility for applying alternative land cover representations from emerging global, U.S. national, and regional land cover products. A case study applies FINN2.1 for regional emission estimates and air quality predictions in Texas during 2012.

The Multi-Resolution Land Characteristics (MRLC) Consortium: 20 years of development and integration of USA national land cover data

USGS Publications Warehouse

Wickham, James D.; Homer, Collin G.; Vogelmann, James E.; McKerrow, Alexa; Mueller, Rick; Herold, Nate; Coluston, John

2014-01-01

The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Program (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.

Production possibility frontiers and socioecological tradeoffs for restoration of fire adapted forests.

PubMed

Ager, Alan A; Day, Michelle A; Vogler, Kevin

2016-07-01

We used spatial optimization to analyze alternative restoration scenarios and quantify tradeoffs for a large, multifaceted restoration program to restore resiliency to forest landscapes in the western US. We specifically examined tradeoffs between provisional ecosystem services, fire protection, and the amelioration of key ecological stressors. The results revealed that attainment of multiple restoration objectives was constrained due to the joint spatial patterns of ecological conditions and socioeconomic values. We also found that current restoration projects are substantially suboptimal, perhaps the result of compromises in the collaborative planning process used by federal planners, or operational constraints on forest management activities. The juxtaposition of ecological settings with human values generated sharp tradeoffs, especially with respect to community wildfire protection versus generating revenue to support restoration and fire protection activities. The analysis and methods can be leveraged by ongoing restoration programs in many ways including: 1) integrated prioritization of restoration activities at multiple scales on public and adjoining private lands, 2) identification and mapping of conflicts between ecological restoration and socioeconomic objectives, 3) measuring the efficiency of ongoing restoration projects compared to the optimal production possibility frontier, 4) consideration of fire transmission among public and private land parcels as a prioritization metric, and 5) finding socially optimal regions along the production frontier as part of collaborative restoration planning. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Nonlinear Model for Hippocampal Cognitive Prosthesis: Memory Facilitation by Hippocampal Ensemble Stimulation

PubMed Central

Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Gerhardt, Gregory A.; Shin, Dae C.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Samuel A.

2012-01-01

Collaborative investigations have characterized how multineuron hippocampal ensembles encode memory necessary for subsequent successful performance by rodents in a delayed nonmatch to sample (DNMS) task and utilized that information to provide the basis for a memory prosthesis to enhance performance. By employing a unique nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded CA1 and CA3 activity, it was possible to extract information encoded in the sample phase necessary for successful performance in the nonmatch phase of the task. The extension of this MIMO model to online delivery of electrical stimulation delivered to the same recording loci that mimicked successful CA1 firing patterns, provided the means to increase levels of performance on a trial-by-trial basis. Inclusion of several control procedures provides evidence for the specificity of effective MIMO model generated patterns of electrical stimulation. Increased utility of the MIMO model as a prosthesis device was exhibited by the demonstration of cumulative increases in DNMS task performance with repeated MIMO stimulation over many sessions on both stimulation and nonstimulation trials, suggesting overall system modification with continued exposure. Results reported here are compatible with and extend prior demonstrations and further support the candidacy of the MIMO model as an effective cortical prosthesis. PMID:22438334

Fire danger assessment using ECMWF weather prediction system

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca; Pappemberger, Florian; Wetterhall, Fredrik

2015-04-01

Weather plays a major role in the birth, growth and death of a wildfire wherever there is availability of combustible vegetation and suitable terrain topography. Prolonged dry periods creates favourable conditions for ignitions, wind can then increase the fire spread, while higher relative humidity, and precipitation (rain or snow) may decrease or extinguish it altogether. The European Forest Fire Information System (EFFIS), started in 2011 under the lead of the European Joint Research Centre (JRC) to monitor and forecast fire danger and fire behaviour in Europe. In 2012 a collaboration with the European Centre for Medium range Weather Forecast (ECMWF) was established to explore the potential of using state of the art weather forecast systems as driving forcing for the calculations of fire risk indices. From this collaboration in 2013 the EC-fire system was born. It implements the three most commonly used fire danger rating systems (NFDRS, FWI and MARK-5) and it is both initialised and forced by gridded atmospheric fields provided either by ECMWF re-analysis or ECMWF ensemble prediction systems. For consistency invariant fields (i.e fuel maps, vegetation cover, topogarphy) and real-time weather information are all provided on the same grid. Similarly global climatological vegetation stage conditions for each day of the year are provided by remote satellite observations. These climatological static maps substitute the traditional man judgement in an effort to create an automated procedure that can work in places where local observations are not available. The system has been in operation for the last year providing an ensemble of daily forecasts for fire indices with lead-times up to 10 days over Europe and Globally. An important part of the system is provided by its (re)-analysis dataset obtained by using the (re)-analysis forcings as drivers to calculate the fire risk indices. This is a crucial part of the whole chain since these fields are used to establish the initial conditions from which the forecast is subsequently run. The reanalysis dataset goes back to year 1980 (the starting year of ERA-Interim integrations) and is updated in quasi real time. In addition of providing the staring point for the operational forecasts it is a very useful dataset for the scope of calibration and verification of the system. Assuming reanalysis fields are good proxies for observations then, by comparison with fire events which really occurred, this dataset can be used to assess the potential predictability of fire risk indices. In this work we will introduce the EC-fire system. Then the reanalysis dataset will be used to identify regions of high fire risk predictability and where the system might be in need of further refinement.

A participatory assessment of post-fire management alternatives in eastern Spain

NASA Astrophysics Data System (ADS)

Llovet, Joan

2015-04-01

Transformational socio-economic changes during the last decades of the 20th century led to the abandonment of mountainous areas in western Mediterranean countries (Puigdefábregas and Mendizábal, 1998). This process was accelerated in the Ayora Valley (inland Valencia province, E Spain) by a major forest fire in 1979. Restoration and management actions were implemented through the 1990's to promote the recovery of the area affected by this fire. In 2010 these past actions were assessed using an integrated and participatory evaluation protocol (IAPro). The selected actions were shrubland regenerated after the fire (no-action); pine plantation over the shrubland; pine forest regenerated after the fire (no-action); and thinning of densely regenerated pines. The assessment involved the identification and engagement of a comprehensive and representative set of local and regional stakeholders who provided a baseline assessment, identified and prioritized essential indicators, considered data collected against those indicators, and participated in re-assessment of actions after an outranking multi-criteria decision aiding integration (MCDA) conducted by the expert team (Roy and Bertier, 1973). This process facilitated a collaborative integration of biophysical indicators (i.e. carbon sequestration, water and soil conservation, soil quality, biodiversity, fire risk and forest health) and socio-economic indicators (i.e. productive, recreational and touristic, aesthetic, and cultural values, cost of the actions, and impact on family finances). It was completed with activities for exchanging experiences and sharing knowledge with the platform of stakeholders. Stakeholder platform suggested that fire risk was the most important indicator, followed by water conservation and soil conservation. Least important indicators were cost of actions, aesthetic value, and recreational and touristic value. Data collected on each action showed the thinned pine forest action with the lowest value on the fire risk criterion; shrubland had a fire risk three times higher, whereas pine plantation and dense pine forest showed a fire risk four times higher than thinned pine forest. Thinned pine forest showed the highest impact on family finances, as well as productive, cultural, recreational and touristic, and aesthetic values. The best value on forest health corresponded to shrubland, and the worst were the dense pine forest and thinned pine forest. Pine plantation showed the highest cost, whereas no-actions had not direct costs. The rest of indicators showed low or inexistent differences between actions. The indicator priorities combined with data collected through the MCDA integration showed that the thinning of densely regenerated pine forest action, outranked the other actions in most of the criteria. The second action was pine plantation, whereas shrubland and dense pine forest obtained the lowest assessment. As conclusion, the participatory methodology was fundamental in understanding the impact of perceptions and stakeholders' priorities in a usually very technical and non-participatory process. Similar methodologies could enhance knowledge exchange between scientists, managers and stakeholders, while improve society-science collaboration in land management and restoration research and practice. Acknowledgements Inhabitants and other people related to the Ayora Valley kindly collaborated with our work. Some collaborators helped us in both field work and meetings with stakeholders. This research has been supported by the projects PRACTICE (EU grant number 226818), RECARE (EU grant number 603498) and GRACCIE (Consolider program, Spanish Ministry of Education and Science grant number CSD2007-00067). The CEAM Foundation is supported by Generalitat Valenciana. References Puigdefábregas, J. and Mendizábal, T. 1998. Perspectives on desertification: Western Mediterranean. Journal of Arid Environments 39: 209-224. Roy, B. and Bertier, P. 1973. La méthode ELECTRE II - Une application au média-planning. In: M. Ross (editor) OR'72. North-Holland Publishing Company, Amsterdam, pp 291-302.

