Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Clarifying evacuation options through fire behavior and traffic modeling

Treesearch

Carol L. Rice; Ronny J. Coleman; Mike Price

2011-01-01

Communities are becoming increasingly concerned with the variety of choices related to wildfire evacuation. We used ArcView with Network Analyst to evaluate the different options for evacuations during wildfire in a case study community. We tested overlaying fire growth patterns with the road network and population characteristics to determine recommendations for...

76 FR 44301 - Information Collection; Homeowner Risk Reduction Behaviors Concerning Wildfire Risks and Climate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-25

... Behaviors Concerning Wildfire Risks and Climate Change Impacts AGENCY: Forest Service, USDA. ACTION: Notice... collection, Homeowner Risk Reduction Behaviors Concerning Wildfire Risks and Climate Change Impacts. The... undertake, and factors that influence these choices, particularly factors related to climate change impacts...

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

A system to evaluate fire impacts from simulated fire behavior in Mediterranean areas of Central Chile.

PubMed

Castillo, Miguel E; Molina, Juan R; Rodríguez Y Silva, Francisco; García-Chevesich, Pablo; Garfias, Roberto

2017-02-01

Wildfires constitute the greatest economic disruption to Mediterranean ecosystems, from a socio-economic and ecological perspective (Molina et al., 2014). This study proposes to classify fire intensity levels based on potential fire behavior in different types of Mediterranean vegetation types, using two geographical scales. The study considered >4 thousand wildfires over a period of 25years, identifying fire behavior on each event, based on simulations using "KITRAL", a model developed in Chile in 1993 and currently used in the entire country. Fire intensity values allowed results to be classified into six fire effects categories (levels), each of them with field indicators linking energy values with damage related to burned vegetation and wildland urban interface zone. These indicators also facilitated a preliminary assessment of wildfire impact on different Mediterranean land uses and, are therefore, a useful tool to prioritize future interventions. Copyright © 2016 Elsevier B.V. All rights reserved.

A tale of two fires: The relative effectiveness of past wildfires in mitigating wildfire behavior and effects

Treesearch

Robert W. Gray; Susan J. Prichard

2015-01-01

The incidence of large, costly landscape-scale fires in western North America is increasing. To combat these fires, researchers and managers have expressed increased interest in investigating the effectiveness of past, stand-replacing wildfires as bottom-up controls on fire spread and severity. Specifically, how effective are past wildfires in mitigating the behavior...

ArcFuels: an ArcMap toolbar for fuel treatment planning and wildfire risk assessment

Treesearch

Nicole M. Vaillant; Alan A. Ager

2014-01-01

Fire behavior modeling and geospatial analysis can provide tremendous insight to land managers in defining both the benefits and potential impacts of fuel treatments in the context of land management goals and public expectations. ArcFuels is a streamlined fuel management planning and wildfire risk assessment system that creates a trans-scale (stand to large landscape...

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2016-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2017-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

Wildfire seasonality and land use: when do wildfires prefer to burn?

PubMed

Bajocco, Sofia; Pezzatti, Gianni Boris; Mazzoleni, Stefano; Ricotta, Carlo

2010-05-01

Because of the increasing anthropogenic fire activity, understanding the role of land-use in shaping wildfire regimes has become a major concern. In the last decade, an increasing number of studies have been carried out on the relationship between land-use and wildfire patterns, in order to identify land-use types where fire behaves selectively, showing a marked preference (or avoidance) in terms of fire incidence. By contrast, the temporal aspects of the relationship between landuse types and wildfire occurrence have received far less attention. The aim of this paper is, thus, to analyze the temporal patterns of fire occurrence in Sardinia (Italy) during the period 2000-2006 to identify land-use types where wildfires occur earlier or later than expected from a random null model. The study highlighted a close relationship between the timing of fire occurrence and land-cover that is primarily governed by two complementary processes: climatic factors that act indirectly on the timing of wildfires determining the spatial distribution of land-use types, and human population and human pressure that directly influence fire ignition. From a practical viewpoint, understanding the temporal trends of wildfires within the different land-use classes can be an effective decision-support tool for fire agencies in managing fire risk and for producing provisional models of fire behavior under changing climatic scenarios and evolving landscapes.

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...

Extreme Wildfire Spread and Behaviour: Case Studies from North Sardinia, Italy

NASA Astrophysics Data System (ADS)

Salis, M.; Arca, B.; Ager, A.; Fois, C.; Bacciu, V.; Duce, P.; Spano, D.

2012-04-01

Worldwide, fire seasons are usually characterized by the occurrence of one or more days with extreme environmental conditions, such as heat waves associated with strong winds. On these days, fires can quickly get out of hand originating large and severe wildfires. In these cases, containment and extinguishment phases are critical, considering that the imperative goal is to keep fire crews, people and animals safe. In this work we will present a set of large and severe wildfires occurred with extreme environmental conditions in the northern area of Sardinia. The most recent wildfire we will describe was ignited on July 13, 2011 in the Oschiri municipality (40°43' N; 9°06' E), and burned about 2,500 ha of wooded and herbaceous pastures and oakwoods in few hours. The second wildfire we will present was ignited on July 23, 2009 in the Bonorva municipality (40°25' N; 8° 46' E), and was responsible for the death of two people and several damages to houses, animals and farms. This wildfire lasted on July 25, and burned about 10,000 ha of wooded and herbaceous pastures; the most of the area was burned during the first day. The last wildfire we will describe was ignited on July 23, 2007 in the Oniferi municipality (40°16' N; 9° 16' E) and burned about 9,000 ha of wooded and herbaceous pastures and oakwoods; about 8,000 ha were burned after 11 hours of propagation. All these wildfires were ignited in days characterized by very hot temperatures associated to the effect of air masses moving from inland North Africa to the Mediterranean Basin, and strong winds from west-south west. This is one of the typical weather pattern associated with large and severe wildfires in North Sardinia, and is well documented in the last years. Weather conditions, fuels and topography factors related to each case study will be accurately analyzed. Moreover, a detailed overview of observed fire spread and behavior and post-fire vegetation recovery will be presented. The fire spread and behavior data collected during the events will be also compared with the results obtained with FARSITE (Finney, 1994) and FLAMMAP (Finney, 2003) models. The main goal of this paper is to thoroughly describe the fire behavior of relevant and recent case studies, in order to learn from it and lessen the chance of making potential mistakes or hazardous firefighting operations in the same environmental conditions. Furthermore, a crucial point is to teach and prepare people and fire crews not to be surprised by severe or abrupt fire behavior under extreme environmental conditions. For these reasons, the combination of analysis, knowledge and awareness of historical case studies, field experience and computer modeling represent a key learning technique.

Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA.

Treesearch

Crystal L. Raymond; David L. Peterson

2005-01-01

We had the rare opportunity to quantify the relationship between fuels and fire severity using prefire surface and canopy fuel data and fire severity data after a wildfire. The study area is a mixed-evergreen forest of southwestern Oregon with a mixed-severity fire regime. Modeled fire behavior showed that thinning reduced canopy fuels, thereby decreasing the potential...

Creation a Geo Big Data Outreach and Training Collaboratory for Wildfire Community

NASA Astrophysics Data System (ADS)

Altintas, I.; Sale, J.; Block, J.; Cowart, C.; Crawl, D.

2015-12-01

A major challenge for the geoscience community is the training and education of current and next generation big data geoscientists. In wildfire research, there are an increasing number of tools, middleware and techniques to use for data science related to wildfires. The necessary computing infrastructures are often within reach and most of the software tools for big data are freely available. But what has been lacking is a transparent platform and training program to produce data science experts who can use these integrated tools effectively. Scientists well versed to take advantage of big data technologies in geoscience applications is of critical importance to the future of research and knowledge advancement. To address this critical need, we are developing learning modules to teach process-based thinking to capture the value of end-to-end systems of reusable blocks of knowledge and integrate the tools and technologies used in big data analysis in an intuitive manner. WIFIRE is an end-to-end cyberinfrastructure for dynamic data-driven simulation, prediction and visualization of wildfire behavior.To this end, we are openly extending an environment we have built for "big data training" (biobigdata.ucsd.edu) to similar MOOC-based approaches to the wildfire community. We are building an environment that includes training modules for distributed platforms and systems, Big Data concepts, and scalable workflow tools, along with other basics of data science including data management, reproducibility and sharing of results. We also plan to provide teaching modules with analytical and dynamic data-driven wildfire behavior modeling case studies which address the needs not only of standards-based K-12 science education but also the needs of a well-educated and informed citizenry.Another part our outreach mission is to educate our community on all aspects of wildfire research. One of the most successful ways of accomplishing this is through high school and undergraduate student internships. Students have worked closely with WIFIRE researchers on various projects including the development of statistical models of wildfire ignition probabilities for southern California, and the development of a smartphone app for crowd-sourced wildfire reporting through social networks such as Twitter and Facebook.

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

Lin, Zhongjie

Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.

PubMed

Bashari, Hossein; Naghipour, Ali Asghar; Khajeddin, Seyed Jamaleddin; Sangoony, Hamed; Tahmasebi, Pejman

2016-09-01

Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.

Integrated wildfire risk assessment: framework development and application on the Lewis and Clark National Forest in Montana, USA.

PubMed

Thompson, Matthew P; Scott, Joe; Helmbrecht, Don; Calkin, Dave E

2013-04-01

The financial, socioeconomic, and ecological impacts of wildfire continue to challenge federal land management agencies in the United States. In recent years, policymakers and managers have increasingly turned to the field of risk analysis to better manage wildfires and to mitigate losses to highly valued resources and assets (HVRAs). Assessing wildfire risk entails the interaction of multiple components, including integrating wildfire simulation outputs with geospatial identification of HVRAs and the characterization of fire effects to HVRAs. We present an integrated and systematic risk assessment framework that entails 3 primary analytical components: 1) stochastic wildfire simulation and burn probability modeling to characterize wildfire hazard, 2) expert-based modeling to characterize fire effects, and 3) multicriteria decision analysis to characterize preference structures across at-risk HVRAs. We demonstrate application of this framework for a wildfire risk assessment performed on the Little Belts Assessment Area within the Lewis and Clark National Forest in Montana, United States. We devote particular attention to our approach to eliciting and encapsulating expert judgment, in which we: 1) adhered to a structured process for using expert judgment in ecological risk assessment, 2) used as our expert base local resource scientists and fire/fuels specialists who have a direct connection to the specific landscape and HVRAs in question, and 3) introduced multivariate response functions to characterize fire effects to HVRAs that consider biophysical variables beyond fire behavior. We anticipate that this work will further the state of wildfire risk science and will lead to additional application of risk assessment to inform land management planning. Copyright © 2012 SETAC.

Wildfires and tourist behaviors in Florida

Treesearch

Brijesh Thapa; Ignatius Cahyanto; Stephen M. Holland; James D. Absher

2013-01-01

The impacts of wildfires on tourism have largely been examined with emphasis on economic losses and recovery strategies. Given the limited research from a demand perspective, this study examined tourist risk perceptions and reactionary behaviors toward wildfires in Florida. Data (N ¼ 771) was collected among a U.S. sample of non-resident overnight leisure travelers...

Trying not to get burned: understanding homeowners' wildfire risk-mitigation behaviors.

PubMed

Brenkert-Smith, Hannah; Champ, Patricia A; Flores, Nicholas

2012-12-01

Three causes have been identified for the spiraling cost of wildfire suppression in the United States: climate change, fuel accumulation from past wildfire suppression, and development in fire-prone areas. Because little is likely to be performed to halt the effects of climate on wildfire risk, and because fuel-management budgets cannot keep pace with fuel accumulation let alone reverse it, changing the behaviors of existing and potential homeowners in fire-prone areas is the most promising approach to decreasing the cost of suppressing wildfires in the wildland-urban interface and increasing the odds of homes surviving wildfire events. Wildfire education efforts encourage homeowners to manage their property to decrease wildfire risk. Such programs may be more effective with a better understanding of the factors related to homeowners' decisions to undertake wildfire risk-reduction actions. In this study, we measured whether homeowners had implemented 12 wildfire risk-mitigation measures in 2 Colorado Front Range counties. We found that wildfire information received from local volunteer fire departments and county wildfire specialists, as well as talking with neighbors about wildfire, were positively associated with higher levels of mitigation. Firsthand experience in the form of preparing for or undertaking an evacuation was also associated with a higher level of mitigation. Finally, homeowners who perceived higher levels of wildfire risk on their property had undertaken higher levels of wildfire-risk mitigation on their property.

Atlas of climatic controls of wildfire in the western United States

USGS Publications Warehouse

Hostetler, S.W.; Bartlein, P.J.; Holman, J.O.

2006-01-01

Wildfire behavior depends on several factors including ecologic characteristics, near-term and antecedent climatic conditions,fuel availability and moisture level, weather, and sources of ignition (lightning or human). The variability and interplay of these factors over many spatial and temporal scales present an ongoing challenge to our ability to forecast a given wildfire season. Here we focus on one aspect of wildfire in the western US through a retrospective analysis of wildfire (starts and area burned) and climate over monthly time scales. We consider prefire conditions up to a year preceding fire outbreaks. For our analysis, we used daily and monthly wildfire records and a combination of observed and model-simulated atmospheric and surface climate data. The focus of this report is on monthly wildfire and climate for the period 1980-2000. Although a longer fire record is desirable, the 21-year record is the longest currently available and it is sufficient for the purpose of a first-order regional analysis. We present the main results in the form of a wildfire-climate atlas for 8 subregions of the West that can be used by resource managers to assess current wildfire conditions relative to high, normal, and low fire years in the historical record. Our results clearly demonstrate the link between wildfire conditions and a small set of climatic variables, and our methodology is a framework for providing near-real-time assessments of current wildfire conditions in the West.

Coupling of Bayesian Networks with GIS for wildfire risk assessment on natural and agricultural areas of the Mediterranean

NASA Astrophysics Data System (ADS)

Scherb, Anke; Papakosta, Panagiota; Straub, Daniel

2014-05-01

Wildfires cause severe damages to ecosystems, socio-economic assets, and human lives in the Mediterranean. To facilitate coping with wildfire risks, an understanding of the factors influencing wildfire occurrence and behavior (e.g. human activity, weather conditions, topography, fuel loads) and their interaction is of importance, as is the implementation of this knowledge in improved wildfire hazard and risk prediction systems. In this project, a probabilistic wildfire risk prediction model is developed, with integrated fire occurrence and fire propagation probability and potential impact prediction on natural and cultivated areas. Bayesian Networks (BNs) are used to facilitate the probabilistic modeling. The final BN model is a spatial-temporal prediction system at the meso scale (1 km2 spatial and 1 day temporal resolution). The modeled consequences account for potential restoration costs and production losses referred to forests, agriculture, and (semi-) natural areas. BNs and a geographic information system (GIS) are coupled within this project to support a semi-automated BN model parameter learning and the spatial-temporal risk prediction. The coupling also enables the visualization of prediction results by means of daily maps. The BN parameters are learnt for Cyprus with data from 2006-2009. Data from 2010 is used as validation data set. A special focus is put on the performance evaluation of the BN for fire occurrence, which is modeled as binary classifier and thus, could be validated by means of Receiver Operator Characteristic (ROC) curves. With the final best models, AUC values of more than 70% for validation could be achieved, which indicates potential for reliable prediction performance via BN. Maps of selected days in 2010 are shown to illustrate final prediction results. The resulting system can be easily expanded to predict additional expected damages in the mesoscale (e.g. building and infrastructure damages). The system can support planning of preventive measures (e.g. state resources allocation for wildfire prevention and preparedness) and assist recuperation plans of damaged areas.

Wildfire spread, hazard and exposure metric raster grids for central Catalonia.

PubMed

Alcasena, Fermín J; Ager, Alan A; Salis, Michele; Day, Michelle A; Vega-Garcia, Cristina

2018-04-01

We provide 40 m resolution wildfire spread, hazard and exposure metric raster grids for the 0.13 million ha fire-prone Bages County in central Catalonia (northeastern Spain) corresponding to node influence grid (NIG), crown fraction burned (CFB) and fire transmission to residential houses (TR). Fire spread and behavior data (NIG, CFB and fire perimeters) were generated with fire simulation modeling considering wildfire season extreme fire weather conditions (97 th percentile). Moreover, CFB was also generated for prescribed fire (Rx) mild weather conditions. The TR smoothed grid was obtained with a geospatial analysis considering large fire perimeters and individual residential structures located within the study area. We made these raster grids available to assist in the optimization of wildfire risk management plans within the study area and to help mitigate potential losses from catastrophic events.

External charring and fire scarring in three western conifers

Treesearch

E. K. Sutherland; Josh Farella; David K Wright; Ian Hyp; K. T. Smith; Donald A. Falk; Estelle Arbellay; Markus Stoffel

2013-01-01

Fires that injure but do not kill trees cause scars used as proxies for the reconstruction of wildfire history. Understanding about these wildfires - and their relationship to vegetation dynamics and climate - has profoundly affected wildfire and land management policy globally. To better understand scarring in the context of wildfire behavior, landscape and biological...

Risk preferences, probability weighting, and strategy tradeoffs in wildfire management

Treesearch

Michael S. Hand; Matthew J. Wibbenmeyer; Dave Calkin; Matthew P. Thompson

2015-01-01

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to...

Understanding the Factors that Influence Perceptions of Post-Wildfire Landscape Recovery Across 25 Wildfires in the Northwestern United States.

PubMed

Kooistra, C; Hall, T E; Paveglio, T; Pickering, M

2018-01-01

Disturbances such as wildfire are important features of forested landscapes. The trajectory of changes following wildfires (often referred to as landscape recovery) continues to be an important research topic among ecologists and wildfire scientists. However, the landscape recovery process also has important social dimensions that may or may not correspond to ecological or biophysical perspectives. Perceptions of landscape recovery may affect people's attitudes and behaviors related to forest and wildfire management. We explored the variables that influence people's perceptions of landscape recovery across 25 fires that occurred in 2011 or 2012 in the United States of Washington, Oregon, Idaho, and Montana and that represented a range of fire behavior characteristics and landscape impacts. Residents near each of the 25 fires were randomly selected to receive questionnaires about their experiences with the nearby fire, including perceived impacts and how the landscape had recovered since the fire. People generally perceived landscapes as recovering, even though only one to two years had passed. Regression analysis suggested that perceptions of landscape recovery were positively related to stronger beliefs about the ecological role of fire and negatively related to loss of landscape attachment, concern about erosion, increasing distance from the fire perimeter, and longer lasting fires. Hierarchical linear modeling (HLM) analysis indicated that the above relationships were largely consistent across fires. These findings highlight that perceptions of post-fire landscape recovery are influenced by more than vegetation changes and include emotional and cognitive factors. We discuss the management implications of these findings.

Understanding the Factors that Influence Perceptions of Post-Wildfire Landscape Recovery Across 25 Wildfires in the Northwestern United States

NASA Astrophysics Data System (ADS)

Kooistra, C.; Hall, T. E.; Paveglio, T.; Pickering, M.

2018-01-01

Disturbances such as wildfire are important features of forested landscapes. The trajectory of changes following wildfires (often referred to as landscape recovery) continues to be an important research topic among ecologists and wildfire scientists. However, the landscape recovery process also has important social dimensions that may or may not correspond to ecological or biophysical perspectives. Perceptions of landscape recovery may affect people's attitudes and behaviors related to forest and wildfire management. We explored the variables that influence people's perceptions of landscape recovery across 25 fires that occurred in 2011 or 2012 in the United States of Washington, Oregon, Idaho, and Montana and that represented a range of fire behavior characteristics and landscape impacts. Residents near each of the 25 fires were randomly selected to receive questionnaires about their experiences with the nearby fire, including perceived impacts and how the landscape had recovered since the fire. People generally perceived landscapes as recovering, even though only one to two years had passed. Regression analysis suggested that perceptions of landscape recovery were positively related to stronger beliefs about the ecological role of fire and negatively related to loss of landscape attachment, concern about erosion, increasing distance from the fire perimeter, and longer lasting fires. Hierarchical linear modeling (HLM) analysis indicated that the above relationships were largely consistent across fires. These findings highlight that perceptions of post-fire landscape recovery are influenced by more than vegetation changes and include emotional and cognitive factors. We discuss the management implications of these findings.

A Monte Carlo Approach to Modeling Wildfire Risk on Changing Landscapes

NASA Astrophysics Data System (ADS)

Burzynski, A. M.; Beavers, A.

2016-12-01

The U.S. Department of Defense (DoD) maintains approximately 28 million acres of land across 420 of their largest installations. These sites harbored 425 federally listed Threatened and Endangered species as of 2013, representing a density of rare species that is several times greater than any other land management agency in the U.S. This is a major driver of DoD natural resources policy and many of these species are affected by wildland fire, both positively and negatively. Military installations collectively experience thousands of wildfires per year, and the majority of ignitions are caused by mission and training activities that can be planned to accommodate fire risk. Motivated by the need for accurately modeled wildfire under the unique land-use conditions of military installations and the assessment of risk exposure at installations throughout the U.S., we developed custom, FARSITE-based scientific software that applies a Monte Carlo approach to wildfire risk analysis. This simulation accounts for the dynamics of vegetation and weather over time, as well as the spatial and temporal distribution of wildfire ignitions, and can be applied to landscapes up to several million acres in size. The data-driven simulation provides insight that feeds directly into mitigation decision-making and can be used to assess future risk scenarios, both real and hypothetical. We highlight an example of a future scenario comparing wildfire behavior between unmitigated fuels and one in which a prescribed burn program is implemented. The same process can be used for a variety of scenarios including changes in vegetation (e.g. new or altered grazing regimes, extreme weather, or drought) and changes in spatiotemporal ignition probability. The modeling capabilities that we apply to predicting wildfire risk on military lands are also relevant to the greater scientific community for modeling wildland fire in the context of environmental change, historical ecology, or climate change.

Modeling Wildfire Hazard in the Western Hindu Kush-Himalayas

NASA Astrophysics Data System (ADS)

Bylow, D.

2012-12-01

Wildfire regimes are a leading driver of global environmental change affecting a diverse array of global ecosystems. Particulates and aerosols produced by wildfires are a primary source of air pollution making the early detection and monitoring of wildfires crucial. The objectives of this study were to model regional wildfire potential and identify environmental, topological, and sociological factors that contribute to the ignition of wildfire events in the Western Hindu Kush-Himalayas of South Asia. The environmental, topological, and sociological factors were used to model regional wildfire potential through multi-criteria evaluation using a method of weighted linear combination. Moderate Resolution Imaging Spectroradiometer (MODIS) and geographic information systems (GIS) data were integrated to analyze regional wildfires and construct the model. Model validation was performed using a holdout cross validation method. The study produced a significant model of wildfire potential in the Western Hindu Kush-Himalayas.; Western Hindu Kush-Himalayas ; Western Hindu Kush-Himalayas Wildfire Potential

Trying not to get burned: Understanding homeowners' wildfire risk-mitigation behaviors

Treesearch

Hannah Brenkert-Smith; Patricia A. Champ; Nicholas Flores

2012-01-01

Three causes have been identified for the spiraling cost of wildfire suppression in the United States: climate change, fuel accumulation from past wildfire suppression, and development in fire-prone areas. Because little is likely to be performed to halt the effects of climate on wildfire risk, and because fuel-management budgets cannot keep pace with fuel accumulation...

Fighting fire with fire: estimating the efficacy of wildfire mitigation programs using propensity scores

Treesearch

David T. Butry

2009-01-01

This paper examines the effect wildfire mitigation has on broad-scale wildfire behavior. Each year, hundreds of million of dollars are spent on fire suppression and fuels management applications, yet little is known, quantitatively, of the returns to these programs in terms of their impact on wildfire extent and intensity. This is especially true when considering that...

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

Treesearch

Avi Bar Massada; Volker C. Radeloff; Susan I. Stewart; Todd J. Hawbaker

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather...

The influence of fuels treatment and landscape arrangement on simulated fire behavior, southern Cascade Range, California

Treesearch

David A. Schmidt; Alan H. Taylor; Carl N. Skinner

2008-01-01

Wildfire behavior can be modified by altering the quantity, structure, and arrangement of fuel (flammable vegetation) by silvicultural treatments such as forest thinning and prescribed burning. The type and arrangement (including landscape location) of treated areas have been demonstrated to influence wildfire behavior. This study analyzes the response of several key...

Effects of mountain pine beetle on fuels and expected fire behavior in lodgepole pine forests, Colorado, USA

Treesearch

Tania Schoennagel; Thomas T. Veblen; Jose F. Negron; Jeremy M. Smith

2012-01-01

In Colorado and southern Wyoming, mountain pine beetle (MPB) has affected over 1.6 million ha of predominantly lodgepole pine forests, raising concerns about effects of MPB-caused mortality on subsequent wildfire risk and behavior. Using empirical data we modeled potential fire behavior across a gradient of wind speeds and moisture scenarios in Green stands compared...

Enhanced Risk of Wildfire Resulting from the Interactions between Pyro-Cumulus and Mountain Waves: Implications for Fire Research and Management

NASA Astrophysics Data System (ADS)

Kim, Y. J.; Linn, R.; Sauer, J.; Canfield, J.; Costigan, K. R.; Munoz-Esparza, D.

2014-12-01

The Los Alamos National Laboratory is conducting a research project to understand the physical mechanisms behind the Las Conchas Fire that occurred in Santa Fe National Forest near Los Alamos, New Mexico on June 26, 2011. Between 8 pm on June 26 and 3 am on June 27, the fire grew from 8,000 to 43,000 acres, spreading downhill in sparse fuels and lighter winds than were present during the first several hours of the fire. Fire behavior experts and fire management officers expected the fire to reach 9,000 to 12,000 acres by sunrise due to the anticipated burning conditions, but it actually increased 440% in size before 3 am, surprising everyone. One viable hypothesis was suggested for this baffling fire behavior: a partial collapse of the soot-laden pyrocumulus column (pyro-cu) that towered above the fire, causing a sustained density current carrying fire at high speed. Moreover, another mechanism has been suggested recently that could have significantly affected the fire characteristics around mountainous regions, such as Jemez Mountains near Los Alamos: the drastic changes in the speed, direction, and gustiness of the winds due to the development of mountain waves. The present research tests these hypotheses and attempts to decipher the combination of environmental conditions, due to pyro-cu and mountain wave interactions, and fire behavior dynamics associated with this anomalous wildfire event. Preliminary results from WRF (Weather Research and Forecasting model) and HIGRAD (High-GRADient model developed at LANL) simulations suggest that these two mechanisms may need to be taken into account in order to fully understand and prepare for atypical wildfire behavior in regions with complex topography. It is possible that the Las Conchas Fire could have directly affected the nearby Los Alamos National Laboratory if the fire broke out concurrently with both pyro-cu and strong mountain waves along the upstream of the Laboratory. This research also addresses its implications for the management as well as the research of wildfire in that, in order to prepare for potential wildfire, the topography of the surrounding region as well as the region of importance itself should be taken into account.

Potential fire behavior in pine flatwood forests following three different fuel reduction techniques

Treesearch

Patrick Brose; Dale Wade

2002-01-01

A computer modeling study to determine the potential fire behavior in pine flatwood forests following three fuel hazard reduction treatments: herbicide, prescribed fire and thinning was conducted in Florida following the 1998 wildfire season. Prescribed fire provided immediate protection but this protection quickly disappeared as the rough recovered. Thinning had a...

Economic analysis of fuel treatments

Treesearch

D. Evan Mercer; Jeffrey P. Prestemon

2012-01-01

The economics of wildfire is complicated because wildfire behavior depends on the spatial and temporal scale at which management decisions made, and because of uncertainties surrounding the results of management actions. Like the wildfire processes they seek to manage, interventions through fire prevention programs, suppression, and fuels management are scale dependent...

Public perspectives on the "wildfire problem."

Treesearch

Antony S. Cheng; Dennis R. Becker

2005-01-01

Just as wildland fire managers must have a working knowledge of fire behavior, they must also understand the social dimensions of wildland fire in order to effectively engage the public.Social scientists are therefore gathering information about public attitudes toward wildland fire and wildfire mitigation. How do people see the "wildfire problem"? What...

Identifying Indicators of Behavior Change: Insights from Wildfire Education Programs

ERIC Educational Resources Information Center

Monroe, Martha C.; Agrawal, Shruti; Jakes, Pamela J.; Kruger, Linda E.; Nelson, Kristen C.; Sturtevant, Victoria

2013-01-01

Environmental educators are challenged to document behavior changes, because change rarely depends solely on outcomes of education programs, but on many factors. An analysis of 15 communities in the United States that have increased their preparedness for wildfire allowed us to explore how education programs encouraged individual and community…

Wind adjustment factors for predicting fire behavior in three fuel types in Alaska.

Treesearch

Rodney A. Norum

1983-01-01

Factors for adjusting wind velocities from the 20-foot standard anemometer height down to an average wildfire midflame height (3.5 ft for the fuels studied) are given for exposed, partially sheltered, and sheltered fuels in Alaska. The values are suitable for predicting wildfire behavior.

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.

Evaluating crown fire rate of spread predictions from physics-based models

Treesearch

C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont

2015-01-01

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...

Winter grazing can reduce wildfire size, intensity, and behavior in a shrub-grassland

USDA-ARS?s Scientific Manuscript database

1. An increase in mega-fires and wildfires in general is a global issue that is expected to become worse with climate change. Fuel treatments are often recommended to decrease the risk, size, intensity, and severity of wildfires; however, the extensive nature of rangelands limits the use of many po...

Identifying indicators of behavior change: insights from wildfire education programs

Treesearch

Martha C. Monroe; Shruti Agrawal; Pamela J. Jakes; Linda E. Kruger; Kristen C. Nelson; Victoria Sturtevant

2013-01-01

Environmental educators are challenged to document behavior changes, because change rarely depends solely on outcomes of education programs, but on many factors. An analysis of 15 communities in the United States that have increased their preparedness for wildfire allowed us to explore how education programs encouraged individual and community change. Agency-sponsored...

Assessment of the FARSITE model for predicting fire behavior in the Southern Appalachian Mountains

Treesearch

Ross J. Phillips; Thomas A. Waldrop; Dean M. Simon

2006-01-01

Fuel reduction treatments are necessary in fire-adapted ecosystems where fire has been excluded for decades and the potential for severe wildfire is high. Using the Fire Area Simulator, FARSITE, we examined the spatial and temporal effects of these treatments on fire behavior in the Southern Appalachian Mountains. With measurements from temperature sensors during...

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

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

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. ?? 2009 Elsevier B.V.

Scientists aim to smoke out wildfire impacts

NASA Astrophysics Data System (ADS)

Cornwall, Warren

2018-06-01

Scientists this summer are taking to the air in an ambitious effort to better understand the chemistry, behavior, and health impacts of wildfire smoke. The flights in an instrument-packed C-130 airplane belonging to the National Science Foundation will be followed in 2019 by flights on a NASA DC-8 research jet by scientists with NASA and the National Oceanic and Atmospheric Administration. The two planes will fly through plumes of wildfire smoke, with a focus on the western United States, where wildfires have grown bigger and more intense. Researchers are saying it's the most comprehensive effort ever to understand wildfire smoke.

Supporting FIRE-suppression strategies combining fire spread MODelling and SATellite data in an operational context in Portugal: the FIRE-MODSAT project

NASA Astrophysics Data System (ADS)

Sá, Ana C. L.; Benali, Akli; Pinto, Renata M. S.; Pereira, José M. C.; Trigo, Ricardo M.; DaCamara, Carlos C.

2014-05-01

Large wildfires are infrequent but account for the most severe environmental, ecological and socio-economic impacts. In recent years Portugal has suffered the impact of major heat waves that fuelled records of burnt area exceeding 400.000ha and 300.000ha in 2003 and 2005, respectively. According to the latest IPCC reports, the frequency and amplitude of summer heat waves over Iberia will very likely increase in the future. Therefore, most climate change studies point to an increase in the number and extent of wildfires. Thus, an increase in both wildfire impacts and fire suppression difficulties is expected. The spread of large wildfires results from a complex interaction between topography, meteorology and fuel properties. Wildfire spread models (e.g. FARSITE) are commonly used to simulate fire growth and behaviour and are an essential tool to understand their main drivers. Additionally, satellite active-fire data have been used to monitor the occurrence, extent, and spread of wildfires. Both satellite data and fire spread models provide different types of information about the spatial and temporal distribution of large wildfires and can potentially be used to support strategic decisions regarding fire suppression resource allocation. However, they have not been combined in a manner that fully exploits their potential and minimizes their limitations. A knowledge gap still exists in understanding how to minimize the impacts of large wildfires, leading to the following research question: What can we learn from past large wildfires in order to mitigate future fire impacts? FIRE-MODSAT is a one-year funded project by the Portuguese Foundation for the Science and Technology (FCT) that is founded on this research question, with the main goal of improving our understanding on the interactions between fire spread and its environmental drivers, to support fire management decisions in an operational context and generate valuable information to improve the efficiency of the fire suppression system. This project proposes to explore an innovative combination of remote sensing and fire spread models in order to 1) better understand the interactions of fire spread drivers that lead to large wildfires; 2) identify the spatio-temporal frames in which large wildfires can be suppressed more efficiently, and 3) explore the essential steps towards an operational use of both tools to assist fire suppression decisions. Preliminary results combine MODIS active-fire data and burn scar perimeters, to derive the main fire spread paths for the 10 largest wildfires that occurred in Portugal between 2001 and 2012. Fire growth and behavior simulations of some of those wildfires are assessed using the active fires data. Results are also compared with the major fire paths to understand the main drivers of fire propagation, through their interactions with topography, vegetation and meteorology. These combined results are also used for spatial and temporal identification of opportunity windows for a more efficient suppression intervention for each fire event. The approach shows promising results, providing a valuable reconstruction of the fire events and retrieval of important parameters related to the complex spread patterns of individual fire events.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, Kostas; Ager, Alan; Finney, Mark; Athanasis, Nikos; Palaiologou, Palaiologos; Vasilakos, Christos

2016-03-01

We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

Difference in information needs for wildfire evacuees and non-evacuees

Treesearch

Sarah M. McCaffrey; Anne-Lise Knox Velez; Jason Alexander Briefel

2013-01-01

This paper examines whether evacuees from two wildfires displayed different information seeking behavior than non-evacuees. Findings are the results of a mail survey sent to residents affected by wildfires outside Flagstaff, Arizona and Boulder, Colorado in 2010. We found evacuees sought information more actively than non-evacuees and placed a greater emphasis on use...

Black swans, power laws, and dragon-kings: Earthquakes, volcanic eruptions, landslides, wildfires, floods, and SOC models

NASA Astrophysics Data System (ADS)

Sachs, M. K.; Yoder, M. R.; Turcotte, D. L.; Rundle, J. B.; Malamud, B. D.

2012-05-01

Extreme events that change global society have been characterized as black swans. The frequency-size distributions of many natural phenomena are often well approximated by power-law (fractal) distributions. An important question is whether the probability of extreme events can be estimated by extrapolating the power-law distributions. Events that exceed these extrapolations have been characterized as dragon-kings. In this paper we consider extreme events for earthquakes, volcanic eruptions, wildfires, landslides and floods. We also consider the extreme event behavior of three models that exhibit self-organized criticality (SOC): the slider-block, forest-fire, and sand-pile models. Since extrapolations using power-laws are widely used in probabilistic hazard assessment, the occurrence of dragon-king events have important practical implications.

Application of Recent Advances in Forward Modeling of Emissions from Boreal and Temperate Wildfires to Real-time Forecasting of Aerosol and Trace Gas Concentrations

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Kasischke, E. S.; Allen, D. J.

2005-12-01

The magnitude of trace gas and aerosol emissions from wildfires is a scientific problem with important implications for atmospheric composition, and is also integral to understanding carbon cycling in terrestrial ecosystems. Recent ecological research on modeling wildfire emissions has integrated theoretical advances derived from ecological fieldwork with improved spatial and temporal databases to produce "post facto" estimates of emissions with high spatial and temporal resolution. These advances have been shown to improve agreement with atmospheric observations at coarse scales, but can in principle be applied to applications, such as forecasting, at finer scales. However, several of the approaches employed in these forward models are incompatible with the requirements of real-time forecasting, requiring modification of data inputs and calculation methods. Because of the differences in data inputs used for real-time and "post-facto" emissions modeling, the key uncertainties in the forward problem are not necessarily the same for these two applications. However, adaptation of these advances in forward modeling to forecasting applications has the potential to improve air quality forecasts, and also to provide a large body of experimental data which can be used to constrain crucial uncertainties in current conceptual models of wildfire emissions. This talk describes a forward modeling method developed at the University of Maryland and its application to the Fire Locating and Modeling of Burning Emissions (FLAMBE) system at the Naval Research Laboratory. Methods for applying the outputs of the NRL aerosol forecasting system to the inverse problem of constraining emissions will also be discussed. The system described can use the feedback supplied by atmospheric observations to improve the emissions source description in the forecasting model, and can also be used for hypothesis testing regarding fire behavior and data inputs.

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

USGS Publications Warehouse

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

Assessing mitigation of wildfire severity by fuel treatments - An example from the coastal plain of Mississippi

Treesearch

Erik J. Martinson; Philip N. Omi

2006-01-01

Fuel treatments such as prescribed fire are a controversial tenet of wildfire management. Despite a well-established theoretical basis for their use, scant empirical evidence currently exists on fuel treatment effectiveness for mitigating the behavior and effects of extreme wildfire events. We report the results of a fire severity evaluation of an escaped prescribed...

Will future climate favor more erratic wildfires in the western United States?

Treesearch

Lifeng Luo; Ying Tang; Shiyuan Zhong; Xindi Bian; Warren E. Heilman

2013-01-01

Wildfires that occurred over the western United States during August 2012 were fewer in number but larger in size when compared with all other Augusts in the twenty-first century. This unique characteristic, along with the tremendous property damage and potential loss of life that occur with large wildfires with erratic behavior, raised the question of whether future...

Effects of Near-Surface Atmospheric Stability and Moisture on Wildfire Behavior and Consequences for Haines Index

Treesearch

Ruiyu Sun; Mary Ann Jenkins

2003-01-01

Since the 1950s, extensive research has been conducted to investigate the relationship between near-surface atmospheric conditions and large wildfire growth and occurrence. Observational studies have demonstrated that near-surface dryness (e-g., Fahnestock 1965) and atmospheric instability (e-g., Brotak and Reifsnyder 1977) are correlated with large wildfire growth and...

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.

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...

Predicting Geomorphic and Hydrologic Risks after Wildfire Using Harmonic and Stochastic Analyses

NASA Astrophysics Data System (ADS)

Mikesell, J.; Kinoshita, A. M.; Florsheim, J. L.; Chin, A.; Nourbakhshbeidokhti, S.

2017-12-01

Wildfire is a landscape-scale disturbance that often alters hydrological processes and sediment flux during subsequent storms. Vegetation loss from wildfires induce changes to sediment supply such as channel erosion and sedimentation and streamflow magnitude or flooding. These changes enhance downstream hazards, threatening human populations and physical aquatic habitat over various time scales. Using Williams Canyon, a basin burned by the Waldo Canyon Fire (2012) as a case study, we utilize deterministic and statistical modeling methods (Fourier series and first order Markov chain) to assess pre- and post-fire geomorphic and hydrologic characteristics, including of precipitation, enhanced vegetation index (EVI, a satellite-based proxy of vegetation biomass), streamflow, and sediment flux. Local precipitation, terrestrial Light Detection and Ranging (LiDAR) scanning, and satellite-based products are used for these time series analyses. We present a framework to assess variability of periodic and nonperiodic climatic and multivariate trends to inform development of a post-wildfire risk assessment methodology. To establish the extent to which a wildfire affects hydrologic and geomorphic patterns, a Fourier series was used to fit pre- and post-fire geomorphic and hydrologic characteristics to yearly temporal cycles and subcycles of 6, 4, 3, and 2.4 months. These cycles were analyzed using least-squares estimates of the harmonic coefficients or amplitudes of each sub-cycle's contribution to fit the overall behavior of a Fourier series. The stochastic variances of these characteristics were analyzed by composing first-order Markov models and probabilistic analysis through direct likelihood estimates. Preliminary results highlight an increased dependence of monthly post-fire hydrologic characteristics on 12 and 6-month temporal cycles. This statistical and probabilistic analysis provides a basis to determine the impact of wildfires on the temporal dependence of geomorphic and hydrologic characteristics, which can be incorporated into post-fire mitigation, management, and recovery-based measures to protect and rehabilitate areas subject to influence from wildfires.

New Developments in Wildfire Pollution Forecasting at the Canadian Meteorological Centre

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Chen, Jack; Munoz-Alpizar, Rodrigo; Davignon, Didier; Beaulieu, Paul-Andre; Landry, Hugo; Menard, Sylvain; Gravel, Sylvie; Moran, Michael

2017-04-01

Environment and Climate Change Canada's air quality forecast system with near-real-time wildfire emissions, named FireWork, was developed in 2012 and has been run by the Canadian Meteorological Centre Operations division (CMCO) since 2013. In June 2016 this system was upgraded to operational status and wildfire smoke forecasts for North America are now available to the general public. FireWork's ability to model the transport and diffusion of wildfire smoke plumes has proved to be valuable to regional air quality forecasters and emergency first responders. Some of the most challenging issues with wildfire pollution modelling concern the production of wildfire emission estimates and near-source dispersion within the air quality model. As a consequence, FireWork is undergoing constant development. During the massive Fort McMurray wildfire event in western Canada in May 2016, for example, different wildfire emissions processing approaches and wildfire emissions injection and dispersion schemes were tested within the air quality model. Work on various FireWork components will continue in order to deliver a new operational version of the forecasting system for the 2017 wildfire season. Some of the proposed improvements will be shown in this presentation along with current and planned FireWork post-processing products.

Assessment of multi-wildfire occurrence data for machine learning based risk modelling

NASA Astrophysics Data System (ADS)

Lim, C. H.; Kim, M.; Kim, S. J.; Yoo, S.; Lee, W. K.

2017-12-01

The occurrence of East Asian wildfires is mainly caused by human-activities, but the extreme drought increased due to the climate change caused wildfires and they spread to large-scale fires. Accurate occurrence location data is required for modelling wildfire probability and risk. In South Korea, occurrence data surveyed through KFS (Korea Forest Service) and MODIS (MODerate-resolution Imaging Spectroradiometer) satellite-based active fire data can be utilized. In this study, two sorts of wildfire occurrence data were applied to select suitable occurrence data for machine learning based wildfire risk modelling. MaxEnt (Maximum Entropy) model based on machine learning is used for wildfire risk modelling, and two types of occurrence data and socio-economic and climate-environment data are applied to modelling. In the results with KFS survey based data, the low relationship was shown with climate-environmental factors, and the uncertainty of coordinate information appeared. The MODIS-based active fire data were found outside the forests, and there were a lot of spots that did not match the actual wildfires. In order to utilize MODIS-based active fire data, it was necessary to extract forest area and utilize only high-confidence level data. In KFS data, it was necessary to separate the analysis according to the damage scale to improve the modelling accuracy. Ultimately, it is considered to be the best way to simulate the wildfire risk by constructing more accurate information by combining two sorts of wildfire occurrence data.

Wildfire simulation using LES with synthetic-velocity SGS models

NASA Astrophysics Data System (ADS)

McDonough, J. M.; Tang, Tingting

2016-11-01

Wildland fires are becoming more prevalent and intense worldwide as climate change leads to warmer, drier conditions; and large-eddy simulation (LES) is receiving increasing attention for fire spread predictions as computing power continues to improve (see, e.g.,). We report results from wildfire simulations over general terrain employing implicit LES for solution of the incompressible Navier-Stokes (N.-S.) and thermal energy equations with Boussinesq approximation, altered with Darcy, Forchheimer and Brinkman extensions, to represent forested regions as porous media with varying (in both space and time) porosity and permeability. We focus on subgrid-scale (SGS) behaviors computed with a synthetic-velocity model, a discrete dynamical system, based on the poor man's N.-S. equations and investigate the ability of this model to produce fire whirls (tornadoes of fire) at the (unresolved) SGS level. Professor, Mechanical Engineering and Mathematics.

ArcFuels10 system overview

Treesearch

Nicole M. Vaillant; Alan A. Ager; John Anderson

2013-01-01

Fire behavior modeling and geospatial analyses can provide tremendous insight for land managers as they grapple with the complex problems frequently encountered in wildfire risk assessments and fire and fuels management planning. Fuel management often is a particularly complicated process in which the benefits and potential impacts of fuel treatments need to be...