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Treesearch

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

"I get by with a little help from my friends": A case study in Holy Cross and Grayling using geographic, ethnographic, and biophysical data to tell the story of climate change effects in the lower-middle Yukon River region

NASA Astrophysics Data System (ADS)

Hollingsworth, T. N.; Brown, C.; Cold, H.; Brinkman, T. J.; Brown, D. N.; Verbyla, D.

2017-12-01

Over the last century, Alaska has warmed more than twice as rapidly as the contiguous US. Climate change in boreal Alaska has created new and undocumented vulnerabilities for rural communities. In rural areas, subsistence harvesters rely on established travel networks to access traditional hunting, fishing, and gathering areas. These routes are being affected by ecosystem disturbances, such as thermokarst and increased wildfire severity, linked to climate change. Understanding these changes requires a collaborative effort, using many different forms of data to tell a complete story. Here, we present a case study from Holy Cross and Grayling, Alaska to demonstrate the importance of cross-discipline data integration. Local subsistence users documented GPS coordinates of encountered sites of ecosystem disturbances influencing their access to subsistence areas. These knowledge holders provided the ethnographic, historical and experiential descriptions of the effects of these changes. Then, remote-sensing imagery allows us to look at how these sites change over time. Finally, we returned to collaborate with subsistence users to visit specific sites and quantify the biophysical mechanisms that describe these disturbances. In Holy Cross, we visited areas that recently burned and are undergoing rapid changes in vegetation. We describe the fire regime characteristics such as fire severity, age of site when it burned, pre-fire composition, and post-fire successional trajectory. In Grayling, we visited areas with drying water bodies and associated vegetation change. We describe the current vegetation structure and composition, looked at potential shifts in soil moisture and used repeat imagery to quantify change in water. Our case study exemplifies the power of participatory research, collaboration, and a cross-disciplinary methodology to expand our collective understanding of landscape-level climate-related changes in boreal Alaska.

Tailored stakeholder products help provide a vulnerability and adaptation assessment of Greek forests due to climate change

NASA Astrophysics Data System (ADS)

Giannakopoulos, Christos; Karali, Anna; Roussos, Anargyros

2014-05-01

Greece, being part of the eastern Mediterranean basin, is an area particularly vulnerable to climate change and associated forest fire risk. The aim of this study is to assess the vulnerability of Greek forests to fire risk occurrence and identify potential adaptation options within the context of climate change through continuous interaction with local stakeholders. To address their needs, the following tools for the provision of climate information services were developed: 1. An application providing fire risk forecasts for the following 3 days (http://cirrus.meteo.noa.gr/forecast/bolam/index.htm) was developed from NOA to address the needs of short term fire planners. 2. A web-based application providing long term fire risk and other fire related indices changes due to climate change (time horizon up to 2050 and 2100) was developed in collaboration with the WWF Greece office to address the needs of long term fire policy makers (http://www.oikoskopio.gr/map/). 3. An educational tool was built in order to complement the two web-based tools and to further expand knowledge in fire risk modeling to address the needs for in-depth training. In particular, the second product provided the necessary information to assess the exposure to forest fires. To this aim, maps depicting the days with elevated fire risk (FWI>30) both for the control (1961-1990) and the near future period (2021-2050) were created by the web-application. FWI is a daily index that provides numerical ratings of relative fire potential based solely on weather observations. The meteorological inputs to the FWI System are daily noon values of temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. It was found that eastern lowlands are more exposed to fire risk followed by eastern high elevation areas, for both the control and near future period. The next step towards vulnerability assessment was to address sensitivity, ie the human-environmental conditions that can worsen or ameliorate the hazard. In our study static information concerning fire affecting factors, namely the topography and vegetation, was used to create a fire hazard map in order to assess the sensitivity factor. Land cover types for the year 2007 were combined with topographic information deriving from a digital elevation model order to produce these maps. High elevation continental areas were found to be the most sensitive areas followed by the lowland continental areas. Exposure and sensitivity were combined to produce the overall impact of climate change to forest fire risk. The adaptive capacity is defined by the ability of forests to adapt to changing environmental conditions. To assess the adaptive capacity of Greek forests, a Multi-Criteria Analysis (MCA) tool was implemented and used by the stakeholders. The major proposed adaptation measures for Greek forests included fire prevention measures and the inclusion of the private forest covered areas in the fire fighting. Finally, vulnerability of Greek forest to fire was estimated as the overall impact of climate change minus the forests' adaptive capacity and was found to be medium for most areas in the country. Acknowledgement: This work was supported by the EU project CLIM-RUN under contract FP7-ENV-2010-265192.

Field modeling of heat transfer in atrium

NASA Astrophysics Data System (ADS)

Nedryshkin, Oleg; Gravit, Marina; Bushuev, Nikolay

2017-10-01

The results of calculating fire risk are an important element in the system of modern fire safety assessment. The article reviews the work on the mathematical modeling of fire in the room. A comparison of different calculation models in the programs of fire risk assessment and fire modeling was performed. The results of full-scale fire tests and fire modeling in the FDS program are presented. The analysis of empirical and theoretical data on fire modeling is made, a conclusion is made about the modeling accuracy in the FDS program.

Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)

USGS Publications Warehouse

Young, John A.; Mahan, Carolyn G.; Forder, Melissa

2017-01-01

Many eastern forest communities depend on fire for regeneration or are enhanced by fire as a restoration practice. However, the use of prescribed fire in the mesic forested environments and the densely populated regions of the eastern United States has been limited. The objective of our research was to develop a science-based approach to prioritizing the use of prescribed fire in appropriate forest types in the eastern United States based on a set of desired management outcomes. Through a process of expert elicitation and data analysis, we assessed and integrated recent vegetation community mapping results along with other available spatial data layers into a spatial prioritization tool for prescribed fire planning at Shenandoah National Park (Virginia, USA). The integration of vegetation spatial data allowed for development of per-pixel priority rankings and exclusion areas enabling precise targeting of fire management activities on the ground, as well as a park-wide ranking of fire planning compartments. We demonstrate the use and evaluation of this approach through implementation and monitoring of a prescribed burn and show that progress is being made toward desired conditions. Integration of spatial data into the fire planning process has served as a collaborative tool for the implementation of prescribed fire projects, which assures projects will be planned in the most appropriate areas to meet objectives that are supported by current science.