Multitemporal Modelling of Socio-Economic Wildfire Drivers in Central Spain between the 1980s and the 2000s: Comparing Generalized Linear Models to Machine Learning Algorithms

PubMed Central

Vilar, Lara; Gómez, Israel; Martínez-Vega, Javier; Echavarría, Pilar; Riaño, David; Martín, M. Pilar

2016-01-01

The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence. GLM base their estimation on wildfire presence-absence observations whereas Maxent on wildfire presence-only. According to indicators like sensitivity or commission error Maxent outperformed GLM in both periods. It achieved a sensitivity of 38.9% and a commission error of 43.9% for the 1980s, and 67.3% and 17.9% for the 2000s. Instead, GLM obtained 23.33, 64.97, 9.41 and 18.34%, respectively. However GLM performed steadier than Maxent in terms of the overall fit. Both models explained wildfires from predictors such as population density and Wildland Urban Interface (WUI), but differed in their relative contribution. As a result of the urban sprawl and an abandonment of rural areas, predictors like WUI and distance to roads increased their contribution to both models in the 2000s, whereas Forest-Grassland Interface (FGI) influence decreased. This study demonstrates that human component can be modelled with a spatio-temporal dimension to integrate it into wildfire risk assessment. PMID:27557113

Multitemporal Modelling of Socio-Economic Wildfire Drivers in Central Spain between the 1980s and the 2000s: Comparing Generalized Linear Models to Machine Learning Algorithms.

PubMed

Vilar, Lara; Gómez, Israel; Martínez-Vega, Javier; Echavarría, Pilar; Riaño, David; Martín, M Pilar

2016-01-01

The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence. GLM base their estimation on wildfire presence-absence observations whereas Maxent on wildfire presence-only. According to indicators like sensitivity or commission error Maxent outperformed GLM in both periods. It achieved a sensitivity of 38.9% and a commission error of 43.9% for the 1980s, and 67.3% and 17.9% for the 2000s. Instead, GLM obtained 23.33, 64.97, 9.41 and 18.34%, respectively. However GLM performed steadier than Maxent in terms of the overall fit. Both models explained wildfires from predictors such as population density and Wildland Urban Interface (WUI), but differed in their relative contribution. As a result of the urban sprawl and an abandonment of rural areas, predictors like WUI and distance to roads increased their contribution to both models in the 2000s, whereas Forest-Grassland Interface (FGI) influence decreased. This study demonstrates that human component can be modelled with a spatio-temporal dimension to integrate it into wildfire risk assessment.

The Impact of CO2-Driven Vegetation Changes on Wildfire Risk

NASA Astrophysics Data System (ADS)

Skinner, C. B.; Poulsen, C. J.

2017-12-01

While wildfires are a key component of natural ecological restoration and succession, they also pose tremendous risks to human life, health, and property. Wildfire frequency is expected to increase in many regions as the radiative effects of elevated CO2 drive warmer surface air temperatures, earlier spring snow melt, and more frequent meteorological drought. However, high CO2 concentrations will also directly impact vegetation growth and physiology, potentially altering wildfire characteristics through changes in fuel amount and surface hydrology. Depending on the biome and time of year, these vegetation-driven responses may mitigate or enhance radiative-driven wildfire changes. In this study, we use a suite of earth system models from the Coupled Model Intercomparison Project 5 with active biogeophysics and biogeochemistry to understand how the vegetation response to high CO2 (CO2 quadrupling) contributes to future changes in wildfire risk across the globe. Across the models, projected CO2 fertilization enhances aboveground biomass (about a 30% leaf area index (LAI) increase averaged across the globe) during the spring and summer months, increasing the availability of wildfire fuel across all biomes. Despite greater LAI, models robustly project widespread reductions in summer season transpiration (about -15% averaged across the globe) in response to reduced stomatal conductance from CO2 physiological forcing. Reduced transpiration warms summer season near surface temperatures and lowers relative humidity across vegetated regions of the mid-to-high latitudes, heightening the risk of wildfire occurrence. However, as transpiration goes down in response to greater plant water use efficiency, a larger fraction of soil water remains in the soil, potentially halting the spread of wildfires in some regions. Given the myriad ways in which the vegetation response to CO2 may alter wildfire risk, and the robustness of the responses across models, an explicit simulation of the wildfire response to CO2-driven vegetation change with the Community Earth System Model will be presented. The results suggest that many atmosphere-centric statistical wildfire metrics do not capture the many processes that will shape future wildfire risk in a high CO2 world and highlight the need for process-based fire modeling.

The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States

PubMed Central

Prestemon, Jeffrey P.; Butry, David T.; Thomas, Douglas S.

2017-01-01

Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires. PMID:28769549

The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States.

PubMed

Prestemon, Jeffrey P; Butry, David T; Thomas, Douglas S

2016-01-01

Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires.

Characterizing Wildfire Regimes and Risk in the USA

NASA Astrophysics Data System (ADS)

Malamud, B. D.; Millington, J. D.; Perry, G. L.

2004-12-01

Over the last decade, high profile wildfires have resulted in numerous fatalities and loss of infrastructure. Wildfires also have a significant impact on climate and ecosystems, with recent authors emphasizing the need for regional-level examinations of wildfire-regime dynamics and change, and the factors driving them. With implications for hazard management, climate studies, and ecosystem research, there is therefore significant interest in appropriate analysis of historical wildfire databases. Insightful studies using wildfire database statistics exist, but are often hampered by the low spatial and/or temporal resolution of their datasets. In this paper, we use a high-resolution dataset consisting of 88,855 USFS wildfires over the time period 1970--2000, and consider wildfire occurrence across the conterminous USA as a function of ecoregion (land units classified by climate, vegetation, and topography), ignition source (anthropogenic vs. lightning), and decade (1970--1979, 1980--1989, 1990--1999). We find that for the conterminous USA (a) wildfires exhibit robust frequency-area power-law behavior in 17 different ecoregions, (b) normalized power-law exponents may be used to compare the scaling of wildfire burned areas between regions, (c) power-law exponents change systematically from east to west, (d) wildfires in 75% of the conterminous USA (particularly the east) have higher power-law exponents for anthropogenic vs. lightning ignition sources, and (e) recurrence intervals for wildfires of a given burned area or larger for each ecoregion can be assessed, allowing for the classification of wildfire regimes for probabilistic hazard estimation in the same vein as is now used for earthquakes. By examining wildfire statistics in a spatially and temporally explicit manner, we are able to present resultant wildfire regime summary statistics and conclusions, along with a probabilistic hazard assessment of wildfire risk at the ecoregion division level across the conterminous USA.

Provision of a wildfire risk map: informing residents in the wildland urban interface.

PubMed

Mozumder, Pallab; Helton, Ryan; Berrens, Robert P

2009-11-01

Wildfires in the wildland urban interface (WUI) are an increasing concern throughout the western United States and elsewhere. WUI communities continue to grow and thus increase the wildfire risk to human lives and property. Information such as a wildfire risk map can inform WUI residents of potential risks and may help to efficiently sort mitigation efforts. This study uses the survey-based contingent valuation (CV) method to examine annual household willingness to pay (WTP) for the provision of a wildfire risk map. Data were collected through a mail survey of the East Mountain WUI area in the State of New Mexico (USA). The integrated empirical approach includes a system of equations that involves joint estimation of WTP values, along with measures of a respondent's risk perception and risk mitigation behavior. The median estimated WTP is around U.S. $12 for the annual wildfire risk map, which covers at least the costs of producing and distributing available risk information. Further, providing a wildfire risk map can help address policy goals emphasizing information gathering and sharing among stakeholders to mitigate the effects of wildfires.

Wildfire Ignitions: A Review of the Science and Recommendations for Empirical Modeling

Treesearch

Jeffrey P. Prestemon; Todd J. Hawbaker; Michael Bowden; John Carpenter; Maureen T. Brooks; Karen L. Abt; Ronda Sutphen; Samuel Scranton

2013-01-01

Deriving from original work under the National Cohesive Wildland Fire Management Strategy completed in 2011, this report summarizes the state of knowledge regarding the underlying causes and the role of wildfire prevention efforts on all major categories of wildfires, including findings from research that have sought to model wildfire occurrences over fine and broad...

Wildfire risk and housing prices: a case study from Colorado Springs.

Treesearch

G.H. Donovan; P.A. Champ; D.T. Butry

2007-01-01

Unlike other natural hazards such as floods, hurricanes, and earthquakes, wildfire risk has not previously been examined using a hedonic property value model. In this article, we estimate a hedonic model based on parcel-level wildfire risk ratings from Colorado Springs. We found that providing homeowners with specific information about the wildfire risk rating of their...

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...

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...

The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California

USGS Publications Warehouse

Richardson, L.A.; Champ, P.A.; Loomis, J.B.

2012-01-01

There is a growing concern that human health impacts from exposure to wildfire smoke are ignored in estimates of monetized damages from wildfires. Current research highlights the need for better data collection and analysis of these impacts. Using unique primary data, this paper quantifies the economic cost of health effects from the largest wildfire in Los Angeles County's modern history. A cost of illness estimate is $9.50 per exposed person per day. However, theory and empirical research consistently find that this measure largely underestimates the true economic cost of health effects from exposure to a pollutant in that it ignores the cost of defensive actions taken as well as disutility. For the first time, the defensive behavior method is applied to calculate the willingness to pay for a reduction in one wildfire smoke induced symptom day, which is estimated to be $84.42 per exposed person per day. ?? 2011.

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.

Climate change beliefs and hazard mitigation behaviors: Homeowners and wildfire risk

Treesearch

Hannah Brenkert-Smith; James R. Meldrum; Patricia A. Champ

2015-01-01

Downscaled climate models provide projections of how climate change may exacerbate the local impacts of natural hazards. The extent to which people facing exacerbated hazard conditions understand or respond to climate-related changes to local hazards has been largely overlooked. In this article, we examine the relationships among climate change beliefs, environmental...

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

USGS Publications Warehouse

Shakesby, Richard A.; Moody, John A.; Martin, Deborah A.; Robichaud, Peter R.

2016-01-01

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.

Assessing the hydrologic response to wildfires in mountainous regions

NASA Astrophysics Data System (ADS)

Havel, Aaron; Tasdighi, Ali; Arabi, Mazdak

2018-04-01

This study aims to understand the hydrologic responses to wildfires in mountainous regions at various spatial scales. The Soil and Water Assessment Tool (SWAT) was used to evaluate the hydrologic responses of the upper Cache la Poudre Watershed in Colorado to the 2012 High Park and Hewlett wildfire events. A baseline SWAT model was established to simulate the hydrology of the study area between the years 2000 and 2014. A procedure involving land use and curve number updating was implemented to assess the effects of wildfires. Application of the proposed procedure provides the ability to simulate the hydrologic response to wildfires seamlessly through mimicking the dynamic of the changes due to wildfires. The wildfire effects on curve numbers were determined comparing the probability distribution of curve numbers after calibrating the model for pre- and post-wildfire conditions. Daily calibration and testing of the model produced very good results. No-wildfire and wildfire scenarios were created and compared to quantify changes in average annual total runoff volume, water budgets, and full streamflow statistics at different spatial scales. At the watershed scale, wildfire conditions showed little impact on the hydrologic responses. However, a runoff increase up to 75 % was observed between the scenarios in sub-watersheds with high burn intensity. Generally, higher surface runoff and decreased subsurface flow were observed under post-wildfire conditions. Flow duration curves developed for burned sub-watersheds using full streamflow statistics showed that less frequent streamflows become greater in magnitude. A linear regression model was developed to assess the relationship between percent burned area and runoff increase in Cache la Poudre Watershed. A strong (R2 > 0.8) and significant (p < 0.001) positive correlation was determined between runoff increase and percentage of burned area upstream. This study showed that the effects of wildfires on hydrology of a watershed are scale-dependent. Also, using full streamflow statistics through application of flow duration curves revealed that the wildfires had a higher effect on peak flows, which may increase the risk of flash floods in post-wildfire conditions.

Predicting wildfire occurrence distribution with spatial point process models and its uncertainty assessment: a case study in the Lake Tahoe Basin, USA

Treesearch

Jian Yang; Peter J. Weisberg; Thomas E. Dilts; E. Louise Loudermilk; Robert M. Scheller; Alison Stanton; Carl Skinner

2015-01-01

Strategic fire and fuel management planning benefits from detailed understanding of how wildfire occurrences are distributed spatially under current climate, and from predictive models of future wildfire occurrence given climate change scenarios. In this study, we fitted historical wildfire occurrence data from 1986 to 2009 to a suite of spatial point process (SPP)...

How wild is your model fire? Constraining WRF-Chem wildfire smoke simulations with satellite observations

NASA Astrophysics Data System (ADS)

Fischer, E. V.; Ford, B.; Lassman, W.; Pierce, J. R.; Pfister, G.; Volckens, J.; Magzamen, S.; Gan, R.

2015-12-01

Exposure to high concentrations of particulate matter (PM) present during acute pollution events is associated with adverse health effects. While many anthropogenic pollution sources are regulated in the United States, emissions from wildfires are difficult to characterize and control. With wildfire frequency and intensity in the western U.S. projected to increase, it is important to more precisely determine the effect that wildfire emissions have on human health, and whether improved forecasts of these air pollution events can mitigate the health risks associated with wildfires. One of the challenges associated with determining health risks associated with wildfire emissions is that the low spatial resolution of surface monitors means that surface measurements may not be representative of a population's exposure, due to steep concentration gradients. To obtain better estimates of ambient exposure levels for health studies, a chemical transport model (CTM) can be used to simulate the evolution of a wildfire plume as it travels over populated regions downwind. Improving the performance of a CTM would allow the development of a new forecasting framework that could better help decision makers estimate and potentially mitigate future health impacts. We use the Weather Research and Forecasting model with online chemistry (WRF-Chem) to simulate wildfire plume evolution. By varying the model resolution, meteorology reanalysis initial conditions, and biomass burning inventories, we are able to explore the sensitivity of model simulations to these various parameters. Satellite observations are used first to evaluate model skill, and then to constrain the model results. These data are then used to estimate population-level exposure, with the aim of better characterizing the effects that wildfire emissions have on human health.

Unraveling the Complexity of Wildland Urban Interface Fires.

PubMed

Mahmoud, Hussam; Chulahwat, Akshat

2018-06-18

Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.

Influence of wildfires on the variability and trend of ozone concentrations in the U.S. Intermountain West

NASA Astrophysics Data System (ADS)

Lu, Xiao; Zhang, Lin; Zhao, Yuanhong; Yue, Xu

2016-04-01

Wildfires are important sources of ozone by emitting large amounts of NOx and NMVOC, main ozone precursors at both global and regional scales. Their influences on ozone in the U.S. Intermountain West have recently received much interest because surface ozone concentrations over that region showed an increasing trend in the past two decades likely due to increasing wildfire emissions in a warming climate. Here we use the Lagrangian particle dispersion model (FLEXPART) as well as the GEOS-Chem chemical transport model to estimate wildfires' contribution on summer (June, July and August; JJA) ozone concentration variations, trends, and extremely high ozone events over the US Intermountain West for the past 22 years (1989-2010). We combine the resident time estimated from the FLEXPART 5-day backward trajectories and a high-resolution fire inventory to define a fire index representing the impact of wildfires on ozone concentration at a particular site for each day of summers 1989-2010. Over 26,000 FLEXPART back-trajectories are conducted for the whole time period and for 13 CASTNet surface monitoring sites. We build a stepwise multiple linear regression (SMLR) model of daily ozone concentrations using fire index and other meteorological variables for each site. The SMLR models explain 53% of the ozone variations (ranging from 12% to 68% for each site). We show that ozone produced from wildfires (calculated from SMLR model) are of high variability at daily scale (ranging from 0.1 ppbv to 20.7 ppbv), but are averaged to lower values of about 0.25-3.5 ppbv for summer mean. We estimate that wildfires magnify inter-annual variations of the regional mean summer ozone for about 32%, compared to the result with wildfires impact excluded from the SMLR model. Wildfire ozone enhancements increase at a rate of 0.04 ppbv per year, accouting for about 20% of the regional summer ozone trend during 1989-2010. Removing wildfires' impact would reduce 35% (46%) of the high-ozone days with measured daily ozone concentrations exceeding 65(75) ppbv, indicating their significant influence on ozone exceptional events. We further compare the wildfire ozone enhancements estimated by the statistical and Lagrangian approach with those estimated from a Eulerian model (GEOS-Chem). Despite highly-correlated results, GEOS-Chem largely overestimates wildfire ozone influences near the source regions and fails to capture ozone production from wildfires at long distance, reflecting deficiencies in current Eulerian models to capture small-scale emissions.

Wildland arson management

Treesearch

Jeffrey P. Prestemon; David T. Butry

2008-01-01

Wildland arson has received scant attention in the resource economics literature, yet is the cause of many large and damaging wildland fires. Research into wildfire management and policy in the United States has been principally concerned with wildfire suppression, fuels treatments, fire science (behavior), and economic efficiency questions. This is unfortunate,...

Use of ultra-high spatial resolution aerial imagery in the estimation of chaparral wildfire fuel loads

Treesearch

Ian T. Schmidt; John F. O' Leary; Douglas A. Stow; Kellie A. Uyeda; Philip Riggan

2016-01-01

Development of methods that more accurately estimate spatial distributions of fuel loads in shrublands allows for improved understanding of ecological processes such as wildfire behavior and postburn recovery. The goal of this study is to develop and test

Automating the Fireshed Assessment Process with ArcGIS

Treesearch

Alan Ager; Klaus Barber

2006-01-01

A library of macros was developed to automate the Fireshed process within ArcGIS. The macros link a number of vegetation simulation and wildfire behavior models (FVS, SVS, FARSITE, and FlamMap) with ESRI geodatabases, desktop software (Access, Excel), and ArcGIS. The macros provide for (1) an interactive linkage between digital imagery, vegetation data, FVS-FFE, and...

Modeling impacts of fire severity on successional trajectories and future fire behavior in Alaskan boreal forests

Treesearch

Jill F. Johnstone; T. Scott Rupp; Mark Olson; David. Verbyla

2011-01-01

Much of the boreal forest in western North America and Alaska experiences frequent, stand-replacing wildfires. Secondary succession after fire initiates most forest stands and variations in fire characteristics can have strong effects on pathways of succession. Variations in surface fire severity that influence whether regenerating forests are dominated by coniferous...

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

A national approach for integrating wildfire simulation modeling into Wildland Urban Interface risk assessments within the United States

Treesearch

Jessica R. Haas; David E. Calkin; Matthew P. Thompson

2013-01-01

Ongoing human development into fire-prone areas contributes to increasing wildfire risk to human life. It is critically important, therefore, to have the ability to characterize wildfire risk to populated places, and to identify geographic areas with relatively high risk. A fundamental component of wildfire risk analysis is establishing the likelihood of wildfire...

Dempster-Shafer theory of evidence: A new approach to spatially model wildfire risk potential in central Chile.

PubMed

González, Cristián; Castillo, Miguel; García-Chevesich, Pablo; Barrios, Juan

2018-02-01

A spatial modeling was applied to Chilean wildfire occurrence, through the Dempster-Shafer's evidence theory and considering the 2006-2010 period for the Valparaiso Region (central Chile), a representative area for this experiment. Results indicate strong spatial correlation between documented wildfires and cumulative evidence maps, resulting in a powerful tool for future wildfire risk prevention programs. Copyright © 2017 Elsevier B.V. All rights reserved.

Disease in a dynamic landscape: host behavior and wildfire reduce amphibian chytrid infection

USGS Publications Warehouse

Hossack, Blake R.; Lowe, Winsor H.; Ware, Joy L.; Corn, Paul Stephen

2013-01-01

Disturbances are often expected to magnify effects of disease, but these effects may depend on the ecology, behavior, and life history of both hosts and pathogens. In many ecosystems, wildfire is the dominant natural disturbance and thus could directly or indirectly affect dynamics of many diseases. To determine how probability of infection by the aquatic fungus Batrachochytrium dendrobatidis (Bd) varies relative to habitat use by individuals, wildfire, and host characteristics, we sampled 404 boreal toads (Anaxyrus boreas boreas) across Glacier National Park, Montana (USA). Bd causes chytridiomycosis, an emerging infectious disease linked with widespread amphibian declines, including the boreal toad. Probability of infection was similar for females and the combined group of males and juveniles. However, only 9% of terrestrial toads were infected compared to >30% of aquatic toads, and toads captured in recently burned areas were half as likely to be infected as toads in unburned areas. We suspect these large differences in infection reflect habitat choices by individuals that affect pathogen exposure and persistence, especially in burned forests where warm, arid conditions could limit Bd growth. Our results show that natural disturbances such as wildfire and the resulting diverse habitats can influence infection across large landscapes, potentially maintaining local refuges and host behaviors that facilitate evolution of disease resistance.

Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.

Post-wildfire recovery of water yield in the Sydney Basin water supply catchments: An assessment of the 2001/2002 wildfires

NASA Astrophysics Data System (ADS)

Heath, J. T.; Chafer, C. J.; van Ogtrop, F. F.; Bishop, T. F. A.

2014-11-01

Wildfire is a recurring event which has been acknowledged by the literature to impact the hydrological cycle of a catchment. Hence, wildfire may have a significant impact on water yield levels within a catchment. In Australia, studies of the effect of fire on water yield have been limited to obligate seeder vegetation communities. These communities regenerate from seed banks in the ground or within woody fruits and are generally activated by fire. In contrast, the Sydney Basin is dominated by obligate resprouter communities. These communities regenerate from fire resistant buds found on the plant and are generally found in regions where wildfire is a regular occurrence. The 2001/2002 wildfires in the Sydney Basin provided an opportunity to investigate the impacts of wildfire on water yield in a number of catchments dominated by obligate resprouting communities. The overall aim of this study was to investigate whether there was a difference in water yield post-wildfire. Four burnt subcatchments and 3 control subcatchments were assessed. A general additive model was calibrated using pre-wildfire data and then used to predict post-wildfire water yield using post-wildfire data. The model errors were analysed and it was found that the errors for all subcatchments showed similar trends for the post-wildfire period. This finding demonstrates that wildfires within the Sydney Basin have no significant medium-term impact on water yield.

An Integrative Review of Empirical Research on Perceptions and Behaviors Related to Prescribed Burning and Wildfire in the United States

NASA Astrophysics Data System (ADS)

Dupéy, Lauren Nicole; Smith, Jordan W.

2018-06-01

Social science research from a variety of disciplines has generated a collective understanding of how individuals prepare for, and respond to, the risks associated with prescribed burning and wildfire. We provide a systematic compilation, review, and quantification of dominant trends in this literature by collecting all empirical research conducted within the U.S. that has addressed perceptions and behaviors surrounding various aspects of prescribed burning and wildfire. We reviewed and quantified this literature using four thematic categories covering: (1) the theory and methods that have been used in previous research; (2) the psychosocial aspects of prescribed burning and wildfire that have been studied; (3) the biophysical characteristics of the fires which have been studied; and (4) the types of fire and management approaches that have been examined. Our integrative review builds on previous literature reviews on the subject by offering new insight on the dominant trends, underutilized approaches, and under-studied topics within each thematic category. For example, we found that a select set of theories (e.g., Protection Motivation Theory, Attribution Theory, etc.) and approaches (e.g., mixed-methods) have only been used sparingly in previous research, even though these theories and approaches can produce insightful results that can readily be implemented by fire-management professionals and decision makers. By identifying trends and gaps in the literature across the thematic categories, we were able to answer four questions that address how future research can make the greatest contribution to our understanding of perceptions and behaviors related to prescribed burning and wildfire.

An Integrative Review of Empirical Research on Perceptions and Behaviors Related to Prescribed Burning and Wildfire in the United States.

PubMed

Dupéy, Lauren Nicole; Smith, Jordan W

2018-06-01

Social science research from a variety of disciplines has generated a collective understanding of how individuals prepare for, and respond to, the risks associated with prescribed burning and wildfire. We provide a systematic compilation, review, and quantification of dominant trends in this literature by collecting all empirical research conducted within the U.S. that has addressed perceptions and behaviors surrounding various aspects of prescribed burning and wildfire. We reviewed and quantified this literature using four thematic categories covering: (1) the theory and methods that have been used in previous research; (2) the psychosocial aspects of prescribed burning and wildfire that have been studied; (3) the biophysical characteristics of the fires which have been studied; and (4) the types of fire and management approaches that have been examined. Our integrative review builds on previous literature reviews on the subject by offering new insight on the dominant trends, underutilized approaches, and under-studied topics within each thematic category. For example, we found that a select set of theories (e.g., Protection Motivation Theory, Attribution Theory, etc.) and approaches (e.g., mixed-methods) have only been used sparingly in previous research, even though these theories and approaches can produce insightful results that can readily be implemented by fire-management professionals and decision makers. By identifying trends and gaps in the literature across the thematic categories, we were able to answer four questions that address how future research can make the greatest contribution to our understanding of perceptions and behaviors related to prescribed burning and wildfire.

Simulating statistics of lightning-induced and man made fires

NASA Astrophysics Data System (ADS)

Krenn, R.; Hergarten, S.

2009-04-01

The frequency-area distributions of forest fires show power-law behavior with scaling exponents α in a quite narrow range, relating wildfire research to the theoretical framework of self-organized criticality. Examples of self-organized critical behavior can be found in computer simulations of simple cellular automata. The established self-organized critical Drossel-Schwabl forest fire model (DS-FFM) is one of the most widespread models in this context. Despite its qualitative agreement with event-size statistics from nature, its applicability is still questioned. Apart from general concerns that the DS-FFM apparently oversimplifies the complex nature of forest dynamics, it significantly overestimates the frequency of large fires. We present a straightforward modification of the model rules that increases the scaling exponent α by approximately 1•3 and brings the simulated event-size statistics close to those observed in nature. In addition, combined simulations of both the original and the modified model predict a dependence of the overall distribution on the ratio of lightning induced and man made fires as well as a difference between their respective event-size statistics. The increase of the scaling exponent with decreasing lightning probability as well as the splitting of the partial distributions are confirmed by the analysis of the Canadian Large Fire Database. As a consequence, lightning induced and man made forest fires cannot be treated separately in wildfire modeling, hazard assessment and forest management.

Modeling the effects of different fuel treatment mosaics on wildfire spread and behavior in a Mediterranean agro-pastoral area.

PubMed

Salis, Michele; Del Giudice, Liliana; Arca, Bachisio; Ager, Alan A; Alcasena-Urdiroz, Fermin; Lozano, Olga; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo

2018-04-15

Wildfire spread and behavior can be limited by fuel treatments, even if their effects can vary according to a number of factors including type, intensity, extension, and spatial arrangement. In this work, we simulated the response of key wildfire exposure metrics to variations in the percentage of treated area, treatment unit size, and spatial arrangement of fuel treatments under different wind intensities. The study was carried out in a fire-prone 625 km 2 agro-pastoral area mostly covered by herbaceous fuels, and located in Northern Sardinia, Italy. We constrained the selection of fuel treatment units to areas covered by specific herbaceous land use classes and low terrain slope (<10%). We treated 2%, 5% and 8% of the landscape area, and identified priority sites to locate the fuel treatment units for all treatment alternatives. The fuel treatment alternatives were designed create diverse mosaics of disconnected treatment units with different sizes (0.5-10 ha, LOW strategy; 10-25 ha, MED strategy; 25-50 ha, LAR strategy); in addition, treatment units in a 100-m buffer around the road network (ROAD strategy) were tested. We assessed pre- and post-treatment wildfire behavior by the Minimum Travel Time (MTT) fire spread algorithm. The simulations replicated a set of southwestern wind speed scenarios (16, 24 and 32 km h -1 ) and the driest fuel moisture conditions observed in the study area. Our results showed that fuel treatments implemented near the existing road network were significantly more efficient than the other alternatives, and this difference was amplified at the highest wind speed. Moreover, the largest treatment unit sizes were the most effective in containing wildfire growth. As expected, increasing the percentage of the landscape treated and reducing wind speed lowered fire exposure profiles for all fuel treatment alternatives, and this was observed at both the landscape scale and for highly valued resources. The methodology presented in this study can support the design and optimization of fuel management programs and policies in agro-pastoral areas of the Mediterranean Basin and herbaceous type landscapes elsewhere, where recurrent grassland fires pose a threat to rural communities, farms and infrastructures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling spatio-temporal wildfire ignition point patterns

Treesearch

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-...

Brief communication: Reaction to fire by savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal: Conceptualization of "fire behavior" and the case for a chimpanzee model.

PubMed

Pruetz, Jill D; LaDuke, Thomas C

2010-04-01

The use and control of fire are uniquely human traits thought to have come about fairly late in the evolution of our lineage, and they are hypothesized to correlate with an increase in intellectual complexity. Given the relatively sophisticated cognitive abilities yet small brain size of living apes compared to humans and even early hominins, observations of wild chimpanzees' reactions to naturally occurring fire can help inform hypotheses about the likely responses of early hominins to fire. We use data on the behavior of savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal during two encounters with wildfires to illuminate the similarities between great apes and humans regarding their reaction to fire. Chimpanzees' close relatedness to our lineage makes them phylogenetically relevant to the study of hominid evolution, and the open, hot and dry environment at Fongoli, similar to the savanna mosaic thought to characterize much of hominid evolution, makes these apes ecologically important as a living primate model as well. Chimpanzees at Fongoli calmly monitor wildfires and change their behavior in anticipation of the fire's movement. The ability to conceptualize the "behavior" of fire may be a synapomorphic trait characterizing the human-chimpanzee clade. If the cognitive underpinnings of fire conceptualization are a primitive hominid trait, hypotheses concerning the origins of the control and use of fire may need revision. We argue that our findings exemplify the importance of using living chimpanzees as models for better understanding human evolution despite recently published suggestions to the contrary. (c) 2009 Wiley-Liss, Inc.

Potential postwildfire debris-flow hazards: a prewildfire evaluation for the Sandia and Manzano Mountains and surrounding areas, central New Mexico

USGS Publications Warehouse

Tillery, Anne C.; Haas, Jessica R.; Miller, Lara W.; Scott, Joe H.; Thompson, Matthew P.

2014-01-01

Wildfire can drastically increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although there is no way to know the exact location, extent, and severity of wildfire, or the subsequent rainfall intensity and duration before it happens, probabilities of fire and debris-flow occurrence for different locations can be estimated with geospatial analysis and modeling efforts. The purpose of this report is to provide information on which watersheds might constitute the most serious, potential, debris-flow hazards in the event of a large-scale wildfire and subsequent rainfall in the Sandia and Manzano Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in the unburned Sandia and Manzano Mountains and surrounding areas were estimated using empirical debris-flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Department of Agriculture Forest Service. The locations of the greatest debris-flow hazards correlate with the areas of steepest slopes and simulated crown-fire behavior. The four subbasins with the highest computed debris-flow probabilities (greater than 98 percent) were all in the Manzano Mountains, two flowing east and two flowing west. Volumes in sixteen subbasins were greater than 50,000 square meters and most of these were in the central Manzanos and the western facing slopes of the Sandias. Five subbasins on the west-facing slopes of the Sandia Mountains, four of which have downstream reaches that lead into the outskirts of the City of Albuquerque, are among subbasins in the 98th percentile of integrated relative debris-flow hazard rankings. The bulk of the remaining subbasins in the 98th percentile of integrated relative debris-flow hazard rankings are located along the highest and steepest slopes of the Manzano Mountains. One of the subbasins is several miles upstream from the community of Tajique and another is several miles upstream from the community of Manzano, both on the eastern slopes of the Manzano Mountains. This prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In northern New Mexico, widespread watershed restoration efforts are being carried out to safeguard vital watersheds against the threat of catastrophic wildfire. This study was initiated to help select ideal locations for the restoration efforts that could have the best return on investment.

Suppression cost forecasts in advance of wildfire seasons

Treesearch

Jeffrey P. Prestemon; Karen Abt; Krista Gebert

2008-01-01

Approaches for forecasting wildfire suppression costs in advance of a wildfire season are demonstrated for two lead times: fall and spring of the current fiscal year (Oct. 1–Sept. 30). Model functional forms are derived from aggregate expressions of a least cost plus net value change model. Empirical estimates of these models are used to generate advance-of-season...

Probabilistic risk models for multiple disturbances: an example of forest insects and wildfires

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Jane L. Hayes

2010-01-01

Building probabilistic risk models for highly random forest disturbances like wildfire and forest insect outbreaks is a challenging. Modeling the interactions among natural disturbances is even more difficult. In the case of wildfire and forest insects, we looked at the probability of a large fire given an insect outbreak and also the incidence of insect outbreaks...

Modeling Tree Mortality Following Wildfire in Pinus ponderosa Forests in the Central Sierra Nevada of California

Treesearch

Jon C. Regelbrugge

1993-01-01

Abstract. We modeled tree mortality occurring two years following wildfire in Pinus ponderosa forests using data from 1275 trees in 25 stands burned during the 1987 Stanislaus Complex fires. We used logistic regression analysis to develop models relating the probability of wildfire-induced mortality with tree size and fire severity for Pinus ponderosa, Calocedrus...

Adaptation to wildfire: A fish story

Treesearch

John Kirkland; Rebecca Flitcroft; Gordon Reeves; Paul Hessburg

2017-01-01

In the Pacific Northwest, native salmon and trout are some of the toughest survivors on the block. Over time, these fish have evolved behavioral adaptations to natural disturbances, and they rely on these disturbances to deliver coarse sediment and wood that become complex stream habitat. Powerful disturbances such as wildfire, postfire landslides, and debris flows may...

Winter grazing decreases wildfire risk, severity, and behavior in semi-arid sagebrush rangelands

USDA-ARS?s Scientific Manuscript database

Wildfires are an ecological and economic risk for many semi-arid rangelands which has resulted in increased pressure for pre-suppression management of fuels. In rangelands, fuel management treatment options are limited by costs. We evaluated winter grazing as a tool to manage fuels and alter fire ...

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

USGS Publications Warehouse

Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

2013-01-01

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

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.

Development of improved wildfire smoke exposure estimates for health studies in the western U.S.

NASA Astrophysics Data System (ADS)

Ivey, C.; Holmes, H.; Loria Salazar, S. M.; Pierce, A.; Liu, C.

2016-12-01

Wildfire smoke exposure is a significant health concern in the western U.S. because large wildfires have increased in size and frequency over the past four years due to drought conditions. The transport phenomena in complex terrain and timing of the wildfire emissions make the smoke plumes difficult to simulate using conventional air quality models. Monitoring data can be used to estimate exposure metrics, but in rural areas the monitoring networks are too sparse to calculate wildfire exposure metrics for the entire population in a region. Satellite retrievals provide global, spatiotemporal air quality information and are used to track pollution plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Particulate matter (PM) exposures can be estimated using columnar aerosol optical depth (AOD), where satellite AOD retrievals serve as a spatial surrogate to simulate surface PM gradients. These exposure models have been successfully used in health effects studies in the eastern U.S. where complex mountainous terrain and surface reflectance do not limit AOD retrival from satellites. Using results from a chemical transport model (CTM) is another effective method to determine spatial gradients of pollutants. However, the CTM does not adequately capture the temporal and spatial distribution of wildfire smoke plumes. By combining the spatiotemporal pollutant fields from both satellite retrievals and CTM results with ground based pollutant observations the spatial wildfire smoke exposure model can be improved. This work will address the challenge of understanding the spatiotemporal distributions of pollutant concentrations to model human exposures of wildfire smoke in regions with complex terrain, where meteorological conditions as well as emission sources significantly influence the spatial distribution of pollutants. The focus will be on developing models to enhance exposure estimates of elevated PM and ozone concentrations from wildfire smoke plumes in the western U.S.

Fish and fire: Post-wildfire sediment dynamics and implications for the viability of trout populations

NASA Astrophysics Data System (ADS)

Murphy, B. P.; Czuba, J. A.; Belmont, P.; Budy, P.; Finch, C.

2017-12-01

Episodic events in steep landscapes, such as wildfire and mass wasting, contribute large pulses of sediment to rivers and can significantly alter the quality and connectivity of fish habitat. Understanding where these sediment inputs occur, how they are transported and processed through the watershed, and their geomorphic effect on the river network is critical to predicting the impact on ecological aquatic communities. The Tushar Mountains of southern Utah experienced a severe wildfire in 2010, resulting in numerous debris flows and the extirpation of trout populations. Following many years of habitat and ecological monitoring in the field, we have developed a modeling framework that links post-wildfire debris flows, fluvial sediment routing, and population ecology in order to evaluate the impact and response of trout to wildfire. First, using the Tushar topographic and wildfire parameters, as well as stochastic precipitation generation, we predict the post-wildfire debris flow probabilities and volumes of mainstem tributaries using the Cannon et al. [2010] model. This produces episodic hillslope sediment inputs, which are delivered to a fluvial sediment, river-network routing model (modified from Czuba et al. [2017]). In this updated model, sediment transport dynamics are driven by time-varying discharge associated with the stochastic precipitation generation, include multiple grain sizes (including gravel), use mixed-size transport equations (Wilcock & Crowe [2003]), and incorporate channel slope adjustments with aggradation and degradation. Finally, with the spatially explicit adjustments in channel bed elevation and grain size, we utilize a new population viability analysis (PVA) model to predict the impact and recovery of fish populations in response to these changes in habitat. Our model provides a generalizable framework for linking physical and ecological models and for evaluating the extirpation risk of isolated fish populations throughout the Intermountain West to the increasing threat of wildfire.

Net benefits of wildfire prevention education efforts

Treesearch

Jeffrey P. Prestemon; David T. Butry; Karen L. Abt; Ronda Sutphen

2010-01-01

Wildfire prevention education efforts involve a variety of methods, including airing public service announcements, distributing brochures, and making presentations, which are intended to reduce the occurrence of certain kinds of wildfires. A Poisson model of preventable Florida wildfires from 2002 to 2007 by fire management region was developed. Controlling for...

Introduction to this special issue on statistics for wildfire processes

Treesearch

Marcia Gumpertz

2009-01-01

This special issue on statistics for wildfire processes brings together foresters, wildfire ecologists, statisticians, mathematicians, and economists. All of these disciplines bring different interests, approaches and expertise to the modeling of wildfire processes. It is not necessarily easy, however, to communicate across disciplines or follow the developments in a...

Iron in the Fire: Searching for Fire's Magnetic Fingerprint using Controlled Heating Experiments, High-Resolution FORCs, IRM Coercivity Spectra, and Low-Temperature Remanence Experiments

NASA Astrophysics Data System (ADS)

Lippert, P. C.; Reiners, P. W.

2014-12-01

Evidence for recent climate-wildfire linkages underscores the need for better understanding of relationships between wildfire and major climate shifts in Earth history, which in turn offers the potential for prognoses for wildfire and human adaptations to it. In particular, what are the links between seasonality and wildfire frequency and severity, and what are the feedbacks between wildfire, landscape evolution, and biogeochemical cycles, particularly the carbon and iron cycles? A key first step in addressing these questions is recovering well-described wildfire records from a variety of paleolandscapes and paleoclimate regimes. Although charcoal and organic biomarkers are commonly used indicators of fire, taphonomic processes and time-consuming analytical preparations often preclude their routine use in some environments and in high-stratigraphic resolution paleowildfire surveying. The phenomenological relationship between fire and magnetic susceptibility can make it a useful surveying tool, but increased magnetic susceptibility in sediments is not unique to fire, and thus limits its diagnostic power. Here we utilize component-specific rock magnetic methods and analytical techniques to identify the rock magnetic fingerprint of wildfire. We use a custom-designed air furnace, a series of iron-free laboratory soils, natural saprolites and soils, and fuels from Arizona Ponderosa pine forests and grasslands to simulate wildfire in a controlled and monitored environment. Soil-ash residues and soil and fuel controls were then characterized using First Order Reversal Curve (FORC) patterns, DC backfield IRM coercivity spectra, low-temperature SIRM demagnetization behavior, and low-temperature cycling of room-temperature SIRM behavior. We will complement these magnetic analyses with high-resolution TEM of magnetic extracts. Here we summarize the systematic changes to sediment magnetism as pyrolitized organic matter is incorporated into artificial and natural soils. These observations help us elucidate the processes and sources responsible for increases in magnetic susceptibility observed in natural burned soils, as well as identify a unique rock magnetic fingerprint for natural wildfire that has the potential to be preserved in sedimentary sequences in the geological record.

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.

Effectiveness of Prescribed Fire as a Fuel Treatment in Californian Coniferous Forests

Treesearch

Nicole M. Vaillant; JoAnn Fites-Kaufman; Scott L. Stephens

2006-01-01

Effective fire suppression for the past century has altered forest structure and increased fuel loads. Prescribed fire as a fuels treatment can reduce wildfire size and severity. This study investigates how prescribed fire affects fuel loads, forest structure, potential fire behavior, and modeled tree mortality at 80th, 90th, and 97.5th percentile fire weather...

Simulation of Long-Term Landscape-Level Fuel Treatment Effects on Large Wildfires

Treesearch

Mark A. Finney; Rob C. Seli; Charles W. McHugh; Alan A. Ager; Berni Bahro; James K. Agee

2006-01-01

A simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of a forest/fuel dynamics simulation module (FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel...

Fuel treatment effectiveness in forests of the upper Atlantic Coastal Plain—an evaluation at two spatial scales

Treesearch

Roger D. Ottmar; Susan J. Prichard

2012-01-01

Fuel treatment effectiveness in Southern forests has been demonstrated using fire behavior modeling and observations of reduced wildfire area and tree damage. However, assessments of treatment effectiveness may be improved with a more rigorous accounting of the fuel characteristics. We present two case studies to introduce a relatively new approach to characterizing...

VISUAL-SEVEIF, a tool for integrating fire behavior simulation and economic evaluation of the impact of Wildfires

Treesearch

Francisco Rodríguez y Silva; Juan Ramón Molina Martínez; Miguel Ángel Herrera Machuca; Jesús Mª Rodríguez Leal

2013-01-01

Progress made in recent years in fire science, particularly as applied to forest fire protection, coupled with the increased power offered by mathematical processors integrated into computers, has led to important developments in the field of dynamic and static simulation of forest fires. Furthermore, and similarly, econometric models applied to economic...

In ecoregions across western USA streamflow increases during post-wildfire recovery

NASA Astrophysics Data System (ADS)

Wine, Michael L.; Cadol, Daniel; Makhnin, Oleg

2018-01-01

Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%-14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%-370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

Impact of wildfires on ozone exceptional events in the Western u.s.

PubMed

Jaffe, Daniel A; Wigder, Nicole; Downey, Nicole; Pfister, Gabriele; Boynard, Anne; Reid, Stephen B

2013-10-01

Wildfires generate substantial emissions of nitrogen oxides (NOx) and volatile organic compounds (VOCs). As such, wildfires contribute to elevated ozone (O3) in the atmosphere. However, there is a large amount of variability in the emissions of O3 precursors and the amount of O3 produced between fires. There is also significant interannual variability as seen in median O3, organic carbon and satellite derived carbon monoxide mixing ratios in the western U.S. To better understand O3 produced from wildfires, we developed a statistical model that estimates the maximum daily 8 h average (MDA8) O3 as a function of several meteorological and temporal variables for three urban areas in the western U.S.: Salt Lake City, UT; Boise, ID; and Reno, NV. The model is developed using data from June-September 2000-2012. For these three locations, the statistical model can explain 60, 52, and 27% of the variability in daily MDA8. The Statistical Model Residual (SMR) can give information on additional sources of O3 that are not explained by the usual meteorological pattern. Several possible O3 sources can explain high SMR values on any given day. We examine several cases with high SMR that are due to wildfire influence. The first case considered is for Reno in June 2008 when the MDA8 reached 82 ppbv. The wildfire influence for this episode is supported by PM concentrations, the known location of wildfires at the time and simulations with the Weather and Research Forecasting Model with Chemistry (WRF-Chem) which indicates transport to Reno from large fires burning in California. The contribution to the MDA8 in Reno from the California wildfires is estimated to be 26 ppbv, based on the SMR, and 60 ppbv, based on WRF-Chem. The WRF-Chem model also indicates an important role for peroxyacetyl nitrate (PAN) in producing O3 during transport from the California wildfires. We hypothesize that enhancements in PAN due to wildfire emissions may lead to regional enhancements in O3 during high fire years. The second case is for the Salt Lake City (SLC) region for August 2012. During this period the MDA8 reached 83 ppbv and the SMR suggests a wildfire contribution of 19 ppbv to the MDA8. The wildfire influence is supported by PM2.5 data, the known location of wildfires at the time, HYSPLIT dispersion modeling that indicates transport from fires in Idaho, and results from the CMAQ model that confirm the fire impacts. Concentrations of PM2.5 and O3 are enhanced during this period, but overall there is a poor relationship between them, which is consistent with the complexities in the secondary production of O3. A third case looks at high MDA8 in Boise, ID, during July 2012 and reaches similar conclusions. These results support the use of statistical modeling as a tool to quantify the influence from wildfires on urban O3 concentrations.