75 FR 5355 - Notice of Extension of Comment Period for NUREG-1934, Nuclear Power Plant Fire Modeling...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-02

..., Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG), Draft Report for Comment AGENCY... 1019195), Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG), Draft Report for Comment... Plant Fire Modeling Application Guide (NPP FIRE MAG)'' is available electronically under ADAMS Accession...

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Current status and future needs of the BehavePlus Fire Modeling System

Treesearch

Patricia L. Andrews

2014-01-01

The BehavePlus Fire Modeling System is among the most widely used systems for wildland fire prediction. It is designed for use in a range of tasks including wildfire behaviour prediction, prescribed fire planning, fire investigation, fuel hazard assessment, fire model understanding, communication and research. BehavePlus is based on mathematical models for fire...

BehavePlus fire modeling system: Past, present, and future

Treesearch

Patricia L. Andrews

2007-01-01

Use of mathematical fire models to predict fire behavior and fire effects plays an important supporting role in wildland fire management. When used in conjunction with personal fire experience and a basic understanding of the fire models, predictions can be successfully applied to a range of fire management activities including wildfire behavior prediction, prescribed...

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

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

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

Improving the Interoperability of Disaster Models: a Case Study of Proposing Fireml for Forest Fire Model

NASA Astrophysics Data System (ADS)

Jiang, W.; Wang, F.; Meng, Q.; Li, Z.; Liu, B.; Zheng, X.

2018-04-01

This paper presents a new standardized data format named Fire Markup Language (FireML), extended by the Geography Markup Language (GML) of OGC, to elaborate upon the fire hazard model. The proposed FireML is able to standardize the input and output documents of a fire model for effectively communicating with different disaster management systems to ensure a good interoperability. To demonstrate the usage of FireML and testify its feasibility, an adopted forest fire spread model being compatible with FireML is described. And a 3DGIS disaster management system is developed to simulate the dynamic procedure of forest fire spread with the defined FireML documents. The proposed approach will enlighten ones who work on other disaster models' standardization work.

Sherborne Missile Fire Frequency with Unconstraint Parameters

NASA Astrophysics Data System (ADS)

Dong, Shaquan

2018-01-01

For the modeling problem of shipborne missile fire frequency, the fire frequency models with unconstant parameters were proposed, including maximum fire frequency models with unconstant parameters, and actual fire frequency models with unconstant parameters, which can be used to calculate the missile fire frequency with unconstant parameters.

Evaluation of a post-fire tree mortality model for western US conifers

Treesearch

Sharon M. Hood; Charles W McHugh; Kevin C. Ryan; Elizabeth Reinhardt; Sheri L. Smith

2007-01-01

Accurately predicting fire-caused mortality is essential to developing prescribed fire burn plans and post-fire salvage marking guidelines. The mortality model included in the commonly used USA fire behaviour and effects models, the First Order Fire Effects Model (FOFEM), BehavePlus, and the Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS), has not...

Fire and Smoke Model Evaluation Experiment (FASMEE): Modeling gaps and data needs

Treesearch

Yongqiang Liu; Adam Kochanski; Kirk Baker; Ruddy Mell; Rodman Linn; Ronan Paugam; Jan Mandel; Aime Fournier; Mary Ann Jenkins; Scott Goodrick; Gary Achtemeier; Andrew Hudak; Matthew Dickson; Brian Potter; Craig Clements; Shawn Urbanski; Roger Ottmar; Narasimhan Larkin; Timothy Brown; Nancy French; Susan Prichard; Adam Watts; Derek McNamara

2017-01-01

Fire and smoke models are numerical tools for simulating fire behavior, smoke dynamics, and air quality impacts of wildland fires. Fire models are developed based on the fundamental chemistry and physics of combustion and fire spread or statistical analysis of experimental data (Sullivan 2009). They provide information on fire spread and fuel consumption for safe and...

Modeling the spatial distribution of forest crown biomass and effects on fire behavior with FUEL3D and WFDS

Treesearch

Russell A. Parsons; William Mell; Peter McCauley

2010-01-01

Crown fire poses challenges to fire managers and can endanger fire fighters. Understanding of how fire interacts with tree crowns is essential to informed decisions about crown fire. Current operational crown fire predictions in the United States assume homogeneous crown fuels. While a new class of research fire models, which model fire behavior with computational...

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

Kang, D. I.; Han, S. H.

A PSA analyst has been manually determining fire-induced component failure modes and modeling them into the PSA logics. These can be difficult and time-consuming tasks as they need much information and many events are to be modeled. KAERI has been developing the IPRO-ZONE (interface program for constructing zone effect table) to facilitate fire PSA works for identifying and modeling fire-induced component failure modes, and to construct a one top fire event PSA model. With the output of the IPRO-ZONE, the AIMS-PSA, and internal event one top PSA model, one top fire events PSA model is automatically constructed. The outputs ofmore » the IPRO-ZONE include information on fire zones/fire scenarios, fire propagation areas, equipment failure modes affected by a fire, internal PSA basic events corresponding to fire-induced equipment failure modes, and fire events to be modeled. This paper introduces the IPRO-ZONE, and its application results to fire PSA of Ulchin Unit 3 and SMART(System-integrated Modular Advanced Reactor). (authors)« less

A method for mapping fire hazard and risk across multiple scales and its application in fire management

Treesearch

Robert E. Keane; Stacy A. Drury; Eva C. Karau; Paul F. Hessburg; Keith M. Reynolds

2010-01-01

This paper presents modeling methods for mapping fire hazard and fire risk using a research model called FIREHARM (FIRE Hazard and Risk Model) that computes common measures of fire behavior, fire danger, and fire effects to spatially portray fire hazard over space. FIREHARM can compute a measure of risk associated with the distribution of these measures over time using...

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

The Great Basin Research and Management Partnership: Facilitating Collaborative Solutions

USDA-ARS?s Scientific Manuscript database

The Great Basin is undergoing major sociological and ecological change as a result of urbanization, changing technology and land use, climate change, limited water resources, altered fire regimes, and invasive species, insects, and disease. Sustaining ecosystems, resources, and human populations of...

Optimizing regional collaborative efforts to achieve long-term discipline-specific objectives

USDA-ARS?s Scientific Manuscript database

Current funding programs focused on multi-disciplinary, multi-agency approaches to regional issues can provide opportunities to address discipline-specific advancements in scientific knowledge. Projects funded through the Agricultural Research Service, Joint Fire Science Program, and the Natural Re...

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...

Assessing and validating RST-FIRES on MSG-SEVIRI data by means a Total Validation Approach (TVA).

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, %Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2015-04-01

Several fire detection methods have been developed through the years for detecting forest fires from space. These algorithms (which may be grouped in single channel, multichannel and contextual algorithms) are generally based on the use of fixed thresholds that, being intrinsically exposed to false alarm proliferation, are often used in a conservative way. As a consequence, most of satellite-based algorithms for fire detection show low sensitivity resulting not suitable in operational contexts. In this work, the RST-FIRES algorithm, which is based on an original multi-temporal scheme of satellite data analysis (RST-Robust Satellite Techniques), is presented. The implementation of RST-FIRES on data provided by Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG) that, offering the best revisit time (i.e. 15 minutes), can be successfully used for detecting fires at early stage, is described here. Moreover, results of a Total Validation Approach (TVA) experimented both in Northern and Southern Italy, in collaboration with local and regional civil protection agencies, are also reported. In particular, TVA allowed us to assess RST-FIRES detections by means of ground check and aerial surveys, demonstrating the good performances offered by RST-FIRES using MSG-SEVIRI data. Indeed, this algorithm was capable of detecting several fires that for their features (e.g., small size, short time duration) would not have appeared in the official reports, highlighting a significant improvement in terms of sensitivity in comparison with other established satellite-based fire detection techniques still preserving a high confidence level of detection.

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.

Near-Real-Time Earth Observation Data Supporting Wildfire Management

NASA Astrophysics Data System (ADS)

Ambrosia, V. G.; Zajkowski, T.; Quayle, B.

2013-12-01

During disaster events, the most critical element needed by responding personnel and management teams is situational intelligence / awareness. During rapidly-evolving events such as wildfires, the need for timely information is critical to save lives, property and resources. The wildfire management agencies in the US rely heavily on remote sensing information both from airborne platforms as well as from orbital assets. The ability to readily have information from those systems, not just data, is critical to effective control and damage mitigation. NASA has been collaborating with the USFS to mature and operationalize various asset-information capabilities to effect improved knowledge of fire-prone areas, monitor wildfire events in real-time, assess effectiveness of fire management strategies, and provide rapid, post-fire assessment for recovery operations. Specific examples of near-real-time remote sensing asset utility include daily MODIS data employed to assess fire potential / wildfire hazard areas, and national-scale hot-spot detection, airborne thermal sensor collected during wildfire events to effect management strategies, EO-1 ALI 'pointable' satellite sensor data to assess fire-retardant application effectiveness, and Landsat 8 and other sensor data to derive burn severity indices for post-fire remediation work. These cases of where near-real-time data is used operationally during the previous few fire seasons will be presented.

Evaluating and operationalizing unmanned aircraft for wildland fire use

NASA Astrophysics Data System (ADS)

Watts, A.

2015-12-01

Many potential uses of unmanned aircraft systems (UAS) related to wildland fire research and operations have been demonstrated, but the vast majority of these have been proof-of-concept or one-time flights. Scientists, practitioners, and firefighting agencies look forward to the widespread adoption of this powerful technology and its regular use. Similarly, the UAS industry awaits opportunities for commercialization. Our collaboration brings together UAS industry, research and management agencies, and universities in the USA and Canada to investigate the perceived effectiveness of UAS for wildland fire use, and the factors affecting their commercial-scale employment. Our current and future activities include market research, training and technology transfer, and deployment of UAS over fires to promote development of sensors as well as their safe integration into fire operations. We will present initial results, and as a part of our presentation we also invite participation of the AGU community for planned future project phases. We anticipate that the outcomes of our work will be useful to potential users who are unfamiliar with UAS, and to researchers and practitioners with experience or an interest in their use in fire and related natural-resource disciplines.

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...

Mercury Emissions Capture Efficiency with Activated Carbon Injection at a Russian Coal-Fired Thermal Power Plant

EPA Science Inventory

This EPA-led project, conducted in collaboration with UNEP, the Swedish Environmental Institute and various Russian Institutes, that demonstrates that the mercury emission control efficiencies of activated carbon injection technologies applied at a Russian power plant burning Rus...

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...

RST-FIRES, an exportable algorithm for early/small fires detection: field validation and algorithm inter-comparison by using MSG-SEVIRI data over Italian Regions

NASA Astrophysics Data System (ADS)

Lisi, M.; Paciello, R.; Filizzola, C.; Corrado, R.; Marchese, F.; Mazzeo, G.; Pergola, N.; Tramutoli, V.

2016-12-01

Fire detection by sensors on-board polar orbiting platforms, due to their relatively low temporal resolution (hours), could results decidedly not adequate to detect short-living events or fires characterized by a strong diurnal cycle and rapid evolution times. The challenge is therefore to try to exploit the very high temporal resolution offered by the geostationary sensors (from 30 to 2,5 minutes) to guarantee a continuous monitoring. Over the last years, many algorithms have been adapted from polar to (or have been specifically designed for) geostationary sensors. Most of them are based on fixed thresholds tests which, to avoid false alarm proliferation, are generally set up in the most conservative way. The result is a low algorithm sensitivity (i.e. only large and/or extremely intense events are generally detected) which could drastically affect Global Fire Emission (GFE) estimate: small fires were recognized to contribute for more than 35% to the global biomass burning carbon emissions. This work describes the multi-temporal change-detection technique named RST-FIRES (Robust Satellite Techniques for FIRES detection and monitoring) which, try to overcome the above mentioned issues being, moreover, immediately exportable on different geographic area and sensors. Its performance in terms of reliability and sensitivity was verified by more than 20,000 SEVIRI images collected throughout the day during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions which provided about 950 near real-time ground and aerial checks of the RST-FIRES detections. This study fully demonstrates the added value of the RST-FIRES technique for the detection of early/small fires and a sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.

The Greek National Observatory of Forest Fires (NOFFi)

NASA Astrophysics Data System (ADS)

Tompoulidou, Maria; Stefanidou, Alexandra; Grigoriadis, Dionysios; Dragozi, Eleni; Stavrakoudis, Dimitris; Gitas, Ioannis Z.

2016-08-01

Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, the effective response to fire events necessitates adequate planning and preparedness before the start of the fire season, as well as quantifying the environmental impacts in case of wildfires. Moreover, the estimation of fire danger provides crucial information required for the optimal allocation and distribution of the available resources. The Greek National Observatory of Forest Fires (NOFFi)—established by the Greek Forestry Service in collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki and the International Balkan Center—aims to develop a series of modern products and services for supporting the efficient forest fire prevention management in Greece and the Balkan region, as well as to stimulate the development of transnational fire prevention and impacts mitigation policies. More specifically, NOFFi provides three main fire-related products and services: a) a remote sensing-based fuel type mapping methodology, b) a semi-automatic burned area mapping service, and c) a dynamically updatable fire danger index providing mid- to long-term predictions. The fuel type mapping methodology was developed and applied across the country, following an object-oriented approach and using Landsat 8 OLI satellite imagery. The results showcase the effectiveness of the generated methodology in obtaining highly accurate fuel type maps on a national level. The burned area mapping methodology was developed as a semi-automatic object-based classification process, carefully crafted to minimize user interaction and, hence, be easily applicable on a near real-time operational level as well as for mapping historical events. NOFFi's products can be visualized through the interactive Fire Forest portal, which allows the involvement and awareness of the relevant stakeholders via the Public Participation GIS (PPGIS) tool.

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.

Microfabricated Gas Sensors Demonstrated in Fire and Emission Applications

NASA Technical Reports Server (NTRS)

Hunter, Gary W.

2003-01-01

A range of microfabricated chemical sensors are being developed to meet the needs of fire detection and emission monitoring in aerospace applications. These sensors have the advantages over traditional technology of minimal size, weight, and power consumption as well as the ability to be placed closer to where the measurements need to be made. Sensor arrays are being developed to address detection needs in environments where multiple species need to be measured. For example, the monitoring of chemical species such as carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons, and other species is important in the detection of fires on airplanes and spacecraft. In contrast, different sensors are necessary for characterizing some aircraft engine designs where the monitoring of nitrogen oxides (NO(x)) and CO is of high interest. Demonstration of both fire and emission microsensor technology was achieved this year in a collaborative effort undertaken by the NASA Glenn Research Center, Case Western Reserve University, and Makel Engineering, Inc.