On The Usage Of Fire Smoke Emissions In An Air Quality Forecasting System To Reduce Particular Matter Forecasting Error

NASA Astrophysics Data System (ADS)

Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; DiMego, G.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

2016-12-01

Wildfires contribute to air quality problems not only towards primary emissions of particular matters (PM) but also emitted ozone precursor gases that can lead to elevated ozone concentration. Wildfires are unpredictable and can be ignited by natural causes such as lightning or accidently by human negligent behavior such as live cigarette. Although wildfire impacts on the air quality can be studied by collecting fire information after events, it is extremely difficult to predict future occurrence and behavior of wildfires for real-time air quality forecasts. Because of the time constraints of operational air quality forecasting, assumption of future day's fire behavior often have to be made based on observed fire information in the past. The United States (U.S.) NOAA/NWS built the National Air Quality Forecast Capability (NAQFC) based on the U.S. EPA CMAQ to provide air quality forecast guidance (prediction) publicly. State and local forecasters use the forecast guidance to issue air quality alerts in their area. The NAQFC fine particulates (PM2.5) prediction includes emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and fires. The fire emission input to the NAQFC is derived from the NOAA NESDIS HMS fire and smoke detection product and the emission module of the US Forest Service BlueSky Smoke Modeling Framework. This study focuses on the error estimation of NAQFC PM2.5 predictions resulting from fire emissions. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that present operational NAQFC fire emissions assumption can lead to a huge error in PM2.5 prediction as fire emissions are sometimes placed at wrong location and time. This PM2.5 prediction error can be propagated from the fire source in the Northwest U.S. to downstream areas as far as the Southeast U.S. From this study, a new procedure has been identified to minimize the aforementioned error. An additional 24 hours reanalysis-run of NAQFC using same-day observed fire emission are being tested. Preliminary results have shown that this procedure greatly improves the PM2.5 predictions at both nearby and downstream areas from fire sources. The 24 hours reanalysis-run is critical and necessary especially during extreme fire events to provide better PM2.5 predictions.

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.

Climate change and growth scenarios for California wildfire

Treesearch

A.L. Westerling; B.P. Bryant; H.K. Preisler; T.P. Holmes; H.G. Hildalgo; T. Das; S.R. Shrestha

2011-01-01

Large wildfire occurrence and burned area are modeled using hydroclimate and landsurface characteristics under a range of future climate and development scenarios. The range of uncertainty for future wildfire regimes is analyzed over two emissions pathways (the Special Report on Emissions Scenarios [SRES] A2 and B1 scenarios); three global climate models (Centre...

A coupled modeling approach to assess the impact of fuel treatments on post-wildfire runoff and erosion

USDA-ARS?s Scientific Manuscript database

The hydrological consequences of wildfires are some of the most significant and long-lasting effects. Since wildfire severity impacts post-fire hydrological response, fuel treatments can be a useful tool for land managers to moderate this response. However, current models focus on only one aspect of...

Development and application of a geospatial wildfire exposure and risk calculation tool

Treesearch

Matthew P. Thompson; Jessica R. Haas; Julie W. Gilbertson-Day; Joe H. Scott; Paul Langowski; Elise Bowne; David E. Calkin

2015-01-01

Applying wildfire risk assessment models can inform investments in loss mitigation and landscape restoration, and can be used to monitor spatiotemporal trends in risk. Assessing wildfire risk entails the integration of fire modeling outputs, maps of highly valued resources and assets (HVRAs), characterization of fire effects, and articulation of relative importance...

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

Probabilistic assessment of wildfire hazard and municipal watershed exposure

Treesearch

Joe Scott; Don Helmbrecht; Matthew P. Thompson; David E. Calkin; Kate Marcille

2012-01-01

The occurrence of wildfires within municipal watersheds can result in significant impacts to water quality and ultimately human health and safety. In this paper, we illustrate the application of geospatial analysis and burn probability modeling to assess the exposure of municipal watersheds to wildfire. Our assessment of wildfire exposure consists of two primary...

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy

Treesearch

Michele Salis; Alan A. Ager; Fermin J. Alcasena; Bachisio Arca; Mark A. Finney; Grazia Pellizzaro; Donatella Spano

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn...

Economic optimisation of wildfire intervention activities

Treesearch

David T. Butry; Jeffrey P. Prestemon; Karen L. Abt; Ronda Sutphen

2010-01-01

We describe how two important tools of wildfire management, wildfire prevention education and prescribed fire for fuels management, can be coordinated to minimise the combination of management costs and expected societal losses resulting from wildland fire. We present a long-run model that accounts for the dynamics of wildfire, the effects of fuels management on...

Modeling the impacts of wildfire on runoff and pollutant transport from coastal watersheds to the nearshore environment.

PubMed

Morrison, Katherine D; Kolden, Crystal A

2015-03-15

Wildfire is a common disturbance that can significantly alter vegetation in watersheds and affect the rate of sediment and nutrient transport to adjacent nearshore oceanic environments. Changes in runoff resulting from heterogeneous wildfire effects are not well-understood due to both limitations in the field measurement of runoff and temporally-limited spatial data available to parameterize runoff models. We apply replicable, scalable methods for modeling wildfire impacts on sediment and nonpoint source pollutant export into the nearshore environment, and assess relationships between wildfire severity and runoff. Nonpoint source pollutants were modeled using a GIS-based empirical deterministic model parameterized with multi-year land cover data to quantify fire-induced increases in transport to the nearshore environment. Results indicate post-fire concentration increases in phosphorus by 161 percent, sediments by 350 percent and total suspended solids (TSS) by 53 percent above pre-fire years. Higher wildfire severity was associated with the greater increase in exports of pollutants and sediment to the nearshore environment, primarily resulting from the conversion of forest and shrubland to grassland. This suggests that increasing wildfire severity with climate change will increase potential negative impacts to adjacent marine ecosystems. The approach used is replicable and can be utilized to assess the effects of other types of land cover change at landscape scales. It also provides a planning and prioritization framework for management activities associated with wildfire, including suppression, thinning, and post-fire rehabilitation, allowing for quantification of potential negative impacts to the nearshore environment in coastal basins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest.

Treesearch

Mark P. Waldrop; Jennifer W. Harden

2008-01-01

Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or...

The effects of thinning and similar stand treatments on fire behavior in Western forests.

Treesearch

Russell T. Graham; Alan E. Harvey; Theresa B. Jain; Jonalea R. Tonn

1999-01-01

In the West, thinning and partial cuttings are being considered for treating millions of forested acres that are overstocked and prone to wildfire. The objectives of these treatments include tree growth redistribution, tree species regulation, timber harvest, wildlife habitat improvement, and wildfire-hazard reduction. Depending on the forest type and its structure,...

Spatial optimization of the pattern of fuel management activities and subsequent effects on simulated wildfires

Treesearch

Young-Hwan Kim; Pete Bettinger; Mark Finney

2009-01-01

Methods for scheduling forest management activities in a spatial pattern (dispersed, clumped, random, and regular) are presented, with the intent to examine the effects of placement of activities on resulting simulated wildfire behavior. Both operational and fuel reduction management prescriptions are examined, and a heuristic was employed to schedule the activities....

Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands

Treesearch

Jian Yang; Hong S. He; Stephen R. Shifley

2008-01-01

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of...

Microbial response to high severity wildfire in the southwest United States

Treesearch

Steven T. Overby; Stephen C. Hart; Gregory S. Newman; Dana Erickson

2006-01-01

Southwest United States ponderosa pine (Pinus ponderosa Dougl. ex Laws) ecosystems have received great attention due to fuel conditions that increase the likelihood of large-scale wildfires with severe fire behavior. The fire season of 2002 demonstrated these extreme fuel load conditions with the largest fires in southwest history. The Jemez District of the Santa Fe...

Ecological risk assessment to support fuels treatment project decisions

Treesearch

Jay O' Laughlin

2010-01-01

Risk is a combined statement of the probability that something of value will be damaged and some measure of the damage’s adverse effect. Wildfires burning in the uncharacteristic fuel conditions now typical throughout the Western United States can damage ecosystems and adversely affect environmental conditions. Wildfire behavior can be modified by prefire fuel...

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

PubMed

Salis, Michele; Ager, Alan A; Alcasena, Fermin J; Arca, Bachisio; Finney, Mark A; Pellizzaro, Grazia; Spano, Donatella

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas.

PubMed

Lozano, Olga M; Salis, Michele; Ager, Alan A; Arca, Bachisio; Alcasena, Fermin J; Monteiro, Antonio T; Finney, Mark A; Del Giudice, Liliana; Scoccimarro, Enrico; Spano, Donatella

2017-10-01

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041-2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities. © 2016 Society for Risk Analysis.

Globally-Applicable Predictive Wildfire Model   a Temporal-Spatial GIS Based Risk Analysis Using Data Driven Fuzzy Logic Functions

NASA Astrophysics Data System (ADS)

van den Dool, G.

2017-11-01

This study (van den Dool, 2017) is a proof of concept for a global predictive wildfire model, in which the temporal-spatial characteristics of wildfires are placed in a Geographical Information System (GIS), and the risk analysis is based on data-driven fuzzy logic functions. The data sources used in this model are available as global datasets, but subdivided into three pilot areas: North America (California/Nevada), Europe (Spain), and Asia (Mongolia), and are downscaled to the highest resolution (3-arc second). The GIS is constructed around three themes: topography, fuel availability and climate. From the topographical data, six derived sub-themes are created and converted to a fuzzy membership based on the catchment area statistics. The fuel availability score is a composite of four data layers: land cover, wood loads, biomass, biovolumes. As input for the climatological sub-model reanalysed daily averaged, weather-related data is used, which is accumulated to a global weekly time-window (to account for the uncertainty within the climatological model) and forms the temporal component of the model. The final product is a wildfire risk score (from 0 to 1) by week, representing the average wildfire risk in an area. To compute the potential wildfire risk the sub-models are combined usinga Multi-Criteria Approach, and the model results are validated against the area under the Receiver Operating Characteristic curve.

Measuring the effect of fuel treatments on forest carbon using landscape risk analysis

Treesearch

A.A. Ager; M.A. Finney; A. McMahan; J. Carthcart

2010-01-01

Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon...

Application of wildfire simulation models for risk analysis

Treesearch

Alan A. Ager; Mark A. Finney

2009-01-01

Wildfire simulation models are being widely used by fire and fuels specialists in the U.S. to support tactical and strategic decisions related to the mitigation of wildfire risk. Much of this application has resulted from the development of a minimum travel time (MTT) fire spread algorithm (M. Finney) that makes it computationally feasible to simulate thousands of...

Examining Atmospheric and Ecological Drivers of Wildfires, Modeling Wildfire Occurrence in the Southwest United States, and Using Atmospheric Sounding Observations to Verify National Weather Service Spot Forecasts

NASA Astrophysics Data System (ADS)

Nauslar, Nicholas J.

This dissertation is comprised of three different papers that all pertain to wildland fire applications. The first paper performs a verification analysis on mixing height, transport winds, and Haines Index from National Weather Service spot forecasts across the United States. The final two papers, which are closely related, examine atmospheric and ecological drivers of wildfire for the Southwest Area (SWA) (Arizona, New Mexico, west Texas, and Oklahoma panhandle) to better equip operational fire meteorologists and managers to make informed decisions on wildfire potential in this region. The verification analysis here utilizes NWS spot forecasts of mixing height, transport winds and Haines Index from 2009-2013 issued for a location within 50 km of an upper sounding location and valid for the day of the fire event. Mixing height was calculated from the 0000 UTC sounding via the Stull, Holzworth, and Richardson methods. Transport wind speeds were determined by averaging the wind speed through the boundary layer as determined by the three mixing height methods from the 0000 UTC sounding. Haines Index was calculated at low, mid, and high elevation based on the elevation of the sounding and spot forecast locations. Mixing height forecasts exhibited large mean absolute errors and biased towards over forecasting. Forecasts of transport wind speeds and Haines Index outperformed mixing height forecasts with smaller errors relative to their respective means. The rainfall and lightning associated with the North American Monsoon (NAM) can vary greatly intra- and inter-annually and has a large impact on wildfire activity across the SWA by igniting or suppressing wildfires. NAM onset thresholds and subsequent dates are determined for the SWA and each Predictive Service Area (PSA), which are sub-regions used by operational fire meteorologists to predict wildfire potential within the SWA, April through September from 1995-2013. Various wildfire activity thresholds using the number of wildfires and large wildfires identified days or time periods with increased wildfire activity for each PSA and the SWA. Self-organizing maps utilizing 500 and 700 hPa geopotential heights and precipitable water were implemented to identify atmospheric patterns contributing to the NAM onset and busy days/periods for each PSA and the SWA. Resulting SOM map types also showed the transition to, during, and from the NAM. Northward and eastward displacements of the subtropical ridge (i.e., four-corners high) over the SWA were associated with NAM onset, and a suppressed subtropical ridge and breakdown of the subtropical ridge map types over the SWA were associated with increased wildfire activity. We implemented boosted regression trees (BRT) to model wildfire occurrence for all and large wildfires for different wildfire types (i.e., lightning, human) across the SWA by PSA. BRT models for all wildfires demonstrated relatively small mean and mean absolute errors and showed better predictability on days with wildfires. Cross-validated accuracy assessments for large wildfires demonstrated the ability to discriminate between large wildfire and non-large wildfire days across all wildfire types. Measurements describing fuel conditions (i.e., 100 and 1000-hour dead fuel moisture, energy release component) were the most important predictors when considering all wildfire types and sizes. However, a combination of fuels and atmospheric predictors (i.e., lightning, temperature) proved most predictive for large wildfire occurrence, and the number of relevant predictors increases for large wildfires indicating more conditions need to align to support large wildfires.

Assessing exposure of human and ecological values to wildfire in Sardinia, Italy

Treesearch

Michele Salis; Alan A. Ager; Bachisio Arca; Mark A. Finney; Valentina Bacciu; Pierpaolo Duce; Donatella Spano

2012-01-01

We used simulation modelling to analyze spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational values and highly valued agricultural areas that are increasingly being threatened by severe wildfires. Historical fire data and wildfire...

Places where wildfire potential and social vulnerability coincide in the coterminous United States

Treesearch

Gabriel Wigtil; Roger B. Hammer; Jeffrey D. Kline; Miranda H. Mockrin; Susan I. Stewart; Daniel Roper; Volker C. Radeloff

2016-01-01

The hazards-of-place model posits that vulnerability to environmental hazards depends on both biophysical and social factors. Biophysical factors determine where wildfire potential is elevated, whereas social factors determine where and how people are affected by wildfire. We evaluated place vulnerability to wildfire hazards in the coterminous US. We developed...

Recreational use management and wildfires in Southern California: Using GIS and visual landscape simulation models for economic assessment

Treesearch

Daniel Moya; Armando González-Cabán; José J. Sánchez; José de la Heras

2013-01-01

Recent advances in fire behavior are conforming strategies for forest management in nonindustrial private and public forests in the western United States. The strategy developed should include identifying the most cost-effective ways for allocating fire management budgets. In recreational areas, visitors’ opinion should be included in forest planning decisions and...

A fuel treatment reduces potential fire severity and increases suppression efficiency in a Sierran mixed conifer forest

Treesearch

Jason J. Moghaddas

2006-01-01

Fuel treatments are being widely implemented on public and private lands across the western U.S. While scientists and managers have an understanding of how fuel treatments can modify potential fire behavior under modeled conditions, there is limited information on how treatments perform under real wildfire conditions in Sierran mixed conifer forests. The Bell Fire...

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific.

PubMed

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires.

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific

PubMed Central

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires. PMID:25691965

Use of Wildfire Smoke Forcasting Model to Mitigate Burden on a Population's Health and Wellbeing Presentation for International Society of Environmental Epidemiology meeting

EPA Science Inventory

Use of Wildfire Smoke Forecasting Model to Mitigate Burden on a Population’s Health and Wellbeing Ana G. Rappold, Neal Fann, Wayne E. Cascio, Robert B. Devlin, David Diaz-Sanchez Background Wildfires are a major source of fine particular matter and other air pollutants as...

The ability of winter grazing to reduce wildfire size, intensity, and fire-induced plant mortality was not demonstrated: A comment on Davies et al. (2015)

EPA Science Inventory

A recent study by Davies et al. sought to test whether winter grazing could reduce wildfire size, fire behavior metrics, and fire-induced plant mortality in shrub-grasslands. The authors concluded that ungrazed rangelands may experience more fire-induced mortality of native peren...

The ability of winter grazing to reduce wildfire size, intensity, and fire-induced plant mortality was not demonstrated: a comment on Davies et al. (2015)

USDA-ARS?s Scientific Manuscript database

A recent study by Davies et al. sought to test whether winter grazing could reduce wildfire size, fire behavior and intensity metrics, and fire-induced plant mortality in shrub-grasslands. The authors concluded that ungrazed rangelands may experience fire-induced mortality of native perennial bunchg...

Variability and persistence of post-fire biological legacies in jack pine-dominated ecosystems of northern Lower Michigan

Treesearch

Daniel Kashian; Gregory Corace; Lindsey Shartell; Deahn M. Donner; Philip Huber

2011-01-01

Stand-replacing wildfires have historically shaped the forest structure of dry, sandy jack pine-dominated ecosystems at stand and landscape scales in northern Lower Michigan. Unique fire behavior during large wildfire events often preserves long strips of unburned trees arranged perpendicular to the direction of fire spread. These biological legacies create...

Science basis for changing forest structure to modify wildfire behavior and severity

Treesearch

Russell T. Graham; Sarah McCaffrey; Theresa B. Jain

2004-01-01

Fire, other disturbances, physical setting, weather, and climate shape the structure and function of forests throughout the Western United States. More than 80 years of fire research have shown that physical setting, fuels, and weather combine to determine wildfire intensity (the rate at which it consumes fuel) and severity (the effect fire has on vegetation, soils,...

Variability and persistence of post-fire biological legacies in jack pine-dominated ecosystems of northern Lower Michigan

Treesearch

Daniel M. Kashian; R. Gregory Corace; Lindsey M. Shartell; Deahn M. Donner; Philip W. Huber

2012-01-01

On the dry, flat, jack pine (Pinus banksiana Lamb.)-dominated ecosystems of the northern Lake States and eastern Canada, wildfire behavior often produces narrow, remnant strips of unburned trees that provide heterogeneity on a landscape historically shaped by stand-replacing wildfires. We used landscape metrics to analyze a chronosequence of aerial...

The Relationship between Wildfires and Tourist Behaviors in Florida: An Exploratory Study

Treesearch

Brijesh Thapa; Stephen M. Holland; James D. Absher

2004-01-01

Introduction Florida is a popular national and international tourist destination with 74.3 million visitors in 2000, and slightly more than half of these visited natural and protected areas (Visit Florida, 2001). However, in recent years, notably in 1998 and 2001, drought conditions have led to wildfires that affected large parts of the state, lead to smoke closure of...

Advances in threat assessment and their application to forest and rangeland management—Volume 2

Treesearch

H. Michael Rauscher; Yasmeen Sands; Danny C. Lee; Jerome S. Beatty

2010-01-01

Risk is a combined statement of the probability that something of value will be damaged and some measure of the damage’s adverse effect. Wildfires burning in the uncharacteristic fuel conditions now typical throughout the Western United States can damage ecosystems and adversely affect environmental conditions. Wildfire behavior can be modified by prefire fuel...

The role of risk perceptions in the risk mitigation process: The case of wildfire in high risk communities

Treesearch

Wade E. Martin; Ingrid M. Martin; Brian Kent

2009-01-01

An important policy question receiving considerable attention concerns the risk perception-risk mitigation process that guides how individuals choose to address natural hazard risks. This question is considered in the context of wildfire. We analyze the factors that influence risk reduction behaviors by homeowners living in the wildland-urban interface. The factors...

Projecting wildfire area burned in the south-eastern United States, 2011-60

Treesearch

Jeffrey P. Prestemon; Uma Shankar; Aijun Xiu; K. Talgo; D. Yang; Ernest Dixon; Donald McKenzie; Karen L. Abt

2016-01-01

Future changes in society and climate are expected to affect wildfire activity in the south-eastern United States. The objective of this research was to understand how changes in both climate and society may affect wildfire in the coming decades.We estimated a three-stage statistical model of wildfire area burned by ecoregion province for lightning and human causes (...

Incorporating fine-scale drought information into an eastern US wildfire hazard model

Treesearch

Matthew P. Peters; Louis R. Iverson

2017-01-01

Wildfires in the eastern United States are generally caused by humans in locations where human development and natural vegetation intermingle, e.g. the wildland–urban interface (WUI). Knowing where wildfire hazards are elevated across the forested landscape may help land managers and property owners plan or allocate resources for potential wildfire threats. In an...

Wildfire smoke exposure and human health: Significant gaps in research for a growing public health issue.

PubMed

Black, Carolyn; Tesfaigzi, Yohannes; Bassein, Jed A; Miller, Lisa A

2017-10-01

Understanding the effect of wildfire smoke exposure on human health represents a unique interdisciplinary challenge to the scientific community. Population health studies indicate that wildfire smoke is a risk to human health and increases the healthcare burden of smoke-impacted areas. However, wildfire smoke composition is complex and dynamic, making characterization and modeling difficult. Furthermore, current efforts to study the effect of wildfire smoke are limited by availability of air quality measures and inconsistent air quality reporting among researchers. To help address these issues, we conducted a substantive review of wildfire smoke effects on population health, wildfire smoke exposure in occupational health, and experimental wood smoke exposure. Our goal was to evaluate the current literature on wildfire smoke and highlight important gaps in research. In particular we emphasize long-term health effects of wildfire smoke, recovery following wildfire smoke exposure, and health consequences of exposure in children. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of wildfire on catchment runoff response: a modeling approach to detect changes in snow-dominated forested catchments

Treesearch

Jan Seibert; Jeffrey J. McDonnell; Richard D. Woodsmith

2010-01-01

Wildfire is an important disturbance affecting hydrological processes through alteration of vegetation cover and soil characteristics. The effects of fire on hydrological systems at the catchment scale are not well known, largely because site specific data from both before and after wildfire are rare. In this study a modelling approach was employed for change detection...

An analysis of wildfire prevention

NASA Technical Reports Server (NTRS)

Heineke, J. M.; Weissenberger, S.

1974-01-01

A model of the production of wildfire ignitions and damages is developed and used to determine wildland activity-regulation decisions, which minimize total expected cost-plus-loss due to wildfires. In this context, the implications of various policy decisions are considered. The resulting decision rules take a form that makes it possible for existing wildfire management agencies to readily adopt them upon collection of the required data.

Using field data to assess model predictions of surface and ground fuel consumption by wildfire in coniferous forests of California

Treesearch

Jamie Lydersen; Brandon M. Collins; Carol Ewell; Alicia Reiner; Jo Ann Fites; Christopher Dow; Patrick Gonzalez; David Saah; John Battles

2014-01-01

Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire...

Wildland fire smoke and human health.

PubMed

Cascio, Wayne E

2018-05-15

The natural cycle of landscape fire maintains the ecological health of the land, yet adverse health effects associated with exposure to emissions from wildfire produce public health and clinical challenges. Systematic reviews conclude that a positive association exists between exposure to wildfire smoke or wildfire particulate matter (PM 2.5 ) and all-cause mortality and respiratory morbidity. Respiratory morbidity includes asthma, chronic obstructive pulmonary disease (COPD), bronchitis and pneumonia. The epidemiological data linking wildfire smoke exposure to cardiovascular mortality and morbidity is mixed, and inconclusive. More studies are needed to define the risk for common and costly clinical cardiovascular outcomes. Susceptible populations include people with respiratory and possibly cardiovascular diseases, middle-aged and older adults, children, pregnant women and the fetus. The increasing frequency of large wildland fires, the expansion of the wildland-urban interface, the area between unoccupied land and human development; and an increasing and aging U.S. population are increasing the number of people at-risk from wildfire smoke, thus highlighting the necessity for broadening stakeholder cooperation to address the health effects of wildfire. While much is known, many questions remain and require further population-based, clinical and occupational health research. Health effects measured over much wider geographical areas and for longer periods time will better define the risk for adverse health outcomes, identify the sensitive populations and assess the influence of social factors on the relationship between exposure and health outcomes. Improving exposure models and access to large clinical databases foreshadow improved risk analysis facilitating more effective risk management. Fuel and smoke management remains an important component for protecting population health. Improved smoke forecasting and translation of environmental health science into communication of actionable information for use by public health officials, healthcare professionals and the public is needed to motivate behaviors that lower exposure and protect public health, particularly among those at high risk. Published by Elsevier B.V.

Wildfire Danger Potential in California

NASA Astrophysics Data System (ADS)

Kafatos, M.; Myoung, B.; Kim, S. H.; Fujioka, F. M.; Kim, J.

2015-12-01

Wildfires are an important concern in California (CA) which is characterized by the semi-arid to arid climate and vegetation types. Highly variable winter precipitation and extended hot and dry warm season in the region challenge an effective strategic fire management. Climatologically, the fire season which is based on live fuel moisture (LFM) of generally below 80% in Los Angeles County spans 4 months from mid-July to mid-November, but it has lasted over 7 months in the past several years. This behavior is primarily due to the ongoing drought in CA during the last decade, which is responsible for frequent outbreaks of severe wildfires in the region. Despite their importance, scientific advances for the recent changes in wildfire risk and effective assessments of wildfire risk are lacking. In the present study, we show impacts of large-scale atmospheric circulations on an early start and then extended length of fire seasons. For example, the strong relationships of North Atlantic Oscillation (NAO) with springtime temperature and precipitation in the SWUS that was recently revealed by our team members have led to an examination of the possible impact of NAO on wildfire danger in the spring. Our results show that the abnormally warm and dry spring conditions associated with positive NAO phases can cause an early start of a fire season and high fire risks throughout the summer and fall. For an effective fire danger assessment, we have tested the capability of satellite vegetation indices (VIs) in replicating in situ LFM of Southern CA chaparral ecosystems by 1) comparing seasonal/interannual characteristics of in-situ LFM with VIs and 2) developing an empirical model function of LFM. Unlike previous studies attempting a point-to-point comparison, we attempt to examine the LFM relationship with VIs averaged over different areal coverage with chamise-dominant grids (i.e., 0.5 km to 25 km radius circles). Lastly, we discuss implications of the results for fire danger assessment and prediction.

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

Ozone from Wildfires: Peering through the Smog

NASA Astrophysics Data System (ADS)

Jaffe, D. A.; Baylon, P.; Wigder, N. L.; Collier, S.; Zhou, S.; Zhang, Q.; Alvarado, M. J.

2014-12-01

In the western US, many areas are near the current air quality standard for O3. Yet there is substantial inter-annual variability (IAV) in the number of days that exceed the O3 air quality threshold (currently 75 ppbv for an 8-hour average). We propose that wildfires are the dominant cause for this IAV. However there are large uncertainties around O3 production from wildfires due to numerous complicating factors. Ozone formation in wildfire plumes differs substantially from urban O3 production in several ways: substantial variations in the emissions, much larger aerosol loadings, a much greater variety of reactive and oxygenated VOCs, rapid and substantial formation of PAN and very different sources of HOx in the plume. These factors make it challenging to model wildfire impacts on photochemistry in the usual way. In this presentation we will show examples of three common situations based on data from the Mt. Bachelor Observatory: Rapid O3 formation (within one day) in a wildfire plume. Slow, but substantial, O3 formation (over days to a week) in a wildfire plume. No detectable O3 formation in a wildfire plume. We will interpret these results with respect to the observed NOy mixing ratios, the photochemical environment, the combustion efficiency, the plume transport and other factors and suggest some key experiments and modeling studies that can help further our understanding of wildfire O3 production.

Differences in human versus lightning fires between urban and rural areas of the boreal forest in interior Alaska

USGS Publications Warehouse

Calef, Monika; Varvak, Anna; McGuire, A. David

2017-01-01

In western North America, the carbon-rich boreal forest is experiencing warmer temperatures, drier conditions and larger and more frequent wildfires. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools for understanding future conditions but they are based on regional generalizations of wildfire behavior and weather that do not adequately account for the complexity of human–fire interactions. To achieve a better understanding of the intensity of human influence on fires in this sparsely populated area and to quantify differences between human and lightning fires, we analyzed fires by both ignition types in regard to human proximity in urban (the Fairbanks subregion) and rural areas of interior Alaska using spatial (Geographic Information Systems) and quantitative analysis methods. We found substantial differences in drivers of wildfire: while increases in fire ignitions and area burned were caused by lightning in rural interior Alaska, in the Fairbanks subregion these increases were due to human fires, especially in the wildland urban interface. Lightning fires are starting earlier and fires are burning longer, which is much more pronounced in the Fairbanks subregion than in rural areas. Human fires differed from lightning fires in several ways: they started closer to settlements and highways, burned for a shorter duration, were concentrated in the Fairbanks subregion, and often occurred outside the brief seasonal window for lightning fires. This study provides important insights that improve our understanding of the direct human influence on recently observed changes in wildfire regime with implications for both fire modeling and fire management.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, K.; Ager, A.; Finney, M.; Athanasis, N.; Palaiologou, P.; Vasilakos, C.

2015-10-01

A Web-GIS wildfire prevention and management platform (AEGIS) was developed as an integrated and easy-to-use decision support tool (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing access to information that is essential for wildfire management. Databases were created with spatial and non-spatial data to support key system functionalities. Updated land use/land cover maps were produced by combining field inventory data with high resolution multispectral satellite images (RapidEye) to be used as inputs in fire propagation modeling with the Minimum Travel Time algorithm. End users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations; i.e. single-fire propagations, conditional burn probabilities and at the landscape-level, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANN) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps produced an integrated output map for fire danger prediction. The system also incorporates weather measurements from remote automatic weather stations and weather forecast maps. The structure of the algorithms relies on parallel processing techniques (i.e. High Performance Computing and Cloud Computing) that ensure computational power and speed. All AEGIS functionalities are accessible to authorized end users through a web-based graphical user interface. An innovative mobile application, AEGIS App, acts as a complementary tool to the web-based version of the system.

Post-fire logging reduces surface woody fuels up to four decades following wildfire

Treesearch

David W. Peterson; Erich Kyle Dodson; Richy J. Harrod

2015-01-01

Severe wildfires create pulses of dead trees that influence future fuel loads, fire behavior, and fire effects as they decay and deposit surface woody fuels. Harvesting fire-killed trees may reduce future surface woody fuels and related fire hazards, but the magnitude and timing of post-fire logging effects on woody fuels have not been fully assessed. To address this...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Using field data to assess model predictions of surface and ground fuel consumption by wildfire in coniferous forests of California

NASA Astrophysics Data System (ADS)

Lydersen, Jamie M.; Collins, Brandon M.; Ewell, Carol M.; Reiner, Alicia L.; Fites, Jo Ann; Dow, Christopher B.; Gonzalez, Patrick; Saah, David S.; Battles, John J.

2014-03-01

Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire emissions however can be difficult due to inherent variability in fuel loads and consumption and a lack of field data of fuel consumption by wildfire. We compare a unique set of fuel data collected immediately before and after six wildfires in coniferous forests of California to fuel consumption predictions of the first-order fire effects model (FOFEM), based on two different available fuel characterizations. We found strong regional differences in the performance of different fuel characterizations, with FOFEM overestimating the fuel consumption to a greater extent in the Klamath Mountains than in the Sierra Nevada. Inaccurate fuel load inputs caused the largest differences between predicted and observed fuel consumption. Fuel classifications tended to overestimate duff load and underestimate litter load, leading to differences in predicted emissions for some pollutants. When considering total ground and surface fuels, modeled consumption was fairly accurate on average, although the range of error in estimates of plot level consumption was very large. These results highlight the importance of fuel load input to the accuracy of modeled fuel consumption and GHG emissions from wildfires in coniferous forests.

Projecting wildfire area burned in the south-eastern United States, 2011-60

Treesearch

Jeff Prestemon; Uma Shankar; Aijun Xiu; K. Talgo; D. Yang; Ernest Dixon IV; Donald McKenzie; Karen L. Abt

2016-01-01

Future changes in society and climate are expected to affect wildfire activity in the south-eastern United States. The objective of this research was to understand how changes in both climate and society may affect wildfire in the coming decades.Weestimated a three-stage statistical model of wildfire area burned by ecoregion province for lightning and human causes (...

What motivates individuals to protect themselves from risks: the case of wildland fires.

PubMed

Martin, Ingrid M; Bender, Holly; Raish, Carol

2007-08-01

This research investigates the cognitive perceptual process that homeowners go through when faced with the decision to protect themselves from the risk of wildfires. This decision can be examined by looking at the interaction between the integrated protection motivation theory-transtheoretical model and different levels of homeowners' subjective knowledge related to wildfire risks. We investigated the role of motivation, decision stages of risk readiness, and subjective knowledge on the number of risk-mitigating actions undertaken by homeowners living in high-risk communities. The results indicate that homeowners who are in an early or precontemplative stage (both low and high subjective knowledge) as well as low knowledge contemplatives are motivated by their perceived degree of vulnerability to mitigate the risk. In contrast, high knowledge contemplatives' potential behavioral changes are more likely to be motivated by increasing their perceptions of the severity of the risk. Risk-mitigating behaviors undertaken by high knowledge action homeowners are influenced by their perceptions of risk severity, self-efficacy, and response efficacy. In contrast, the low knowledge action homeowners engage in risk reduction behaviors without the influence of any of the PMT variables; demonstrating their motivation to emulate others in their community. These results have implications for the type of information that should be used to effectively communicate risks in an effort to influence the diverse homeowner segments to engage in risk-reduction behaviors.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US.

PubMed

Hurteau, Matthew D

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010-2019), mid (2050-2059), and late (2090-2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8-48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US

PubMed Central

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010–2019), mid (2050–2059), and late (2090–2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8–48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink. PMID:28046079

Refining the cheatgrass-fire cycle in the Great Basin: Precipitation timing and fine fuel composition predict wildfire trends.

PubMed

Pilliod, David S; Welty, Justin L; Arkle, Robert S

2017-10-01

Larger, more frequent wildfires in arid and semi-arid ecosystems have been associated with invasion by non-native annual grasses, yet a complete understanding of fine fuel development and subsequent wildfire trends is lacking. We investigated the complex relationships among weather, fine fuels, and fire in the Great Basin, USA. We first modeled the annual and time-lagged effects of precipitation and temperature on herbaceous vegetation cover and litter accumulation over a 26-year period in the northern Great Basin. We then modeled how these fine fuels and weather patterns influence subsequent wildfires. We found that cheatgrass cover increased in years with higher precipitation and especially when one of the previous 3 years also was particularly wet. Cover of non-native forbs and native herbs also increased in wet years, but only after several dry years. The area burned by wildfire in a given year was mostly associated with native herb and non-native forb cover, whereas cheatgrass mainly influenced area burned in the form of litter derived from previous years' growth. Consequently, multiyear weather patterns, including precipitation in the previous 1-3 years, was a strong predictor of wildfire in a given year because of the time needed to develop these fine fuel loads. The strong relationship between precipitation and wildfire allowed us to expand our inference to 10,162 wildfires across the entire Great Basin over a 35-year period from 1980 to 2014. Our results suggest that the region's precipitation pattern of consecutive wet years followed by consecutive dry years results in a cycle of fuel accumulation followed by weather conditions that increase the probability of wildfire events in the year when the cycle transitions from wet to dry. These patterns varied regionally but were strong enough to allow us to model annual wildfire risk across the Great Basin based on precipitation alone.

Refining the cheatgrass–fire cycle in the Great Basin: Precipitation timing and fine fuel composition predict wildfire trends

USGS Publications Warehouse

Pilliod, David S.; Welty, Justin; Arkle, Robert

2017-01-01

Larger, more frequent wildfires in arid and semi-arid ecosystems have been associated with invasion by non-native annual grasses, yet a complete understanding of fine fuel development and subsequent wildfire trends is lacking. We investigated the complex relationships among weather, fine fuels, and fire in the Great Basin, USA. We first modeled the annual and time-lagged effects of precipitation and temperature on herbaceous vegetation cover and litter accumulation over a 26-year period in the northern Great Basin. We then modeled how these fine fuels and weather patterns influence subsequent wildfires. We found that cheatgrass cover increased in years with higher precipitation and especially when one of the previous 3 years also was particularly wet. Cover of non-native forbs and native herbs also increased in wet years, but only after several dry years. The area burned by wildfire in a given year was mostly associated with native herb and non-native forb cover, whereas cheatgrass mainly influenced area burned in the form of litter derived from previous years’ growth. Consequently, multiyear weather patterns, including precipitation in the previous 1–3 years, was a strong predictor of wildfire in a given year because of the time needed to develop these fine fuel loads. The strong relationship between precipitation and wildfire allowed us to expand our inference to 10,162 wildfires across the entire Great Basin over a 35-year period from 1980 to 2014. Our results suggest that the region's precipitation pattern of consecutive wet years followed by consecutive dry years results in a cycle of fuel accumulation followed by weather conditions that increase the probability of wildfire events in the year when the cycle transitions from wet to dry. These patterns varied regionally but were strong enough to allow us to model annual wildfire risk across the Great Basin based on precipitation alone.

Repeating cardiopulmonary health effects in rural North Carolina population during a second large peat wildfire.

PubMed

Tinling, Melissa A; West, J Jason; Cascio, Wayne E; Kilaru, Vasu; Rappold, Ana G

2016-01-27

Cardiovascular health effects of fine particulate matter (PM2.5) exposure from wildfire smoke are neither definitive nor consistent with PM2.5 from other air pollution sources. Non-comparability among wildfire health studies limits research conclusions. We examined cardiovascular and respiratory health outcomes related to peat wildfire smoke exposure in a population where strong associations were previously reported for the 2008 Evans Road peat wildfire. We conducted a population-based epidemiologic investigation of associations between daily county-level modeled wildfire PM2.5 and cardiopulmonary emergency department (ED) visits during the 2011 Pains Bay wildfire in eastern North Carolina. We estimated changes in the relative risk cumulative over 0-2 lagged days of wildfire PM2.5 exposure using a quasi-Poisson regression model adjusted for weather, weekends, and poverty. Relative risk associated with a 10 μg/m(3) increase in 24-h PM2.5 was significantly elevated in adults for respiratory/other chest symptoms 1.06 (1.00-1.13), upper respiratory infections 1.13 (1.05-1.22), hypertension 1.05 (1.00-1.09) and 'all-cause' cardiac outcomes 1.06 (1.00-1.13) and in youth for respiratory/other chest symptoms 1.18 (1.06-1.33), upper respiratory infections 1.14 (1.04-1.24) and 'all-cause' respiratory conditions 1.09 (1.01-1.17). Our results replicate evidence for increased risk of cardiovascular outcomes from wildfire PM2.5 and suggest that cardiovascular health should be considered when evaluating the public health burden of wildfire smoke.

A Five-Year CMAQ PM2.5 Model Performance for Wildfires and Prescribed Fires

NASA Astrophysics Data System (ADS)

Wilkins, J. L.; Pouliot, G.; Foley, K.; Rappold, A.; Pierce, T. E.

2016-12-01

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. We will also review plume rise to see how it affects model bias and compare CMAQ current fire emissions input to an hourly dataset from FLAMBE.

Inclusion of biomass burning in WRF-Chem: Impact of wildfires on weather forecasts

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

Grell, G. A.; Freitas, Saulo; Stuefer, Martin

2011-06-06

A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather forecasts using model resolutions of 10km and 2km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the final emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation ledmore » to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 hours of the integration, but significantly stronger storms during the afternoon hours.« less

Long-term effects of wildfire on greater sage-grouse - integrating population and ecosystem concepts for management in the Great Basin

USGS Publications Warehouse

Coates, Peter S.; Ricca, Mark A.; Prochazka, Brian G.; Doherty, Kevin E.; Brooks, Matthew L.; Casazza, Michael L.

2015-09-10

Greater sage-grouse (Centrocercus urophasianus; hereinafter, sage-grouse) are a sagebrush obligate species that has declined concomitantly with the loss and fragmentation of sagebrush ecosystems across most of its geographical range. The species currently is listed as a candidate for federal protection under the Endangered Species Act (ESA). Increasing wildfire frequency and changing climate frequently are identified as two environmental drivers that contribute to the decline of sage-grouse populations, yet few studies have rigorously quantified their effects on sage-grouse populations across broad spatial scales and long time periods. To help inform a threat assessment within the Great Basin for listing sage-grouse in 2015 under the ESA, we conducted an extensive analysis of wildfire and climatic effects on sage-grouse population growth derived from 30 years of lek-count data collected across the hydrographic Great Basin of Western North America. Annual (1984–2013) patterns of wildfire were derived from an extensive dataset of remotely sensed 30-meter imagery and precipitation derived from locally downscaled spatially explicit data. In the sagebrush ecosystem, underlying soil conditions also contribute strongly to variation in resilience to disturbance and resistance to plant community changes (R&R). Thus, we developed predictions from models of post-wildfire recovery and chronic effects of wildfire based on three spatially explicit R&R classes derived from soil moisture and temperature regimes. We found evidence of an interaction between the effects of wildfire (chronically affected burned area within 5 kilometers of a lek) and climatic conditions (spring through fall precipitation) after accounting for a consistent density-dependent effect. Specifically, burned areas near leks nullifies population growth that normally follows years with relatively high precipitation. In models, this effect results in long-term population declines for sage-grouse despite cyclic periods of high precipitation. Based on 30-year projections of burn and recovery rates, our population model predicted steady and substantial long-term declines in population size across the Great Basin. Further, example management scenarios that may help offset adverse wildfire effects are provided by models of varying levels of fire suppression and post-wildfire restoration that focus on areas especially important to sage-grouse populations. These models illustrate how sage-grouse population persistence likely will be compromised as sagebrush ecosystems and sage-grouse habitat are degraded by wildfire, especially in a warmer and drier climate, and by invasion of annual grasses that can increase wildfire frequency and size in the Great Basin.

The net benefits of human-ignited wildfire forecasting: the case of tribal land units in the United States

Treesearch

Jeff Prestemon; David T. Butry; Douglas S. Thomas

2016-01-01

Research shows that some categories of human-ignited wildfires may be forecastable, owing to their temporal clustering, with the possibility that resources could be predeployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the...

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.

Social Networks and Adaptation to Environmental Change: The Case of Central Oregon's Fire-Prone Forest Landscape

NASA Astrophysics Data System (ADS)

Fischer, A.

2012-12-01

Social networks are the patterned interactions among individuals and organizations through which people refine their beliefs and values, negotiate meanings for things and develop behavioral intentions. The structure of social networks has bearing on how people communicate information, generate and retain knowledge, make decisions and act collectively. Thus, social network structure is important for how people perceive, shape and adapt to the environment. We investigated the relationship between social network structure and human adaptation to wildfire risk in the fire-prone forested landscape of Central Oregon. We conducted descriptive and non-parametric social network analysis on data gathered through interviews to 1) characterize the structure of the network of organizations involved in forest and wildfire issues and 2) determine whether network structure is associated with organizations' beliefs, values and behaviors regarding fire and forest management. Preliminary findings indicate that fire protection and forest-related organizations do not frequently communicate or cooperate, suggesting that opportunities for joint problem-solving, innovation and collective action are limited. Preliminary findings also suggest that organizations with diverse partners are more likely to hold adaptive beliefs about wildfire and work cooperatively. We discuss the implications of social network structure for adaptation to changing environmental conditions such as wildfire risk.

Integrating wildfire plume rises within atmospheric transport models

NASA Astrophysics Data System (ADS)

Mallia, D. V.; Kochanski, A.; Wu, D.; Urbanski, S. P.; Krueger, S. K.; Lin, J. C.

2016-12-01

Wildfires can generate significant pyro-convection that is responsible for releasing pollutants, greenhouse gases, and trace species into the free troposphere, which are then transported a significant distance downwind from the fire. Oftentimes, atmospheric transport and chemistry models have a difficult time resolving the transport of smoke from these wildfires, primarily due to deficiencies in estimating the plume injection height, which has been highlighted in previous work as the most important aspect of simulating wildfire plume transport. As a result of the uncertainties associated with modeled wildfire plume rise, researchers face difficulties modeling the impacts of wildfire smoke on air quality and constraining fire emissions using inverse modeling techniques. Currently, several plume rise parameterizations exist that are able to determine the injection height of fire emissions; however, the success of these parameterizations has been mixed. With the advent of WRF-SFIRE, the wildfire plume rise and injection height can now be explicitly calculated using a fire spread model (SFIRE) that is dynamically linked with the atmosphere simulated by WRF. However, this model has only been tested on a limited basis due to computational costs. Here, we will test the performance of WRF-SFIRE in addition to several commonly adopted plume parameterizations (Freitas, Sofiev, and Briggs) for the 2013 Patch Springs (Utah) and 2012 Baker Canyon (Washington) fires, for both of which observations of plume rise heights are available. These plume rise techniques will then be incorporated within a Lagrangian atmospheric transport model (STILT) in order to simulate CO and CO2 concentrations during NASA's CARVE Earth Science Airborne Program over Alaska during the summer of 2012. Initial model results showed that STILT model simulations were unable to reproduce enhanced CO concentrations produced by Alaskan fires observed during 2012. Near-surface concentrations were drastically overestimated while free tropospheric concentrations of CO were underestimated, likely a result of STILT injecting the fire emissions strictly into the PBL. We show in this study to what degree coupling the STILT model with an external plume rise model can help mitigate these problems.

Analyzing wildfire exposure on Sardinia, Italy

NASA Astrophysics Data System (ADS)

Salis, Michele; Ager, Alan A.; Arca, Bachisio; Finney, Mark A.; Alcasena, Fermin; Bacciu, Valentina; Duce, Pierpaolo; Munoz Lozano, Olga; Spano, Donatella

2014-05-01

We used simulation modeling based on the minimum travel time algorithm (MTT) to analyze wildfire exposure of key ecological, social and economic features on Sardinia, Italy. Sardinia is the second largest island of the Mediterranean Basin, and in the last fifty years experienced large and dramatic wildfires, which caused losses and threatened urban interfaces, forests and natural areas, and agricultural productions. Historical fires and environmental data for the period 1995-2009 were used as input to estimate fine scale burn probability, conditional flame length, and potential fire size in the study area. With this purpose, we simulated 100,000 wildfire events within the study area, randomly drawing from the observed frequency distribution of burn periods and wind directions for each fire. Estimates of burn probability, excluding non-burnable fuels, ranged from 0 to 1.92x10-3, with a mean value of 6.48x10-5. Overall, the outputs provided a quantitative assessment of wildfire exposure at the landscape scale and captured landscape properties of wildfire exposure. We then examined how the exposure profiles varied among and within selected features and assets located on the island. Spatial variation in modeled outputs resulted in a strong effect of fuel models, coupled with slope and weather. In particular, the combined effect of Mediterranean maquis, woodland areas and complex topography on flame length was relevant, mainly in north-east Sardinia, whereas areas with herbaceous fuels and flat areas were in general characterized by lower fire intensity but higher burn probability. The simulation modeling proposed in this work provides a quantitative approach to inform wildfire risk management activities, and represents one of the first applications of burn probability modeling to capture fire risk and exposure profiles in the Mediterranean basin.

Understanding Broadscale Wildfire Risks in a Human-Dominated Landscape

Treesearch

Jeffrey P. Prestemon; John M. Pye; David T. Butry; Thomas P. Holmes; D. Evan Mercer

2002-01-01

Broadscale statistical evaluations of wildfire incidence can answer policy relevant questions about the effectiveness of microlevel vegetation management and can identify subjects needing further study. A dynamic time series cross-sectional model was used to evaluate the statistical links between forest wildfire and vegetation management, human land use, and climatic...

National database for calculating fuel available to wildfires

Treesearch

Donald McKenzie; Nancy H.F. French; Roger D. Ottmar

2012-01-01

Wildfires are increasingly emerging as an important component of Earth system models, particularly those that involve emissions from fires and their effects on climate. Currently, there are few resources available for estimating emissions from wildfires in real time, at subcontinental scales, in a spatially consistent manner. Developing subcontinental-scale databases...

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.

Evaluation of wildfire patterns at the wildland-urban fringe across the continental U.S.

NASA Astrophysics Data System (ADS)

Kinoshita, A. M.; Hogue, T. S.

2014-12-01

Wildfires threaten ecosystems and urban development across the United States, posing significant implications for land management and natural processes such as watershed hydrology. This study investigates the spatial association between large wildfires and urbanization. Several geospatial dataset are combined to map wildfires (Monitoring Trends in Burn Severity for 1984 to 2012) and housing density (SILVIS Lab Spatial Analysis for Conservation and Sustainability decadal housing density for 1940 to 2030) relative to natural wildlands across the contiguous U.S. Several buffers (i.e. 25 km) are developed around wildlands (Protected Areas Database of the United States) to quantify the change and relationship in spatial fire and housing density patterns. Since 1984, wildfire behavior is cyclical and follows general climatology, where warmer years have more and larger fires. Ignition locations also follow transportation corridors and development which provide easy accessibility to wildlands. In California, both fire frequency and total acres burned exhibit increasing trends (statistically significant at 95%). The 1980s average wildfire frequency and total acres burned was 3100 fires and approximately 1200 km2, respectively. These numbers have increased to 2200 fires and over 1500 km2 in the 2010 to 2012 period alone. Initial observations also show that decennial population and area burned for four major Californian counties (Los Angeles, San Bernardino, San Diego, and Shasta) show strong correlation between the last decade of burned area, urban-fringe proximity, and urbanization trends. Improving our understanding of human induced wildfire regimes provides key information on urban fringe communities most vulnerable to the wildfire risks and can help inform regional development planning.

Using Haines Index coupled with fire weather model predicted from high resolution LAM forecasts to asses wildfire extreme behaviour in Southern Europe.

NASA Astrophysics Data System (ADS)

Gaetani, Francesco; Baptiste Filippi, Jean; Simeoni, Albert; D'Andrea, Mirko

2010-05-01

Haines Index (HI) was developed by USDA Forest Service to measure the atmosphere's contribution to the growth potential of a wildfire. The Haines Index combines two atmospheric factors that are known to have an effect on wildfires: Stability and Dryness. As operational tools, HI proved its ability to predict plume dominated high intensity wildfires. However, since HI does not take into account the fuel continuity, composition and moisture conditions and the effects of wind and topography on fire behaviour, its use as forecasting tool should be carefully considered. In this work we propose the use of HI, predicted from HR Limited Area Model forecasts, coupled with a Fire Weather model (i.e., RISICO system) fully operational in Italy since 2003. RISICO is based on dynamic models able to represent in space and in time the effects that environment and vegetal physiology have on fuels and, in turn, on the potential behaviour of wildfires. The system automatically acquires from remote databases a thorough data-set of input information both of in situ and spatial nature. Meteorological observations, radar data, Limited Area Model weather forecasts, EO data, and fuel data are managed by a Unified Interface able to process a wide set of different data. Specific semi-physical models are used in the system to simulate the dynamics of the fuels (load and moisture contents of dead and live fuel) and the potential fire behaviour (rate of spread and linear intensity). A preliminary validation of this approach will be provided with reference to Sardinia and Corsica Islands, two major islands of the Mediterranean See frequently affected by extreme plume dominated wildfires. A time series of about 3000 wildfires burnt in Sardinia and Corsica in 2007 and 2008 will be used to evaluate the capability of HI coupled with the outputs of the Fire Weather model to forecast the actual risk in time and in space.

Wildfire Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Thompson, M.

2013-12-01

Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

Evaluation of a CFD-based Wind Model Optimized for ABL Flows: Comparisons with Observations from a Tall Isolated Mountain

NASA Astrophysics Data System (ADS)

Wagenbrenner, N. S.; Forthofer, J.; Butler, B.

2015-12-01

Near-surface wind predictions are important for a number of applications, including transport and dispersion, wind energy forecasting, and wildfire behavior. Researchers and forecasters would benefit from a wind model that could be readily applied to complex terrain for use in these disciplines. Unfortunately, near-surface winds in complex terrain are not handled well by traditional modeling approaches. Computational fluid dynamics (CFD) models are increasingly being applied to simulate atmospheric boundary layer (ABL) flows, especially in wind energy applications; however, the standard functionality provided in commercial CFD models is not suitable for ABL flows. Appropriate CFD modeling in the ABL requires modification of empirically-derived wall function parameters and boundary conditions to avoid erroneous streamwise gradients due to inconsistences between inlet profiles and specified boundary conditions. This work presents a new version of a wind model, WindNinja, developed for wildfire applications in complex terrain. The new version offers two options for flow simulations: 1) the native, fast-running mass-consistent method available in previous versions and 2) a CFD approach based on the OpenFOAM toolbox and optimized for ABL flows. The model is described and evaluations of predictions with surface wind data collected from a recent field campaign at a tall isolated mountain are presented. CFD models have typically been evaluated with data collected from relatively simple terrain (e.g., low-elevation hills such as Askervein and Bolund) compared to the highly rugged terrain found in many regions, such as the western U.S. Here we provide one of the first evaluations of a CFD model over real terrain with ruggedness approaching that of landscapes characteristic of the western U.S. and other regions prone to wildfire. A comparison of predictions from the native mass-consistent method and the new CFD method is provided.

Coupling the Biophysical and Social Dimensions of Wildfire Risk to Improve Wildfire Mitigation Planning.

PubMed

Ager, Alan A; Kline, Jeffrey D; Fischer, A Paige

2015-08-01

We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire-prone landscapes. The methods and tools provide an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community-wide risk perceptions and to predict property owners' capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire-prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape-scale prioritization of fuel management investments by government entities. © 2015 Society for Risk Analysis.

Diurnal variations of wildfire emissions in Europe: analysis of the MODIS and SEVIRI measurements in the framework of the regional scale air pollution modelling

NASA Astrophysics Data System (ADS)

Konovalov, Igor B.; Beekmann, Matthias; Kaiser, Johannes W.; Shudyaev, Anton A.; Yurova, Alla; Kuznetsova, Irina N.

2013-04-01

Wildfires episodically provide a major contribution to air pollution in many regions of the world. For example, the extreme air pollution level and strongly reduced visibility were observed in the Central European region of Russia during the intensive wildfire events in summer of 2010. Such episodes provide a strong impetus for further developments in air pollution modeling, aimed at improving the ability of chemistry transport models to simulate and predict evolution of atmospheric composition affected by wildfires. The main goals of our study are (1) to investigate the diurnal cycles of air pollutant emissions from wildfires in several European regions, taking into account the fire radiative power (FRP) satellite measurements for different vegetation land cover types and (2) to examine the possibilities of improving air pollution simulations by assimilating the diurnal variability of the FRP measurements performed by the polar orbiting (MODIS) and geostationary (SEVIRI) satellite instruments into a chemistry transport model. These goals are addressed for the case of wildfires occurred in summer 2010. The analysis of both the MODIS and SEVIRI data indicate that air pollutant emissions from wildfires in Europe in summer 2010 were typically much larger during daytime than during nighttime. The important exception is intensive fires around Moscow, featuring an almost "flat" diurnal cycle. These findings confirm the similar results reported earlier [1] but also extend them by attributing the flat diurnal cycle only to forest fires and by examining a hypothetical association of the "abnormal" diurnal cycle of FRP with peat fires. The derived diurnal variations of wildfire emissions have been used in the framework of the modeling system employed in our previous studies of the atmospheric effects of the 2010 Russian wildfires [2, 3]. The numerical experiments reveal that while the character of the diurnal variation of wildfire emissions has a rather small impact on the simulated evolution of primary air pollutants (such as CO and PM10), it considerably affects variability of daily ozone maximums. Moreover, it is found that assimilating the diurnal variability of wildfire emissions derived from the FRP measurements into our model leads to significant improvements in the agreement between the simulated and measured ozone concentrations in the Moscow region. References: 1. Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527-554, doi:10.5194/bg-9-527-2012, 2012. 2. Konovalov, I. B., Beekmann, M., Kuznetsova, I. N., Yurova, A., and Zvyagintsev, A. M.: Atmospheric impacts of the 2010 Russian wildfires: integrating modelling and measurements of an extreme air pollution episode in the Moscow region, Atmos. Chem. Phys., 11, 10031-10056, doi:10.5194/acp-11-10031-2011, 2011. 3. Konovalov, I.B., Beekmann, M., D'Anna, B., and George C.: Significant light induced ozone loss on biomass burning aerosol:Evidence from chemistry-transport modeling based on new laboratory studies, Geophys. Res. Lett., 39, L17807, doi:10.1029/2012GL052432, 2012.

Mega wildfire in the World Biosphere Reserve (UNESCO), Torres del Paine National Park, Patagonia - Chile 2012: Work experience in extreme behavior conditions in the context of global warming

Treesearch

René Cifuentes Medina

2013-01-01

Mega wildfires are critical, high-impact events that cause severe environmental, economic and social damage, resulting, in turn, in high-cost suppression operations and the need for mutual support, phased use of resources and the coordinated efforts of civilian government agencies, the armed forces, private companies and the international community. The mega forest...

The effect of personal experience on choice-based preferences for wildfire protection programs

Treesearch

Tom Holmes; Armando Gonzalez-Caban; John Loomis; Jose Sanchez

2013-01-01

In this paper, we investigate homeowner preferences and willingness to pay for wildfire protection programs using a choice experiment with three attributes: risk, loss and cost. Preference heterogeneity among survey respondents was examined using three econometric models and risk preferences were evaluated by comparing willingness to pay for wildfire protection...

Examining heterogeneity and wildfire management expenditures using spatially and temporally descriptive data

Treesearch

Michael S. Hand; Matthew P. Thompson; Dave Calkin

2016-01-01

Increasing costs of wildfire management have highlighted the need to better understand suppression expenditures and potential tradeoffs of land management activities that may affect fire risks. Spatially and temporally descriptive data is used to develop a model of wildfire suppression expenditures, providing new insights into the role of spatial and temporal...

Efficient and Equitable Design of Wildfire Mitigation Programs

Treesearch

Thomas P. Holmes; Karen L. Abt; Robert Huggett; Jeffrey P. Prestemon

2007-01-01

Natural resource economists have addresssed the economic effienciency of expenditures on wildfire mitigation for nearly a century (Gope and Gorte 1979). Beginning with the work of Sparhawk (1925), the theory of efficent wildfire mitigation developed alolng conceptual lines drawn form neoclassical economics. The objective of the traditional least-cost-plus-loss model...

Role of buoyant flame dynamics in wildfire spread

Treesearch

Mark A. Finney; Jack D. Cohen; Jason M. Forthofer; Sara S. McAllister; Michael J. Gollner; Daniel J. Gorham; Kozo Saito; Nelson K. Akafuah; Brittany A. Adam; Justin D. English

2015-01-01

Large wildfires of increasing frequency and severity threaten local populations and natural resources and contribute carbon emissions into the earth-climate system. Although wildfires have been researched and modeled for decades, no verifiable physical theory of spread is available to form the basis for the precise predictions needed to manage fires more effectively...

Comparing erosion risks from forest operations to wildfire

Treesearch

William J. Elliot; Peter R. Robichaud

2001-01-01

Wildfire and forest operations remove vegetation and disturb forest soils. Both of these effects can lead to an increased risk of soil erosion. Operations to reduce forest fuel loads, however, may reduce the risk of wildfire. This paper presents research and modeling results which show that under many conditions, carefully planned operations with adequate buffers,...

Wildfire potential mapping over the state of Mississippi: A land surface modeling approach

Treesearch

William H. Cooke; Georgy V. Mostovoy; Valentine G. Anantharaj; W. Matt Jolly

2012-01-01

A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern part of Mississippi. The following three indices were tested and used to simulate spatial and temporal wildfire probability changes: (1) the accumulated difference between daily precipitation and potential...

Tools to aid post-wildfire assessment and erosion-mitigation treatment decisions

Treesearch

Peter R. Robichaud; Louise E. Ashmun

2013-01-01

A considerable investment in post-fire research over the past decade has improved our understanding of wildfire effects on soil, hydrology, erosion and erosion-mitigation treatment effectiveness. Using this new knowledge, we have developed several tools to assist land managers with post-wildfire assessment and treatment decisions, such as prediction models, research...

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

Treesearch

Richard A. Shakesby; John A. Moody; Deborah A. Martin; Pete Robichaud

2016-01-01

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including...

Capturing spatiotemporal variation in wildfires for improving postwildfire debris‐flow hazard assessments [Chapter 20

Treesearch

Jessica Haas; Matthew Thompson; Anne Tillery; Joe H. Scott

2017-01-01

Wildfires can increase the frequency and magnitude of catastrophic debris flows. Integrated, proactive naturalhazard assessment would therefore characterize landscapes based on the potential for the occurrence and interactions of wildfires and postwildfire debris flows. This chapter presents a new modeling effort that can quantify the variability surrounding a key...

Wildfire suppression cost forecasts from the US Forest Service

Treesearch

Karen L. Abt; Jeffrey P. Prestemon; Krista M. Gebert

2009-01-01

The US Forest Service and other land-management agencies seek better tools for nticipating future expenditures for wildfire suppression. We developed regression models for forecasting US Forest Service suppression spending at 1-, 2-, and 3-year lead times. We compared these models to another readily available forecast model, the 10-year moving average model,...

Wildfire ignition-distribution modelling: a comparative study in the Huron-Manistee National Forest, Michigan, USA

Treesearch

Avi Bar Massada; Alexandra D. Syphard; Susan I. Stewart; Volker C. Radeloff

2012-01-01

Wildfire ignition distribution models are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar species-distribution models...

The Role of Wildfire, Prescribed Fire, and Mountain Pine Beetle Infestations on the Population Dynamics of Black-Backed Woodpeckers in the Black Hills, South Dakota

PubMed Central

Rota, Christopher T.; Millspaugh, Joshua J.; Rumble, Mark A.; Lehman, Chad P.; Kesler, Dylan C.

2014-01-01

Wildfire and mountain pine beetle infestations are naturally occurring disturbances in western North American forests. Black-backed woodpeckers (Picoides arcticus) are emblematic of the role these disturbances play in creating wildlife habitat, since they are strongly associated with recently-killed forests. However, management practices aimed at reducing the economic impact of natural disturbances can result in habitat loss for this species. Although black-backed woodpeckers occupy habitats created by wildfire, prescribed fire, and mountain pine beetle infestations, the relative value of these habitats remains unknown. We studied habitat-specific adult and juvenile survival probabilities and reproductive rates between April 2008 and August 2012 in the Black Hills, South Dakota. We estimated habitat-specific adult and juvenile survival probability with Bayesian multi-state models and habitat-specific reproductive success with Bayesian nest survival models. We calculated asymptotic population growth rates from estimated demographic rates with matrix projection models. Adult and juvenile survival and nest success were highest in habitat created by summer wildfire, intermediate in MPB infestations, and lowest in habitat created by fall prescribed fire. Mean posterior distributions of population growth rates indicated growing populations in habitat created by summer wildfire and declining populations in fall prescribed fire and mountain pine beetle infestations. Our finding that population growth rates were positive only in habitat created by summer wildfire underscores the need to maintain early post-wildfire habitat across the landscape. The lower growth rates in fall prescribed fire and MPB infestations may be attributed to differences in predator communities and food resources relative to summer wildfire. PMID:24736502

The role of wildfire, prescribed fire, and mountain pine beetle infestations on the population dynamics of black-backed woodpeckers in the black hills, South Dakota.

PubMed

Rota, Christopher T; Millspaugh, Joshua J; Rumble, Mark A; Lehman, Chad P; Kesler, Dylan C

2014-01-01

Wildfire and mountain pine beetle infestations are naturally occurring disturbances in western North American forests. Black-backed woodpeckers (Picoides arcticus) are emblematic of the role these disturbances play in creating wildlife habitat, since they are strongly associated with recently-killed forests. However, management practices aimed at reducing the economic impact of natural disturbances can result in habitat loss for this species. Although black-backed woodpeckers occupy habitats created by wildfire, prescribed fire, and mountain pine beetle infestations, the relative value of these habitats remains unknown. We studied habitat-specific adult and juvenile survival probabilities and reproductive rates between April 2008 and August 2012 in the Black Hills, South Dakota. We estimated habitat-specific adult and juvenile survival probability with Bayesian multi-state models and habitat-specific reproductive success with Bayesian nest survival models. We calculated asymptotic population growth rates from estimated demographic rates with matrix projection models. Adult and juvenile survival and nest success were highest in habitat created by summer wildfire, intermediate in MPB infestations, and lowest in habitat created by fall prescribed fire. Mean posterior distributions of population growth rates indicated growing populations in habitat created by summer wildfire and declining populations in fall prescribed fire and mountain pine beetle infestations. Our finding that population growth rates were positive only in habitat created by summer wildfire underscores the need to maintain early post-wildfire habitat across the landscape. The lower growth rates in fall prescribed fire and MPB infestations may be attributed to differences in predator communities and food resources relative to summer wildfire.

Assessing increasing susceptibility to wildfire at the wildland-urban fringe in the western United States

NASA Astrophysics Data System (ADS)

Kinoshita, A. M.; Hogue, T. S.

2013-05-01

Much of the western U.S. is increasingly susceptible to wildfire activity due to drier conditions, elevated fuel loads, and expanding urbanization. As population increases, development pushes the urban boundary further into wildlands, creating more potential for human interaction at the wildland-urban interface (WUI), primarily from human ignitions and fire suppression policies. The immediate impacts of wildfires include vulnerability to debris flows, flooding, and impaired water quality. Fires also alter longer-term hydrological and ecosystem behavior. The current study utilizes geospatial datasets to investigate historical wildfire size and frequency relative to the WUI for a range of cities across western North America. California, the most populous state in the U.S., has an extensive fire history. The decennial population and acres burned for four major counties (Los Angeles, San Bernardino, San Diego, and Shasta) in California show that increasing wildfire size and frequency follow urbanization trends, with high correlation between the last decade of burned area, urban-fringe proximity, and increasing population. Ultimately, results will provide information on urban fringe communities that are most vulnerable to the risks associated with wildfire and post-fire impacts. In light of evolving land use policies (i.e. forest management and treatment, development at the urban-fringe) and climate change, it is critical to advance our knowledge of the implications that these conditions pose to urban centers, communicate risks to the public, and ultimately provide guidance for wildfire management.

Wildfires as collateral effects of wildlife electrocution: An economic approach to the situation in Spain in recent years.

PubMed

Guil, Francisco; Soria, Mª Ángeles; Margalida, Antoni; Pérez-García, Juan M

2018-06-01

The interaction between wildlife and power lines has collateral effects that include wildfires and Carbon Dioxide (CO 2 ) emissions. However, currently available information is scarce and so new approaches are needed to increase our understanding of this issue. Here, we present the first analysis of wildfires and their incidence as a result of this interaction in Spain during the period 2000-2012. Amongst the 2788 Power-Line Mediated Wildfires (PLMW recorded) during this period, 30 records of Fauna Mediated Wildfires (FMW) were found, with an average affected vegetation cover of 9.06ha. Our findings suggest that no significant differences were observed between the amount of affected surface area due to fauna mediated wildfires and power-line mediated wildfires. In both cases, a space-grouping trend was observed. In terms of changing trends over time, after the first incident detected in 2005, the number of incidents increased until 2008, year in which the percentage of wildfires caused by wildlife stabilized at approximately 2.4% of all power-line-induced wildfires. Population density and road abundance were variables that better explained PLMW whereas for FMW, the models that included land use and raptor abundance. In the multivariate model, FMW emergence was positively related with population density, percentage of grazing areas and Natura 2000 cover, and predatory abundance; and negatively with the percentage of forested area. No significant differences were observed between the species of birds that caused wildfires and the species of ringed birds killed by electrocution. The economic and environmental impact due to necessary repairs, the loss of biodiversity and CO 2 emissions represent an estimated net value of €7.6-12.4M for the period 2000-2012, which indicates the importance of the economic and environmental costs associated with wildfires. Copyright © 2017 Elsevier B.V. All rights reserved.

Particulate Air Pollution from Wildfires in the Western US under Climate Change

PubMed Central

Liu, Jia Coco; Mickley, Loretta J.; Sulprizio, Melissa P.; Dominici, Francesca; Yue, Xu; Ebisu, Keita; Anderson, Georgiana Brooke; Khan, Rafi F. A.; Bravo, Mercedes A.; Bell, Michelle L.

2016-01-01

Wildfire can impose a direct impact on human health under climate change. While the potential impacts of climate change on wildfires and resulting air pollution have been studied, it is not known who will be most affected by the growing threat of wildfires. Identifying communities that will be most affected will inform development of fire management strategies and disaster preparedness programs. We estimate levels of fine particulate matter (PM2.5) directly attributable to wildfires in 561 western US counties during fire seasons for the present-day (2004-2009) and future (2046-2051), using a fire prediction model and GEOS-Chem, a 3-D global chemical transport model. Future estimates are obtained under a scenario of moderately increasing greenhouse gases by mid-century. We create a new term “Smoke Wave,” defined as ≥2 consecutive days with high wildfire-specific PM2.5, to describe episodes of high air pollution from wildfires. We develop an interactive map to demonstrate the counties likely to suffer from future high wildfire pollution events. For 2004-2009, on days exceeding regulatory PM2.5 standards, wildfires contributed an average of 71.3% of total PM2.5. Under future climate change, we estimate that more than 82 million individuals will experience a 57% and 31% increase in the frequency and intensity, respectively, of Smoke Waves. Northern California, Western Oregon and the Great Plains are likely to suffer the highest exposure to widlfire smoke in the future. Results point to the potential health impacts of increasing wildfire activity on large numbers of people in a warming climate and the need to establish or modify US wildfire management and evacuation programs in high-risk regions. The study also adds to the growing literature arguing that extreme events in a changing climate could have significant consequences for human health. PMID:28642628

Particulate Air Pollution from Wildfires in the Western US under Climate Change.

PubMed

Liu, Jia Coco; Mickley, Loretta J; Sulprizio, Melissa P; Dominici, Francesca; Yue, Xu; Ebisu, Keita; Anderson, Georgiana Brooke; Khan, Rafi F A; Bravo, Mercedes A; Bell, Michelle L

2016-10-01

Wildfire can impose a direct impact on human health under climate change. While the potential impacts of climate change on wildfires and resulting air pollution have been studied, it is not known who will be most affected by the growing threat of wildfires. Identifying communities that will be most affected will inform development of fire management strategies and disaster preparedness programs. We estimate levels of fine particulate matter (PM 2.5 ) directly attributable to wildfires in 561 western US counties during fire seasons for the present-day (2004-2009) and future (2046-2051), using a fire prediction model and GEOS-Chem, a 3-D global chemical transport model. Future estimates are obtained under a scenario of moderately increasing greenhouse gases by mid-century. We create a new term "Smoke Wave," defined as ≥2 consecutive days with high wildfire-specific PM 2.5 , to describe episodes of high air pollution from wildfires. We develop an interactive map to demonstrate the counties likely to suffer from future high wildfire pollution events. For 2004-2009, on days exceeding regulatory PM 2.5 standards, wildfires contributed an average of 71.3% of total PM 2.5 . Under future climate change, we estimate that more than 82 million individuals will experience a 57% and 31% increase in the frequency and intensity, respectively, of Smoke Waves. Northern California, Western Oregon and the Great Plains are likely to suffer the highest exposure to widlfire smoke in the future. Results point to the potential health impacts of increasing wildfire activity on large numbers of people in a warming climate and the need to establish or modify US wildfire management and evacuation programs in high-risk regions. The study also adds to the growing literature arguing that extreme events in a changing climate could have significant consequences for human health.

Wildfire Risk Management: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Thompson, M.; Calkin, D. E.; Hand, M. S.; Kreitler, J.

2014-12-01

In this presentation we address federal wildfire risk management largely through the lens of economics, targeting questions related to costs, effectiveness, efficiency, and tradeoffs. Beyond risks to resources and assets such as wildlife habitat, watersheds, and homes, wildfires present financial risk and budgetary instability for federal wildfire management agencies due to highly variable annual suppression costs. Despite its variability, the costs of wildfire management have continued to escalate and account for an ever-growing share of overall agency budgets, compromising abilities to attain other objectives related to forest health, recreation, timber management, etc. Trends associated with a changing climate and human expansion into fire-prone areas could lead to additional suppression costs in the future, only further highlighting the need for an ability to evaluate economic tradeoffs in investments across the wildfire management spectrum. Critically, these economic analyses need to accurately capture the complex spatial and stochastic aspects of wildfire, the inherent uncertainty associated with monetizing environmental impacts of wildfire, the costs and effectiveness of alternative management policies, and linkages between pre-fire investments and active incident management. Investing in hazardous fuels reduction and forest restoration in particular is a major policy lever for pre-fire risk mitigation, and will be a primary focus of our presentation. Evaluating alternative fuel management and suppression policies could provide opportunities for significant efficiency improvements in the development of risk-informed management fire management strategies. Better understanding tradeoffs of fire impacts and costs can help inform policy questions such as how much of the landscape to treat and how to balance investments in treating new areas versus maintaining previous investments. We will summarize current data needs, knowledge gaps, and other factors influencing research and development on this critically important topic. Specifically we will focus on how to embed simulation models within an economic framework, how to link fire models with models of wildfire management expenditures, how to evaluate alternative management policies, and how to measure cost-effectiveness.

Transferability of habitat suitability models for nesting woodpeckers associated with wildfire

Treesearch

Quresh S. Latif; Vicki Saab; Jeff P. Hollenbeck; Jonathan G. Dudley

2016-01-01

Following wildfire, forest managers are challenged with meeting both socioeconomic demands (e.g., salvage logging) and mandates requiring habitat conservation for disturbance-associated wildlife (e.g., woodpeckers). Habitat suitability models for nesting woodpeckers can be informative, but tests of model transferability are needed to understand how broadly...

The dynamical evolution and air-quality impacts of the smoke plumes from 2016 Southeastern Wildfires

NASA Astrophysics Data System (ADS)

WANG, B.; Newchurch, M.; Kuang, S.; Wang, L.

2017-12-01

The 2016 Southeastern United States Wildfires are a series of wildfires along the Southern Appalachians during October-December in 2016, which approximately burned 127,555 acres (about 516 km2) in Georgia, Tennessee, North Carolina and South Carolina (see Incident Information System at https://inciweb.nwcg.gov/). This study will focus on the dynamical evolution and air-quality impacts of the smoke plumes within a short-term, but representative period during this wildfires event. This study combined remote-sensing data and in situ measurements with trajectory model to detect low-altitude smoke plume transport due to the 2016 southeastern wildfire. The smoke plumes were observed by ceilometer to arrive over Huntsville, AL area at low altitude and subsequently mixed down to the surface from Nov 12 to Nov 14. The wildfire had adverse effects on the surface air quality over the southeast region from both satellite and in situ measurement. The daily max 8-hour CO and daily mean PM2.5 data in five states were examined to show the influence. Both rural and urban sites were analyzed to track the wildfire and anthropogenic sources. Backward trajectory model calculation preliminarily confirmed the origin of the smoke plumes over Huntsville area, the transport at low altitudes, and the mechanism for bringing the pollutants to the surface.

Key factors controlling ozone production in wildfire plumes

NASA Astrophysics Data System (ADS)

Jaffe, D. A.

2017-12-01

Production of ozone in wildfire plumes is complex and highly variable. As a wildfire plume mixes into an urban area, ozone is often, but not always, produced. We have examined multiple factors that can help explain some of this variability. This includes CO/NOy enhancement ratios, photolysis rates, PAN/NOy fraction and degree of NOx oxidation. While fast ozone production is well known, on average, ozone production increases downwind in a plume for several days. Peroxyacetyl nitrate (PAN) is likely a key cause for delayed ozone formation. Recent observations at the Mt. Bachelor Observatory a mountain top observatory relatively remote from nearby anthropogenic influence and in Boise Idaho, an urban setting, show the importance of PAN in wildfire plumes. From these observations we can devise a conceptual model that considers four factors in ozone production: NOx/VOC emission ratio; degree of NOx oxidation; transport time and pathway; and mixing with urban pollutants. Using this conceptual model, we can then devise a lagrangian modeling strategy that can be used to improve our understanding of ozone production in wildfire plumes, both in remote and urban settings.

A Five- Year CMAQ Model Performance for Wildfires and ...

EPA Pesticide Factsheets

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Restoring forest structure and process stabilizes forest carbon in wildfire-prone southwestern ponderosa pine forests.

PubMed

Hurteau, Matthew D; Liang, Shuang; Martin, Katherine L; North, Malcolm P; Koch, George W; Hungate, Bruce A

2016-03-01

Changing climate and a legacy of fire-exclusion have increased the probability of high-severity wildfire, leading to an increased risk of forest carbon loss in ponderosa pine forests in the southwestern USA. Efforts to reduce high-severity fire risk through forest thinning and prescribed burning require both the removal and emission of carbon from these forests, and any potential carbon benefits from treatment may depend on the occurrence of wildfire. We sought to determine how forest treatments alter the effects of stochastic wildfire events on the forest carbon balance. We modeled three treatments (control, thin-only, and thin and burn) with and without the occurrence of wildfire. We evaluated how two different probabilities of wildfire occurrence, 1% and 2% per year, might alter the carbon balance of treatments. In the absence of wildfire, we found that thinning and burning treatments initially reduced total ecosystem carbon (TEC) and increased net ecosystem carbon balance (NECB). In the presence of wildfire, the thin and burn treatment TEC surpassed that of the control in year 40 at 2%/yr wildfire probability, and in year 51 at 1%/yr wildfire probability. NECB in the presence of wildfire showed a similar response to the no-wildfire scenarios: both thin-only and thin and burn treatments increased the C sink. Treatments increased TEC by reducing both mean wildfire severity and its variability. While the carbon balance of treatments may differ in more productive forest types, the carbon balance benefits from restoring forest structure and fire in southwestern ponderosa pine forests are clear.

Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models

Treesearch

Robert E. Keane; Eva Karau

2010-01-01

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology...

Smoke consequences of new wildfire regimes driven by climate change

Treesearch

Donald McKenzie; Uma Shankar; Robert E. Keane; E. Natasha Stavros; Warren E. Heilman; Douglas G. Fox; Allen C. Riebau

2014-01-01

Smoke from wildfires has adverse biological and social consequences, and various lines of evidence suggest that smoke from wildfires in the future may be more intense and widespread, demanding that methods be developed to address its effects on people, ecosystems, and the atmosphere. In this paper, we present the essential ingredients of a modeling system for...

Social media approaches to modeling wildfire smoke dispersion: spatiotemporal and social scientific investigations

Treesearch

Sonya Sachdeva; Sarah M. McCaffrey; Dexter Locke

2016-01-01

Wildfires have significant effects on human populations, economically, environmentally, and in terms of their general wellbeing. Smoke pollution, in particular, from either prescribed burns or uncontrolled wildfires, can have significant health impacts. Some estimates suggest that smoke dispersion from fire events may affect the health of one in three residents in the...

Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds

Treesearch

Joel B. Sankey; Jason Kreitler; Todd J. Hawbaker; Jason L. McVay; Mary Ellen Miller; Erich R. Mueller; Nicole M. Vaillant; Scott E. Lowe; Temuulen T. Sankey

2017-01-01

The area burned annually by wildfires is expected to increase worldwide due to climate change. Burned areas increase soil erosion rates within watersheds, which can increase sedimentation in downstream rivers and reservoirs. However, which watersheds will be impacted by future wildfires is largely unknown. Using an ensemble of climate, fire, and erosion models, we show...

Economics of wildfire management: The development and application of suppression expenditure models

Treesearch

Michael S. Hand; Krista M. Gebert; Jingjing Liang; David E. Calkin; Matthew P. Thompson; Mo Zhou

2014-01-01

In the United States, increased wildland fire activity over the last 15 years has resulted in increased pressure to balance the cost, benefits, and risks of wildfire management. Amid increased public scrutiny and a highly variable wildland fire environment, a substantial body of research has developed to study factors affecting the cost-effectiveness of wildfire...

Optimizing smoke and plume rise modeling approaches at local scales

Treesearch

Derek V. Mallia; Adam K. Kochanski; Shawn P. Urbanski; John C. Lin

2018-01-01

Heating from wildfires adds buoyancy to the overlying air, often producing plumes that vertically distribute fire emissions throughout the atmospheric column over the fire. The height of the rising wildfire plume is a complex function of the size of the wildfire, fire heat flux, plume geometry, and atmospheric conditions, which can make simulating plume rises difficult...

Protect Thy Neighbor: Investigating the Spatial Externalities of Community Wildfire Hazard Mitigation

Treesearch

David Butry; Geoffrey Donovan

2008-01-01

Climate change, increased wildland fuels, and residential development patterns in fire-prone areas all combine to make wildfire risk mitigation an important public policy issue. One approach to wildfire risk mitigation is to encourage homeowners to use fire-resistant building materials and to create defensible spaces around their homes. We develop a theoretical model...

Characterization of Wildfire-Induced Aerosol Emissions From the Maritime Continent Peatland and Central African Dry Savannah with MISR and CALIPSO Aerosol Products

NASA Astrophysics Data System (ADS)

Lee, Huikyo; Jeong, Su-Jong; Kalashnikova, Olga; Tosca, Mika; Kim, Sang-Woo; Kug, Jong-Seong

2018-03-01

Aerosol plumes from wildfires affect the Earth's climate system through regulation of the radiative budget and clouds. However, optical properties of aerosols from individual wildfire smoke plumes and their resultant impact on regional climate are highly variable. Therefore, there is a critical need for observations that can constrain the partitioning between different types of aerosols. Here we present the apparent influence of regional ecosystem types on optical properties of wildfire-induced aerosols based on remote sensing observations from two satellite instruments and three ground stations. The independent observations commonly show that the ratio of the absorbing aerosols is significantly lower in smoke plumes from the Maritime Continent than those from Central Africa, so that their impacts on regional climate are different. The observed light-absorbing properties of wildfire-induced aerosols are explained by dominant ecosystem types such as wet peatlands for the Maritime Continent and dry savannah for Central Africa, respectively. These results suggest that the wildfire-aerosol-climate feedback processes largely depend on the terrestrial environments from which the fires originate. These feedbacks also interact with climate under greenhouse warming. Our analysis shows that aerosol optical properties retrieved based on satellite observations are critical in assessing wildfire-induced aerosols forcing in climate models. The optical properties of carbonaceous aerosol mixtures used by state-of-the-art chemistry climate models may overestimate emissions for absorbing aerosols from wildfires over the Maritime Continent.

Assessing influences on social vulnerability to wildfire using surveys, spatial data and wildfire simulations.

PubMed

Paveglio, Travis B; Edgeley, Catrin M; Stasiewicz, Amanda M

2018-05-01

A growing body of research focuses on identifying patterns among human populations most at risk from hazards such as wildfire and the factors that help explain performance of mitigations that can help reduce that risk. Emerging policy surrounding wildfire management emphasizes the need to better understand such social vulnerability-or human populations' potential exposure to and sensitivity from wildfire-related impacts, including their ability to reduce negative impacts from the hazard. Studies of social vulnerability to wildfire often pair secondary demographic data with a variety of vegetation and wildfire simulation models to map potential risk. However, many of the assumptions made by those researchers about the demographic, spatial or perceptual factors that influence social vulnerability to wildfire have not been fully evaluated or tested against objective measures of potential wildfire risk. The research presented here utilizes self-reported surveys, GIS data, and wildfire simulations to test the relationships between select perceptual, demographic, and property characteristics of property owners against empirically simulated metrics for potential wildfire related damages or exposure. We also evaluate how those characteristics relate to property owners' performance of mitigations or support for fire management. Our results suggest that parcel characteristics provide the most significant explanation of variability in wildfire exposure, sensitivity and overall wildfire risk, while the positive relationship between income or property values and components of social vulnerability stands in contrast to typical assumptions from existing literature. Respondents' views about agency or government management helped explain a significant amount of variance in wildfire sensitivity, while the importance of wildfire risk in selecting a residence was an important influence on mitigation action. We use these and other results from our effort to discuss updated considerations for determining social vulnerability to wildfire and articulate alternative means to collect such information. Copyright © 2018 Elsevier Ltd. All rights reserved.

A numerical modeling investigation of erosion and debris flows following the 2016 Fish Fire in the San Gabriel Mountains, CA, USA

NASA Astrophysics Data System (ADS)

Tang, H.; McGuire, L.; Rengers, F. K.; Kean, J. W.; Staley, D. M.

2017-12-01

Wildfire significantly changes the hydrological characteristics of soil for a period of several years and increases the likelihood of flooding and debris flows during high-intensity rainfall in steep watersheds. Hazards related to post-fire flooding and debris flows increase as populations expand into mountainous areas that are susceptible to wildfire, post-wildfire flooding, and debris flows. However, our understanding of post-wildfire debris flows is limited due to a paucity of direct observations and measurements, partially due to the remote locations where debris flows tend to initiate. In these situations, numerical modeling becomes a very useful tool for studying post-wildfire debris flows. Research based on numerical modeling improves our understanding of the physical mechanisms responsible for the increase in erosion and consequent formation of debris flows in burned areas. In this contribution, we study changes in sediment transport efficiency with time since burning by combining terrestrial laser scanning (TLS) surveys of a hillslope burned during the 2016 Fish Fire with numerical modeling of overland flow and sediment transport. We also combine the numerical model with measurements of debris flow timing to explore relationships between post-wildfire rainfall characteristics, soil infiltration capacity, hillslope erosion, and debris flow initiation at the drainage basin scale. Field data show that an initial rill network developed on the hillslope, and became more efficient over time as the overall rill density decreased. Preliminary model results suggest that this can be achieved when flow driven detachment mechanisms dominate and raindrop-driven detachment is minimized. Results also provide insight into the hydrologic and geomorphic conditions that lead to debris flow initiation within recently burned areas.

Capturing spatiotemporal variation in wildfires for improving postwildfire debris-flow hazard assessments: Chapter 20

USGS Publications Warehouse

Haas, Jessica R.; Thompson, Matthew P.; Tillery, Anne C.; Scott, Joe H.

2017-01-01

Wildfires can increase the frequency and magnitude of catastrophic debris flows. Integrated, proactive natural hazard assessment would therefore characterize landscapes based on the potential for the occurrence and interactions of wildfires and postwildfire debris flows. This chapter presents a new modeling effort that can quantify the variability surrounding a key input to postwildfire debris-flow modeling, the amount of watershed burned at moderate to high severity, in a prewildfire context. The use of stochastic wildfire simulation captures variability surrounding the timing and location of ignitions, fire weather patterns, and ultimately the spatial patterns of watershed area burned. Model results provide for enhanced estimates of postwildfire debris-flow hazard in a prewildfire context, and multiple hazard metrics are generated to characterize and contrast hazards across watersheds. Results can guide mitigation efforts by allowing planners to identify which factors may be contributing the most to the hazard rankings of watersheds.

Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management.

PubMed

Hand, Michael S; Wibbenmeyer, Matthew J; Calkin, David E; Thompson, Matthew P

2015-10-01

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting. © 2015 Society for Risk Analysis.

Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems.

PubMed

Coates, Peter S; Ricca, Mark A; Prochazka, Brian G; Brooks, Matthew L; Doherty, Kevin E; Kroger, Travis; Blomberg, Erik J; Hagen, Christian A; Casazza, Michael L

2016-10-25

Iconic sagebrush ecosystems of the American West are threatened by larger and more frequent wildfires that can kill sagebrush and facilitate invasion by annual grasses, creating a cycle that alters sagebrush ecosystem recovery post disturbance. Thwarting this accelerated grass-fire cycle is at the forefront of current national conservation efforts, yet its impacts on wildlife populations inhabiting these ecosystems have not been quantified rigorously. Within a Bayesian framework, we modeled 30 y of wildfire and climatic effects on population rates of change of a sagebrush-obligate species, the greater sage-grouse, across the Great Basin of western North America. Importantly, our modeling also accounted for variation in sagebrush recovery time post fire as determined by underlying soil properties that influence ecosystem resilience to disturbance and resistance to invasion. Our results demonstrate that the cumulative loss of sagebrush to direct and indirect effects of wildfire has contributed strongly to declining sage-grouse populations over the past 30 y at large spatial scales. Moreover, long-lasting effects from wildfire nullified pulses of sage-grouse population growth that typically follow years of higher precipitation. If wildfire trends continue unabated, model projections indicate sage-grouse populations will be reduced to 43% of their current numbers over the next three decades. Our results provide a timely example of how altered fire regimes are disrupting recovery of sagebrush ecosystems and leading to substantial declines of a widespread indicator species. Accordingly, we present scenario-based stochastic projections to inform conservation actions that may help offset the adverse effects of wildfire on sage-grouse and other wildlife populations.

Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems

USGS Publications Warehouse

Coates, Peter S.; Ricca, Mark; Prochazka, Brian; Brooks, Matthew L.; Doherty, Kevin E.; Kroger, Travis; Blomberg, Erik J.; Hagen, Christian A.; Casazza, Michael L.

2016-01-01

Iconic sagebrush ecosystems of the American West are threatened by larger and more frequent wildfires that can kill sagebrush and facilitate invasion by annual grasses, creating a cycle that alters sagebrush ecosystem recovery post disturbance. Thwarting this accelerated grass–fire cycle is at the forefront of current national conservation efforts, yet its impacts on wildlife populations inhabiting these ecosystems have not been quantified rigorously. Within a Bayesian framework, we modeled 30 y of wildfire and climatic effects on population rates of change of a sagebrush-obligate species, the greater sage-grouse, across the Great Basin of western North America. Importantly, our modeling also accounted for variation in sagebrush recovery time post fire as determined by underlying soil properties that influence ecosystem resilience to disturbance and resistance to invasion. Our results demonstrate that the cumulative loss of sagebrush to direct and indirect effects of wildfire has contributed strongly to declining sage-grouse populations over the past 30 y at large spatial scales. Moreover, long-lasting effects from wildfire nullified pulses of sage-grouse population growth that typically follow years of higher precipitation. If wildfire trends continue unabated, model projections indicate sage-grouse populations will be reduced to 43% of their current numbers over the next three decades. Our results provide a timely example of how altered fire regimes are disrupting recovery of sagebrush ecosystems and leading to substantial declines of a widespread indicator species. Accordingly, we present scenario-based stochastic projections to inform conservation actions that may help offset the adverse effects of wildfire on sage-grouse and other wildlife populations.

Sediment-phosphorus dynamics can shift aquatic ecology and cause downstream legacy effects after wildfire in large river systems.