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

Investigating Hastily-Formed Collaborative Networks

DTIC Science & Technology

2007-03-01

support a minimum range of 250 meters since this is the minimum required length of a fire hose . • Jurisdiction Area Network (JAN): This is the main...but typical braided one-half inch polypropylene rope weighs less than two pounds per one hundred 4-19 feet and has tensile strengths greater than two

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

The pyrohealth transition: how combustion emissions have shaped health through human history.

PubMed

Johnston, Fay H; Melody, Shannon; Bowman, David M J S

2016-06-05

Air pollution from landscape fires, domestic fires and fossil fuel combustion is recognized as the single most important global environmental risk factor for human mortality and is associated with a global burden of disease almost as large as that of tobacco smoking. The shift from a reliance on biomass to fossil fuels for powering economies, broadly described as the pyric transition, frames key patterns in human fire usage and landscape fire activity. These have produced distinct patters of human exposure to air pollution associated with the Agricultural and Industrial Revolutions and post-industrial the Earth global system-wide changes increasingly known as the Anthropocene. Changes in patterns of human fertility, mortality and morbidity associated with economic development have been previously described in terms of demographic, epidemiological and nutrition transitions, yet these frameworks have not explicitly considered the direct consequences of combustion emissions for human health. To address this gap, we propose a pyrohealth transition and use data from the Global Burden of Disease (GBD) collaboration to compare direct mortality impacts of emissions from landscape fires, domestic fires, fossil fuel combustion and the global epidemic of tobacco smoking. Improving human health and reducing the environmental impacts on the Earth system will require a considerable reduction in biomass and fossil fuel combustion.This article is part of the themed issue 'The interaction of fire and mankind'. © 2016 The Author(s).

The pyrohealth transition: how combustion emissions have shaped health through human history

PubMed Central

Johnston, Fay H.; Melody, Shannon

2016-01-01

Air pollution from landscape fires, domestic fires and fossil fuel combustion is recognized as the single most important global environmental risk factor for human mortality and is associated with a global burden of disease almost as large as that of tobacco smoking. The shift from a reliance on biomass to fossil fuels for powering economies, broadly described as the pyric transition, frames key patterns in human fire usage and landscape fire activity. These have produced distinct patters of human exposure to air pollution associated with the Agricultural and Industrial Revolutions and post-industrial the Earth global system-wide changes increasingly known as the Anthropocene. Changes in patterns of human fertility, mortality and morbidity associated with economic development have been previously described in terms of demographic, epidemiological and nutrition transitions, yet these frameworks have not explicitly considered the direct consequences of combustion emissions for human health. To address this gap, we propose a pyrohealth transition and use data from the Global Burden of Disease (GBD) collaboration to compare direct mortality impacts of emissions from landscape fires, domestic fires, fossil fuel combustion and the global epidemic of tobacco smoking. Improving human health and reducing the environmental impacts on the Earth system will require a considerable reduction in biomass and fossil fuel combustion. This article is part of the themed issue ‘The interaction of fire and mankind’. PMID:27216506

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.

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.

The combined use of the RST-FIRES algorithm and geostationary satellite data to timely detect fires

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2017-04-01

Timely detection of fires may enable a rapid contrast action before they become uncontrolled and wipe out entire forests. Remote sensing, especially based on geostationary satellite data, can be successfully used to this aim. Differently from sensors onboard polar orbiting platforms, instruments on geostationary satellites guarantee a very high temporal resolution (from 30 to 2,5 minutes) which may be usefully employed to carry out a "continuous" monitoring over large areas as well as to timely detect fires at their early stages. Together with adequate satellite data, an appropriate fire detection algorithm should be used. Over the last years, many fire detection algorithms have been just adapted from polar to geostationary sensors and, consequently, the very high temporal resolution of geostationary sensors is not exploited at all in tests for fire identification. In addition, even when specifically designed for geostationary satellite sensors, fire detection algorithms are frequently based on fixed thresholds tests which are generally set up in the most conservative way to avoid false alarm proliferation. The result is a low algorithm sensitivity which generally means that only large and/or extremely intense events are detected. This work describes the Robust Satellite Techniques for FIRES detection and monitoring (RST-FIRES) which is a multi-temporal change-detection technique trying to overcome the above mentioned issues. Its performance in terms of reliability and sensitivity was verified using data acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG) geostationary platform. More than 20,000 SEVIRI images, collected during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions, were used. About 950 near real-time ground and aerial checks of the RST-FIRES detections were performed. This study also demonstrates the added value of the RST-FIRES technique to detect starting/small fires and its sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.

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.

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.

Monitoring Fires from Space: a case study in transitioning from research to applications

NASA Astrophysics Data System (ADS)

Justice, C. O.; Giglio, L.; Vadrevu, K. P.; Csiszar, I. A.; Schroeder, W.; Davies, D.

2012-12-01

This paper discusses the heritage and relationships between science and applications in the context of global satellite-based fire monitoring. The development of algorithms for satellite-based fire detection has been supported primarily by NASA for the polar orbiters with a global focus, and initially by NOAA and more recently by EUMETSAT for the geostationary satellites, with a regional focus. As the feasibility and importance of space-based fire monitoring was recognized, satellite missions were designed to include fire detection capabilities. As a result, the algorithms and accuracy of the detections have improved. Due to the role of fire in the Earth System and its relevance to society, at each step in the development of the sensing capability the research has made a transition into fire-related applications to such an extent that there is now broad use of these data worldwide. The origin of the polar-orbiting satellite fire detection capability was with the AVHRR sensor beginning in the early 1980s, but was transformed with the launch of the EOS MODIS instruments, which included sensor characteristics specifically for fire detection. NASA gave considerable emphasis on the accuracy assessment of the fire detection and the development of fire characterization and burned area products from MODIS. Collaboration between the MODIS Fire Team and the RSAC USFS, initiated in the context of the Montana wildfires of 2001, prompted the development of a Rapid Response System for fire data and eventually led to operational use of MODIS data by the USFS for strategic fire monitoring. Building on this success, the Fire Information for Resource Management Systems (FIRMS) project was funded by NASA Applications to further develop products and services for the fire information community. The FIRMS was developed as a web-based geospatial tool, offering a range of geospatial data services, including SMS text messaging and is now widely used. This system, developed in the research domain, has now been successfully moved to an operational home at the UN FAO, as the Global Fire Information Management System (GFIMS). With a view to operational data continuity, the Suomi-NPP/JPSS VIIRS system was also designed with a fire detection capability, and is providing promising results for fire monitoring both from the standard operational production system and experimental product enhancements. International coordination on fire observations and outreach has been successfully developed under the GOFC GOLD program.

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.

Soil, Weeds, and Computers

ERIC Educational Resources Information Center

McClennen, Nate

2004-01-01

Events in a community can lead to valuable learning experiences in science. By the end of the summer of 2001, the Green Knoll Fire had burned almost 4000 acres of forest south of Wilson, Wyoming. This article describes how students at the Journeys School of Teton Science Schools participated in a collaborative project with the United States Forest…

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.