PubMed

Emelko, Monica B; Stone, Micheal; Silins, Uldis; Allin, Don; Collins, Adrian L; Williams, Chris H S; Martens, Amanda M; Bladon, Kevin D

2016-03-01

Global increases in the occurrence of large, severe wildfires in forested watersheds threaten drinking water supplies and aquatic ecology. Wildfire effects on water quality, particularly nutrient levels and forms, can be significant. The longevity and downstream propagation of these effects as well as the geochemical mechanisms regulating them remain largely undocumented at larger river basin scales. Here, phosphorus (P) speciation and sorption behavior of suspended sediment were examined in two river basins impacted by a severe wildfire in southern Alberta, Canada. Fine-grained suspended sediments (<125 μm) were sampled continuously during ice-free conditions over a two-year period (2009-2010), 6 and 7 years after the wildfire. Suspended sediment samples were collected from upstream reference (unburned) river reaches, multiple tributaries within the burned areas, and from reaches downstream of the burned areas, in the Crowsnest and Castle River basins. Total particulate phosphorus (TPP) and particulate phosphorus forms (nonapatite inorganic P, apatite P, organic P), and the equilibrium phosphorus concentration (EPC0 ) of suspended sediment were assessed. Concentrations of TPP and the EPC0 were significantly higher downstream of wildfire-impacted areas compared to reference (unburned) upstream river reaches. Sediments from the burned tributary inputs contained higher levels of bioavailable particulate P (NAIP) - these effects were also observed downstream at larger river basin scales. The release of bioavailable P from postfire, P-enriched fine sediment is a key mechanism causing these effects in gravel-bed rivers at larger basin scales. Wildfire-associated increases in NAIP and the EPC0 persisted 6 and 7 years after wildfire. Accordingly, this work demonstrated that fine sediment in gravel-bed rivers is a significant, long-term source of in-stream bioavailable P that contributes to a legacy of wildfire impacts on downstream water quality, aquatic ecology, and drinking water treatability. © 2015 John Wiley & Sons Ltd.

Effect of wildfires on physicochemical changes of watershed dissolved organic matter.

PubMed

Revchuk, Alex D; Suffet, I H

2014-04-01

Physicochemical characterization of dissolved organic carbon (DOC) provides essential data to describe watershed characteristics after drastic changes caused by wildfires. Post-fire watershed behavior is important for water source selection, management, and drinking water treatment optimization. Using ash and other burned vegetation fragments, a leaching procedure was implemented to describe physicochemical changes to watershed DOC caused by wildfires. Samples were collected after the 2007 and 2009 wildfires near Santa Barbara, California. Substantial differences in size distribution (measured by ultrafiltration), polarity (measured by polarity rapid assessment method), and the origin of leached DOC (measured by fluorescence) were observed between burned and unburned sites. Recently burned ash had 10 times the DOC leaching potential, and was dominated by large size fragments, compared to weathered 2-year-old ash. Charged DOC fractions were found to positively correlate with DOC size, whereas hydrophobic and hydrophilic DOC fractions were not. Proteins were only observed in recently burned ash and were indicative of recent post-fire biological activity.

Social amplification of wildfire risk: The role of social interactions and information sources

Treesearch

Hannah Brenkert-Smith; Katherine L. Dickinson; Patricia A. Champ; Nicholas Flores

2013-01-01

Wildfire is a persistent and growing threat across much of the western United States. Understanding how people living in fire-prone areas perceive this threat is essential to the design of effective risk management policies. Drawing on the social amplification of risk framework, we develop a conceptual model of wildfire risk perceptions that incorporates the social...

Evaluating alternative prescribed burning policies to reduce net economic damages from wildfire

Treesearch

D. Evan Mercer; Jeffrey P. Prestemon; David T. Butry; John M. Pye

2007-01-01

We estimate a wildfire risk model with a new measure of wildfire output, intensity-weighted risk and use it in Monte Carlo simulations to estimate welfare changes from alternative prescribed burning policies. Using Volusia County, Florida as a case study, an annual prescribed burning rate of 13% of all forest lands maximizes net welfare; ignoring the effects on...

Comparing production function models for wildfire risk analysis in the wildland-urban interface

Treesearch

D. Evan Mercer; Jeffrey P. Prestemon

2005-01-01

Wildfires create damages in the wildland-urban interface (WUI) that total hundreds of millions of dollars annually in the United States. Understanding how fires are produced in built-up areas near and within fire prone landscapes requires evaluating and quantifling the roles that humans play in fire regimes. We outline a typology of wildfire production functions (WPFs...

What Is the Price of Catastrophic Wildfire?

Treesearch

David T. Butry; D. Evan Mercer; Jeffrey P. Prestemon; John M. Pye; Thomas P. Holmes

2001-01-01

We modeled and analyzed the economic impacts of the six weeks of large, catastrophic wild-fires in northeastern Florida in June and July 1998, among Florida's most devastating in recent history. The result of the unusually strong El Níño-Southern Oscillation (ENSO) in 1998, the Florida wildfires produced economic impacts of at least $600 million, similar in...

Using the forest, people, fire agent-based social network model to investigate interactions in social-ecological systems

Treesearch

Paige Fischer; Adam Korejwa; Jennifer Koch; Thomas Spies; Christine Olsen; Eric White; Derric Jacobs

2013-01-01

Wildfire links social and ecological systems in dry-forest landscapes of the United States. The management of these landscapes, however, is bifurcated by two institutional cultures that have different sets of beliefs about wildfire, motivations for managing wildfire risk, and approaches to administering policy. Fire protection, preparedness, and response agencies often...

Future respiratory hospital admissions from wildfire smoke under climate change in the Western US

NASA Astrophysics Data System (ADS)

Coco Liu, Jia; Mickley, Loretta J.; Sulprizio, Melissa P.; Yue, Xu; Peng, Roger D.; Dominici, Francesca; Bell, Michelle L.

2016-12-01

Background. Wildfires are anticipated to be more frequent and intense under climate change. As a result, wildfires may emit more air pollutants that can harm health in communities in the future. The health impacts of wildfire smoke under climate change are largely unknown. Methods. We linked projections of future levels of fine particulate matter (PM2.5) specifically from wildfire smoke under the A1B climate change scenario using the GEOS-Chem model for 2046-2051, present-day estimates of hospital admission impacts from wildfire smoke, and future population projections to estimate the change in respiratory hospital admissions for persons ≥65 years by county (n = 561) from wildfire PM2.5 under climate change in the Western US. Results. The increase in intense wildfire smoke days from climate change would result in an estimated 178 (95% confidence interval: 6.2, 361) additional respiratory hospital admissions in the Western US, accounting for estimated future increase in the elderly population. Climate change is estimated to impose an additional 4990 high-pollution smoke days. Central Colorado, Washington and southern California are estimated to experience the highest percentage increase in respiratory admissions from wildfire smoke under climate change. Conclusion. Although the increase in number of respiratory admissions from wildfire smoke seems modest, these results provide important scientific evidence of an often-ignored aspect of wildfire impact, and information on their anticipated spatial distribution. Wildfires can cause serious social burdens such as property damage and suppression cost, but can also raise health problems. The results provide information that can be incorporated into development of environmental and health policies in response to climate change. Climate change adaptation policies could incorporate scientific evidence on health risks from natural disasters such as wildfires.

Wildfire-specific Fine Particulate Matter and Risk of Hospital Admissions in Urban and Rural Counties.

PubMed

Liu, Jia Coco; Wilson, Ander; Mickley, Loretta J; Dominici, Francesca; Ebisu, Keita; Wang, Yun; Sulprizio, Melissa P; Peng, Roger D; Yue, Xu; Son, Ji-Young; Anderson, G Brooke; Bell, Michelle L

2017-01-01

The health impacts of wildfire smoke, including fine particles (PM2.5), are not well understood and may differ from those of PM2.5 from other sources due to differences in concentrations and chemical composition. First, for the entire Western United States (561 counties) for 2004-2009, we estimated daily PM2.5 concentrations directly attributable to wildfires (wildfires-specific PM2.5), using a global chemical transport model. Second, we defined smoke wave as ≥2 consecutive days with daily wildfire-specific PM2.5 > 20 μg/m, with sensitivity analysis considering 23, 28, and 37 μg/m. Third, we estimated the risk of cardiovascular and respiratory hospital admissions associated with smoke waves for Medicare enrollees. We used a generalized linear mixed model to estimate the relative risk of hospital admissions on smoke wave days compared with matched comparison days without wildfire smoke. We estimated that about 46 million people of all ages were exposed to at least one smoke wave during 2004 to 2009 in the Western United States. Of these, 5 million are Medicare enrollees (≥65 years). We found a 7.2% (95% confidence interval: 0.25%, 15%) increase in risk of respiratory admissions during smoke wave days with high wildfire-specific PM2.5 (>37 μg/m) compared with matched non smoke wave days. We did not observe an association between smoke wave days with wildfire-specific PM2.5 ≤ 37 μg/mand respiratory or cardiovascular admissions. Respiratory effects of wildfire-specific PM2.5 may be stronger than that of PM2.5 from other sources. Short-term exposure to wildfire-specific PM2.5was associated with risk of respiratory diseases in the elderly population in the Western United States during severe smoke days. See video abstract at, http://links.lww.com/EDE/B137.

Wildfire-specific Fine Particulate Matter and Risk of Hospital Admissions in Urban and Rural Counties

PubMed Central

Liu, Jia Coco; Wilson, Ander; Mickley, Loretta J; Dominici, Francesca; Ebisu, Keita; Wang, Yun; Sulprizio, Melissa P; Peng, Roger D; Yue, Xu; Son, Ji-Young; Anderson, G. Brooke; Bell, Michelle L.

2016-01-01

Background The health impacts of wildfire smoke, including fine particles (PM2.5), are not well understood and may differ from those of PM2.5 from other sources due to differences in concentrations and chemical composition. Methods First, for the entire Western US (561 counties) for 2004–2009, we estimated daily PM2.5 concentrations directly attributable to wildfires (wildfires-specific PM2.5), using a global chemical transport model. Second, we defined smoke wave as ≥2 consecutive days with daily wildfire-specific PM2.5>20µg/m3, with sensitivity analysis considering 23µg/m3, 28µg/m3, and 37µg/m3. Third, we estimated the risk of cardiovascular and respiratory hospital admissions associated with smoke waves for Medicare enrollees. We used a generalized linear mixed model to estimate the relative risk of hospital admissions on smoke wave days compared to matched comparison days without wildfire smoke. Results We estimated that about 46 million people of all ages were exposed to at least one smoke wave during 2004 to 2009 in the Western US. Of these, 5 million are Medicare enrollees (≥65y). We found a 7.2% (95% confidence interval: 0.25%, 15%) increase in risk of respiratory admissions during smoke wave days with high wildfire-specific PM2.5 (>37µg/m3) compared to matched non-smoke-wave days. We did not observe an association between smoke wave days with wildfire-PM2.5≤37µg/m3 and respiratory or cardiovascular admissions. Respiratory effects of wildfire-specific PM2.5 may be stronger than that of PM2.5 from other sources. Conclusion Short-term exposure to wildfire-specific PM2.5 was associated with risk of respiratory diseases in the elderly population in the Western US during severe smoke days. PMID:27648592

Assessing Landscape Scale Wildfire Exposure for Highly Valued Resources in a Mediterranean Area

NASA Astrophysics Data System (ADS)

Alcasena, Fermín J.; Salis, Michele; Ager, Alan A.; Arca, Bachisio; Molina, Domingo; Spano, Donatella

2015-05-01

We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km2 located in central Sardinia, Italy. The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap. We simulated 90,000 fires that replicated recent large fire events in the area spreading under severe weather conditions to generate detailed maps of wildfire likelihood and intensity. Then, we linked fire modeling outputs to a geospatial risk assessment framework focusing on buffer areas around HVR. The results highlighted a large variation in burn probability and fire intensity in the vicinity of HVRs, and allowed us to identify the areas most exposed to wildfires and thus to a higher potential damage. Fire intensity in the HVR buffers was mainly related to fuel types, while wind direction, topographic features, and historically based ignition pattern were the key factors affecting fire likelihood. The methodology presented in this work can have numerous applications, in the study area and elsewhere, particularly to address and inform fire risk management, landscape planning and people safety on the vicinity of HVRs.

Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

PubMed

Reid, Colleen E; Jerrett, Michael; Petersen, Maya L; Pfister, Gabriele G; Morefield, Philip E; Tager, Ira B; Raffuse, Sean M; Balmes, John R

2015-03-17

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.

Synthesis of knowledge of extreme fire behavior: volume 2 for fire behavior specialists, researchers, and meteorologists

Treesearch

Paul A. Werth; Brian E. Potter; Martin E. Alexander; Craig B. Clements; Miguel G. Cruz; Mark A. Finney; Jason M. Forthofer; Scott L. Goodrick; Chad Hoffman; W. Matt Jolly; Sara S. McAllister; Roger D. Ottmar; Russell A. Parsons

2016-01-01

The National Wildfire Coordinating Group’s definition of extreme fire behavior indicates a level of fire behavior characteristics that ordinarily precludes methods of direct control action. One or more of the following is usually involved: high rate of spread, prolific crowning/ spotting, presence of fire whirls, and strong convection column. Predictability is...

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Massada, Avi Bar; Radeloff, Volker C.; Stewart, Susan I.; Hawbaker, Todd J.

2009-01-01

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfirerisk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfirerisk to a 60,000 ha WUI area in northwesternWisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfirerisk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfirerisk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfirerisk and those most vulnerable under extreme weather conditions.

Evaluation of High Resolution Rapid Refresh-Smoke (HRRR-Smoke) model products for a case study using surface PM2.5 observations

NASA Astrophysics Data System (ADS)

Deanes, L. N.; Ahmadov, R.; McKeen, S. A.; Manross, K.; Grell, G. A.; James, E.

2016-12-01

Wildfires are increasing in number and size in the western United States as climate change contributes to warmer and drier conditions in this region. These fires lead to poor air quality and diminished visibility. The High Resolution Rapid Refresh-Smoke modeling system (HRRR-Smoke) is designed to simulate fire emissions and smoke transport with high resolution. The model is based on the Weather Research and Forecasting model, coupled with chemistry (WRF-Chem) and uses fire detection data from the Visible Infrared and Imaging Radiometer Suite (VIIRS) satellite instrument to simulate wildfire emissions and their plume rise. HRRR-Smoke is used in both real-time applications and case studies. In this study, we evaluate the HRRR-Smoke for August 2015, during one of the worst wildfire seasons on record in the United States, by focusing on wildfires that occurred in the northwestern US. We compare HRRR-Smoke simulations with hourly fine particulate matter (PM2.5) observations from the Air Quality System (https://www.epa.gov/aqs) from multiple air quality monitoring sites in Washington state. PM2.5 data includes measurements from urban, suburban and remote sites in the state. We discuss the model performance in capturing large PM2.5 enhancements detected at surface sites due to wildfires. We present various statistical parameters to demonstrate HRRR-Smoke's performance in simulating surface PM2.5 levels.

Evaluation of Enviro-HIRLAM model and aerosols effect during wildfires episodes in Europe and Central Russia in summer 2010

NASA Astrophysics Data System (ADS)

Nuterman, Roman; Pagh Nielsen, Kristian; Baklanov, Alexander; Kaas, Eigil

2014-05-01

The summer of 2010 was characterized by severe weather events such as floods, heat waves and droughts across Middle East, most of Europe and European Russia. Among them the wildfires in Portugal and European Russia were some of the most prominent and led to substantial increase of atmospheric aerosols concentration. For instance, pollution from Russian wildfires, which were the most noticeable, spread around the entire central part of the country and also dispersed towards the Northern Europe. This study is devoted to Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) model evaluation and analysis of radiation balance change due to increased aerosol burden caused by wildfires in Russia. For this purpose the model was forced by boundary and initial conditions produced by ECMWF (European Center for Medium-Range Weather Forecast) IFS and MOZART models for meteorology and atmospheric composition, respectively. The model setup included aerosol microphysics module M7 with simple tropospheric sulfur chemistry, anthropogenic emissions by TNO, wildfires emissions by FMI and interactive sea-salt and dust emissions. During the model run surface data assimilation of meteorological parameters was applied. The HIRLAM Savijarvi radiation scheme has been improved to account explicitly for aerosol radiation interactions. So that the short-wave radiative transfer calculations are performed as standard 2-stream calculations for averages of aerosol optical properties weighted over the entire spectrum. The model shows good correlation of particulate matter (PM) concentrations on diurnal cycle as well as day-to-day variability, but one always has negative bias of PM. The Enviro-HIRLAM is able to capture concentration peaks both from short-term and long-term trans boundary transport of PM and predicted the Aerosol Optical Thickness (at 550 nm) up to 2 over wildfire-polluted regions. And the direct radiative forcing is less than -100 W/m2.

Highly buoyant bent-over plumes in a boundary layer

NASA Astrophysics Data System (ADS)

Tohidi, Ali; Kaye, Nigel B.

2016-04-01

Highly buoyant plumes, such as wildfire plumes, in low to moderate wind speeds have initial trajectories that are steeper than many industrial waste plumes. They will rise further into the atmosphere before bending significantly. In such cases the plume's trajectory will be influenced by the vertical variation in horizontal velocity of the atmospheric boundary layer. This paper examined the behavior of a plume in an unstratified environment with a power-law ambient velocity profile. Examination of previously published experimental measurements of plume trajectory show that inclusion of the boundary layer velocity profile in the plume model often provides better predictions of the plume trajectory compared to algebraic expressions developed for uniform flow plumes. However, there are many cases in which uniform velocity profile algebraic expressions are as good as boundary layer models. It is shown that it is only important to model the role of the atmospheric boundary layer velocity profile in cases where either the momentum length (square root of source momentum flux divided by the reference wind speed) or buoyancy length (buoyancy flux divided by the reference wind speed cubed) is significantly greater than the plume release height within the boundary layer. This criteria is rarely met with industrial waste plumes, but it is important in modeling wildfire plumes.

Seeking common ground: protecting homes from wildfires while making forests more resilient to fire

Treesearch

Noreen Parks; Alan Ager

2011-01-01

Federal policies direct public-land managers to reduce wildfire risks for urban areas close to wildlands, while broader agency goals call for landscape restoration to create fire-resilient forests. This study used wildfires simulation modeling to examine the tradeoffs between focusing fuel reduction efforts on a wildland-urban interface (WUI) in Oregon’s Blue Mountains...

Analyzing wildfire exposure and source–sink relationships on a fire prone forest landscape

Treesearch

Alan A. Ager; Nicole M. Vaillant; Mark A. Finney; Haiganoush K. Preisler

2012-01-01

We used simulation modeling to analyze wildfire exposure to social and ecological values on a 0.6 million ha national forest in central Oregon, USA. We simulated 50,000 wildfires that replicated recent fire events in the area and generated detailed maps of burn probability (BP) and fire intensity distributions. We also recorded the ignition locations and size of each...

A mixed logit model of homeowner preferences for wildfire hazard reduction

Treesearch

Thomas P. Holmes; John Loomis; Armando González-Cabán

2009-01-01

People living in the wildland-urban interface (WUI) are at greater risk of suffering major losses of property and life from wildfires. Over the past several decades the prevailing view has been that wildfire risk in rural areas was exogenous to the activities of homeowners. In response to catastrophic fires in the WUI over the past few years, recent approaches to fire...

A Mixed Logit Model of Homeowner Preferences for Wildfire Hazard Reduction

Treesearch

Thomas P. Holmes; John Loomis; Armando Gonzalez-Caban

2010-01-01

People living in the wildland-urban interface (WUI) are at greater risk of suffering major losses of property and life from wildfires. Over the past several decades the prevailing view has been that wildfire risk in rural areas was exogenous to the activities of homeowners. In response to catastrophic fires in the WUI over the past few years, recent approaches to fire...

Economic analysis of prescribed burning for wildfire management in Western Australia

Treesearch

Veronique Florec; David Pannell; Michael Burton; Joel Kelso; Drew Mellor; George Milne

2013-01-01

Wildfires can cause significant damage to ecosystems, life and property, and wildfire events that do not involve people and property are becoming rare. With the expansion of the rural– urban interface in Western Australia and elsewhere, objectives of life and property protection become more difficult to achieve. We applied the cost plus net value change (C+NVC) model...

Minority households’ willingness to pay for public and private wildfire risk reduction in Florida

Treesearch

Armando González-Cabán; José J. Sánchez

2017-01-01

The purpose of this work is to estimate willingness to pay (WTP) for minority (African-American and Hispanic) homeowners in Florida for private and public wildfire risk-reduction programs and also to test for differences in response between the two groups. A random parameter logit and latent class model allowed us to determine if there is a difference in wildfire...

Assessing watershed-wildfire risks on National Forest System lands in the Rocky Mountain Region of the United States

Treesearch

Matthew P. Thompson; Joe Scott; Paul G. Langowski; Julie W. Gilbertson-Day; Jessica R. Haas; Elise M. Bowne

2013-01-01

Wildfires can cause significant negative impacts to water quality with resultant consequences for the environment and human health and safety, as well as incurring substantial rehabilitation and water treatment costs. In this paper we will illustrate how state-of-the-art wildfire simulation modeling and geospatial risk assessment methods can be brought to bear to...

Carbon benefits from fuel treatments

Treesearch

Jim Cathcart; Alan A. Ager; Andrew McMahan; Mark Finney; Brian Watt

2010-01-01

Landscape simulation modeling is used to examine whether fuel treatments result in a carbon offset from avoided wildfire emissions. The study landscape was a 169,200-acre watershed located in south-central Oregon. Burn probability modeling was employed under extreme weather and fuel moisture conditions. Expected carbon stocks post-treatment, post-wildfire were...

Measuring the effect of fuel treatments on forest carbon using landscape risk analysis

NASA Astrophysics Data System (ADS)

Ager, A. A.; Finney, M. A.; McMahan, A.; Cathcart, J.

2010-12-01

Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the non-treatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the long-term balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.

Sources and Implications of Bias and Uncertainty in a Century of US Wildfire Activity Data

NASA Astrophysics Data System (ADS)

Short, K.

2013-12-01

The statistical analysis of wildfire activity is a critical component of national wildfire planning, operations, and research in the United States (US). Wildfire activity data have been collected in the US for over a century. Yet, to this day, no single unified system of wildfire record-keeping exists. Data for analysis are generally harvested from archival summary reports from federal or interagency fire organizations; incident-level wildfire reporting systems of the federal, state, and local fire services; and, increasingly, remote-sensing programs. It is typical for research into wildfire activity patterns for all or part of the last century to require data from several of these sources and perhaps others. That work is complicated by the disunity of the various datasets and potentially compromised by inherent reporting biases, discussed here. The availability of wildfire records with the information content and geospatial precision generally sought for increasingly popular climatological analyses and the modeling of contemporary wildfire risk is limited to recent decades. We explain how the disunity and idiosyncrasies of US wildfire reporting have largely precluded true interagency, or all-lands, analyses of even recent wildfire activity and hamstrung some early risk modeling efforts. We then describe our efforts to acquire, standardize, error-check, compile, scrub, and evaluate the completeness of US federal, state, and local wildfire records from 1992-2011 for the national interagency Fire Program Analysis (FPA) application. The resulting FPA Fire-Occurrence Database (FPA FOD) includes nearly 1.6 million records from the 20-year period, with values for at least the following core data elements: location at least as precise as a Public Land Survey System section (2.6-km2 grid), discovery date, and final fire size. The FPA FOD is publicly available from the Research Data Archive of the US Department of Agriculture, Forest Service (http://dx.doi.org/10.2737/RDS-2013-0009). While necessarily incomplete in some aspects, the database is intended to facilitate fairly high-resolution geospatial analysis of wildfire activity over the past two decades, based on available information from the authoritative systems of record. Formal non-federal wildfire reporting has been on the rise over the past several decades, and users of national datasets like the FPA FOD must beware of state and local reporting biases to avoid drawing spurious conclusions when analysing the data. Apparent trends in the numbers and area burned by wildfires, for example, may be the result of multiple factors, including changes in climate, fuels, demographics (e.g. population density), fire-management policies, and - as we underscore here - levels of reporting.

Potential changes in forest composition could reduce impacts of climate change on boreal wildfires.

PubMed

Terrier, Aurélie; Girardin, Martin P; Périé, Catherine; Legendre, Pierre; Bergeron, Yves

2013-01-01

There is general consensus that wildfires in boreal forests will increase throughout this century in response to more severe and frequent drought conditions induced by climate change. However, prediction models generally assume that the vegetation component will remain static over the next few decades. As deciduous species are less flammable than conifer species, it is reasonable to believe that a potential expansion of deciduous species in boreal forests, either occurring naturally or through landscape management, could offset some of the impacts of climate change on the occurrence of boreal wildfires. The objective of this study was to determine the potential of this offsetting effect through a simulation experiment conducted in eastern boreal North America. Predictions of future fire activity were made using multivariate adaptive regression splines (MARS) with fire behavior indices and ecological niche models as predictor variables so as to take into account the effects of changing climate and tree distribution on fire activity. A regional climate model (RCM) was used for predictions of future fire risk conditions. The experiment was conducted under two tree dispersal scenarios: the status quo scenario, in which the distribution of forest types does not differ from the present one, and the unlimited dispersal scenario, which allows forest types to expand their range to fully occupy their climatic niche. Our results show that future warming will create climate conditions that are more prone to fire occurrence. However, unlimited dispersal of southern restricted deciduous species could reduce the impact of climate change on future fire occurrence. Hence, the use of deciduous species could be a good option for an efficient strategic fire mitigation strategy aimed at reducing fire Propagation in coniferous landscapes and increasing public safety in remote populated areas of eastern boreal Canada under climate change.

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Church, Richard; Ustin, Susan L.; Brass, James A. (Technical Monitor)

2001-01-01

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Fine particulate matter (PM2.5 ) exposure during a prolonged wildfire period and emergency department visits for asthma.

PubMed

Haikerwal, Anjali; Akram, Muhammad; Sim, Malcolm R; Meyer, Mick; Abramson, Michael J; Dennekamp, Martine

2016-01-01

The 2006-2007 wildfire period was one of the most extensive and long lasting fires in Australian history with high levels of fine particulate matter (PM2.5 ). Large populations were exposed to smoke for over 2 months. The study aimed to investigate the association between wildfire-related PM2.5 exposure and emergency department (ED) visits for asthma. A time-stratified case-crossover design was used to investigate associations between daily average PM2.5 and ED attendances for asthma from December 2006 to January 2007. ED data were obtained from the Victorian Emergency Minimum Dataset. Smoke dispersion during the wildfire event was modelled using a validated chemical transport model. Exposure data (daily average PM2.5 , temperature and relative humidity) were modelled for the study period. Various lag periods were investigated. There were 2047 ED attendances for asthma during the study period. After adjusting for temperature and relative humidity, an interquartile range increase in PM2.5 levels of 8.6 μg/m(3) was associated with an increase in ED attendances for asthma by 1.96% (95%CI: 0.02, 3.94) on the day of exposure. Lag periods up to 2 days prior did not show any association. A strong association was observed among women 20 years and older (5.08% 95%CI: 1.76, 8.51). Wildfire-related PM2.5 was associated with increased risk of ED attendance for asthma during the wildfire event. It is important to understand the role of wildfire PM2.5 as a trigger for asthma presentations. © 2015 Asian Pacific Society of Respirology.

Chemical fields during Southeast Nexus (SENEX) field experiment and design of verification metrics for efficacy of capturing wild fire emissions

NASA Astrophysics Data System (ADS)

Lee, P.

2016-12-01

Wildfires are commonplace in North America. Air pollution resulted from wildfires pose a significant risk for human health and crop damage. The pollutants alter the vertical distribution of many atmospheric constituents including O3 and many fine particulate (PM) species. Compared to anthropogenic emissions of air pollutants, emissions from wildfires are largely uncontrolled and unpredictable. Therefore, quantitatively describing wildfire emissions and their contributions to air pollution remains a substantial challenge for atmospheric modeler and air quality forecasters. In this study, we investigated the modification and redistribution of atmospheric composition within the Conterminous U.S (CONUS) by wild fire plumes originated within and outside of the CONUS. We used the National Air Quality Forecasting Capability (NAQFC) to conduct the investigation. NAQFC uses dynamic lateral chemical boundary conditions derived from the National Weather Service experimental global aerosol tracer model accounting for intrusion of fire-associated aerosol species. Within CONUS, the NAQFC derives both gaseous and aerosol wildfire associated species from the National Environmental Satellite, Data, and Information Service (NESDIS) hazard mapping system (HMS) hot-spot detection, and US Forestry Service Blue-sky protocol for quantifying fire characteristics, and the US EPA Sparse Matrix Object Kernel Emission (SMOKE) calculation for plume rise. Attributions of both of these wildfire influences inherently reflect the aged plumes intruded into the CONUS through the model boundaries as well as the fresher emissions from sources within the CONUS. Both emission sources contribute significantly to the vertical structure modification of the atmosphere. We conducted case studies within the fire active seasons to demonstrate some possible impacts on the vertical structures of O3 and PM species by the wildfire activities.

Modeling Fire Emissions across Central and Southern Italy: Implications for Land and Fire Management

NASA Astrophysics Data System (ADS)

Bacciu, V. M.; Salis, M.; Spano, D.

2015-12-01

Fires play a relevant role in the global and regional carbon cycle, representing a remarkable source of CO2 and other greenhouse gases (GHG) that influence atmosphere budgets and climate. In addition, the wildfire increase projected in Southern Europe due to climate change (CC) and concurrent exacerbation of extreme weather conditions could also lead to a significant rise in GHG. Recently, in the context of the Italian National Adaptation Strategy to Climate Change (SNAC), several approaches were identified as valuable tools to adapt and mitigate the impacts of CC on wildfires, in order to reduce landscape susceptibility and to contribute to the efforts of carbon emission mitigation proposed within the Kyoto protocol. Active forest and fuel management (such as prescribed burning, fuel reduction and removal, weed and flammable shrub control, creation of fuel discontinuity) is recognised to be a key element to adapt and mitigate the impacts of CC on wildfires. Despite this, overall there is a lack of studies about the effectiveness of fire emission mitigation strategies. The current work aims to analyse the potential of a combination of fuel management practices in mitigating emissions from forest fires and evaluate valuable and viable options across Central and Southern Italy. These objectives were achieved throughout a retrospective application of an integrated approach combining a fire emission model (FOFEM - First Order Fire Effect Model) with spatially explicit, comprehensive, and accurate fire, vegetation and weather data for the period 2004-2012. Furthermore, a number of silvicultural techniques were combined to develop several fuel management scenarios and then tested to evaluate their potential in mitigating fire emissions.The preliminary results showed the crucial role of appropriate fuel, fire behavior, and weather data to reduce bias in quantifying the source and the composition of fire emissions and to attain reasonable estimations. Also, the current study highlighted that balanced combination of fuel management techniques could not only be a viable mean to reduce fire emissions but at the same time prevent future wildfires and the related threat to human lives and activities.

Pattern and process of prescribed fires influence effectiveness at reducing wildfire severity in dry coniferous forests

USGS Publications Warehouse

Arkle, Robert S.; Pilliod, David S.; Welty, Justin L.

2012-01-01

We examined the effects of three early season (spring) prescribed fires on burn severity patterns of summer wildfires that occurred 1–3 years post-treatment in a mixed conifer forest in central Idaho. Wildfire and prescribed fire burn severities were estimated as the difference in normalized burn ratio (dNBR) using Landsat imagery. We used GIS derived vegetation, topography, and treatment variables to generate models predicting the wildfire burn severity of 1286–5500 30-m pixels within and around treated areas. We found that wildfire severity was significantly lower in treated areas than in untreated areas and significantly lower than the potential wildfire severity of the treated areas had treatments not been implemented. At the pixel level, wildfire severity was best predicted by an interaction between prescribed fire severity, topographic moisture, heat load, and pre-fire vegetation volume. Prescribed fire severity and vegetation volume were the most influential predictors. Prescribed fire severity, and its influence on wildfire severity, was highest in relatively warm and dry locations, which were able to burn under spring conditions. In contrast, wildfire severity peaked in cooler, more mesic locations that dried later in the summer and supported greater vegetation volume. We found considerable evidence that prescribed fires have landscape-level influences within treatment boundaries; most notable was an interaction between distance from the prescribed fire perimeter and distance from treated patch edges, which explained up to 66% of the variation in wildfire severity. Early season prescribed fires may not directly target the locations most at risk of high severity wildfire, but proximity of these areas to treated patches and the discontinuity of fuels following treatment may influence wildfire severity and explain how even low severity treatments can be effective management tools in fire-prone landscapes.

Understanding Changes in Modeled Land Surface Characteristics Prior to Lightning-Initiated Holdover Fire Breakout

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Case, Jonathan L.; Hain, Christopher R.; White, Kristopher; Wachter, J. Brent; Nauslar, Nicholas; MacNamara, Brittany

2018-01-01

Lightning initiated wildfires are only 16% of the total number of wildfires within the United States, but account for 56% of the acreage burned. One of the challenges with lightning-initiated wildfires is their ability to "holdover" which means smolder for up to 2+ weeks before breaking out into a full fledged fire. This work helps characterize the percentage of holdover events due to lightning, and helps quantify changes in the land surface characteristics to help understand trends in soil moisture and vegetation stress that potentially contribute to the fire breaking out into a full wildfire.

Synthesis of knowledge of extreme fire behavior: volume I for fire managers

Treesearch

Paul A. Werth; Brian E. Potter; Craig B. Clements; Mark A. Finney; Scott L. Goodrick; Martin E. Alexander; Miguel G. Cruz; Jason A. Forthofer; Sara S. McAllister

2011-01-01

The National Wildfire Coordinating Group definition of extreme fire behavior (EFB) indicates a level of fire behavior characteristics that ordinarily precludes methods of direct control action. One or more of the following is usually involved: high rate of spread, prolific crowning/spotting, presence of fire whirls, and strong convection column. Predictability is...

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

USGS Publications Warehouse

Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.

2005-01-01

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

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...

Effects of fire suppression under a changing climate in Pacific Northwest mixed-pine forests

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Bart, R. R.; Kennedy, M. C.; Abatzoglou, J. T.; Kolden, C.; Adam, J. C.

2017-12-01

The frequency of large and severe wildfires has increased over recent decades in many regions across the Western U.S., including the Pacific and Inland Northwest. This increase is likely driven in large part by wildfire suppression, which has promoted fuel accumulation in western landscapes. Recent studies also suggest that anthropogenic climate change intensifies wildfire activity by increasing fuel aridity. However, the contribution of these drivers to observed changes in fire regime is not well quantified at regional scales. Understanding the relative influence of climate and fire suppression is crucial for both projecting the effects of climate change on future fire spread, and for developing site-specific fuel management strategies under a new climate paradigm. To quantify the extent to which fire suppression and climate change have contributed to increases in wildfire activity in the Pacific Northwest, we conduct a modeling experiment using the ecohydrologic model RHESSys and the coupled stochastic fire spread model WMFire. Specifically, we use historical climate inputs from GCMs, combined with fire suppression scenarios to gauge the extent to which these drivers promote the spread of severe wildfires in Johnson Creek, a large (565-km2) mixed-pine dominated subcatchment of the Southfork Salmon River; part of the larger Columbia River Basin. We run 500 model iterations for suppressed, intermediate, and unsuppressed fire management scenarios, both with and without climate change in a factorial design, focusing on fire spread surrounding two extreme fire years in Johnson Creek (1998 and 2007). After deriving fire spread "fingerprints" for each combination of possible drivers, we evaluate the extent to which these fingerprints match observations in the fire record. We expect that climate change plays a role in the spread of large and severe wildfires in Johnson Creek, but the magnitude of this effect is mediated by prior suppression. Preliminary results suggest that management strategies aimed at reducing the extent of contiguous even-aged fuels may help curtail climate-driven increases in wildfire severity in Pacific Northwest watersheds.

Birth weight following pregnancy during the 2003 Southern California wildfires.

PubMed

Holstius, David M; Reid, Colleen E; Jesdale, Bill M; Morello-Frosch, Rachel

2012-09-01

In late October 2003, a series of wildfires exposed urban populations in Southern California to elevated levels of air pollution over several weeks. Previous research suggests that short-term hospital admissions for respiratory outcomes increased specifically as a result of these fires. We assessed the impact of a wildfire event during pregnancy on birth weight among term infants. Using records for singleton term births delivered to mothers residing in California's South Coast Air Basin (SoCAB) during 2001-2005 (n = 886,034), we compared birth weights from pregnancies that took place entirely before or after the wildfire event (n = 747,590) with those where wildfires occurred during the first (n = 60,270), second (n = 39,435), or third (n = 38,739) trimester. The trimester-specific effects of wildfire exposure were estimated using a fixed-effects regression model with several maternal characteristics included as covariates. Compared with pregnancies before and after the wildfires, mean birth weight was estimated to be 7.0 g lower [95% confidence interval (CI): -11.8, -2.2] when the wildfire occurred during the third trimester, 9.7 g lower when it occurred during the second trimester (95% CI: -14.5, -4.8), and 3.3 g lower when it occurred during the first trimester (95% CI: -7.2, 0.6). Pregnancy during the 2003 Southern California wildfires was associated with slightly reduced average birth weight among infants exposed in utero. The extent and increasing frequency of wildfire events may have implications for infant health and development.

Assessing landscape scale wildfire exposure for highly valued resources in a Mediterranean area.

PubMed

Alcasena, Fermín J; Salis, Michele; Ager, Alan A; Arca, Bachisio; Molina, Domingo; Spano, Donatella

2015-05-01

We used a fire simulation modeling approach to assess landscape scale wildfire exposure for highly valued resources and assets (HVR) on a fire-prone area of 680 km(2) located in central Sardinia, Italy. The study area was affected by several wildfires in the last half century: some large and intense fire events threatened wildland urban interfaces as well as other socioeconomic and cultural values. Historical wildfire and weather data were used to inform wildfire simulations, which were based on the minimum travel time algorithm as implemented in FlamMap. We simulated 90,000 fires that replicated recent large fire events in the area spreading under severe weather conditions to generate detailed maps of wildfire likelihood and intensity. Then, we linked fire modeling outputs to a geospatial risk assessment framework focusing on buffer areas around HVR. The results highlighted a large variation in burn probability and fire intensity in the vicinity of HVRs, and allowed us to identify the areas most exposed to wildfires and thus to a higher potential damage. Fire intensity in the HVR buffers was mainly related to fuel types, while wind direction, topographic features, and historically based ignition pattern were the key factors affecting fire likelihood. The methodology presented in this work can have numerous applications, in the study area and elsewhere, particularly to address and inform fire risk management, landscape planning and people safety on the vicinity of HVRs.

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Wildfire air pollution hazard during the 21st century

NASA Astrophysics Data System (ADS)

Knorr, Wolfgang; Dentener, Frank; Lamarque, Jean-François; Jiang, Leiwen; Arneth, Almut

2017-07-01

Wildfires pose a significant risk to human livelihoods and are a substantial health hazard due to emissions of toxic smoke. Previous studies have shown that climate change, increasing atmospheric CO2, and human demographic dynamics can lead to substantially altered wildfire risk in the future, with fire activity increasing in some regions and decreasing in others. The present study re-examines these results from the perspective of air pollution risk, focussing on emissions of airborne particulate matter (PM2. 5), combining an existing ensemble of simulations using a coupled fire-dynamic vegetation model with current observation-based estimates of wildfire emissions and simulations with a chemical transport model. Currently, wildfire PM2. 5 emissions exceed those from anthropogenic sources in large parts of the world. We further analyse two extreme sets of future wildfire emissions in a socio-economic, demographic climate change context and compare them to anthropogenic emission scenarios reflecting current and ambitious air pollution legislation. In most regions of the world, ambitious reductions of anthropogenic air pollutant emissions have the potential to limit mean annual pollutant PM2. 5 levels to comply with World Health Organization (WHO) air quality guidelines for PM2. 5. Worst-case future wildfire emissions are not likely to interfere with these annual goals, largely due to fire seasonality, as well as a tendency of wildfire sources to be situated in areas of intermediate population density, as opposed to anthropogenic sources that tend to be highest at the highest population densities. However, during the high-fire season, we find many regions where future PM2. 5 pollution levels can reach dangerous levels even for a scenario of aggressive reduction of anthropogenic emissions.

Factors related to building loss due to wildfires in the conterminous United States.

PubMed

Alexandre, Patricia M; Stewart, Susan I; Keuler, Nicholas S; Clayton, Murray K; Mockrin, Miranda H; Bar-Massada, Avi; Syphard, Alexandra D; Radeloff, Volker C

2016-10-01

Wildfire is globally an important ecological disturbance affecting biochemical cycles and vegetation composition, but also puts people and their homes at risk. Suppressing wildfires has detrimental ecological effects and can promote larger and more intense wildfires when fuels accumulate, which increases the threat to buildings in the wildland-urban interface (WUI). Yet, when wildfires occur, typically only a small proportion of the buildings within the fire perimeter are lost, and the question is what determines which buildings burn. Our goal was to examine which factors are related to building loss when a wildfire occurs throughout the United States. We were particularly interested in the relative roles of vegetation, topography, and the spatial arrangement of buildings, and how their respective roles vary among ecoregions. We analyzed all fires that occurred within the conterminous United States from 2000 to 2010 and digitized which buildings were lost and which survived according to Google Earth historical imagery. We modeled the occurrence as well as the percentage of buildings lost within clusters using logistic and linear regression. Overall, variables related to topography and the spatial arrangement of buildings were more frequently present in the best 20 regression models than vegetation-related variables. In other words, specific locations in the landscape have a higher fire risk, and certain development patterns can exacerbate that risk. Fire policies and prevention efforts focused on vegetation management are important, but insufficient to solve current wildfire problems. Furthermore, the factors associated with building loss varied considerably among ecoregions suggesting that fire policy applied uniformly across the United States will not work equally well in all regions and that efforts to adapt communities to wildfires must be regionally tailored. © 2016 by the Ecological Society of America.

Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands.

PubMed

Yang, Jian; He, Hong S; Shifley, Stephen R

2008-07-01

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthropogenic constraints on the spatial pattern of fire occurrence with that on burn probability (i.e., the probability that fire will spread to a particular location). Spatial point pattern analysis and landscape succession fire model (LANDIS) were used to create maps to show the contrast. We quantified spatial controls on both fire occurrence and fire spread in the Midwest Ozark Highlands region, USA. This area exhibits a typical anthropogenic surface fire regime. We found that (1) human accessibility and land ownership were primary limiting factors in shaping clustered fire origin locations; (2) vegetation and topography had a negligible influence on fire occurrence in this anthropogenic regime; (3) burn probability was higher in grassland and open woodland than in closed-canopy forest, even though fire occurrence density was less in these vegetation types; and (4) biotic and abiotic factors were secondary descriptive ingredients for determining the spatial patterns of burn probability. This study demonstrates how fire occurrence and spread interact with landscape patterns to affect the spatial distribution of wildfire risk. The application of spatial point pattern data analysis would also be valuable to researchers working on landscape forest fire models to integrate historical ignition location patterns in fire simulation.

Soot superaggregates from flaming wildfires and their direct radiative forcing.

PubMed

Chakrabarty, Rajan K; Beres, Nicholas D; Moosmüller, Hans; China, Swarup; Mazzoleni, Claudio; Dubey, Manvendra K; Liu, Li; Mishchenko, Michael I

2014-07-01

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension Df ≈ 1.8 mobility diameter Dm ≤ 1 μm, and aerodynamic diameter Da ≤ 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic Df ≈ 2.6, Dm > 1 μm, and Da ≤ 300 nm that form via the cluster-dense aggregation mechanism. We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. At 550 nm wavelength, [corrected] we estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(f) ≈ 1.8) [corrected] aggregates, and ≈90% more warming than the volume-equivalent spherical soot particles simulated in climate models.

Role of buoyant flame dynamics in wildfire spread.

PubMed

Finney, Mark A; Cohen, Jack D; Forthofer, Jason M; McAllister, Sara S; Gollner, Michael J; Gorham, Daniel J; Saito, Kozo; Akafuah, Nelson K; Adam, Brittany A; English, Justin D

2015-08-11

Large wildfires of increasing frequency and severity threaten local populations and natural resources and contribute carbon emissions into the earth-climate system. Although wildfires have been researched and modeled for decades, no verifiable physical theory of spread is available to form the basis for the precise predictions needed to manage fires more effectively and reduce their environmental, economic, ecological, and climate impacts. Here, we report new experiments conducted at multiple scales that appear to reveal how wildfire spread derives from the tight coupling between flame dynamics induced by buoyancy and fine-particle response to convection. Convective cooling of the fine-sized fuel particles in wildland vegetation is observed to efficiently offset heating by thermal radiation until convective heating by contact with flames and hot gasses occurs. The structure and intermittency of flames that ignite fuel particles were found to correlate with instabilities induced by the strong buoyancy of the flame zone itself. Discovery that ignition in wildfires is critically dependent on nonsteady flame convection governed by buoyant and inertial interaction advances both theory and the physical basis for practical modeling.

Role of buoyant flame dynamics in wildfire spread

PubMed Central

Finney, Mark A.; Cohen, Jack D.; Forthofer, Jason M.; McAllister, Sara S.; Gollner, Michael J.; Gorham, Daniel J.; Saito, Kozo; Akafuah, Nelson K.; Adam, Brittany A.; English, Justin D.

2015-01-01

Large wildfires of increasing frequency and severity threaten local populations and natural resources and contribute carbon emissions into the earth-climate system. Although wildfires have been researched and modeled for decades, no verifiable physical theory of spread is available to form the basis for the precise predictions needed to manage fires more effectively and reduce their environmental, economic, ecological, and climate impacts. Here, we report new experiments conducted at multiple scales that appear to reveal how wildfire spread derives from the tight coupling between flame dynamics induced by buoyancy and fine-particle response to convection. Convective cooling of the fine-sized fuel particles in wildland vegetation is observed to efficiently offset heating by thermal radiation until convective heating by contact with flames and hot gasses occurs. The structure and intermittency of flames that ignite fuel particles were found to correlate with instabilities induced by the strong buoyancy of the flame zone itself. Discovery that ignition in wildfires is critically dependent on nonsteady flame convection governed by buoyant and inertial interaction advances both theory and the physical basis for practical modeling. PMID:26183227

Soot superaggregates from flaming wildfires and their direct radiative forcing

PubMed Central

Chakrabarty, Rajan K.; Beres, Nicholas D.; Moosmüller, Hans; China, Swarup; Mazzoleni, Claudio; Dubey, Manvendra K.; Liu, Li; Mishchenko, Michael I.

2014-01-01

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension Df ≈ 1.8 mobility diameter Dm ≤ 1 μm, and aerodynamic diameter Da ≤ 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic Df ≈ 2.6, Dm > 1 μm, and Da ≤ 300 nm that form via the cluster-dense aggregation mechanism. We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (Df ≈ 1.8) aggregates, and ≈90% more warming than the volume-equivalent spherical soot particles simulated in climate models. PMID:24981204

Wildfires

MedlinePlus

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Assessing Climate Change in Early Warm Season and Impacts on Wildfire Potential in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kafatos, M.; Kim, S. H.; Kim, J.; Nghiem, S. V.; Fujioka, F.; Myoung, B.

2016-12-01

Wildfires are an important concern in the Southwestern United States (SWUS) where the prevalent semi-arid to arid climate, vegetation types and hot and dry warm seasons challenge strategic fire management. Although they are part of the natural cycle related to the region's climate, significant growth of urban areas and expansion of the wildland-urban interface, have made wildfires a serious high-risk hazard. Previous studies also showed that the SWUS region is prone to frequent droughts due to large variations in wet season rainfall and has suffered from a number of severe wildfires in the recent decades. Despite the increasing trend in large wildfires, future wildfire risk assessment studies at regional scales for proactive adaptations are lacking. Our previous study revealed strong correlations between the North Atlantic Oscillation (NAO) and temperatures during March-June in SWUS. The abnormally warm and dry conditions in an NAO-positive spring, combined with reduced winter precipitation, can cause an early start of a fire season and extend it for several seasons, from late spring to fall. A strong interannual variation of the Keetch-Byram Drought Index (KBDI) during the early warm season was also found in the 35 year period 1979 - 2013 of the North American Regional Reanalysis (NARR) dataset. Thus, it is crucial to investigate the climate change impact that early warm season temperatures have on future wildfire danger potential. Our study reported here examines fine-resolution fire-weather variables for 2041-2070 projected in the North American Regional Climate Change Assessment Program (NARCCAP). The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas concentration pathways. The local wildfire potential in future climate is investigated using both the Keetch-Byram Drought Index (KBDI) and the Canadian Fire Weather Index (FWI) which have been widely used for assessing wildfire potential in the U.S.A and Canada, respectively.

Impacts of climate change on large forest wildfire of Washington and Oregon

NASA Astrophysics Data System (ADS)

Yang, Z.; Davis, R. J.; Yost, A.; Cohen, W. B.

2014-12-01

Climate changes in the 21st century were projected to have major impact on wildfire. The state of Washington and Oregon contains a tightly coupled forest ecosystem and fire regime. The objective of this study was to examine the impact of future climate changes for large wildfire in the two states. MAXENT algorithm was used to develop a large forest wildfire suitability model using historical fire for the 1971-2000 time period and validated for 1981-2010 time period . Input variables include climate (e.g. July-August temperature) and topographic variables (e.g. elevation). The model test AUC of 0.77±0.1. Using the predicted versus expected curve and methods described by Hirzel and others (Hirzel et al. 2006), we reclassified the model into four classes; low suitability (0-0.36), moderate suitability 0.36-0.5), high suitability (0.5-0.75), and very high suitability (0.75-1.0). To examine the future climate change impact, climate scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) from 33 different climate models were used to predict the large wildfire suitability from 1971-2100 using the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset. Results from ensembles of all the climate scenarios showed that the area with high and very high suitability for large wildfire increased under all 4 climate scenarios from 1971 to 2100. However, under RCP 2.6, the area start to decline from 2080 while the other three scenarios keep increasing. On the extreme case of RCP 8.5, very high suitable area increases from less than 1% during 1971-2000 to 14.9% during 2070-2100. Details about temporal patterns for the study area and changes by ecoregions will be presented.

Legacy effects of wildfire on stream thermal regimes and rainbow trout ecology: an integrated analysis of observation and individual-based models

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.; Neuswanger, Jason R.; Railsback, Steven F.

2015-01-01

Management of aquatic resources in fire-prone areas requires understanding of fish species’ responses to wildfire and of the intermediate- and long-term consequences of these disturbances. We examined Rainbow Trout populations in 9 headwater streams 10 y after a major wildfire: 3 with no history of severe wildfire in the watershed (unburned), 3 in severely burned watersheds (burned), and 3 in severely burned watersheds subjected to immediate events that scoured the stream channel and eliminated streamside vegetation (burned and reorganized). Results of a previous study of this system suggested the primary lasting effects of this wildfire history on headwater stream habitat were differences in canopy cover and solar radiation, which led to higher summer stream temperatures. Nevertheless, trout were present throughout streams in burned watersheds. Older age classes were least abundant in streams draining watersheds with a burned and reorganized history, and individuals >1 y old were most abundant in streams draining watersheds with an unburned history. Burned history corresponded with fast growth, low lipid content, and early maturity of Rainbow Trout. We used an individual-based model of Rainbow Trout growth and demographic patterns to determine if temperature interactions with bioenergetics and competition among individuals could lead to observed phenotypic and ecological differences among populations in the absence of other plausible mechanisms. Modeling suggested that moderate warming associated with wildfire and channel disturbance history leads to faster individual growth, which exacerbates competition for limited food, leading to decreases in population densities. The inferred mechanisms from this modeling exercise suggest the transferability of ecological patterns to a variety of temperature-warming scenarios.

Combining Landsat TM multispectral satellite imagery and different modelling approaches for mapping post-fire erosion changes in a Mediterranean site

NASA Astrophysics Data System (ADS)

Petropoulos, George P.; Kairis, Orestis; Karamesouti, Mina; Papanikolaou, Ioannis D.; Kosmas, Constantinos

2013-04-01

South European countries are naturally vulnerable to wildfires. Their natural resources such as soil, vegetation and water may be severely affected by wildfires, causing an imminent environmental deterioration due to the complex interdependence among biophysical components. Soil surface water erosion is a natural process essential for soil formation that is affected by such interdependences. Accelerated erosion due to wildfires, constitutes a major restrictive factor for ecosystem sustainability. In 2007, South European countries were severely affected by wildfires, with more than 500,000 hectares of land burnt in that year alone, well above the average of the last 30 years. The present work examines the changes in spatial variability of soil erosion rates as a result of a wildfire event that took place in Greece in 2007, one of the most devastating years in terms of wildfire hazards. Regional estimates of soil erosion rates before and after the fire outbreak were derived from the Revised Universal Soil Loss Equation (RUSLE, Renard et al. 1991) and the Pan-European Soil Erosion Risk Assessment model (PESERA, Kirkby, 1999; Kirkby et al., 2000). Inputs for both models included climatic, land-use, soil type, topography and land use management data. Where appropriate, both models were also fed with input data derived from the analysis of LANDSAT TM satellite imagery available in our study area, acquired before and shortly after the fire suppression. Our study was compiled and performed in a GIS environment. In overall, the loss of vegetation from the fire outbreak caused a substantial increase of soil erosion rates in the affected area, particularly towards the steep slopes. Both tested models were compared to each other and noticeable differences were observed in the soil erosion predictions before and after the fire event. These are attributed to the different parameterization requirements of the 2 models. This quantification of sediment supply through the river network provides also important insights regarding both the present-day sedimentation processes in the study area as well as the potential flooding hazard. Our work underpins that valuable contribution of remote sensing technology, combined with modeling approaches for depicting the spatial distribution of changes in erosion rates after the wildfire. KEYWORDS: erosion risk, RUSLE, PESERA, wildland fires, LANDSAT TM, remote sensing, Geographical Information Systems, Greece.

Uncertainty and risk in wildland fire management: A review

Treesearch

Matthew P. Thompson; Dave E. Calkin

2011-01-01

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to...

Forecasting intentional wildfires using temporal and spatiotemporal autocorrelations

Treesearch

Jeffrey P. Prestemon; María L. Chas-Amil; Julia M. Touza; Scott L. Goodrick

2012-01-01

We report daily time series models containing both temporal and spatiotemporal lags, which are applied to forecasting intentional wildfires in Galicia, Spain. Models are estimated independently for each of the 19 forest districts in Galicia using a 1999–2003 training dataset and evaluated out-of-sample with a 2004–06 dataset. Poisson autoregressive models of order P –...

Simulating Forest Carbon Dynamics in Response to Large-scale Fuel Reduction Treatments Under Projected Climate-fire Interactions in the Sierra Nevada Mountains, USA

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.

2016-12-01

The interaction of warmer, drier climate and increasing large wildfires, coupled with increasing fire severity resulting from fire-exclusion are anticipated to undermine forest carbon (C) stock stability and C sink strength in the Sierra Nevada forests. Treatments, including thinning and prescribed burning, to reduce biomass and restore forest structure have proven effective at reducing fire severity and lessening C loss when treated stands are burned by wildfire. However, the current pace and scale of treatment implementation is limited, especially given recent increases in area burned by wildfire. In this study, we used a forest landscape model (LANDIS-II) to evaluate the role of implementation timing of large-scale fuel reduction treatments in influencing forest C stock and fluxes of Sierra Nevada forests with projected climate and larger wildfires. We ran 90-year simulations using climate and wildfire projections from three general circulation models driven by the A2 emission scenario. We simulated two different treatment implementation scenarios: a `distributed' (treatments implemented throughout the simulation) and an `accelerated' (treatments implemented during the first half century) scenario. We found that across the study area, accelerated implementation had 0.6-10.4 Mg ha-1 higher late-century aboveground biomass (AGB) and 1.0-2.2 g C m-2 yr-1 higher mean C sink strength than the distributed scenario, depending on specific climate-wildfire projections. Cumulative wildfire emissions over the simulation period were 0.7-3.9 Mg C ha-1 higher for distributed implementation relative to accelerated implementation. However, simulations with both implementation practices have considerably higher AGB and C sink strength as well as lower wildfire emission than simulations in the absence of fuel reduction treatments. The results demonstrate the potential for implementing large-scale fuel reduction treatments to enhance forest C stock stability and C sink strength under projected climate-wildfire interactions. Given climate and wildfire would become more stressful since the mid-century, a forward management action would grant us more C benefits.

Spacetime Distributions of Wildfire Areas and Emissions of Carbon-Containing Gases and Aerosols in Northern Eurasia according to Satellite-Monitoring Data

NASA Astrophysics Data System (ADS)

Bondur, V. G.; Gordo, K. A.; Kladov, V. L.

2017-12-01

Based on online wildfire satellite-monitoring data, distributions of burned-out areas, as well as emission volumes of carbon-containing gases (CO and CO2) and fine aerosols (PM2.5), for different regions and months in 2005-2016 (across the territory of Russia) and in 2010-2016 (northern Eurasia) are analyzed. Distinctive features of the seasonal behavior of wildfires and emission volumes of carbon-containing gases and fine aerosols for different regions of northern Eurasia are determined. It is shown that between 2005 and 2016 the annual area of territories burned out during wildfires in Russia decreased by almost a factor of 2.6 owing to early detection and suppression of fire sources. It is determined that in 2014-2016 the relative size of burned-out areas in Ukraine increased 6-9-fold and volumes of CO, CO2, and PM2.5 emissions by more than a factor of 6.5-7.5 times when compared to earlier years and these characteristics for other European countries.

Introduction-2nd Fire Behavior and Fuels Conference: The fire environment-innovations, management, and policy

Treesearch

Wayne Cook; Bret W. Butler

2007-01-01

The 2nd Fire Behavior and Fuels Conference: Fire Environment -- Innovations, Management and Policy was held in Destin, FL, March 26-30, 2007. Following on the success of the 1st Fire Behavior and Fuels Conference, this conference was initiated in response to the needs of the National Wildfire Coordinating Group -- Fire Environment Working Team.

An Assessment of Land Surface and Lightning Characteristics Associated with Lightning-Initiated Wildfires

NASA Technical Reports Server (NTRS)

Coy, James; Schultz, Christopher J.; Case, Jonathan L.

2017-01-01

Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? Combine observed cloud-to-ground (CG) flashes with real-time land surface model output, and Compare data with areas where lightning did not start a wildfire to determine what land surface conditions and lightning characteristics were responsible for causing wildfires. Statistical differences between suspected fire-starters and non-fire-starters were peak-current dependent 0-10 cm Volumetric and Relative Soil Moisture comparisons were statistically dependent to at least the p = 0.05 independence level for both polarity flash types Suspected fire-starters typically occurred in areas of lower soil moisture than non-fire-starters. GVF value comparisons were only found to be statistically dependent for -CG flashes. However, random sampling of the -CG non-fire starter dataset revealed that this relationship may not always hold.

Potential postwildfire debris-flow hazards—A prewildfire evaluation for the Jemez Mountains, north-central New Mexico

USGS Publications Warehouse

Tillery, Anne C.; Haas, Jessica R.

2016-08-11

Wildfire can substantially increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although the exact location, extent, and severity of wildfire or subsequent rainfall intensity and duration cannot be known, probabilities of fire and debris‑flow occurrence for given locations can be estimated with geospatial analysis and modeling. The purpose of this report is to provide information on which watersheds might constitute the most serious potential debris-flow hazards in the event of a large-scale wildfire and subsequent rainfall in the Jemez Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in both the unburned and previously burned areas of the Jemez Mountains and surrounding areas were estimated using empirical debris-flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Forest Service.Of the 4,998 subbasins modeled for this study, computed debris-flow probabilities in 671 subbasins were greater than 80 percent in response to the 100-year recurrence interval, 30-minute duration rainfall event. These subbasins ranged in size from 0.01 to 6.57 square kilometers (km2), with an average area of 0.29 km2, and were mostly steep, upstream tributaries to larger channels in the area. Modeled debris-flow volumes in 465 subbasins were greater than 10,000 cubic meters (m3), and 14 of those subbasins had modeled debris‑flow volumes greater than 100,000 m3.The rankings of integrated relative debris-flow hazard indexes for each subbasin were generated by multiplying the individual subbasin values for debris-flow volume, debris‑flow probability, and average burn probability. The subbasins with integrated hazard index values in the top 2 percent typically are large, upland tributaries to canyons and channels primarily in the Upper Rio Grande and Rio Grande-Santa Fe watershed areas. No subbasins in this group have basin areas less than 1.0 km2. Many of these areas already had significant mass‑wasting episodes following the Las Conchas Fire in 2011. Other subbasins with integrated hazard index values in the top 2 percent are scattered throughout the Jemez River watershed area, including some subbasins in the interior of the Valles Caldera. Only a few subbasins in the top integrated hazard index group are in the Rio Chama watershed area.This prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In north‑central New Mexico, widespread watershed restoration efforts are being done to safeguard vital watersheds against the threat of catastrophic wildfire. This study was designed to help select ideal locations for the restoration efforts that could have the best return on investment.

Combining fire and erosion modeling to target forest management activities

Treesearch

William J. Elliot; Mary Ellen Miller; Nic Enstice

2015-01-01

Forests deliver a number of important ecosystem services including clean water. When forests are disturbed by wildfire, the timing, quantity and quality of runoff are altered. A modeling study was carried out in a forested watershed in California to determine the risk of wildfire, and the potential post-fire sediment delivery from approximately 6-ha hillslope polygons...

A polygon-based modeling approach to assess exposure of resources and assets to wildfire

Treesearch

Matthew P. Thompson; Joe Scott; Jeffrey D. Kaiden; Julie W. Gilbertson-Day

2013-01-01

Spatially explicit burn probability modeling is increasingly applied to assess wildfire risk and inform mitigation strategy development. Burn probabilities are typically expressed on a per-pixel basis, calculated as the number of times a pixel burns divided by the number of simulation iterations. Spatial intersection of highly valued resources and assets (HVRAs) with...

Targeting forest management through fire and erosion modeling

Treesearch

William J. Elliot; Mary Ellen Miller; Nic Enstice

2016-01-01

Forests deliver a number of important ecosystem services, including clean water. When forests are disturbed by wildfire, the timing, quantity and quality of runoff are altered. A modelling study was conducted in a forested watershed in California, USA, to determine the risk of wildfire, and the potential post-fire sediment delivery from ~4-ha hillslope polygons within...

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...

Statistical model for forecasting monthly large wildfire events in western United States

Treesearch

Haiganoush K. Preisler; Anthony L. Westerling

2006-01-01

The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes the development of a statistical model for assessing the forecasting skills of fire-danger predictors and producing 1-month-...

Birth Weight following Pregnancy during the 2003 Southern California Wildfires

PubMed Central

Holstius, David M.; Reid, Colleen E.; Jesdale, Bill M.

2012-01-01

Background: In late October 2003, a series of wildfires exposed urban populations in Southern California to elevated levels of air pollution over several weeks. Previous research suggests that short-term hospital admissions for respiratory outcomes increased specifically as a result of these fires. Objective: We assessed the impact of a wildfire event during pregnancy on birth weight among term infants. Methods: Using records for singleton term births delivered to mothers residing in California’s South Coast Air Basin (SoCAB) during 2001–2005 (n = 886,034), we compared birth weights from pregnancies that took place entirely before or after the wildfire event (n = 747,590) with those where wildfires occurred during the first (n = 60,270), second (n = 39,435), or third (n = 38,739) trimester. The trimester-specific effects of wildfire exposure were estimated using a fixed-effects regression model with several maternal characteristics included as covariates. Results: Compared with pregnancies before and after the wildfires, mean birth weight was estimated to be 7.0 g lower [95% confidence interval (CI): –11.8, –2.2] when the wildfire occurred during the third trimester, 9.7 g lower when it occurred during the second trimester (95% CI: –14.5, –4.8), and 3.3 g lower when it occurred during the first trimester (95% CI: –7.2, 0.6). Conclusions: Pregnancy during the 2003 Southern California wildfires was associated with slightly reduced average birth weight among infants exposed in utero. The extent and increasing frequency of wildfire events may have implications for infant health and development. PMID:22645279

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.

Towards the development of full-fledged forest fire information systems

NASA Astrophysics Data System (ADS)

Baetens, J.; De Baets, B.

2012-12-01

Throughout the last decades much efforts have been spent in obtaining an increased understanding of wildfire dynamics and the way it is influenced by prevailing environmental conditions and settings, such as temperature, humidity, topography, vegetation abundance, and so on, since such a profound apprehension is a prerequisite for achieving enhanced wildfire prevention measures, as well as for optimizing fire fighting and disaster management. Amongst other things, this pursuit has culminated in the deployment of wildfire information systems, such as the Canadian Wildfire Information System (CWFIS), the European Forest Fire Information System (EFFIS) and the United States Active Fire Mapping Program and Landscape Fire and Resource Management Planning Tools (LANDFIRE), which inform any interested stakeholder, be it a citizen or a government official, about the current fire risk, the extent and location of current fires, the inflammability of the vegetation, and so on. Taking into account the coverage of these systems, it should be clear that they strongly rely upon satellite imagery that is obtained from dedicated sensors, such as the Moderate-Resolution Imaging Spectroradiometer (MODIS) on board of NASA's Terra and Aqua satellites and the Advanced Very High Resolution Radiometer (AVHRR) that is carried by NOAA satellites, or more general-purpose instruments on board of spacecrafts such as Landsat or SPOT. Yet, to this day the aforementioned information systems have not yet embraced the power of mathematical modeling in order to enable trustworthy forecasts of the spatio-temporal propagation of wildfires given their current extent, which would nonetheless be extremely useful for optimizing fire fighting and disaster management, taking appropriate preventive measures, and so on. The deployment of such full-fledged wildfire information systems requires a high-level integration of (real-time) satellite imagery, weather reports and forecasts, geographic information, and finally mathematical models that constitute a mathematization of the underlying environmental processes, and which are indispensable for attaining sound and trustworthy wildfire forecasts, just as their meteorological counterparts are exploited to yield meaningful weather forecasts. As a very first step towards the development of a full-fledged wildfire information system, we demonstrate how MODIS imagery, Anderson fuel maps and geographic information can be combined to achieve meaningful wildfire forecasts given the current extent of the considered wildfire. Such a high-level integration is illustrated for a wildfire that swept through a natural area in Arizona, United States, near the border with New Mexico, between days 148 and 166 of the year 2011. Taking into account the spatial discreteness of the exploited information, which follows from its storage in geographical information systems, we rely upon a spatially discrete mathematical model, i.e. a coupled-map lattice, for mimicking the spatio-temporal wildfire propagation that can be extended in a next stage. Since setting up a full-fledged wildfire information system requires a highly multidisciplinary approach in which foresters, mathematicians, computer scientists, physicists, ecologists and others need to be involved, we hope to stimulate the joint efforts in accomplishing this task by means of our contribution.

Examining boreal peatland vulnerability to wildfire: a cross-scale perspective (Invited)

NASA Astrophysics Data System (ADS)

Thompson, D. K.; Waddington, J. M.; Parisien, M.; Simpson, B. N.; Morris, P. J.; Kettridge, N.

2013-12-01

The contemporary state of peatlands in boreal western Canada is largely a reflection of the equilibrium between peat accumulation and a natural wildfire disturbance regime. However, additional disturbances of climate change and direct anthropogenic impacts are compounding natural wildfire disturbance, leading to the potential of more severe fire and in cases complete ecosystem shifts away from peatlands altogether. Here we present a cross-scale perspective on the vulnerability of peatlands to wildfire in the context of cumulative anthropogenic impacts. At the plot scale, laboratory burning and modelling has identified the exposure of high density humified peat at the surface as being more vulnerable to deep combustion compared to low-density features such as hummock microforms. At the stand scale, studies of tree impacts on moss light availability has identified critically high tree densities where combustion-resistant Sphagnum mosses are out-competed by drier and more flammable feathermosses. Widespread resource development has created seismic lines, cutlines, and associated linear disturbances at densities approaching 1.5 km km-2 in some areas. Our modelling of wind and solar radiation across varying linear disturbance widths and canopy heights reveals increased risk of wildfire ignition and spread at specific width-height ratios. Regionally, we show that streamflow observations can offer insight into drought and seasonal wildfire risk in peatland-dominated portions of the boreal plain. Integrated wildfire management in the boreal forest can benefit from the inclusion of these cross-scale processes and feedbacks we have identified when balancing the often competing interests of ecosystem integrity, economics, and community protection.

Improving European Wildfire Emergency Information Services

NASA Astrophysics Data System (ADS)

Bielski, Conrad; Whitmore, Ceri; O'Brien, Victoria; Zeug, Gunter; Kalas, Milan; Porras, Ignasi; Solé, Josep Maria; Gálvez, Pedro; Navarro, Maria; Nurmi, Pertti; Kilpinen, Juha; Ylinen, Kaisa; Furllanelo, Cesare; Maggio, Valerio; Alikadic, Azra; Dolci, Claudia

2017-04-01

European wildfires are a seasonal natural hazard that many regions must battle regularly. However, as European urbanization continues to encroach on natural areas and the climate changes it is likely that the frequency of wildfires will increase likewise the number of areas prone to wildfires. It is therefore paramount not only to increase public awareness of this natural hazard but also to be prepared by improving wildfire hazard forecasting, monitoring, and mapping. As part of the H2020 funded project entitled Improving Resilience to Emergencies through Advanced Cyber Technologies: I-REACT (Grant Agreement #700256) , there is a task with the goal to develop models and implement technologies to improve the support around the entire emergency management cycle with respect to wildfire hazards. Based on operational weather forecasts, pan-European geospatial data as well as regularly acquired Earth Observation imagery through the Copernicus program, and other sources of information such as social media channels a European wildfire service is being developed. This will be achieved by improving on the successes of the European Forest Fire Information Service (EFFIS) and the guidance of emergency managers experienced in wildfire hazards. Part of the research will be to reduce the number of false alarms. However, once a wildfire has been identified, the system focuses on the disaster region to provide situational information to the decision makers applying state-of-the-art approaches to improve disaster response. Post-wildfire information will continue to be produced for damage and recovery assessments. Ultimately, I-REACT expects to reduce wildfire costs to life, property and livelihood. This work will improve wildfire disaster emergency management through the development and integration of new data and technologies respectively as well as the knowledge from emergency managers who not only understand the hazard itself but also can provide insights into the information that can help them do their jobs better.

Impact of wildfire-induced land cover modification on local meteorology: A sensitivity study of the 2003 wildfires in Portugal

NASA Astrophysics Data System (ADS)

Hernandez, Charles; Drobinski, Philippe; Turquety, Solène

2015-10-01

Wildfires alter land cover creating changes in dynamic, vegetative, radiative, thermal and hydrological properties of the surface. However, how so drastic changes induced by wildfires and how the age of the burnt scar affect the small and meso-scale atmospheric boundary layer dynamics are largely unknown. These questions are relevant for process analysis, meteorological and air quality forecast but also for regional climate analysis. Such questions are addressed numerically in this study on the case of the Portugal wildfires in 2003 as a testbed. In order to study the effects of burnt scars, an ensemble of numerical simulations using the Weather Research and Forecasting modeling system (WRF) have been performed with different surface properties mimicking the surface state immediately after the fire, few days after the fire and few months after the fire. In order to investigate such issue in a seamless approach, the same modelling framework has been used with various horizontal resolutions of the model grid and land use, ranging from 3.5 km, which can be considered as the typical resolution of state-of-the art regional numerical weather prediction models to 14 km which is now the typical target resolution of regional climate models. The study shows that the combination of high surface heat fluxes over the burnt area, large differential heating with respect to the preserved surroundings and lower surface roughness produces very intense frontogenesis with vertical velocity reaching few meters per second. This powerful meso-scale circulation can pump more humid air from the surroundings not impacted by the wildfire and produce more cloudiness over the burnt area. The influence of soil temperature immediately after the wildfire ceases is mainly seen at night as the boundary-layer remains unstably stratified and lasts only few days. So the intensity of the induced meso-scale circulation decreases with time, even though it remains until full recovery of the vegetation. Finally all these effects are simulated whatever the land cover and model resolution and there are thus robust processes in both regional climate simulations and process studies or short-time forecast. However, the impact of burnt scars on the precipitation signal remains very uncertain, especially because low precipitation is at stake.

Development of the GEM-MACH-FireWork System: An Air Quality Model with On-line Wildfire Emissions within the Canadian Operational Air Quality Forecast System

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Chen, Jack; Beaulieu, Paul-Andre; Anselmp, David; Gravel, Sylvie; Moran, Mike; Menard, Sylvain; Davignon, Didier

2014-05-01

A wildfire emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the U.S.A., including Alaska, fire location information is needed for both of these large countries. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This "on the fly" approach to the insertion of the fire emissions provides flexibility and efficiency since on-line meteorology is used and computational overhead in emissions pre-processing is reduced. GEM-MACH-FireWork, an experimental wildfire version of GEM-MACH, was run in real-time mode for the summers of 2012 and 2013 in parallel with the normal operational version. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions and computed objective scores will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions into the operational air quality forecast system.

Postfire logging in riparian areas.

Treesearch

Gordon H. Reeves; Peter A. Bisson; Bruce E. Rieman; Lee E. Benda

2006-01-01

We reviewed the behavior of wildfire in riparian zones, primarily in the western United States, and the potential ecological consequences of postfire logging. Fire behavior in riparian zones is complex, but many aquatic and riparian organisms exhibit a suite of adaptations that allow relatively rapid recovery after fire. Unless constrained by other factors, fish tend...

An instrument for rapid, accurate, determination of fuel moisture content

Treesearch

Stephen S. Sackett

1980-01-01

Moisture contents of dead and living fuels are key variables in fire behavior. Accurate, real-time fuel moisture data are required for prescribed burning and wildfire behavior predictions. The convection oven method has become the standard for direct fuel moisture content determination. Efforts to quantify fuel moisture through indirect methods have not been...

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-05-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: a level-set-based fire propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the non-linearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially-uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based data assimilation algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically-generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of data assimilation strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-11-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: an Eulerian front propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation (DA) algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the nonlinearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based DA algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach, as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of DA strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

An optimization modeling approach to awarding large fire support wildfire helicopter contracts from the US Forest Service

Treesearch

Stephanie A. Snyder; Keith D. Stockmann; Gaylord E. Morris

2012-01-01

The US Forest Service used contracted helicopter services as part of its wildfire suppression strategy. An optimization decision-modeling system was developed to assist in the contract selection process. Three contract award selection criteria were considered: cost per pound of delivered water, total contract cost, and quality ratings of the aircraft and vendors....

Wildfire potential evaluation during a drought event with a regional climate model and NDVI

Treesearch

Y. Liu; J. Stanturf; S. Goodrick

2010-01-01

Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional...

Wildfire disturbance impacts on streamflow from western USA watersheds

NASA Astrophysics Data System (ADS)

Cadol, D.; Wine, M.; Makhnin, O.

2017-12-01

Worldwide rapid changes in climate overlaid on changing land management paradigms have dramatically altered ecological disturbance regimes worldwide including in western North America. Ecological disturbances impacted include woody encroachment, pest pathogen complexes, riparian forest changes, and wildfire. These disturbances impact the hydrologic cycle, though the nature of these impacts has been difficult to quantify. Perhaps the greatest challenge is that most basins worldwide are ungauged. Taking wildfire as a globally relevant example of a key ecological disturbance, even within gauged basins, post-wildfire hydrologic response is spatially and temporally variable, affected by a host of variables including fire frequency, area burned, and recovery trajectory. Hydrologic response to wildfire is further understood to be a non-linear function of watershed characteristics and climate. Here we provide a framework that utilizes remote sensing, statistical modeling, field measurements, and geospatial methods to provide first-order estimates of ecological disturbance hydrologic impacts. We apply this framework to compare ecological disturbance hydrologic impacts amongst selected watersheds in the western USA. Here we show that ecological disturbance impacts on hydrology are highly variable, and in many cases have an effect magnitude similar to that modeled for temperature and precipitation changes.

Wildfires, Ecosystem Services, and Biodiversity in Tropical Dry Forest in India.

PubMed

Schmerbeck, Joachim; Fiener, Peter

2015-08-01

This review is intended to contribute to the understanding of the interlinkage between wildfire in India's tropical dry forest (TDF) and selected ecosystem services (ES), namely forest provisioning and water regulating services, as well as biodiversity. TDF covers approximately 146,000 km(2) (4.4%) of India, whereas according to the MODIS fire product about 2200 km(2) (1.4%) burns per year. As studies on wildfire effects upon ESs and biodiversity in Indian TDFs are rare we partly transferred findings from other (dry) forest areas to the environmental situation in India. In India (intentionally lit) wildfires have a very important connection to local livelihoods and the availability of non-wood forest products. Very important adverse long-term effects are the deterioration of forest ecosystems and soil degradation. The potential for TDF to regulate hydrological cycles is expected to be greater in the absence of fire than with it. A general judgment on the effect of fire on biodiversity is difficult as it depends on the community and species involved but a loss of biodiversity under regular burnings is apparent. Consequently, forest managers need sound knowledge regarding the interplay of wildfires and ecosystem behavior in general and more specific knowledge regarding the effects on taxa being considered for conservation efforts. Generally, much more research is needed to understand the trade-offs between the short-term benefits gained from forest provisioning services and long-term adverse effects.

Wildfires, Ecosystem Services, and Biodiversity in Tropical Dry Forest in India

NASA Astrophysics Data System (ADS)

Schmerbeck, Joachim; Fiener, Peter

2015-08-01

This review is intended to contribute to the understanding of the interlinkage between wildfire in India's tropical dry forest (TDF) and selected ecosystem services (ES), namely forest provisioning and water regulating services, as well as biodiversity. TDF covers approximately 146,000 km2 (4.4 %) of India, whereas according to the MODIS fire product about 2200 km2 (1.4 %) burns per year. As studies on wildfire effects upon ESs and biodiversity in Indian TDFs are rare we partly transferred findings from other (dry) forest areas to the environmental situation in India. In India (intentionally lit) wildfires have a very important connection to local livelihoods and the availability of non-wood forest products. Very important adverse long-term effects are the deterioration of forest ecosystems and soil degradation. The potential for TDF to regulate hydrological cycles is expected to be greater in the absence of fire than with it. A general judgment on the effect of fire on biodiversity is difficult as it depends on the community and species involved but a loss of biodiversity under regular burnings is apparent. Consequently, forest managers need sound knowledge regarding the interplay of wildfires and ecosystem behavior in general and more specific knowledge regarding the effects on taxa being considered for conservation efforts. Generally, much more research is needed to understand the trade-offs between the short-term benefits gained from forest provisioning services and long-term adverse effects.

Blending Model Output with satellite-based and in-situ observations to produce high-resolution estimates of population exposure to wildfire smoke

NASA Astrophysics Data System (ADS)

Lassman, William

In the western US, emissions from wildfires and prescribed fire have been associated with degradation of regional air quality. Whereas atmospheric aerosol particles with aerodynamic diameters less than 2.5 mum (PM2.5) have known impacts on human health, there is uncertainty in how particle composition, concentrations, and exposure duration impact the associated health response. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of PM2.5 in the western US. While composition and source of the aerosol is thought to be an important factor in the resulting human health-effects, this is currently not well-understood; therefore, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools are commonly used to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations, and each of these exposure-estimation tools have associated strengths and weakness. In this thesis, we investigate the utility of blending these tools together to produce highly accurate estimates of smoke exposure during the 2012 fire season in Washington for use in an epidemiological case study. For blending, we use a ridge regression model, as well as a geographically weighted ridge regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using Leave-One-Out Cross-Validation. Due to the number of in-situ monitors present during this time period, we find that predictions based on in-situ monitors were more accurate for this particular fire season than the CTM simulations and satellite-based observations, so blending provided only marginal improvements above the in-situ observations. However, we show that in hypothetical cases with fewer surface monitors, the two blending techniques can produce substantial improvement over any of the individual tools.

A structural equation model analysis of relationships among ENSO, seasonal descriptors and wildfires.

PubMed

Slocum, Matthew G; Orzell, Steve L

2013-01-01

Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site's wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season's drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R (2) score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes.

Overview and Evaluation of a Smoke Modeling System and other Tools used during Wildfire Incident Deployments

NASA Astrophysics Data System (ADS)

ONeill, S. M.; Larkin, N. K.; Martinez, M.; Rorig, M.; Solomon, R. C.; Dubowy, J.; Lahm, P. W.

2017-12-01

Specialists operationally deployed to wildfires to forecast expected smoke conditions for the public use many tools and information. These Air Resource Advisors (ARAs) are deployed as part of the Wildland Fire Air Quality Response Program (WFAQRP) and rely on smoke models, monitoring data, meteorological information, and satellite information to produce daily Smoke Outlooks for a region impacted by smoke from wildfires. These Smoke Outlooks are distributed to air quality and health agencies, published online via smoke blogs and other social media, and distributed by the Incident Public Information Officer (PIO), and ultimately to the public. Fundamental to these operations are smoke modeling systems such as the BlueSky Smoke Modeling Framework, which combines fire activity information, mapped fuel loadings, consumption and emissions models, and air quality/dispersion models such as HYSPLIT to produce predictions of PM2.5 concentrations downwind of wildland fires. Performance of this system at a variety of meteorological resolutions, fire initialization information, and vertical allocation of emissions is evaluated for the Summer of 2015 when over 400,000 hectares burned in the northwestern US state of Washington and 1-hr average fine particulate matter (PM2.5) concentrations exceeded 700 μg/m3. The performance of the system at the 12-km, 4-km, and 1.33-km resolutions is evaluated using 1-hr average PM2.5 measurements from permanent monitors and temporary monitors deployed specifically for wildfires by ARAs on wildfire incident command teams. At the higher meteorological resolution (1.33-km) the terrain features are more detailed, showing better valley structures and in general, PM2.5 concentrations were greater in the valleys with the 1.33-km meteorological domain than with the 4-km domain.

A Structural Equation Model Analysis of Relationships among ENSO, Seasonal Descriptors and Wildfires

PubMed Central

Slocum, Matthew G.; Orzell, Steve L.

2013-01-01

Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site’s wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season’s drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R 2 score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes. PMID:24086670

Wildfire-Migration Dynamics: Lessons from Colorado’s Fourmile Canyon Fire

PubMed Central

Nawrotzki, Raphael J.; Brenkert-Smith, Hannah; Hunter, Lori M.; Champ, Patricia A.

2014-01-01

The number of people living in wildfire prone wildland-urban interface (WUI) communities is on the rise. Yet, no prior study has investigated wildfire-induced residential relocation from WUI areas after a major fire event. To provide insight into the association between socio-demographic and socio-psychological characteristics and wildfire related intention to move, we use data from a survey of WUI residents in Boulder and Larimer Counties, Colorado. The data were collected two months after the devastating Fourmile Canyon fire destroyed 169 homes and burned over 6,000 acres of public and private land. Although working with a small migrant sample, logistic regression models demonstrate that survey respondents intending to move in relation to wildfire incidence do not differ socio-demographically from their non-migrant counterparts. They do, however, show significantly higher levels of risk perception. Investigating destination choices shows a preference for short distance moves. PMID:24882943

County-level analysis of the impact of temperature and population increases on California wildfire data

USGS Publications Warehouse

Baltar, M.; Keeley, Jon E.; Schoenberg, F.P.

2013-01-01

The extent to which the apparent increase in wildfire incidence and burn area in California from 1990 to 2006 is affected by population and temperature increases is examined. Using generalized linear models with random effects, we focus on the estimated impacts of increases in mean daily temperatures and populations in different counties on wildfire in those counties, after essentially controlling for the overall differences between counties in their overall mean temperatures and populations. We find that temperature increase appears to have a significant positive impact on both total burn area and number of observed wildfires. Population growth appears to have a much less pronounced impact on total burn area than do annual temperature increases, and population growth appears to be negatively correlated with the total number of observed wildfires. These effects are especially pronounced in the winter season and in Southern California counties.

Rapid increases and time-lagged declines in amphibian occupancy after wildfire.

PubMed

Hossack, Blake R; Lowe, Winsor H; Corn, Paul Stephen

2013-02-01

Climate change is expected to increase the frequency and severity of drought and wildfire. Aquatic and moisture-sensitive species, such as amphibians, may be particularly vulnerable to these modified disturbance regimes because large wildfires often occur during extended droughts and thus may compound environmental threats. However, understanding of the effects of wildfires on amphibians in forests with long fire-return intervals is limited. Numerous stand-replacing wildfires have occurred since 1988 in Glacier National Park (Montana, U.S.A.), where we have conducted long-term monitoring of amphibians. We measured responses of 3 amphibian species to fires of different sizes, severity, and age in a small geographic area with uniform management. We used data from wetlands associated with 6 wildfires that burned between 1988 and 2003 to evaluate whether burn extent and severity and interactions between wildfire and wetland isolation affected the distribution of breeding populations. We measured responses with models that accounted for imperfect detection to estimate occupancy during prefire (0-4 years) and different postfire recovery periods. For the long-toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), occupancy was not affected for 6 years after wildfire. But 7-21 years after wildfire, occupancy for both species decreased ≥ 25% in areas where >50% of the forest within 500 m of wetlands burned. In contrast, occupancy of the boreal toad (Anaxyrus boreas) tripled in the 3 years after low-elevation forests burned. This increase in occupancy was followed by a gradual decline. Our results show that accounting for magnitude of change and time lags is critical to understanding population dynamics of amphibians after large disturbances. Our results also inform understanding of the potential threat of increases in wildfire frequency or severity to amphibians in the region. ©2012 Society for Conservation Biology.

Rapid increases and time-lagged declines in amphibian occupancy after wildfire

USGS Publications Warehouse

Hossack, Blake R.; Lowe, Winsor H.; Corn, Paul Stephen

2013-01-01

Climate change is expected to increase the frequency and severity of drought and wildfire. Aquatic and moisture-sensitive species, such as amphibians, may be particularly vulnerable to these modified disturbance regimes because large wildfires often occur during extended droughts and thus may compound environmental threats. However, understanding of the effects of wildfires on amphibians in forests with long fire-return intervals is limited. Numerous stand-replacing wildfires have occurred since 1988 in Glacier National Park (Montana, U.S.A.), where we have conducted long-term monitoring of amphibians. We measured responses of 3 amphibian species to fires of different sizes, severity, and age in a small geographic area with uniform management. We used data from wetlands associated with 6 wildfires that burned between 1988 and 2003 to evaluate whether burn extent and severity and interactions between wildfire and wetland isolation affected the distribution of breeding populations. We measured responses with models that accounted for imperfect detection to estimate occupancy during prefire (0-4 years) and different postfire recovery periods. For the long-toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), occupancy was not affected for 6 years after wildfire. But 7-21 years after wildfire, occupancy for both species decreased ≥ 25% in areas where >50% of the forest within 500 m of wetlands burned. In contrast, occupancy of the boreal toad (Anaxyrus boreas) tripled in the 3 years after low-elevation forests burned. This increase in occupancy was followed by a gradual decline. Our results show that accounting for magnitude of change and time lags is critical to understanding population dynamics of amphibians after large disturbances. Our results also inform understanding of the potential threat of increases in wildfire frequency or severity to amphibians in the region.

Impact of capturing rainfall scavenging intermittency using cloud superparameterization on simulated continental scale wildfire smoke transport

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.

2011-12-01

Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.

Do investments in wildfire risk reduction lead to downstream watershed service outcomes? An integrated wildfire-erosion-economic analysis of return on investment from fuel treatments in Colorado

NASA Astrophysics Data System (ADS)

Wilson, C.; Jones, K.; Addington, R.; Cannon, J.; Cheng, T.; Gannon, B.; Kampf, S. K.; Saavedra, F.; Wei, Y.; Wolk, B.

2016-12-01

Large, severe wildfires negatively impact forested watersheds in the Western United States and jeopardize critical ecosystem services. Specifically, severe wildfires increase overland flow and runoff that contains sediment and debris, and cause other natural hazards such as floods. High erosion from burned watersheds can fill water supply reservoirs and clog water filtration systems, which has direct costs to water utilities in the form of increased water treatment costs and damage to infrastructure. With increasing wildfire risk due to global climate change and other factors, municipal water providers and users have been investing in management practices to reduce high-severity wildfire risk and increase source water security. In this research we integrate wildfire and erosion prediction models to estimate the return on investment from wildfire fuel treatments in the Upper South Platte watershed, southwest of Denver, Colorado. Denver Water and the U.S. Forest Service created the Forest-To-Faucets Partnership, one of the first payments for watershed services (PWS) programs in the United States. To date they have spent more than $30 million in the Upper South Platte to restore forests and conduct fuel reduction work across landownerships. However, due to the lack of appropriate analytical tools, it is still unclear what returns are being achieved with these investments, aside from the total number of acres treated. In this analysis we consider three treatment scenarios - current fuel treatment investments, a series of investments based on prioritization criteria, and investments based on accessibility - and model potential burn probability, fire severity and erosion. We then estimate the economic benefits of avoiding runoff using past expenditures by Denver Water and compare these to treatment costs. This research directly informs management practices in the Upper South Platte watershed and provides a framework that can inform decisions to optimize location, size, and type of wildfire treatments that maximize financial returns on investments, enhancing the resilience of forested watersheds to fire risk. More broadly, this project illustrates the evolution of PWS programs towards a more intensive analytical approach to estimating return on investments by linking ecological and economic outcomes.