Using Space Technologies for a timely detection of forest fires: the experience of end-users in 3 Italian Regions

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Belloni, Antonella; Benigno, Giuseppe; Biancardi, Alberto; Corrado, Rosita; Coviello, Irina; De Costanzo, Giovanni; Genzano, Nicola; Lacava, Teodosio; Lisi, Mariano; Marchese, Francesco; Mazzeo, Giuseppe; Merzagora, Cinzio; Paciello, Rossana; Pergola, Nicola; Sannazzaro, Filomena; Serio, Salvatore; Tramutoli, Valerio

2013-04-01

Every year, hundreds of thousands of hectares of European forests are destroyed by fires. Due to the particular topography, landscape and demographic distribution in Europe (very different from typical scenarios of China, USA, Canada and Australia), rapidity in fire sighting is still the determining factor in limiting damages to people and goods. Moreover, the possibility of early fire detection means also potentially to reduce the size of the event to be faced, the necessary fire fighting resources and, therefore, even the reaction times. In such a context, integration of satellite technologies (mainly high temporal resolution data) and traditional surveillance systems within the fire fighting procedures seems to positively impact on the effectiveness of active fire fighting as demonstrated by recent experiences over Italian territory jointly performed by University of Basilicata, IMAA-CNR and Local Authorities. Real time implementation was performed since 2007, during fire seasons, over several Italian regions with different fire regimes and features, in order to assess the actual potential of different satellite-based fire detection products to support regional and local authorities in efficiently fighting fires and better mitigating their negative effects. Real-time campaigns were carried out in strict collaboration with end-users within the framework of specific projects (i.e. the AVVISA, AVVISTA and AVVISA-Basilicata projects) funded by Civil Protection offices of Regione Lombardia, Provincia Regionale di Palermo and Regione Basilicata in charge of fire risk management and mitigation. A tailored training program was dedicated to the personnel of Regional Civil Protection offices in order to ensure the full understanding and the better integration of satellite based products and tools within the existing fire fighting protocols. In this work, outcomes of these practices are shown and discussed, especially highlighting the impact that a real time satellite system may have in assisting and complementing traditional surveillance systems to mitigate damages due to fires. In particular, the usefulness of satellite technology in an operational context was demonstrated mainly in reference to: i) the possibility of identifying fires at an early stage (so avoiding that small hotbeds could extend and become dangerous for citizens and destructive for environmental protected areas) as well as ii) the possibility to have an effective territorial control (e.g. discovering illegal burning fires such as unauthorized cleaning fires, and permitting local authorities to rapidly intervene and catch red-handed pyromaniacs).

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.

Understanding spatial variability in perennial grass restoration following shrub removal in the Chihuahuan Desert: The restore New Mexico collaborative monitoring program

USDA-ARS?s Scientific Manuscript database

Grassland to shrubland transitions are well documented throughout the desert grassland region of the Chihuahuan Desert. These transitions were triggered in the early 20th century by overgrazing of perennial grasses during drought periods, loss of fire regimes, and seed dispersal by livestock. Shrubl...

Erosion and restoration of two headwater wetlands following an extreme wildfire

Treesearch

Jonathan Long; Javis Davis

2016-01-01

Wildfire can damage headwater wetlands, yet the value of post-fire restoration treatments in channels has been contested. Staff from the White Mountain Apache Tribe, students from the local Cibecue Community School, and researchers from the U.S. Forest Service collaboratively recorded channel responses over 13 years at two headwater wetlands lying within watersheds...

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

KSC-2014-2804

NASA Image and Video Library

2014-05-01

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Bill Martin, a URS Federal Technical Services helicopter pilot in the agency's Aircraft Operations, is interviewed near the Shuttle Landing Facility. He discussed working with spaceport Fire Rescue personnel to develop procedures for using agency helicopters to transport injured patients to a local hospital. The training activity took place in Kennedy's Launch Complex 39 turn-basin parking lot. It was part of a new training program developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dimitri Gerondidakis

KSC-2014-2805

NASA Image and Video Library

2014-05-01

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Mark Huetter, assistant chief of Training for the center's Fire Rescue Department, is interviewed near the Shuttle Landing Facility. He discussed working with pilots in NASA Aircraft Operations to develop procedures for using agency helicopters to transport injured patients to a local hospital. The training activity took place in Kennedy's Launch Complex 39 turn-basin parking lot. It was part of a new training program developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dimitri Gerondidakis

KSC-2014-2779

NASA Image and Video Library

2014-04-30

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, a Fire Rescue vehicle stands by in a parking area near the Vehicle Assembly Building for training with pilots in NASA Aircraft Operations. The exercise is designed to develop procedures for using agency helicopters to transport injured patients to a local hospital. The activity taking place in Kennedy's Launch Complex 39 turn-basin parking lot was only one of several drills. It was part of a new training program that was developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dan Casper

KSC-2014-2802

NASA Image and Video Library

2014-05-01

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Bill Martin, a URS Federal Technical Services helicopter pilot in the agency's Aircraft Operations, is interviewed near the Shuttle Landing Facility. He discussed working with spaceport Fire Rescue personnel to develop procedures for using agency helicopters to transport injured patients to a local hospital. The training activity took place in Kennedy's Launch Complex 39 turn-basin parking lot. It was part of a new training program developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dimitri Gerondidakis

KSC-2014-2759

NASA Image and Video Library

2014-04-29

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Fire Rescue vehicles line up in a parking area near the Vehicle Assembly Building for training with pilots in NASA Aircraft Operations. The exercise is designed to develop procedures for using agency helicopters to transport injured patients to a local hospital. The activity taking place in Kennedy's Launch Complex 39 turn-basin parking lot was only one of several drills. It was part of a new training program that was developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dan Casper

KSC-2014-2803

NASA Image and Video Library

2014-05-01

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Bill Martin, a URS Federal Technical Services helicopter pilot in the agency's Aircraft Operations, is interviewed near the Shuttle Landing Facility. He discussed working with spaceport Fire Rescue personnel to develop procedures for using agency helicopters to transport injured patients to a local hospital. The training activity took place in Kennedy's Launch Complex 39 turn-basin parking lot. It was part of a new training program developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dimitri Gerondidakis

KSC-2014-2806

NASA Image and Video Library

2014-05-01

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, Mark Huetter, assistant chief of Training for the center's Fire Rescue Department, is interviewed near the Shuttle Landing Facility. He discussed working with pilots in NASA Aircraft Operations to develop procedures for using agency helicopters to transport injured patients to a local hospital. The training activity took place in Kennedy's Launch Complex 39 turn-basin parking lot. It was part of a new training program developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dimitri Gerondidakis

KSC-2014-2794

NASA Image and Video Library

2014-04-30

CAPE CANAVERAL, Fla. -- Following a training exercise at NASA's Kennedy Space Center in Florida, helicopter pilot Bill Martin, a URS Federal Technical Services in the agency's Aircraft Operations, left, confers with Mark Huetter of Chenega Security & Support Solutions. Martin serves as assistant chief of Training for the center's Fire Rescue Department. The activity taking place in Kennedy's Launch Complex 39 turn-basin parking lot was only one of several drills. It was part of a new training program that was developed by Kennedy's Fire Rescue department along with NASA Aircraft Operations to sharpen the skills needed to help rescue personnel learn how to collaborate with helicopter pilots in taking injured patients to hospitals as quickly as possible. Photo credit: NASA/Dan Casper

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.

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.

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.

Provoking "Eureka" moments for effective infection control strategies.

PubMed

Pittet, Didier

2014-01-01

Safety is now a fundamental principle of patient care and a critical component of quality management. Health care-associated infection prevention strategies need to be constantly revisited and updated to be effective. The "Geneva hand hygiene model" is a typical example of a breakthrough innovatory campaign that caught fire and went viral worldwide, thanks to its adoption by the World Health Organization (WHO) as the First Global Patient Safety Challenge. The campaign remains an inspiration for further innovation. To encourage new and disruptive technologies with the potential to improve patient safety through the successful implementation of the WHO multimodal strategy, the University of Geneva Hospitals/WHO Collaborating Centre on Patient Safety, together with the Aesculap Academy, have created a series of "Hand Hygiene Excellence Awards" and "Hand Hygiene Innovation Awards" worldwide.