Cardio-respiratory outcomes associated with exposure to wildfire smoke are modified by measures of community health

PubMed Central

2012-01-01

Background Characterizing factors which determine susceptibility to air pollution is an important step in understanding the distribution of risk in a population and is critical for setting appropriate policies. We evaluate general and specific measures of community health as modifiers of risk for asthma and congestive heart failure following an episode of acute exposure to wildfire smoke. Methods A population-based study of emergency department visits and daily concentrations of fine particulate matter during a wildfire in North Carolina was performed. Determinants of community health defined by County Health Rankings were evaluated as modifiers of the relative risk. A total of 40 mostly rural counties were included in the study. These rankings measure factors influencing health: health behaviors, access and quality of clinical care, social and economic factors, and physical environment, as well as, the outcomes of health: premature mortality and morbidity. Pollutant concentrations were obtained from a mathematically modeled smoke forecasting system. Estimates of relative risk for emergency department visits were based on Poisson mixed effects regression models applied to daily visit counts. Results For asthma, the strongest association was observed at lag day 0 with excess relative risk of 66%(28,117). For congestive heart failure the excess relative risk was 42%(5,93). The largest difference in risk was observed after stratifying on the basis of Socio-Economic Factors. Difference in risk between bottom and top ranked counties by Socio-Economic Factors was 85% and 124% for asthma and congestive heart failure respectively. Conclusions The results indicate that Socio-Economic Factors should be considered as modifying risk factors in air pollution studies and be evaluated in the assessment of air pollution impacts. PMID:23006928

Cardio-respiratory outcomes associated with exposure to wildfire smoke are modified by measures of community health.

PubMed

Rappold, Ana G; Cascio, Wayne E; Kilaru, Vasu J; Stone, Susan L; Neas, Lucas M; Devlin, Robert B; Diaz-Sanchez, David

2012-09-24

Characterizing factors which determine susceptibility to air pollution is an important step in understanding the distribution of risk in a population and is critical for setting appropriate policies. We evaluate general and specific measures of community health as modifiers of risk for asthma and congestive heart failure following an episode of acute exposure to wildfire smoke. A population-based study of emergency department visits and daily concentrations of fine particulate matter during a wildfire in North Carolina was performed. Determinants of community health defined by County Health Rankings were evaluated as modifiers of the relative risk. A total of 40 mostly rural counties were included in the study. These rankings measure factors influencing health: health behaviors, access and quality of clinical care, social and economic factors, and physical environment, as well as, the outcomes of health: premature mortality and morbidity. Pollutant concentrations were obtained from a mathematically modeled smoke forecasting system. Estimates of relative risk for emergency department visits were based on Poisson mixed effects regression models applied to daily visit counts. For asthma, the strongest association was observed at lag day 0 with excess relative risk of 66% (28,117). For congestive heart failure the excess relative risk was 42% (5,93). The largest difference in risk was observed after stratifying on the basis of Socio-Economic Factors. Difference in risk between bottom and top ranked counties by Socio-Economic Factors was 85% and 124% for asthma and congestive heart failure respectively. The results indicate that Socio-Economic Factors should be considered as modifying risk factors in air pollution studies and be evaluated in the assessment of air pollution impacts.

Wildfire exposure and fuel management on western US national forests.

PubMed

Ager, Alan A; Day, Michelle A; McHugh, Charles W; Short, Karen; Gilbertson-Day, Julie; Finney, Mark A; Calkin, David E

2014-12-01

Substantial investments in fuel management activities on national forests in the western US are part of a national strategy to reduce human and ecological losses from catastrophic wildfire and create fire resilient landscapes. Prioritizing these investments within and among national forests remains a challenge, partly because a comprehensive assessment that establishes the current wildfire risk and exposure does not exist, making it difficult to identify national priorities and target specific areas for fuel management. To gain a broader understanding of wildfire exposure in the national forest system, we analyzed an array of simulated and empirical data on wildfire activity and fuel treatment investments on the 82 western US national forests. We first summarized recent fire data to examine variation among the Forests in ignition frequency and burned area in relation to investments in fuel reduction treatments. We then used simulation modeling to analyze fine-scale spatial variation in burn probability and intensity. We also estimated the probability of a mega-fire event on each of the Forests, and the transmission of fires ignited on national forests to the surrounding urban interface. The analysis showed a good correspondence between recent area burned and predictions from the simulation models. The modeling also illustrated the magnitude of the variation in both burn probability and intensity among and within Forests. Simulated burn probabilities in most instances were lower than historical, reflecting fire exclusion on many national forests. Simulated wildfire transmission from national forests to the urban interface was highly variable among the Forests. We discuss how the results of the study can be used to prioritize investments in hazardous fuel reduction within a comprehensive multi-scale risk management framework. Published by Elsevier Ltd.

The association of wildfire smoke with respiratory and cardiovascular emergency department visits in Colorado in 2012: a case crossover study.

PubMed

Alman, Breanna L; Pfister, Gabriele; Hao, Hua; Stowell, Jennifer; Hu, Xuefei; Liu, Yang; Strickland, Matthew J

2016-06-04

In 2012, Colorado experienced one of its worst wildfire seasons of the past decade. The goal of this study was to investigate the relationship of local PM2.5 levels, modeled using the Weather Research and Forecasting Model with Chemistry, with emergency department visits and acute hospitalizations for respiratory and cardiovascular outcomes during the 2012 Colorado wildfires. Conditional logistic regression was used to assess the relationship between both continuous and categorical PM2.5 and emergency department visits during the wildfire period, from June 5(th) to July 6(th) 2012. For respiratory outcomes, we observed positive relationships between lag 0 PM2.5 and asthma/wheeze (1 h max OR 1.01, 95 % CI (1.00, 1.01) per 10 μg/m(3); 24 h mean OR 1.04 95 % CI (1.02, 1.06) per 5 μg/m(3)), and COPD (1 h max OR 1.01 95 % CI (1.00, 1.02) per 10 μg/m(3); 24 h mean OR 1.05 95 % CI (1.02, 1.08) per 5 μg/m(3)). These associations were also positive for 2-day and 3-day moving average lag periods. When PM2.5 was modeled as a categorical variable, bronchitis also showed elevated effect estimates over the referent groups for lag 0 24 h average concentration. Cardiovascular results were consistent with no association. We observed positive associations between PM2.5 from wildfire and respiratory diseases, supporting evidence from previous research that wildfire PM2.5 is an important source for adverse respiratory health outcomes.

Critical shear stress for erosion of cohesive soils subjected to temperatures typical of wildfires

USGS Publications Warehouse

Moody, J.A.; Dungan, Smith J.; Ragan, B.W.

2005-01-01

[1] Increased erosion is a well-known response after wildfire. To predict and to model erosion on a landscape scale requires knowledge of the critical shear stress for the initiation of motion of soil particles. As this soil property is temperature-dependent, a quantitative relation between critical shear stress and the temperatures to which the soils have been subjected during a wildfire is required. In this study the critical shear stress was measured in a recirculating flume using samples of forest soil exposed to different temperatures (40??-550??C) for 1 hour. Results were obtained for four replicates of soils derived from three different types of parent material (granitic bedrock, sandstone, and volcanic tuffs). In general, the relation between critical shear stress and temperature can be separated into three different temperature ranges (275??C), which are similar to those for water repellency and temperature. The critical shear stress was most variable (1.0-2.0 N m-2) for temperatures 2.0 N m-2) between 175?? and 275??C, and was essentially constant (0.5-0.8 N m-2) for temperatures >275??C. The changes in critical shear stress with temperature were found to be essentially independent of soil type and suggest that erosion processes in burned watersheds can be modeled more simply than erosion processes in unburned watersheds. Wildfire reduces the spatial variability of soil erodibility associated with unburned watersheds by eliminating the complex effects of vegetation in protecting soils and by reducing the range of cohesion associated with different types of unburned soils. Our results indicate that modeling the erosional response after a wildfire depends primarily on determining the spatial distribution of the maximum soil temperatures that were reached during the wildfire. Copyright 2005 by the American Geophysical Union.

Detection of the long-range transport of wildfire pollution to the Arctic using a network of ground-based FTIR spectrometers, satellite observations and model result

NASA Astrophysics Data System (ADS)

Lutsch, E.; Conway, S. A.; Strong, K.; Jones, D. B. A.; Drummond, J. R.; Ortega, I.; Hannigan, J. W.; Makarova, M.; Notholt, J.; Blumenstock, T.; Sussmann, R.; Mahieu, E.; Kasai, Y.; Clerbaux, C.

2017-12-01

We present a multi-year time series of the total columns of carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C2H6) obtained by Fourier Transform Infrared (FTIR) spectrometer measurements at nine sites. Six are high-latitude sites: Eureka, Nunavut; Ny Alesund, Norway; Thule, Greenland; Kiruna, Sweden; Poker Flat, Alaska and St. Petersburg, Russia and three are mid-latitude sites; Zugspitze, Germany; Jungfraujoch, Switzerland and Toronto, Ontario. For each site, the inter-annual trends and seasonal variabilities of the CO total column time series are accounted for, allowing ambient concentrations to be determined. Enhancements above ambient levels are then used to identify possible wildfire pollution events. Since the abundance of each trace gas species emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the other long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution. Back-trajectories from HYSPLIT and FLEXPART as well as fire detections from the Moderate Resolution Spectroradiometer (MODIS) allow the source regions of the detected enhancements to be determined while satellite observations of CO from the Measurement of Pollution in the Troposphere (MOPITT) and Infrared Atmospheric Sounding Interferometer (IASI) instruments can be used to track the transport of the smoke plume. Differences in travel times between sites allows ageing of biomass burning plumes to be determined, providing a means to infer the physical and chemical processes affecting the loss of each species during transport. Comparisons of ground-based FTIR measurements to GEOS-Chem chemical transport model results are used to investigate these processes, evaluate wildfire emission inventories and infer the influence of wildfire emissions on the Arctic.

Towards Data-Driven Simulations of Wildfire Spread using Ensemble-based Data Assimilation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Bart, J.; Ricci, S. M.; Cuenot, B.; Trouvé, A.; Duchaine, F.; Morel, T.

2012-12-01

Real-time predictions of a propagating wildfire remain a challenging task because the problem involves both multi-physics and multi-scales. The propagation speed of wildfires, also called the rate of spread (ROS), is indeed determined by complex interactions between pyrolysis, combustion and flow dynamics, atmospheric dynamics occurring at vegetation, topographical and meteorological scales. Current operational fire spread models are mainly based on a semi-empirical parameterization of the ROS in terms of vegetation, topographical and meteorological properties. For the fire spread simulation to be predictive and compatible with operational applications, the uncertainty on the ROS model should be reduced. As recent progress made in remote sensing technology provides new ways to monitor the fire front position, a promising approach to overcome the difficulties found in wildfire spread simulations is to integrate fire modeling and fire sensing technologies using data assimilation (DA). For this purpose we have developed a prototype data-driven wildfire spread simulator in order to provide optimal estimates of poorly known model parameters [*]. The data-driven simulation capability is adapted for more realistic wildfire spread : it considers a regional-scale fire spread model that is informed by observations of the fire front location. An Ensemble Kalman Filter algorithm (EnKF) based on a parallel computing platform (OpenPALM) was implemented in order to perform a multi-parameter sequential estimation where wind magnitude and direction are in addition to vegetation properties (see attached figure). The EnKF algorithm shows its good ability to track a small-scale grassland fire experiment and ensures a good accounting for the sensitivity of the simulation outcomes to the control parameters. As a conclusion, it was shown that data assimilation is a promising approach to more accurately forecast time-varying wildfire spread conditions as new airborne-like observations of the fire front location get available. [*] Rochoux, M.C., Delmotte, B., Cuenot, B., Ricci, S., and Trouvé, A. (2012) "Regional-scale simulations of wildland fire spread informed by real-time flame front observations", Proc. Combust. Inst., 34, in press http://dx.doi.org/10.1016/j.proci.2012.06.090 EnKF-based tracking of small-scale grassland fire experiment, with estimation of wind and fuel parameters.

Allocating Fire Mitigation Funds on the Basis of the Predicted Probabilities of Forest Wildfire

Treesearch

Ronald E. McRoberts; Greg C. Liknes; Mark D. Nelson; Krista M. Gebert; R. James Barbour; Susan L. Odell; Steven C. Yaddof

2005-01-01

A logistic regression model was used with map-based information to predict the probability of forest fire for forested areas of the United States. Model parameters were estimated using a digital layer depicting the locations of wildfires and satellite imagery depicting thermal hotspots. The area of the United States in the upper 50th percentile with respect to...

A wildfire risk modeling system for evaluating landscape fuel treatment strategies

Treesearch

Alan Ager; Mark Finney; Andrew McMahan

2006-01-01

Despite a wealth of literature and models concerning wildfire risk, field units in Federal land management agencies lack a clear framework and operational tools to measure how risk might change from proposed fuel treatments. In an actuarial context, risk is defined as the expected value change from a fire, calculated as the product of (1) probability of a fire at a...

An on-line interface for integrated modeling of wildlife, climate, and society for strategic planning for the Sky Islands

Treesearch

Barron J. Orr; Wolfgang Grunberg; Amanda B. Cockerham; Anne Y. Thwaits; Heather S. Severson; Noah M. D. Lerman; Rachel M. Miller; Michael Haseltine; Barbara J. Morehouse; Jonathan T. Overpeck; Stephen R. Yool; Thomas W. Swetnam; Gary L. Christopherson

2005-01-01

The demand for strategic planning tools that account for climate and human influences on wildfire hazard is growing. In response, the University of Arizona, through an EPA STAR Grant has undertaken interdisciplinary research to characterize the human and climate dimensions of wildfire. The resulting Fire-Climate-Society (FCS-1) prototype model developed for Sky Islands...

Fuel treatment effects on tree-based forest carbon storage and emissions under modeled wildfire scenarios

Treesearch

M. Hurteau; M. North

2009-01-01

Forests are viewed as a potential sink for carbon (C) that might otherwise contribute to climate change. It is unclear, however, how to manage forests with frequent fire regimes to maximize C storage while reducing C emissions from prescribed burns or wildfire. We modeled the effects of eight different fuel treatments on treebased C storage and release over a century,...

A Five- Year CMAQ Model Performance for Wildfires and Prescribed Fires

EPA Science Inventory

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissio...

Current and Future Impacts of Wildfires on PM2.5 and Public Health in Colorado

NASA Astrophysics Data System (ADS)

Liu, Y.; Strickland, M.; Fu, J. S.; Geng, G.; Chang, H. H.; Liu, Y.

2017-12-01

In recent decades, the Western United States has seen heightened wildfire activity, characterized by a higher frequency of large wildfires a longer fire season, larger fire size, and a greater total area burned. With projected temperature increases, soil moisture reduction, and more frequent air stagnation, the burden of wildfires on air quality and public health will likely increase. With state-of-the-art climate and air quality models; ground and satellite measurements; and detailed health information, we will investigate the impacts of historical and future wildfires on air quality and public health in Colorado under various climate change scenarios and population growth patterns. As the first step of this project, we developed a Bayesian fusion model with satellite aerosol, cloud and fire data as well as CMAQ simulation results to estimate PM2.5 and ozone concentrations during the fire season of 2011 - 2014 at 1 km spatial resolution. These exposure estimates will be used together with emergency department (ED) visits and acute hospitalizations data in Colorado to develop region-specific concentration-response (C-R) functions. These C-R functions in combination with projected future PM2.5 and O3 will be used in the EPA BenMAP framework to estimate the impacts of future wildfires on public health. This research addresses an important link between climate and aerosol research and could significantly increase our understanding of the implications of climate change for PM and public health in the Rocky Mountains Region.

The influences of wildfires and stratospheric-tropospheric exchange on ozone during seacions mission over St. Louis

NASA Astrophysics Data System (ADS)

Wilkins, Joseph L.

The influence of wildfire biomass burning and stratospheric air mass transport on tropospheric ozone (O3) concentrations in St. Louis during the SEAC4RS and SEACIONS-2013 measurement campaigns has been investigated. The Lagrangian particle dispersion model FLEXPART-WRF analysis reveals that 55% of ozonesonde profiles during SEACIONS were effected by biomass burning. Comparing ozonesonde profiles with numerical simulations show that as biomass burning plumes age there is O3 production aloft. A new plume injection height technique was developed based on the Naval Research Laboratory's (NRL) detection algorithm for pyro-convection. The NRL method identified 29 pyro-cumulonimbus events that occurred during the summer of 2013, of which 13 (44%) impacted the SEACIONS study area, and 4 (14%) impacted the St. Louis area. In this study, we investigate wildfire plume injection heights using model simulations and the FLAMBE emissions inventory using 2 different algorithms. In the first case, wildfire emissions are injected at the surface and allowed to mix within the boundary layer simulated by the meteorological model. In the second case, the injection height of wildfire emissions is determined by a guided deep-convective pyroCb run using the NRL detection algorithm. Results show that simulations using surface emissions were able to represent the transport of carbon monoxide plumes from wildfires when the plumes remained below 5 km or occurred during large convective systems, but that the surface effects were over predicted. The pyroCb cases simulated the long-range transport of elevated plumes above 5 km 68% of the time. In addition analysis of potential vorticity suggests that stratospheric intrusions or tropopause folds affected 13 days (48%) when there were sonde launches and 27 days (44%) during the entire study period. The largest impact occurred on September 12, 2013 when ozone-rich air impacted the nocturnal boundary layer. By analyzing ozonesonde profiles with meteorological transport models, we were able to identify biomass burning and stratospheric intrusions in St. Louis.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Moving beyond traditional fire management practices to better minimize community vulnerability to wildfire in southern California

NASA Astrophysics Data System (ADS)

Syphard, A. D.; Keeley, J. E.; Brennan, T. J.

2010-12-01

Wildfires are an important natural process in southern California, but they also present a major hazard for human life and property. The region leads the nation in fire-related losses, and since 2001, wildfires have damaged or destroyed more than 10,000 homes. As human ignitions have increased along with urban development and population growth, fire frequency has also surged, and most home losses occur in large fires when ignitions coincide with Santa Ana windstorms. As the region accommodates more growth in the future, the wildfire threat promises to continue. We will thus explore how a broader, more comprehensive approach to fire management could improve upon traditional approaches for reducing community vulnerability. The traditional approach to mitigating fire risk, in addition to fire suppression, has been to reduce fuel through construction of fuel breaks. Despite increasing expenditure on these treatments, there has been little empirical study of their role in controlling large fires. We will present the results of a study in which we constructed and analyzed a spatial database of fuel breaks in southern California national forests. Our objective was to better understand characteristics of fuel breaks that affect the behavior of large fires and to map where fires and fuel breaks most commonly intersect. We found that fires stopped at fuel breaks 22-47% of the time, depending on the forest, and the reason fires stopped was invariably related to firefighter access and management activities. Fire weather and fuel break condition were also important. The study illustrates the importance of strategic location of fuel breaks because they have been most effective where they provided access for firefighting activities. While fuel breaks have played a role in controlling wildfires at the Wildland Urban Interface, we are evaluating alternative approaches for reducing community vulnerability, including land use planning. Recent research shows that the amount and spatial arrangement of human infrastructure, such as roads and housing developments, strongly influences wildfire patterns. Therefore, we hypothesize that the spatial arrangement and location of housing development is likely to affect the susceptibility of lives and property to fire. In other words, potential for urban loss may be greatest at specific housing densities, spatial patterns of development, and locations of development. If these risk factors can be identified, mapped, and modeled, it is possible that vulnerability to wildfire could be substantially minimized through careful planning for future development - especially because future development will likely increase the region’s fire risk. To address these possibilities, we are evaluating past housing loss in relation to land use planning, in conjunction with other variables that influence fire patterns. We are also exploring alternative future scenarios to identify optimum land use planning strategies for minimizing fire risk.

Forecast-based Interventions Can Reduce the Health and Economic Burden of Wildfires

EPA Science Inventory

We simulated public health forecast-based interventions during a wildfire smoke episode in rural North Carolina to show the potential for use of modeled smoke forecasts toward reducing the health burden and showed a significant economic benefit of reducing exposures. Daily and co...

Climate, CO2, and demographic impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2015-09-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation. Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation - wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations comprise Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models using two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs), sensitivity tests for the effect of climate and CO2, as well as a sensitivity analysis using two alternative parameterisations of the semi-empirical burned-area model. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load, and faster litter turnover in a warmer climate.

Climate, CO2 and human population impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2016-01-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.

Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation-wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations use Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models. These were combined with two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs) to assess the sensitivity of emissions to the effect of climate, CO2 and humans. In addition, two alternative parameterisations of the semi-empirical burned-area model were applied. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load and faster litter turnover in a warmer climate.

Soot Superaggregates from Flaming Wildfires and Their Direct Radiative Forcing

NASA Technical Reports Server (NTRS)

Chakrabarty, Rajan K.; Beres, Nicholas D.; Moosmuller,Hans; China, Swarup; Mazzoleni, Claudio; Dubey, Manvendra K.; Liu, Li; Mishchenko, Michael I.

2014-01-01

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension D(sub f) approximately equals 1.8 mobility diameter D(sub m) (is) less than or equal to 1 micron, and aerodynamic diameter D(sub a) (is) less than or equal to 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic D(sub f) approximately equals 2.6,D(sub m) (is) greater than 1 micron, and D(sub a) is less than or equal to 300 nm that form via the cluster-dense aggregation mechanism.We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(sub f) approximately equals 1.8) aggregates, and approximately equals 90% more warming than the volume-equivalent spherical soot particles simulated in climate models.

Modeling wildfire incident complexity dynamics.

PubMed

Thompson, Matthew P

2013-01-01

Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.

Current research issues related to post-wildfire runoff and erosion processes

USGS Publications Warehouse

Moody, John A.; Shakesby, Richard A.; Robichaud, Peter R.; Cannon, Susan H.; Martin, Deborah A.

2013-01-01

Research into post-wildfire effects began in the United States more than 70 years ago and only later extended to other parts of the world. Post-wildfire responses are typically transient, episodic, variable in space and time, dependent on thresholds, and involve multiple processes measured by different methods. These characteristics tend to hinder research progress, but the large empirical knowledge base amassed in different regions of the world suggests that it should now be possible to synthesize the data and make a substantial improvement in the understanding of post-wildfire runoff and erosion response. Thus, it is important to identify and prioritize the research issues related to post-wildfire runoff and erosion. Priority research issues are the need to: (1) organize and synthesize similarities and differences in post-wildfire responses between different fire-prone regions of the world in order to determine common patterns and generalities that can explain cause and effect relations; (2) identify and quantify functional relations between metrics of fire effects and soil hydraulic properties that will better represent the dynamic and transient conditions after a wildfire; (3) determine the interaction between burned landscapes and temporally and spatially variable meso-scale precipitation, which is often the primary driver of post-wildfire runoff and erosion responses; (4) determine functional relations between precipitation, basin morphology, runoff connectivity, contributing area, surface roughness, depression storage, and soil characteristics required to predict the timing, magnitudes, and duration of floods and debris flows from ungaged burned basins; and (5) develop standard measurement methods that will ensure the collection of uniform and comparable runoff and erosion data. Resolution of these issues will help to improve conceptual and computer models of post-wildfire runoff and erosion processes.

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.

White-headed woodpecker nesting ecology after wildfire

Treesearch

Catherine S. Wightman; Victoria A. Saab; Chris Forristal; Kim Mellen-Mclean; Amy Markus

2010-01-01

Within forests susceptible to wildfire and insect infestations, land managers need to balance dead tree removal and habitat requirements for wildlife species associated with snags. We used Mahalanobis distance methods to develop predictive models of white-headed woodpecker (Picoides albolarvatus) nesting habitat in postfire ponderosa pine (Pinus ponderosa)-dominated...

Modeling wildfire incident complexity dynamics

Treesearch

Matthew P. Thompson

2013-01-01

Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire...

Quantifying the potential impacts of fuel treatments on wildfire suppression costs

Treesearch

Matthew P. Thompson; Nicole M. Vaillant; Jessica R. Haas; Krista M. Gebert; Keith D. Stockmann

2013-01-01

Modeling the impacts and effects of hazardous fuel reduction treatments is a pressing issue within the wildfire management community. Prospective evaluation of fuel treatment effectiveness allows for comparison of alternative treatment strategies in terms of socioeconomic and ecological impacts and facilitates analysis of tradeoffs across land-management objectives....

PM2.5 concentrations observed and modeled for the 2016 southern Appalachian wildfire event

EPA Science Inventory

During November 2016, wildfires in the southern Appalachian region of the United States burned over 125,00 acres leading to a widespread outbreak of elevated levels of fine particulate matter (PM2.5). Daily average concentrations above the current National Ambient Air Quality Sta...

REFINING FIRE EMISSIONS FOR AIR QUALITY MODELING WITH REMOTELY-SENSED FIRE COUNTS: A WILDFIRE CASE STUDY

EPA Science Inventory

This paper examines the use of Moderate Resolution Imaging Spectroradiometer (MODIS) observed active fire data (pixel counts) to refine the National Emissions Inventory (NEI) fire emission estimates for major wildfire events. This study was motivated by the extremely limited info...

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

Wildfire risk assessment in a typical Mediterranean wildland-urban interface of Greece.

PubMed

Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita

2015-04-01

The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.

Wildfire Risk Assessment in a Typical Mediterranean Wildland-Urban Interface of Greece

NASA Astrophysics Data System (ADS)

Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita

2015-04-01

The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.

Building Fire Behavior Analyst (FBAN) capability and capacity: Lessons learned From Victoria, Australia's Bushfire Behavior Predictive Services Strategy

Treesearch

K. E. Gibos; A. Slijepcevic; T. Wells; L. Fogarty

2015-01-01

Wildland fire managers must frequently make meaning from chaos in order to protect communities and infrastructure from the negative impacts of fire. Fire management personnel are increasingly turning to science to support their experience-based decision-making processes and to provide clear, confident leadership for communities frequently exposed to risk from wildfire...

Mastication and prescribed fire influences on tree mortality and predicted fire behavior in ponderosa pine

Treesearch

Alicia L. Reiner; Nicole M. Vaillant; Scott N. Dailey

2012-01-01

The purpose of this study was to provide land managers with information on potential wildfire behavior and tree mortality associated with mastication and masticated/fire treatments in a plantation. Additionally, the effect of pulling fuels away from tree boles before applying fire treatment was studied in relation to tree mortality. Fuel characteristics and tree...

Investigation of firebrand generation from an experimental fire: Development of a reliable data collection methodology

Treesearch

Jan C. Thomas; Eric V. Mueller; Simon Santamaria; Michael Gallagher; Mohamad El Houssami; Alexander Filkov; Kenneth Clark; Nicholas Skowronski; Rory M. Hadden; William Mell; Albert Simeoni

2017-01-01

An experimental approach has been developed to quantify the characteristics and flux of firebrands during a management-scale wildfire in a pine-dominated ecosystem. By characterizing the local fire behavior and measuring the temporal and spatial variation in firebrand collection, the flux of firebrands has been related to the fire behavior for the first time. This...

Photo Series for Estimating Post-Hurricane Residues and Fire Behavior in Southern Pine

Treesearch

Dale D. Wade; James K. Forbus; James M. Saveland

1993-01-01

Following Hurricane Hugo, fuels were sampled on nine 2-acre blocks which were then burned during the spring wildfire season. The study was superimposed on dormant-season fire-interval research plots established in 1958 on the Francis Marion National Forest near Charleston, SC. Photographs of preburn fuel loads, fire behavior, and postburn fuel loads were taken to...

A spatial evaluation of global wildfire-water risks to human and natural systems.

PubMed

Robinne, François-Nicolas; Bladon, Kevin D; Miller, Carol; Parisien, Marc-André; Mathieu, Jérôme; Flannigan, Mike D

2018-01-01

The large mediatic coverage of recent massive wildfires across the world has emphasized the vulnerability of freshwater resources. The extensive hydrogeomorphic effects from a wildfire can impair the ability of watersheds to provide safe drinking water to downstream communities and high-quality water to maintain riverine ecosystem health. Safeguarding water use for human activities and ecosystems is required for sustainable development; however, no global assessment of wildfire impacts on water supply is currently available. Here, we provide the first global evaluation of wildfire risks to water security, in the form of a spatially explicit index. We adapted the Driving forces-Pressure-State-Impact-Response risk analysis framework to select a comprehensive set of indicators of fire activity and water availability, which we then aggregated to a single index of wildfire-water risk using a simple additive weighted model. Our results show that water security in many regions of the world is potentially vulnerable, regardless of socio-economic status. However, in developing countries, a critical component of the risk is the lack of socio-economic capability to respond to disasters. Our work highlights the importance of addressing wildfire-induced risks in the development of water security policies; the geographic differences in the components of the overall risk could help adapting those policies to different regional contexts. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Fuel treatment impacts on estimated wildfire carbon loss from forests in Montana, Oregon, California, and Arizona

USGS Publications Warehouse

Stephens, Scott L.; Boerner, Ralph E.J.; Maghaddas, Jason J.; Maghaddas, Emily E.Y.; Collins, Brandon M.; Dow, Christopher B.; Edminster, Carl; Fiedler, Carl E.; Fry, Danny L.; Hartsough, Bruce R.; Keeley, Jon E.; Knapp, Eric E.; McIver, James D.; Skinner, Carl N.; Youngblood, Andrew P.

2012-01-01

Using forests to sequester carbon in response to anthropogenically induced climate change is being considered across the globe. A recent U.S. executive order mandated that all federal agencies account for sequestration and emissions of greenhouse gases, highlighting the importance of understanding how forest carbon stocks are influenced by wildfire. This paper reports the effects of the most common forest fuel reduction treatments on carbon pools composed of live and dead biomass as well as potential wildfire emissions from six different sites in four western U.S. states. Additionally, we predict the median forest product life spans and uses of materials removed during mechanical treatments. Carbon loss from modeled wildfire-induced tree mortality was lowest in the mechanical plus prescribed fire treatments, followed by the prescribed fire-only treatments. Wildfire emissions varied from 10–80 Mg/ha and were lowest in the prescribed fire and mechanical followed by prescribed fire treatments at most sites. Mean biomass removals per site ranged from approximately 30–60 dry Mg/ha; the median lives of products in first use varied considerably (from <10 to >50 years). Our research suggests most of the benefits of increased fire resistance can be achieved with relatively small reductions in current carbon stocks. Retaining or growing larger trees also reduced the vulnerability of carbon loss from wildfire. In addition, modeled vulnerabilities to carbon losses and median forest product life spans varied considerably across our study sites, which could be used to help prioritize treatment implementation.

Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques

USGS Publications Warehouse

Richardson, Leslie; Loomis, John B.; Champ, Patricia A.

2013-01-01

Estimating the economic benefits of reduced health damages due to improvements in environmental quality continues to challenge economists. We review welfare measures associated with reduced wildfire smoke exposure, and a unique dataset from California’s Station Fire of 2009 allows for a comparison of cost of illness (COI) estimates with willingness to pay (WTP) measures. The WTP for one less symptom day is estimated to be $87 and $95, using the defensive behavior and contingent valuation methods, respectively. These WTP estimates are not statistically different but do differ from a $3 traditional daily COI estimate and $17 comprehensive daily COI estimate.

Detecting Spatial Patterns of Natural Hazards from the Wikipedia Knowledge Base

NASA Astrophysics Data System (ADS)

Fan, J.; Stewart, K.

2015-07-01

The Wikipedia database is a data source of immense richness and variety. Included in this database are thousands of geotagged articles, including, for example, almost real-time updates on current and historic natural hazards. This includes usercontributed information about the location of natural hazards, the extent of the disasters, and many details relating to response, impact, and recovery. In this research, a computational framework is proposed to detect spatial patterns of natural hazards from the Wikipedia database by combining topic modeling methods with spatial analysis techniques. The computation is performed on the Neon Cluster, a high performance-computing cluster at the University of Iowa. This work uses wildfires as the exemplar hazard, but this framework is easily generalizable to other types of hazards, such as hurricanes or flooding. Latent Dirichlet Allocation (LDA) modeling is first employed to train the entire English Wikipedia dump, transforming the database dump into a 500-dimension topic model. Over 230,000 geo-tagged articles are then extracted from the Wikipedia database, spatially covering the contiguous United States. The geo-tagged articles are converted into an LDA topic space based on the topic model, with each article being represented as a weighted multidimension topic vector. By treating each article's topic vector as an observed point in geographic space, a probability surface is calculated for each of the topics. In this work, Wikipedia articles about wildfires are extracted from the Wikipedia database, forming a wildfire corpus and creating a basis for the topic vector analysis. The spatial distribution of wildfire outbreaks in the US is estimated by calculating the weighted sum of the topic probability surfaces using a map algebra approach, and mapped using GIS. To provide an evaluation of the approach, the estimation is compared to wildfire hazard potential maps created by the USDA Forest service.

Global Pyrogeography: the Current and Future Distribution of Wildfire

PubMed Central

Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine

2009-01-01

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494

Pastoral wildfires in the Mediterranean: understanding their linkages to land cover patterns in managed landscapes.

PubMed

Ruiz-Mirazo, Jabier; Martínez-Fernández, Jesús; Vega-García, Cristina

2012-05-15

The pastoral use of fire to regenerate rangelands is a major cause of wildfires in many Mediterranean countries. Despite producing important environmental impacts, this phenomenon has hardly ever been studied separately from other wildfire ignition causes. As extensive livestock breeding relies on the available pasture resources, we hypothesised that a higher rate of pastoral wildfire ignitions could be associated with land cover patterns, as these reflect the spatial arrangement of human activities in managed landscapes. To investigate these patterns, we studied landscape structure and the pastoral wildfires recorded between 1988 and 2000 in 24 Nature Park landscapes in Andalusia (Spain). The CORINE Land Cover map was reclassified according to five levels of grazing use and landscape metrics were calculated. Neural networks were developed to model the relationship between landscape metrics and pastoral wildfires, obtaining a set of significant variables which are discussed in the frame of land and livestock management in the region. We conclude that pastoral wildfire ignitions are more likely in landscapes where the pattern of being dominated by a matrix composed of several large patches of low to moderate grazing use, and having abundant small and elongated patches of higher grazing use, is more extreme. This pattern could be reflecting the persistence of numerous small livestock farms within an increasingly abandoned agrarian landscape. To prevent pastoral wildfires, land management could attempt to enlarge and merge those small patches of higher grazing use, reducing the amount of interface and their intermixture with the surrounding poorer pasture resources. Copyright © 2011 Elsevier Ltd. All rights reserved.

Health effects of the 2012 Valencia (Spain) wildfires on children in a cohort study.

PubMed

Vicedo-Cabrera, Ana M; Esplugues, Ana; Iñíguez, Carmen; Estarlich, Marisa; Ballester, Ferran

2016-06-01

In July 2012, two simultaneous wildfires burnt a big area in Valencia (Spain), where a birth cohort study (INMA) is being developed. The heavy smoke covered the whole INMA study area for several days. We aimed at evaluating the 2012 Valencia wildfire effects on the health of children enrolled in the INMA-Valencia cohort. Two weeks after the extinction of the wildfires, a phone survey was conducted and finally 460 individuals were enrolled. We considered a wildfire period (12-day interval when they were active) and a control period (12-day interval just before wildfires). Parents were asked about respiratory symptoms experienced during both periods, and during wildfires only about the preventive measures adopted and the perception of exposure, along with individual data collected through the different follow-up surveys of the cohort. Conditional logistic regression models were applied, and we included interaction terms for asthma/rhinitis and level of perception of exposure; 82.4 % perceived smoke smell outdoors, 40 % indoors and more than 90 % of the families observed the presence of ash. An adjusted odds ratio of 3.11 [95 % confidence interval 1.62-5.97] for itchy/watery eyes and 3.02 [1.41-6.44] for sore throat was obtained. Significant interaction terms for rhinitis and asthma in itchy/watery eyes and sneezing, and only asthma for sore throat were obtained. Exposure to wildfire smoke was associated with increased respiratory symptoms in this child population, particularly affecting susceptible individuals with asthma or rhinitis.

On the effects of wildfires on precipitation in Southern Africa

NASA Astrophysics Data System (ADS)

De Sales, Fernando; Okin, Gregory S.; Xue, Yongkang; Dintwe, Kebonye

2018-03-01

This study investigates the impact of wildfire on the climate of Southern Africa. Moderate resolution imaging spectroradiometer derived burned area fraction data was implemented in a set of simulations to assess primarily the role of wildfire-induced surface changes on monthly precipitation. Two post-fire scenarios are examined namely non-recovering and recovering vegetation scenarios. In the former, burned vegetation fraction remains burned until the end of the simulations, whereas in the latter it is allowed to regrow following a recovery period. Control simulations revealed that the model can dependably capture the monthly precipitation and surface temperature averages in Southern Africa thus providing a reasonable basis against which to assess the impacts of wildfire. In general, both wildfire scenarios have a negative impact on springtime precipitation. September and October were the only months with statistically significant precipitation changes. During these months, precipitation in the region decreases by approximately 13 and 9% in the non-recovering vegetation scenario, and by about 10 and 6% in the recovering vegetation wildfire scenario, respectively. The primary cause of precipitation deficit is the decrease in evapotranspiration resulting from a reduction in surface net radiation. Areas impacted by the precipitation reduction includes the Luanda, Kinshasa, and Brazzaville metropolitan areas, The Angolan Highlands, which are the source of the Okavango Rive, and the Okavango Delta region. This study suggests that a probable intensification in wildfire frequency and extent resulting from projected population increase and global warming in Southern Africa could potentially exacerbate the impacts of wildfires in the region's seasonal precipitation.

Application of wildfire simulation methods to assess wildfire exposure in a Mediterranean fire-prone area (Sardinia, Italy)

NASA Astrophysics Data System (ADS)

Salis, M.; Ager, A.; Arca, B.; Finney, M.; Bacciu, V. M.; Spano, D.; Duce, P.

2012-12-01

Spatial and temporal patterns of fire spread and behavior are dependent on interactions among climate, topography, vegetation and fire suppression efforts (Pyne et al. 1996; Viegas 2006; Falk et al. 2007). Humans also play a key role in determining frequency and spatial distribution of ignitions (Bar Massada et al, 2011), and thus influence fire regimes as well. The growing incidence of catastrophic wildfires has led to substantial losses for important ecological and human values within many areas of the Mediterranean basin (Moreno et al. 1998; Mouillot et al. 2005; Viegas et al. 2006a; Riaño et al. 2007). The growing fire risk issue has led to many new programs and policies of fuel management and risk mitigation by environmental and fire agencies. However, risk-based methodologies to help identify areas characterized by high potential losses and prioritize fuel management have been lacking for the region. Formal risk assessment requires the joint consideration of likelihood, intensity, and susceptibility, the product of which estimates the chance of a specific loss (Brillinger 2003; Society of Risk Analysis, 2006). Quantifying fire risk therefore requires estimates of a) the probability of a specific location burning at a specific intensity and location, and b) the resulting change in financial or ecological value (Finney 2005; Scott 2006). When large fires are the primary cause of damage, the application of this risk formulation requires modeling fire spread to capture landscape properties that affect burn probability. Recently, the incorporation of large fire spread into risk assessment systems has become feasible with the development of high performance fire simulation systems (Finney et al. 2011) that permit the simulation of hundreds of thousands of fires to generate fine scale maps of burn probability, flame length, and fire size, while considering the combined effects of weather, fuels, and topography (Finney 2002; Andrews et al. 2007; Ager and Finney 2009; Finney et al. 2009; Salis et al. 2012 accepted). In this work, we employed wildfire simulation methods to quantify wildfire exposure to human and ecological values for the island of Sardinia, Italy. The work was focused on the risk and exposure posed by large fires (e.g. 100 - 10,000 ha), and considers historical weather, ignition patterns and fuels. We simulated 100,000 fires using burn periods that replicated the historical size distribution on the Island, and an ignition probability grid derived from historic ignition data. We then examine spatial variation in three exposure components (burn probability, flame length, fire size) among important human and ecological values. The results allowed us to contract exposure among and within the various features examined, and highlighted the importance of human factors in shaping wildfire exposure in Sardinia. The work represents the first application of burn probability modeling in the Mediterranean region, and sets the stage for expanded work in the region to quantify risk from large fires

Model simulations of flood and debris flow timing in steep catchments after wildfire

USGS Publications Warehouse

Rengers, Francis K.; McGuire, Luke; Kean, Jason W.; Staley, Dennis M.; Hobley, D.E.J

2016-01-01

Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.

Predicting mortality for five California conifers following wildfire

Treesearch

Sharon M. Hood; Sheri L. Smith; Daniel R. Cluck

2010-01-01

Fire injury was characterized and survival monitored for 5677 trees >25cm DBH from five wildfires in California that occurred between 2000 and 2004. Logistic regression models for predicting the probability of mortality 5-years after fire were developed for incense cedar (Calocedrus decurrens (Torr.) Florin), white fir (Abies concolor (Gord. & Glend.) Lindl. ex...

Regimes of dry convection above wildfires: Idealized numerical simulations and dimensional analysis

Treesearch

Michael T. Kiefer; Matthew D. Parker; Joseph J. Charney

2009-01-01

Wildfires are capable of inducing atmospheric circulations that result predominantly from large temperature anomalies produced by the fire. The fundamental dynamics through which a forest fire and the atmosphere interact to yield different convective regimes is still not well understood. This study uses the Advanced Regional Prediction System (ARPS) model to...

Quantifying and Monetizing Potential Climate Change Policy Impacts on Terrestrial Ecosystem Carbon Storage and Wildfires in the United States

EPA Science Inventory

This paper quantifies and monetizes climate change impacts on carbon stored in terrestrial vegetation and wildfire incidence in the contiguous United States to assess the benefits of alternative mitigation policies. The MC-1 dynamic global vegetation model was used to develop int...

A Collaborative Approach to Community Wildfire Hazard Reduction

Treesearch

Marc Titus; Jennifer Hinderman

2006-01-01

This paper highlights the very successful collaborative approach to community wildfire hazard reduction being used in the 5 county NW Region of the Washington State Department of Natural Resources. NW Region cooperators have created a successful model to help affected communities reduce their risks to wildland fire. Identified high risk communities have been approached...

Assessment of Air Quality Impacts from the 2013 Rim Fire

EPA Science Inventory

Wildfires account for a significant fraction of PM2.5 emissions in the U.S., the majority of which are organic aerosols. This work aims to quantify modeled impacts of wildfires, specifically the 2013 Rim Fire, and focuses on how recent organic aerosol updates in CMAQ v5.2 effect ...

Quantifying the potential impacts of fuel treatments on wildfire suppression costs volume

Treesearch

Matthew P. Thompson; Nicole M. Vaillant; Jessica R. Haas; Krista M. Gebert; Keith D. Stockmann

2013-01-01

Modeling the impacts and effects of hazardous fuel reduction treatments is a pressing issue within the wildfire management community. Prospective evaluation of fuel treatments allows for comparison of alternative treatment strategies in terms of socioeconomic and ecological impacts and facilitates analysis of tradeoffs across land management objectives (Stockmann et al...

Accepting uncertainty, assessing risk: decision quality in managing wildfire, forest resource values, and new technology

Treesearch

Jeffrey G. Borchers

2005-01-01

The risks, uncertainties, and social conflicts surrounding uncharacteristic wildfire and forest resource values have defied conventional approaches to planning and decision-making. Paradoxically, the adoption of technological innovations such as risk assessment, decision analysis, and landscape simulation models by land management organizations has been limited. The...

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

Differential respiratory health effects from the 2008 northern California wildfires: A spatiotemporal approach.

PubMed

Reid, Colleen E; Jerrett, Michael; Tager, Ira B; Petersen, Maya L; Mann, Jennifer K; Balmes, John R

2016-10-01

We investigated health effects associated with fine particulate matter during a long-lived, large wildfire complex in northern California in the summer of 2008. We estimated exposure to PM2.5 for each day using an exposure prediction model created through data-adaptive machine learning methods from a large set of spatiotemporal data sets. We then used Poisson generalized estimating equations to calculate the effect of exposure to 24-hour average PM2.5 on cardiovascular and respiratory hospitalizations and ED visits. We further assessed effect modification by sex, age, and area-level socioeconomic status (SES). We observed a linear increase in risk for asthma hospitalizations (RR=1.07, 95% CI=(1.05, 1.10) per 5µg/m(3) increase) and asthma ED visits (RR=1.06, 95% CI=(1.05, 1.07) per 5µg/m(3) increase) with increasing PM2.5 during the wildfires. ED visits for chronic obstructive pulmonary disease (COPD) were associated with PM2.5 during the fires (RR=1.02 (95% CI=(1.01, 1.04) per 5µg/m(3) increase) and this effect was significantly different from that found before the fires but not after. We did not find consistent effects of wildfire smoke on other health outcomes. The effect of PM2.5 during the wildfire period was more pronounced in women compared to men and in adults, ages 20-64, compared to children and adults 65 or older. We also found some effect modification by area-level median income for respiratory ED visits during the wildfires, with the highest effects observed in the ZIP codes with the lowest median income. Using a novel spatiotemporal exposure model, we found some evidence of differential susceptibility to exposure to wildfire smoke. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

WRF simulation over complex terrain during a southern California wildfire event

NASA Astrophysics Data System (ADS)

Lu, W.; Zhong, S.; Charney, J. J.; Bian, X.; Liu, S.