Simulating historical disturbance regimes and stand structures in old-forest ponderosa pine/Douglas-fir forests

Treesearch

Mike Hillis; Vick Applegate; Steve Slaughter; Michael G. Harrington; Helen Smith

2001-01-01

Forest Service land managers, with the collaborative assistance from research, applied a disturbance based restoration strategy to rehabilitate a greatly-altered, high risk Northern Rocky Mountain old-forest ponderosa pine-Douglas-fir stand. Age-class structure and fire history for the site have been documented in two research papers (Arno and others 1995, 1997)....

Go with the flow by way of interdisciplinary collaboration: Sharing, integrating and opening access to data from various studies in the Cache la Poudre watershed following fire and flood

USDA-ARS?s Scientific Manuscript database

The United States Department of Agriculture, Agricultural Research Service Long-Term Agroecosystem Research (LTAR) Network consists of 18 sites across the continental United States. LTAR scientists seek to determine ways to ensure sustainability and enhance food production and ecosystem services at ...

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.

Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005

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

Rupp, Susan P.

2005-10-01

In May 2000, the Cerro Grande Fire burned approximately 17,200 ha in north-central New Mexico as the result of an escaped prescribed burn initiated by Bandelier National Monument. The interaction of large-scale fires, vegetation, and elk is an important management issue, but few studies have addressed the ecological implications of vegetative succession and landscape heterogeneity on ungulate populations following large-scale disturbance events. Primary objectives of this research were to identify elk movement pathways on local and landscape scales, to determine environmental factors that influence elk movement, and to evaluate movement and distribution patterns in relation to spatial and temporal aspectsmore » of the Cerro Grande Fire. Data collection and assimilation reflect the collaborative efforts of National Park Service, U.S. Forest Service, and Department of Energy (Los Alamos National Laboratory) personnel. Geographic positioning system (GPS) collars were used to track 54 elk over a period of 3+ years and locational data were incorporated into a multi-layered geographic information system (GIS) for analysis. Preliminary tests of GPS collar accuracy indicated a strong effect of 2D fixes on position acquisition rates (PARs) depending on time of day and season of year. Slope, aspect, elevation, and land cover type affected dilution of precision (DOP) values for both 2D and 3D fixes, although significant relationships varied from positive to negative making it difficult to delineate the mechanism behind significant responses. Two-dimensional fixes accounted for 34% of all successfully acquired locations and may affect results in which those data were used. Overall position acquisition rate was 93.3% and mean DOP values were consistently in the range of 4.0 to 6.0 leading to the conclusion collar accuracy was acceptable for modeling purposes. SAVANNA, a spatially explicit, process-oriented ecosystem model, was used to simulate successional dynamics. Inputs to the SAVANNA included a land cover map, long-term weather data, soil maps, and a digital elevation model. Parameterization and calibration were conducted using field plots. Model predictions of herbaceous biomass production and weather were consistent with available data and spatial interpolations of snow were considered reasonable for this study. Dynamic outputs generated by SAVANNA were integrated with static variables, movement rules, and parameters developed for the individual-based model through the application of a habitat suitability index. Model validation indicated reasonable model fit when compared to an independent test set. The finished model was applied to 2 realistic management scenarios for the Jemez Mountains and management implications were discussed. Ongoing validation of the individual-based model presented in this dissertation provides an adaptive management tool that integrates interdisciplinary experience and scientific information, which allows users to make predictions about the impact of alternative management policies.« less

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.

Emissions from Coal Fires and Their Impact on the Environment

USGS Publications Warehouse

Kolker, Allan; Engle, Mark; Stracher, Glenn; Hower, James; Prakash, Anupma; Radke, Lawrence; ter Schure, Arnout; Heffern, Ed

2009-01-01

Self-ignited, naturally occurring coal fires and fires resulting from human activities persist for decades in underground coal mines, coal waste piles, and unmined coal beds. These uncontrolled coal fires occur in all coal-bearing parts of the world (Stracher, 2007) and pose multiple threats to the global environment because they emit greenhouse gases - carbon dioxide (CO2), and methane (CH4) - as well as mercury (Hg), carbon monoxide (CO), and other toxic substances (fig. 1). The contribution of coal fires to the global pool of atmospheric CO2 is little known but potentially significant. For China, the world's largest coal producer, it is estimated that anywhere between 10 million and 200 million metric tons (Mt) of coal reserves (about 0.5 to 10 percent of production) is consumed annually by coal fires or made inaccessible owing to fires that hinder mining operations (Rosema and others, 1999; Voigt and others, 2004). At this proportion of production, coal amounts lost to coal fires worldwide would be two to three times that for China. Assuming this coal has mercury concentrations similar to those in U.S. coals, a preliminary estimate of annual Hg emissions from coal fires worldwide is comparable in magnitude to the 48 tons of annual Hg emissions from all U.S. coal-fired power-generating stations combined (U.S. Environmental Protection Agency, 2002). In the United States, the combined cost of coal-fire remediation projects, completed, budgeted, or projected by the U.S. Department of the Interior's Office of Surface Mining Reclamation and Enforcement (OSM), exceeds $1 billion, with about 90% of that in two States - Pennsylvania and West Virginia (Office of Surface Mining Enforcement and Reclamation, 2008; fig. 2). Altogether, 15 States have combined cumulative OSM coal-fire project costs exceeding $1 million, with the greatest overall expense occurring in States where underground coal fires are predominant over surface fires, reflecting the greater cost of extinguishing underground fires (fig. 2) (see 'Controlling Coal Fires'). In this fact sheet we review how coal fires occur, how they can be detected by airborne and remote surveys, and, most importantly, the impact coal-fire emissions may have on the environment and human health. In addition, we describe recent efforts by the U.S. Geological Survey (USGS) and collaborators to measure fluxes of CO2, CO, CH4, and Hg, using groundbased portable detectors, and combining these approaches with airborne thermal imaging and CO2 measurements. The goal of this research is to develop approaches that can be extrapolated to large fires and to extrapolate results for individual fires in order to estimate the contribution of coal fires as a category of global emissions.

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...

Forest Management and the Evolution of Project Design in Dynamic Wildland Urban Interface Fire Environments

NASA Astrophysics Data System (ADS)

Conway, S.

2014-12-01

The Truckee Ranger District on the Tahoe National Forest, in the heart of the Sierra Nevada Mountains, has a rich history of human activities. Native American influences, comstock-era logging, fire suppression, development, and recreation have all shaped the natural environment into what it is today. Like much of our national forests in California, forest conditions that have developed are generally much more homogenous and less resistant to disturbance from fire, insect, and disease than they might have been without the myriad of human influences. However, in order to improve the resiliency of our forests to stand replacing disturbances like high severity fire, while managing for integrated anthropomorphic values, it is imperative that management evolve to meet those dynamic needs. Recent advances in remote sensing and GIS allow land managers more access to forest information and can inform site specific prescriptions to change site specific undesirable conditions. It is ecologically and politically complex, yet our forests deserve that microscope. This particular presentation will focus on how the Truckee Ranger District began this process of incorporating several values, generated from stakeholder collaboration, into one project's goals and how those lessons learned informed their most recent project.

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

Multi-Function Gas Fired Heat Pump

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

Abu-Heiba, Ahmad; Vineyard, Edward Allan

2015-11-01

The aim of this project was to design a residential fuel fired heat pump and further improve efficiency in collaboration with an industry partner – Southwest Gas, the developer of the Nextaire commercial rooftop fuel-fired heat pump. Work started in late 2010. After extensive search for suitable engines, one manufactured by Marathon was selected. Several prototypes were designed and built over the following four years. Design changes were focused on lowering the cost of components and the cost of manufacturing. The design evolved to a final one that yielded the lowest cost. The final design also incorporates noise and vibrationmore » reduction measures that were verified to be effective through a customer survey. ETL certification is currently (as of November 2015) underway. Southwest Gas is currently in talks with GTI to reach an agreement through which GTI will assess the commercial viability and potential of the heat pump. Southwest Gas is searching for investors to manufacture the heat pump and introduce it to the market.« less

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.

Use of Taguchi design of experiments to optimize and increase robustness of preliminary designs

NASA Technical Reports Server (NTRS)

Carrasco, Hector R.

1992-01-01

The research performed this summer includes the completion of work begun last summer in support of the Air Launched Personnel Launch System parametric study, providing support on the development of the test matrices for the plume experiments in the Plume Model Investigation Team Project, and aiding in the conceptual design of a lunar habitat. After the conclusion of last years Summer Program, the Systems Definition Branch continued with the Air Launched Personnel Launch System (ALPLS) study by running three experiments defined by L27 Orthogonal Arrays. Although the data was evaluated during the academic year, the analysis of variance and the final project review were completed this summer. The Plume Model Investigation Team (PLUMMIT) was formed by the Engineering Directorate to develop a consensus position on plume impingement loads and to validate plume flowfield models. In order to obtain a large number of individual correlated data sets for model validation, a series of plume experiments was planned. A preliminary 'full factorial' test matrix indicated that 73,024 jet firings would be necessary to obtain all of the information requested. As this was approximately 100 times more firings than the scheduled use of Vacuum Chamber A would permit, considerable effort was needed to reduce the test matrix and optimize it with respect to the specific objectives of the program. Part of the First Lunar Outpost Project deals with Lunar Habitat. Requirements for the habitat include radiation protection, a safe haven for occasional solar flare storms, an airlock module as well as consumables to support 34 extra vehicular activities during a 45 day mission. The objective for the proposed work was to collaborate with the Habitat Team on the development and reusability of the Logistics Modules.

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...

Large-Scale Spacecraft Fire Safety Experiments in ISS Resupply Vehicles

NASA Technical Reports Server (NTRS)

Ruff, Gary A.; Urban, David

2013-01-01

Our understanding of the fire safety risk in manned spacecraft has been limited by the small scale of the testing we have been able to conduct in low-gravity. Fire growth and spread cannot be expected to scale linearly with sample size so we cannot make accurate predictions of the behavior of realistic scale fires in spacecraft based on the limited low-g testing to date. As a result, spacecraft fire safety protocols are necessarily very conservative and costly. Future crewed missions are expected to be longer in duration than previous exploration missions outside of low-earth orbit and accordingly, more complex in terms of operations, logistics, and safety. This will increase the challenge of ensuring a fire-safe environment for the crew throughout the mission. Based on our fundamental uncertainty of the behavior of fires in low-gravity, the need for realistic scale testing at reduced gravity has been demonstrated. To address this concern, a spacecraft fire safety research project is underway to reduce the uncertainty and risk in the design of spacecraft fire safety systems by testing at nearly full scale in low-gravity. This project is supported by the NASA Advanced Exploration Systems Program Office in the Human Exploration and Operations Mission Directorate. The activity of this project is supported by an international topical team of fire experts from other space agencies to maximize the utility of the data and to ensure the widest possible scrutiny of the concept. The large-scale space flight experiment will be conducted on three missions; each in an Orbital Sciences Corporation Cygnus vehicle after it has deberthed from the ISS. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew allows the fire products to be released into the cabin. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. The international topical team is collaborating with the NASA team in the definition of the experiment requirements and performing supporting analysis, experimentation and technology development.

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

Comment on "Effect of coal-fired power generation on visibility in a nearby National Park (Terhorst and Berkman, 2010)"

NASA Astrophysics Data System (ADS)

White, W. H.; Farber, R. J.; Malm, W. C.; Nuttall, M.; Pitchford, M. L.; Schichtel, B. A.

2012-08-01

Few electricity generating stations received more environmental scrutiny during the last quarter of the twentieth century than did the Mohave Power Project (MPP), a coal-fired facility near Grand Canyon National Park. Terhorst and Berkman (2010) examine regional aerosol monitoring data collected before and after the plant's 2006 retirement for retrospective evidence of MPP's impact on visibility in the Park. The authors' technical analysis is thoughtfully conceived and executed, but is misleadingly presented as discrediting previous studies and their interpretation by regulators. In reality the Terhorst-Berkman analysis validates a consensus on MPP's visibility impact that was established years before its closure, in a collaborative assessment undertaken jointly by Federal regulators and MPP's owners.

Shadows of Previous Days - a Journey Into Digital Reconstruction

NASA Astrophysics Data System (ADS)

Linsinger, S.

2013-02-01

In November 2011 the listed state rooms on the second floor of the Viennese city palace Am Hof 2 were largely destroyed by fire. The historic rooms on the ground floor, the monumental, marble-clad bank service hall and the wood-panelled club rooms all suffered badly from other consequences of the fire such as water and smoke damage. Planning and concept development for the reconstruction of the interior elements made of various materials was carried out be a team of specialist conservators in close collaboration with the Bundesdenkmalamt (Federal Monuments Office). This paper will confine itself to describing the planning, concept development and production of the sample areas for the wooden elements although in practice concept development for all materials ran parallel.

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.

Smoke, Clouds, and Radiation-Brazil (SCAR-B) Experiment

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Hobbs, P. V.; Kirchoff, V. W. J. H.; Artaxo, P.; Remer, L. A.; Holben, B. N.; King, M. D.; Ward, D. E.; Prins, E. M.; Longo, K. M.;

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.

[Recruitment and training of prehospital emergency care nurses in Paris].

PubMed

Pladec, Boris Martin le; Menoret, Romuald; Rodes, Raphaël

2016-11-01

In collaboration with the ambulance driver and the emergency doctor, the prehospital nurse provides care in a universe which is often difficult and sometimes hostile. Whether they are a nurse from the Samu (urgent medical aid service) or from the Paris fire service, how are they recruited and what training do these emergency care professionals receive? Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Collaborating for success: implementation of the interior Alaska inventory

Treesearch

Brendt Mueller; Dan Irvine

2015-01-01

Interior Alaska’s boreal forests are approximately 112 million acres in size, or 15 percent of the United States forest land. This is currently a very dynamic region with rising temperatures, melting permafrost, changes in vegetation, fire, carbon, and water cycles due to a warming climate. This is the last forested area in the United States where the national Forest...

BIONETS (THREE STACKED HYDRAULIC FRACTURES) CONTAINING SOLID OXYGEN SOURCE (SOS), ISOLITE (FIRED DIATOMACIOUS EARTH) AND BACTERIAL STRAIN PM1 TO STIMULATE IN SITU BIOREMEDIATION OF MTBE AND BTEX IN SOILS AND GROUNDWATER

EPA Science Inventory

Collaboration with Office of Research and Development, Region 8, Foremost Solutions, University of California, and Native American Flathead Tribe lead to the development and demonstration of this treatment technology. In place BioNetsTM were developed, initiated, studied and used...

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.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

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.