2012-03-01

In October 2007, the largest wildfire-related evacuation in California's history occurred as severe wildfires broke out across southern California. Smoke from these wildfires contributed to elevated pollutant concentrations in the atmosphere, affecting air quality in a vast region of the western United States. High-resolution numerical simulations were performed using the Weather Research and Forecast (WRF) model to understand the atmospheric conditions during the wildfire episode and how the complex circulation patterns might affect smoke transport and dispersion. The simulated meteorological fields were validated using surface and upper air observations in California and Nevada. To distinguish the performance of the WRF in different geographic regions, the surface stations were grouped into coastal sites, valley and basin sites, and mountain sites, and the results for the three categories were analyzed and intercompared. For temperature and moisture, the mountain category has the best agreement with the observations, while the coastal category was the worst. For wind, the model performance for the three categories was very similar. The flow patterns over complex terrain were also analyzed under different synoptic conditions and the possible impact of the terrain on smoke and pollutant pathways is analyzed by employing a Lagrangian Particle Dispersion Model. When high mountains prevent the smoke from moving inland, the mountain passes act as active pathways for smoke transport; meanwhile, chimney effect helps inject the pollutants to higher levels, where they are transported regionally. The results highlight the role of complex topography in the assessment of the possible smoke transport patterns in the region.

Response of Sierra Nevada forests to projected climate-wildfire interactions.

PubMed

Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy

2017-05-01

Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.

Seeing through the Smoke: A collaborative, multidisciplinary effort to address the interplay between wildfire, climate, air quality, and health

NASA Astrophysics Data System (ADS)

Brey, S. J.; Fischer, E. V.; Pierce, J. R.; Ford, B.; Lassman, W.; Pfister, G.; Volckens, J.; Gan, R.; Magzamen, S.; Barnes, E. A.

2015-12-01

Exposure to wildfire smoke plumes represents an episodic, uncertain, and potentially growing threat to public health in the western United States. The area burned by wildfires in this region has increased over recent decades, and the future of fires within this region is largely unknown. Future fire emissions are intimately linked to future meteorological conditions, which are uncertain due to the variability of climate model outputs and differences between representative concentration pathways (RCP) scenarios. We know that exposure to wildfire smoke is harmful, particularly for vulnerable populations. However the literature on the heath effects of wildfire smoke exposure is thin, particularly when compared to the depth of information we have on the effects of exposure to smoke of anthropogenic origin. We are exploring the relationships between climate, fires, air quality and public health through multiple interdisciplinary collaborations. We will present several examples from these projects including 1) an analysis of the influence of fire on ozone abundances over the United States, and 2) efforts to use a high-resolution weather forecasting model to nail down exposure within specific smoke plumes. We will also highlight how our team works together. This discussion will include examples of the university structure that facilitates our current collaborations, and the lessons we have learned by seeking stakeholder input to make our science more useful.

A critical assessment of the Burning Index in Los Angeles County, California

USGS Publications Warehouse

Schoenberg, F.P.; Chang, H.-C.; Keeley, J.E.; Pompa, J.; Woods, J.; Xu, H.

2007-01-01

The Burning Index (BI) is commonly used as a predictor of wildfire activity. An examination of data on the BI and wildfires in Los Angeles County, California, from January 1976 to December 2000 reveals that although the BI is positively associated with wildfire occurrence, its predictive value is quite limited. Wind speed alone has a higher correlation with burn area than BI, for instance, and a simple alternative point process model using wind speed, relative humidity, precipitation and temperature well outperforms the BI in terms of predictive power. The BI is generally far too high in winter and too low in fall, and may exaggerate the impact of individual variables such as wind speed or temperature during times when other variables, such as precipitation or relative humidity, render the environment ill suited for wildfires. ?? IAWF 2007.

The influence of an incomplete fuels treatment on fire behavior and effects in the 2007 Tin Cup Fire, Bitterroot National Forest, Montana

Treesearch

Michael Harrington; Erin Noonan-Wright

2010-01-01

Extensive forested areas have received fuels treatments in recent decades and significant funding is available for additional treatments in an attempt to mitigate undesirable high wildfire intensities and impacts. Fuel treatment successes and failures in moderating fire behavior and effects can be found in quantified and anecdotal reports. Questions remain about the...

Predicting the effect of climate change on wildfire behavior and initial attack success

Treesearch

Jeremy S. Fried; J. Keith Gilless; William J. Riley; Tadashi J. Moody; Clara Simon de Blas; Katharine Hayhoe; Max Mortiz; Scott Stephens; Margaret Torn

2008-01-01

This study focused on how climate change-induced effects on weather will translate into changes in wildland fire severity and outcomes in California, particularly on the effectiveness of initial attack at limiting the number of fires that escape initial attack. The results indicate that subtle shifts in fire behavior of the sort that might be induced by the climate...

Fuels and predicted fire behavior in the southern Appalachian Mountains and fire and fire surrogate treatments

Treesearch

Thomas Waldrop; Ross J. Phillips; Dean A. Simon

2010-01-01

This study tested the success of fuel reduction treatments for mitigating wildfire behavior in an area that has had little previous research on fire, the southern Appalachian Mountains. A secondary objective of treatments was to restore the community to an open woodland condition. Three blocks of four treatments were installed in a mature hardwood forest in western...

The effects of hillslope-scale variability in burn severity on post-fire sediment delivery

NASA Astrophysics Data System (ADS)

Quinn, Dylan; Brooks, Erin; Dobre, Mariana; Lew, Roger; Robichaud, Peter; Elliot, William

2017-04-01

With the increasing frequency of wildfire and the costs associated with managing the burned landscapes, there is an increasing need for decision support tools that can be used to assess the effectiveness of targeted post-fire management strategies. The susceptibility of landscapes to post-fire soil erosion and runoff have been closely linked with the severity of the wildfire. Wildfire severity maps are often spatial complex and largely dependent upon total vegetative biomass, fuel moisture patterns, direction of burn, wind patterns, and other factors. The decision to apply targeted treatment to a specific landscape and the amount of resources dedicated to treating a landscape should ideally be based on the potential for excessive sediment delivery from a particular hillslope. Recent work has suggested that the delivery of sediment to a downstream water body from a hillslope will be highly influenced by the distribution of wildfire severity across a hillslope and that models that do not capture this hillslope scale variability would not provide reliable sediment and runoff predictions. In this project we compare detailed (10 m) grid-based model predictions to lumped and semi-lumped hillslope approaches where hydrologic parameters are fixed based on hillslope scale averaging techniques. We use the watershed scale version of the process-based Watershed Erosion Prediction Projection (WEPP) model and its GIS interface, GeoWEPP, to simulate the fire impacts on runoff and sediment delivery using burn severity maps at a watershed scale. The flowpath option in WEPP allows for the most detail representation of wildfire severity patterns (10 m) but depending upon the size of the watershed, simulations are time consuming and computational demanding. The hillslope version is a simpler approach which assigns wildfire severity based on the severity level that is assigned to the majority of the hillslope area. In the third approach we divided hillslopes in overland flow elements (OFEs) and assigned representative input values on a finer scale within single hillslopes. Each of these approaches were compared for several large wildfires in the mountainous ranges of central Idaho, USA. Simulations indicated that predictions based on lumped hillslope modeling over-predict sediment transport by as much as 4.8x in areas of high to moderate burn severity. Annual sediment yield within the simulated watersheds ranged from 1.7 tonnes/ha to 6.8 tonnes/ha. The disparity between simulated sediment yield with these approaches was attributed to hydrologic connectivity of the burn patterns within the hillslope. High infiltration rates between high severity sites can greatly reduce the delivery of sediment. This research underlines the importance of accurately representing soil burn severity along individual hillslopes in hydrologic models and the need for modeling approaches to capture this variability to reliability simulate soil erosion.

Turbulence and fire-spotting effects into wild-land fire simulators

NASA Astrophysics Data System (ADS)

Kaur, Inderpreet; Mentrelli, Andrea; Bosseur, Frédéric; Filippi, Jean-Baptiste; Pagnini, Gianni

2016-10-01

This paper presents a mathematical approach to model the effects and the role of phenomena with random nature such as turbulence and fire-spotting into the existing wildfire simulators. The formulation proposes that the propagation of the fire-front is the sum of a drifting component (obtained from an existing wildfire simulator without turbulence and fire-spotting) and a random fluctuating component. The modelling of the random effects is embodied in a probability density function accounting for the fluctuations around the fire perimeter which is given by the drifting component. In past, this formulation has been applied to include these random effects into a wildfire simulator based on an Eulerian moving interface method, namely the Level Set Method (LSM), but in this paper the same formulation is adapted for a wildfire simulator based on a Lagrangian front tracking technique, namely the Discrete Event System Specification (DEVS). The main highlight of the present study is the comparison of the performance of a Lagrangian and an Eulerian moving interface method when applied to wild-land fire propagation. Simple idealised numerical experiments are used to investigate the potential applicability of the proposed formulation to DEVS and to compare its behaviour with respect to the LSM. The results show that DEVS based wildfire propagation model qualitatively improves its performance (e.g., reproducing flank and back fire, increase in fire spread due to pre-heating of the fuel by hot air and firebrands, fire propagation across no fuel zones, secondary fire generation, ...) when random effects are included according to the present formulation. The performance of DEVS and LSM based wildfire models is comparable and the only differences which arise among the two are due to the differences in the geometrical construction of the direction of propagation. Though the results presented here are devoid of any validation exercise and provide only a proof of concept, they show a strong inclination towards an intended operational use. The existing LSM or DEVS based operational simulators like WRF-SFIRE and ForeFire respectively can serve as an ideal basis for the same.

Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile

NASA Astrophysics Data System (ADS)

Cuchiara, Gustavo C.; Rappenglück, Bernhard; Angelica Rubio, Maria; Lissi, Eduardo; Gramsch, Ernesto; Garreaud, Rene D.

2017-04-01

Wildfires are a significant direct source of atmospheric pollutants; on a global scale biomass burning is believed to be the largest source of primary fine particles in the atmosphere and the second largest source of trace gases after anthropogenic emission sources. During the summer of 2014, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. The biomass-burning plume was transported towards the metropolitan area of Santiago and exacerbated the air quality in this region. In this study, we investigated this wildfire event using a forward plume-rise and a chemistry (WRF/Chem) simulation. These data sets provided an opportunity to validate a regional air-quality simulation over Santiago, and a unique case to assess the performance of biomass burning plume modeling in complex topography and validated against an established air quality network. The results from both meteorological and air quality models provide insights about the transport of biomass-burning plumes from the wildfire region towards the metropolitan region of Santiago de Chile. We studied a seven-day period between January 01-07, 2014, and the impact of biomass burning plume emissions estimated by Fire Inventory from NCAR version 1 (FINNv1) on the air quality of Santiago de Chile.

Measuring the consequences of wildfires in a Bayesian network with vulnerability and exposure indicators

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Botzler, Sebastian; Krug, Kai; Straub, Daniel

2013-04-01

Mediterranean climate type areas have always been experiencing fire events. However, population growth and expansion of urban centers into wildland areas during the 20th century (expansion of wildland-urban interface) has increased the threat to humans and their activities. Life and property losses, damage on infrastructure and crops, and forest degradation are some of the damages caused by wildfires. Although fires repeatedly occur along the Mediterranean basin, not all areas have experienced severe consequences. The extent of damage by wildfires is influenced by several factors, such as population density, vegetation type, topography, weather conditions and social preparedness [1]. Wildfire consequence estimation by means of vulnerability and exposure indicators is an essential part of wildfire risk analysis. Vulnerability indicators express the conditions that increase the susceptibility of a site to the impact of wildfires and exposure indicators describe the elements at risk [2],[3]. Appropriate indicators to measure wildfire vulnerability and exposure can vary with scale and site. The consequences can be classified into economic, social, environmental and safety, and they can be tangible (human life losses, buildings damaged) or intangible (damage of cultural heritage site). As a consequence, a variety of approaches exist and there is a lack of generalized unified easy-to-implement methodologies. In this study we present a methodology for measuring consequences of wildfires in a Mediterranean area in the mesoscale (1 km² spatial resolution). Vulnerability and exposure indicators covering all consequence levels are identified and their interrelations are stressed. Variables such as building materials, roofing type, and average building values are included in the economic vulnerability level. Safety exposure is expressed by population density, demographic structure, street density and distance to closest fire station. Environmental vulnerability of protected areas and rare species is also included. Presence of cultural heritage sites, power stations and power line network influence social exposure. The conceptual framework is demonstrated with a Bayesian Network (BN). The BN model incorporates empirical observation, physical models and expert knowledge; it can also explicitly account for uncertainty in the indicators. The proposed model is applied to the island of Cyprus. Maps support the demonstration of results. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA. [2] UN/ISDR (International Strategy for Disaster Reduction (2004): Living with Risk: A Global Review of Disaster Reduction Initiatives, Geneva, UN Publications. [3] Birkmann, J. (2006): Measuring vulnerability to natural hazards: towards disaster resilient societies. United Nations University Press, Tokyo, Japan.

Observations and impacts of transported Canadian wildfire smoke on ozone and aerosol air quality in the Maryland region on June 9-12, 2015.

PubMed

Dreessen, Joel; Sullivan, John; Delgado, Ruben

2016-09-01

Canadian wildfire smoke impacted air quality across the northern Mid-Atlantic (MA) of the United States during June 9-12, 2015. A multiday exceedance of the new 2015 70-ppb National Ambient Air Quality Standard (NAAQS) for ozone (O3) followed, resulting in Maryland being incompliant with the Environmental Protection Agency's (EPA) revised 2015 O3 NAAQS. Surface in situ, balloon-borne, and remote sensing observations monitored the impact of the wildfire smoke at Maryland air quality monitoring sites. At peak smoke concentrations in Maryland, wildfire-attributable volatile organic compounds (VOCs) more than doubled, while non-NOx oxides of nitrogen (NOz) tripled, suggesting long range transport of NOx within the smoke plume. Peak daily average PM2.5 was 32.5 µg m(-3) with large fractions coming from black carbon (BC) and organic carbon (OC), with a synonymous increase in carbon monoxide (CO) concentrations. Measurements indicate that smoke tracers at the surface were spatially and temporally correlated with maximum 8-hr O3 concentrations in the MA, all which peaked on June 11. Despite initial smoke arrival late on June 9, 2015, O3 production was inhibited due to ultraviolet (UV) light attenuation, lower temperatures, and nonoptimal surface layer composition. Comparison of Community Multiscale Air Quality (CMAQ) model surface O3 forecasts to observations suggests 14 ppb additional O3 due to smoke influences in northern Maryland. Despite polluted conditions, observations of a nocturnal low-level jet (NLLJ) and Chesapeake Bay Breeze (BB) were associated with decreases in O3 in this case. While infrequent in the MA, wildfire smoke may be an increasing fractional contribution to high-O3 days, particularly in light of increased wildfire frequency in a changing climate, lower regional emissions, and tighter air quality standards. The presented event demonstrates how a single wildfire event associated with an ozone exceedance of the NAAQS can prevent the Baltimore region from complying with lower ozone standards. This relatively new problem in Maryland is due to regional reductions in NOx emissions that led to record low numbers of ozone NAAQS violations in the last 3 years. This case demonstrates the need for adequate means to quantify and justify ozone impacts from wildfires, which can only be done through the use of observationally based models. The data presented may also improve future air quality forecast models.

Wildfire risk management on a landscape with public and private ownership: Who pays for protection?

Treesearch

Gwenlyn Busby; Heidi J. Albers

2010-01-01

Wildfire, like many natural hazards, affects large landscapes with many landowners and the risk individual owners face depends on both individual and collective protective actions. In this study, we develop a spatially explicit game theoretic model to examine the strategic interaction between landowners' hazard mitigation decisions on a landscape with public and...

Financial considerations of policy options to enhance biomass utilization for reducing wildfire hazards

Treesearch

Dennis R. Becker; Debra Larson; Eini C. Lowell

2009-01-01

The Harvest Cost-Revenue Estimator, a financial model, was used to examine the cost sensitivity of forest biomass harvesting scenarios to targeted policies designed to stimulate wildfire hazardous fuel reduction projects. The policies selected represent actual policies enacted by federal and state governments to provide incentive to biomass utilization and are aimed at...

Coupled influences of topography and wind on wildland fire behaviour

Treesearch

Rodman Linn; Judith Winterkamp; Carleton Edminster; Jonah J. Colman; William S. Smith

2007-01-01

Ten simulations were performed with the HIGRAD/FIRETEC wildfire behaviour model in order to explore its utility in studying wildfire behaviour in inhomogeneous topography. The goal of these simulations is to explore the potential extent of the coupling between the fire, atmosphere, and topography. The ten simulations described in this paper include five different...

A Model Based Analysis of the Role of an Upper-Level Front and Stratospheric Intrusion in the Mack Lake Fire

Treesearch

Tarisa K. Zimet; Jonathan E. Martin

2003-01-01

Meteorological assessment of wildfire risk has traditionally involved identification of several synoptic types empirically determined to influence wildfire spread. Such weather types are characterized by identifiable synoptic-scale structures and processes. Schroeder et. al. (1964) identified four recognizable synoptic-scale patterns that contribute most frequently to...

Valuing hypothetical wildfire impacts with a Kuhn–Tucker model of recreation demand

Treesearch

Jose Sanchez; Ken Baerenklau; Armando Gonzalez-Caban

2016-01-01

This study uses a nonmarket valuation method to investigate the recreation values of the San Jacinto Wilderness in southern California. The analysis utilizes survey data from a stated-choice experiment involving backcountry visitors who responded to questions about hypothetical wildfire burn scenarios. Benefits of landscape preservation are derived using a Kuhn-Tucker...

Repeated wildfires alter forest recovery of mixed-conifer ecosystems.

PubMed

Stevens-Rumann, Camille; Morgan, Penelope

2016-09-01

Most models project warmer and drier climates that will contribute to larger and more frequent wildfires. However, it remains unknown how repeated wildfires alter post-fire successional patterns and forest structure. Here, we test the hypothesis that the number of wildfires, as well as the order and severity of wildfire events interact to alter forest structure and vegetation recovery and implications for vegetation management. In 2014, we examined forest structure, composition, and tree regeneration in stands that burned 1-18 yr before a subsequent 2007 wildfire. Three important findings emerged: (1) Repeatedly burned forests had 15% less woody surface fuels and 31% lower tree seedling densities compared with forests that only experienced one recent wildfire. These repeatedly burned areas are recovering differently than sites burned once, which may lead to alternative ecosystem structure. (2) Order of burn severity (high followed by low severity compared with low followed by high severity) did influence forest characteristics. When low burn severity followed high, forests had 60% lower canopy closure and total basal area with 92% fewer tree seedlings than when high burn severity followed low. (3) Time between fires had no effect on most variables measured following the second fire except large woody fuels, canopy closure and tree seedling density. We conclude that repeatedly burned areas meet many vegetation management objectives of reduced fuel loads and moderate tree seedling densities. These differences in forest structure, composition, and tree regeneration have implications not only for the trajectories of these forests, but may reduce fire intensity and burn severity of subsequent wildfires and may be used in conjunction with future fire suppression tactics. © 2016 by the Ecological Society of America.

Assessing Wildfire Effects in North American Boreal Peatlands through Field and Remote Sensing Analysis

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; French, N. H. F.; Endres, S.; Kane, E. S.; Jenkins, L. K.; Hanes, C.; Battaglia, M., Jr.; de Groot, W.

2017-12-01

Wildfire is a natural disturbance factor in high northern latitude (HNL) ecosystems occurring primarily through lightning ignitions. However, there is evidence that frequency of wildfire in both boreal and arctic landscapes is increasing with climate change. Higher temperatures and reduced precipitation is leading to widespread seasonal drying in some HNL landscapes, thereby increasing wildfire frequency and severity. In 2014, Northwest Territories (NWT) Canada had a record breaking year of wildfire, burning over 3.4 million hectares of upland forests, peatlands, and even emergent wetlands. Fire activity occurred across seasons (spring, summer, and fall) in the Taiga Shield and Boreal Plains ecozones. Similar large fire years have occurred in boreal Alaska in 2004 and 2015. Under NASA ABoVE, boreal peatlands of Alberta and NWT Canada are the focus of both field and remote sensing studies to better understand their vulnerability and resiliency to wildfire. Landsat and radar satellite imagery are being used to develop remote sensing algorithms specific to peatlands to map and monitor not only burn severity but also organic soil moisture, peatland type (e.g. bog vs. fen) and biomass form (herbaceous, shrub, forest dominated). Field data analysis of tree recruitment, in situ moisture, burn severity, fuel loading and other biophysical parameters are currently being synthesized from three field seasons. The field and remote sensing data are being integrated with CanFIRE (a carbon emissions and fire effects model) to better understand the wildfire effects to peatlands. The spatial information allows for better quantification of the landscape heterogeneity of peatlands, thus providing new insights to landscape scale changes and allowing improved understanding of the implications of increasing wildfire in HNL ecosystems.

Development of multi-year land cover data to assess wildfire impacts to coastal watersheds and the nearshore environment

NASA Astrophysics Data System (ADS)

Morrison, Katherine D.

In the Mediterranean ecosystems of coastal California, wildfire is a common disturbance that can significantly alter vegetation in watersheds that transport sediment and nutrients to the adjacent nearshore oceanic environment. We assess the impact of two wildfires that burned in 2008 on land cover and to the nearshore environment along the Big Sur coast in central California. We created a multi-year land cover dataset to assess changes to coastal watersheds as a result of fire. This land cover dataset was then used to model changes in nonpoint source pollutants transported to the nearshore environment. Results indicate post-fire increases in percent export compared to pre-fire years and also link wildfire severity to the specific land cover changes that subsequently increase exports of pollutants and sediment to the nearshore environment. This approach is a replicable across watersheds and also provides a framework for including the nearshore environment as a value at risk terrestrial land management revolving around wildfire, including suppression, thinning, and other activities that change land cover at a landscape scale.

Return on investment from fuel treatments to reduce severe wildfire and erosion in a watershed investment program in Colorado.

PubMed

Jones, Kelly W; Cannon, Jeffery B; Saavedra, Freddy A; Kampf, Stephanie K; Addington, Robert N; Cheng, Antony S; MacDonald, Lee H; Wilson, Codie; Wolk, Brett

2017-08-01

A small but growing number of watershed investment programs in the western United States focus on wildfire risk reduction to municipal water supplies. This paper used return on investment (ROI) analysis to quantify how the amounts and placement of fuel treatment interventions would reduce sediment loading to the Strontia Springs Reservoir in the Upper South Platte River watershed southwest of Denver, Colorado following an extreme fire event. We simulated various extents of fuel mitigation activities under two placement strategies: (a) a strategic treatment prioritization map and (b) accessibility. Potential fire behavior was modeled under each extent and scenario to determine the impact on fire severity, and this was used to estimate expected change in post-fire erosion due to treatments. We found a positive ROI after large storm events when fire mitigation treatments were placed in priority areas with diminishing marginal returns after treating >50-80% of the forested area. While our ROI results should not be used prescriptively they do show that, conditional on severe fire occurrence and precipitation, investments in the Upper South Platte could feasibly lead to positive financial returns based on the reduced costs of dredging sediment from the reservoir. While our analysis showed positive ROI focusing only on post-fire erosion mitigation, it is important to consider multiple benefits in future ROI calculations and increase monitoring and evaluation of these benefits of wildfire fuel reduction investments for different site conditions and climates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wildfire risk adaptation: propensity of forestland owners to purchase wildfire insurance in the southern United States

Treesearch

Jianbang Gan; Adam Jarrett; Cassandra Johnson Gaither

2014-01-01

Economic and ecological damages caused by wildfire are alarming, and such damages are expected to rise with changes in wildfire regimes, calling for more effective wildfire mitigation and adaptation strategies. Among wildfire adaptation options for forestland owners is purchasing wildfire insurance, which provides compensation to those insured if a wildfire damages...

Smoke exposure and associated health effects across several fire seasons and locations in the Western US

NASA Astrophysics Data System (ADS)

O'Dell, K.; Ford, B.; Gan, R.; Liu, J.; Lassman, W.; Burke, M.; Pfister, G.; Vaidyanathan, A.; Volckens, J.; Magzamen, S.; Fischer, E. V.; Pierce, J. R.

2017-12-01

Wildfires are a significant source of particulate matter in the western United States. Wildfire activity in this region has increased over the past few decades and is projected to continue to increase further due to warmer and drier conditions. Particulate matter with diameters smaller than or equal to 2.5 microns (PM2.5) has known adverse effects on human health. However, due to an inconsistent association of wildfire PM2.5 and several disease outcomes, it is unclear if wildfire PM exerts similar health impacts as anthropogenic PM. Improved wildfire smoke exposure estimates are needed to gain a clearer understanding of the health impacts of wildfire PM2.5. Characterizing PM2.5 concentrations from wildfire smoke is challenging due to the transient nature of smoke. Current methods of determining smoke exposure rely on satellite retrievals of aerosol optical depth (AOD), estimates from chemical transport models (CTMs), or values reported by surface monitoring sites; each of these data sources has some limitations. To improve the accuracy of our exposure estimates, we developed new methods to blend these data. Our results indicate that blending information from the above-mentioned data sources along with counts of wildfire-smoke-related social-media posts results in better characterization of smoke exposure than any individual tool. We link our daily smoke PM2.5 exposure estimates with hospitalization and urgent-care admission data from Washington, Oregon, and Colorado during several fire seasons as well as prescription filling data from Oregon. We find a robust relationship, where a 10 μg m-3 increase in smoke is significantly associated with a 9.5% (95% CI: 6.2, 12.9) increase in the rate of asthma admissions and a 7.7% increase (95% CI: 6.5. 8.8) in the risk for respiratory rescue medication prescription refills. There was no significant association between smoke exposure and any cardiovascular endpoints. Our findings support the association of wildfire smoke exposure with adverse respiratory events, including subclinical outcomes, but we did not find significant associations with any cardiovascular outcomes. Public health messaging should target vulnerable populations to avoid smoke exposure during wildfire events.

Impact of Wildfire on Solute Release in Forested Catchments, Jemez River, New Mexico, USA

NASA Astrophysics Data System (ADS)

Sanchez, R. A.; Meixner, T.; McIntosh, J. C.; Chorover, J.

2017-12-01

Wildfires represent a large disturbance to the hydrology and biogeochemistry of forested catchments. The number, size and severity of wildfires have significantly increased in the western United States since 1990. Nutrients and other elements (e.g. Ca) that were taken up and stored by biomass are released from burned vegetation during forest fires and transported downgradient via overland flow, shallow subsurface flow, and/or deep groundwater flow. Ash accumulations on hillslopes may also store particulate carbon and contain elevated concentrations of elements that maybe leached into surface and ground water over extended periods of time. In 2013, the Thompson Ridge wildfire burned headwater catchments in the Jemez River Basin Critical Zone Observatory (JRB-CZO) within the Valles Caldera National Preserve, New Mexico USA. The burn severity and area impacted were different in the three headwater catchments. This study investigated the impact of the wildfire on surface water quality, including how the fire-induced impacts evolved with time, and how biogeochemical processes controlled post-fire solute concentrations in the surface water. Comparison of pre- and post-fire surface water solute chemistry shows increases in major cations and anions following fire. Increases in nitrate and sulfate concentrations in streams after the wildfire were likely from leaching of burned biomass. The elevated NO3- and SO42- concentrations persisted for over two years, and were even higher during spring snowmelt. Meanwhile, base cation concentrations increased immediately, within a few weeks after the fire, likely related to leaching from combusted organic matter; and, over a period of approximately two months, base cation concentrations returned to pre-fire levels. Trace element behavior was also altered by fire. For example, while pre-fire aluminum concentrations in stream flow increased significantly during the wet seasons (snowmelt and monsoons), the post-fire observations do not show significant changes with increase in discharge.

Uncertainty in Wildfire Behavior

NASA Astrophysics Data System (ADS)

Finney, M.; Cohen, J. D.

2013-12-01

The challenge of predicting or modeling fire behavior is well recognized by scientists and managers who attempt predictions of fire spread rate or growth. At the scale of the spreading fire, the uncertainty in winds, moisture, fuel structure, and fire location make accurate predictions difficult, and the non-linear response of fire spread to these conditions means that average behavior is poorly represented by average environmental parameters. Even more difficult are estimations of threshold behaviors (e.g. spread/no-spread, crown fire initiation, ember generation and spotting) because the fire responds as a step-function to small changes in one or more environmental variables, translating to dynamical feedbacks and unpredictability. Recent research shows that ignition of fuel particles, itself a threshold phenomenon, depends on flame contact which is absolutely not steady or uniform. Recent studies of flame structure in both spreading and stationary fires reveals that much of the non-steadiness of the flames as they contact fuel particles results from buoyant instabilities that produce quasi-periodic flame structures. With fuel particle ignition produced by time-varying heating and short-range flame contact, future improvements in fire behavior modeling will likely require statistical approaches to deal with the uncertainty at all scales, including the level of heat transfer, the fuel arrangement, and weather.

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).

New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

2009-12-01

Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product was developed for routine near-real time verification of these predictions. The footprint of the predicted smoke from identified fires is verified with satellite observations of the spatial extent of smoke aerosols (5km resolution). Based on geostationary aerosol optical depth measurements that provide good time resolution of the horizontal spatial extent of the plumes, these observations do not yield quantitative concentrations of smoke particles at the surface. Predicted surface smoke concentrations are consistent with the limited number of in situ observations of total fine particle mass from all sources; however they are much higher than predicted for most CONUS fires. To assess uncertainty associated with fire emissions estimates, sensitivity analyses are in progress.

Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Gregory, A. E.; Benedict, K. K.; Zhang, S.; Savickas, J.

2017-12-01

Large scale, high severity wildfires in forests have become increasingly prevalent in the western United States due to fire exclusion. Although past work has focused on the immediate consequences of wildfire (ie. runoff magnitude and debris flow), little has been done to understand the post wildfire hydrologic consequences of vegetation regrowth. Furthermore, vegetation is often characterized by static parameterizations within hydrological models. In order to understand the temporal relationship between hydrologic processes and revegetation, we modularized and partially automated the hydrologic modeling process to increase connectivity between remotely sensed data, the Virtual Watershed Platform (a data management resource, called the VWP), input meteorological data, and the Precipitation-Runoff Modeling System (PRMS). This process was used to run simulations in the Valles Caldera of NM, an area impacted by the 2011 Las Conchas Fire, in PRMS before and after the Las Conchas to evaluate hydrologic process changes. The modeling environment addressed some of the existing challenges faced by hydrological modelers. At present, modelers are somewhat limited in their ability to push the boundaries of hydrologic understanding. Specific issues faced by modelers include limited computational resources to model processes at large spatial and temporal scales, data storage capacity and accessibility from the modeling platform, computational and time contraints for experimental modeling, and the skills to integrate modeling software in ways that have not been explored. By taking an interdisciplinary approach, we were able to address some of these challenges by leveraging the skills of hydrologic, data, and computer scientists; and the technical capabilities provided by a combination of on-demand/high-performance computing, distributed data, and cloud services. The hydrologic modeling process was modularized to include options for distributing meteorological data, parameter space experimentation, data format transformation, looping, validation of models and containerization for enabling new analytic scenarios. The user interacts with the modules through Jupyter Notebooks which can be connected to an on-demand computing and HPC environment, and data services built as part of the VWP.

Carbon dynamics in the future forest: the importance of long-term successional legacy and climate–fire interactions

Treesearch

Louise Loudermilk; Robert Scheller; Peter Weisberg; Jian Yang; Thomas Dilts; Sarah Karam; Carl Skinner

2013-01-01

Understanding how climate change may influence forest carbon (C) budgets requires knowledge of forest growth relationships with regional climate, long-term forest succession, and past and future disturbances, such as wildfires and timber harvesting events. We used a landscape-scale model of forest succession, wildfire, and C dynamics (LANDIS-II) to evaluate the effects...

Spatiotemporal dynamics of simulated wildfire, forest management, and forest succession in central Oregon, USA

Treesearch

Ana M. G. Barros; Alan A. Ager; Michelle A. Day; Haiganoush K. Preisler; Thomas A. Spies; Eric White; Robert J. Pabst; Keith A. Olsen; Emily Platt; John D. Bailey; John P. Bolte

2017-01-01

We use the simulation model Envision to analyze long-term wildfire dynamics and the effects of different fuel management scenarios in central Oregon, USA. We simulated a 50-year future where fuel management activities were increased by doubling and tripling the current area treated while retaining existing treatment strategies in terms of spatial distribution and...

Development and application of a probabilistic method for wildfire suppression cost modeling

Treesearch

Matthew P. Thompson; Jessica R. Haas; Mark A. Finney; David E. Calkin; Michael S. Hand; Mark J. Browne; Martin Halek; Karen C. Short; Isaac C. Grenfell

2015-01-01

Wildfire activity and escalating suppression costs continue to threaten the financial health of federal land management agencies. In order to minimize and effectively manage the cost of financial risk, agencies need the ability to quantify that risk. A fundamental aim of this research effort, therefore, is to develop a process for generating risk-based metrics for...

Modeling soil heating and moisture transport under extreme conditions: Forest fires and slash pile burns

Treesearch

W. J. Massman

2012-01-01

Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the...

Trends in global wildfire potential in a changing climate

Treesearch

Y. Liu; J.A. Stanturf; S.L. Goodrick

2009-01-01

The trend in global wildfire potential under the climate change due to the greenhouse effect is investigated. Fire potential is measured by the Keetch-Byram Drought Index (KBDI), which is calculated using the observed maximum temperature and precipitation and projected changes at the end of this century (2070–2100) by general circulation models (GCMs) for present and...

Wildfires in the Lab: Simple Experiment and Models for the Exploration of Excitable Dynamics

ERIC Educational Resources Information Center

Punckt, Christian; Bodega, Pablo S.; Kaira, Prabha; Rotermund, Harm H.

2015-01-01

Wildfires lead to the loss of life and property in many parts of the world. Understanding their dangers and, more particularly, the underlying dynamics which lead to fires of catastrophic scale contributes to better awareness as well as prevention and firefighting capabilities within the affected areas. In order to enable a basic understanding of…

Using WEPP technology to predict erosion and runoff following wildfire

Treesearch

William J. Elliot; Ina Sue Miller; Brandon D. Glaza

2006-01-01

Erosion following wildfire can be as much as 1000 times the erosion from an undisturbed forest. In August, 2005, the largest fire in the lower 48 states occurred in the Umatilla National Forest in Southeast Washington. Researchers from the Rocky Mountain Research Station assisted the forest in estimating soil erosion using three different applications of the WEPP model...

Science You Can Use Bulletin: Wildfire triage: Targeting mitigation based on social, economic, and ecological values

Treesearch

Karl Malcolm; Matthew Thompson; Dave Calkin; Mark Finney; Alan Ager

2012-01-01

Evaluating the risks of wildfire relative to the valuable resources found in any managed landscape requires an interdisciplinary approach. Researchers at the Rocky Mountain Research Station and Western Wildland Threat Assessment Center developed such a process, using a combination of techniques rooted in fire modeling and ecology, economics, decision sciences, and the...

Modeling relationships among 217 fires using remote sensing of burn severity in southern pine forests

Treesearch

Sparkle L. Malone; Leda N. Kobziar; Christina L. Staudhammer; Amr Abd-Elrahman

2011-01-01

Pine flatwoods forests in the southeastern US have experienced severe wildfires over the past few decades, often attributed to fuel load build-up. These forest communities are fire dependent and require regular burning for ecosystem maintenance and health. Although prescribed fire has been used to reduce wildfire risk and maintain ecosystem integrity, managers are...

Modeling climate changes and wildfire interactions: Effects on whitebark pine (Pinus albicaulis) and implications for restoration, Glacier National Park, Montana, USA

Treesearch

Rachel A. Loehman; Allissa Corrow; Robert E. Keane

2011-01-01

Climate changes are projected to profoundly influence vegetation patterns and community compositions, either directly through increased species mortality and shifts in species distributions, or indirectly through disturbance dynamics such as increased wildfire activity and extent, shifting fire regimes, and pathogenesis. High-elevation landscapes have been shown to be...

Allowing a wildfire to burn: estimating the effect on future fire suppression costs

Treesearch

Rachel M. Houtman; Claire A. Montgomery; Aaron R. Gagnon; David E. Calkin; Thomas G. Dietterich; Sean McGregor; Mark Crowley

2013-01-01

Where a legacy of aggressive wildland fire suppression has left forests in need of fuel reduction, allowing wildland fire to burn may provide fuel treatment benefits, thereby reducing suppression costs from subsequent fires. The least-cost-plus-net-value-change model of wildland fire economics includes benefits of wildfire in a framework for evaluating suppression...

Combustion efficiency and emission factors for wildfire-season fires in mixed conifer forests of the northern Rocky Mountains, US

Treesearch

S. P. Urbanski

2013-01-01

In the US, wildfires and prescribed burning present significant challenges to air regulatory agencies attempting to achieve and maintain compliance with air quality regulations. Fire emission factors (EF) are essential input for the emission models used to develop wildland fire emission inventories. Most previous studies quantifying wildland fire EF of temperate...

Regional variation in fire weather controls the reported occurrence of Scottish wildfires

PubMed Central

Legg, Colin J.

2016-01-01

Fire is widely used as a traditional habitat management tool in Scotland, but wildfires pose a significant and growing threat. The financial costs of fighting wildfires are significant and severe wildfires can have substantial environmental impacts. Due to the intermittent occurrence of severe fire seasons, Scotland, and the UK as a whole, remain somewhat unprepared. Scotland currently lacks any form of Fire Danger Rating system that could inform managers and the Fire and Rescue Services (FRS) of periods when there is a risk of increased of fire activity. We aimed evaluate the potential to use outputs from the Canadian Fire Weather Index system (FWI system) to forecast periods of increased fire risk and the potential for ignitions to turn into large wildfires. We collated four and a half years of wildfire data from the Scottish FRS and examined patterns in wildfire occurrence within different regions, seasons, between urban and rural locations and according to FWI system outputs. We used a variety of techniques, including Mahalanobis distances, percentile analysis and Thiel-Sen regression, to scope the best performing FWI system codes and indices. Logistic regression showed significant differences in fire activity between regions, seasons and between urban and rural locations. The Fine Fuel Moisture Code and the Initial Spread Index did a tolerable job of modelling the probability of fire occurrence but further research on fuel moisture dynamics may provide substantial improvements. Overall our results suggest it would be prudent to ready resources and avoid managed burning when FFMC > 75 and/or ISI > 2. PMID:27833814

Regional variation in fire weather controls the reported occurrence of Scottish wildfires.

PubMed

Davies, G Matt; Legg, Colin J

2016-01-01

Fire is widely used as a traditional habitat management tool in Scotland, but wildfires pose a significant and growing threat. The financial costs of fighting wildfires are significant and severe wildfires can have substantial environmental impacts. Due to the intermittent occurrence of severe fire seasons, Scotland, and the UK as a whole, remain somewhat unprepared. Scotland currently lacks any form of Fire Danger Rating system that could inform managers and the Fire and Rescue Services (FRS) of periods when there is a risk of increased of fire activity. We aimed evaluate the potential to use outputs from the Canadian Fire Weather Index system (FWI system) to forecast periods of increased fire risk and the potential for ignitions to turn into large wildfires. We collated four and a half years of wildfire data from the Scottish FRS and examined patterns in wildfire occurrence within different regions, seasons, between urban and rural locations and according to FWI system outputs. We used a variety of techniques, including Mahalanobis distances, percentile analysis and Thiel-Sen regression, to scope the best performing FWI system codes and indices. Logistic regression showed significant differences in fire activity between regions, seasons and between urban and rural locations. The Fine Fuel Moisture Code and the Initial Spread Index did a tolerable job of modelling the probability of fire occurrence but further research on fuel moisture dynamics may provide substantial improvements. Overall our results suggest it would be prudent to ready resources and avoid managed burning when FFMC > 75 and/or ISI > 2.

Assessing accuracy of a probabilistic model for very large fire in the Rocky Mountains: A High Park Fire case study

NASA Astrophysics Data System (ADS)

Stavros, E.; Abatzoglou, J. T.; Larkin, N.; McKenzie, D.; Steel, A.

2012-12-01

Across the western United States, the largest wildfires account for a major proportion of the area burned and substantially affect mountain forests and their associated ecosystem services, among which is pristine air quality. These fires commandeer national attention and significant fire suppression resources. Despite efforts to understand the influence of fuel loading, climate, and weather on annual area burned, few studies have focused on understanding what abiotic factors enable and drive the very largest wildfires. We investigated the correlation between both antecedent climate and in-situ biophysical variables and very large (>20,000 ha) fires in the western United States from 1984 to 2009. We built logistic regression models, at the spatial scale of the national Geographic Area Coordination Centers (GACCs), to estimate the probability that a given day is conducive to a very large wildfire. Models vary in accuracy and in which variables are the best predictors. In a case study of the conditions of the High Park Fire, neighboring Fort Collins, Colorado, occurring in early summer 2012, we evaluate the predictive accuracy of the Rocky Mountain model.

Epidemic cholera spreads like wildfire

NASA Astrophysics Data System (ADS)

Roy, Manojit; Zinck, Richard D.; Bouma, Menno J.; Pascual, Mercedes

2014-01-01

Cholera is on the rise globally, especially epidemic cholera which is characterized by intermittent and unpredictable outbreaks that punctuate periods of regional disease fade-out. These epidemic dynamics remain however poorly understood. Here we examine records for epidemic cholera over both contemporary and historical timelines, from Africa (1990-2006) and former British India (1882-1939). We find that the frequency distribution of outbreak size is fat-tailed, scaling approximately as a power-law. This pattern which shows strong parallels with wildfires is incompatible with existing cholera models developed for endemic regions, as it implies a fundamental role for stochastic transmission and local depletion of susceptible hosts. Application of a recently developed forest-fire model indicates that epidemic cholera dynamics are located above a critical phase transition and propagate in similar ways to aggressive wildfires. These findings have implications for the effectiveness of control measures and the mechanisms that ultimately limit the size of outbreaks.

Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression

PubMed Central

Petrovic, Nada; Alderson, David L.; Carlson, Jean M.

2012-01-01

Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605

Epidemic cholera spreads like wildfire

PubMed Central

Roy, Manojit; Zinck, Richard D.; Bouma, Menno J.; Pascual, Mercedes

2014-01-01

Cholera is on the rise globally, especially epidemic cholera which is characterized by intermittent and unpredictable outbreaks that punctuate periods of regional disease fade-out. These epidemic dynamics remain however poorly understood. Here we examine records for epidemic cholera over both contemporary and historical timelines, from Africa (1990–2006) and former British India (1882–1939). We find that the frequency distribution of outbreak size is fat-tailed, scaling approximately as a power-law. This pattern which shows strong parallels with wildfires is incompatible with existing cholera models developed for endemic regions, as it implies a fundamental role for stochastic transmission and local depletion of susceptible hosts. Application of a recently developed forest-fire model indicates that epidemic cholera dynamics are located above a critical phase transition and propagate in similar ways to aggressive wildfires. These findings have implications for the effectiveness of control measures and the mechanisms that ultimately limit the size of outbreaks. PMID:24424273

Epidemic cholera spreads like wildfire.

PubMed

Roy, Manojit; Zinck, Richard D; Bouma, Menno J; Pascual, Mercedes

2014-01-15

Cholera is on the rise globally, especially epidemic cholera which is characterized by intermittent and unpredictable outbreaks that punctuate periods of regional disease fade-out. These epidemic dynamics remain however poorly understood. Here we examine records for epidemic cholera over both contemporary and historical timelines, from Africa (1990-2006) and former British India (1882-1939). We find that the frequency distribution of outbreak size is fat-tailed, scaling approximately as a power-law. This pattern which shows strong parallels with wildfires is incompatible with existing cholera models developed for endemic regions, as it implies a fundamental role for stochastic transmission and local depletion of susceptible hosts. Application of a recently developed forest-fire model indicates that epidemic cholera dynamics are located above a critical phase transition and propagate in similar ways to aggressive wildfires. These findings have implications for the effectiveness of control measures and the mechanisms that ultimately limit the size of outbreaks.

Application of wildfire simulation models for risk analysis

NASA Astrophysics Data System (ADS)

Ager, A.; Finney, M.

2009-04-01

Wildfire simulation models are being widely used by fire and fuels specialists in the U.S. to support tactical and strategic decisions related to the mitigation of wildfire risk. Much of this application has resulted from the development of a minimum travel time (MTT) fire spread algorithm (M. Finney) that makes it computationally feasible to simulate thousands of fires and generate burn probability and intensity maps over large areas (10,000 - 2,000,000 ha). The MTT algorithm is parallelized for multi-threaded processing and is imbedded in a number of research and applied fire modeling applications. High performance computers (e.g., 32-way 64 bit SMP) are typically used for MTT simulations, although the algorithm is also implemented in the 32 bit desktop FlamMap3 program (www.fire.org). Extensive testing has shown that this algorithm can replicate large fire boundaries in the heterogeneous landscapes that typify much of the wildlands in the western U.S. In this paper, we describe the application of the MTT algorithm to understand spatial patterns of burn probability (BP), and to analyze wildfire risk to key human and ecological values. The work is focused on a federally-managed 2,000,000 ha landscape in the central interior region of Oregon State, USA. The fire-prone study area encompasses a wide array of topography and fuel types and a number of highly valued resources that are susceptible to fire. We quantitatively defined risk as the product of the probability of a fire and the resulting consequence. Burn probabilities at specific intensity classes were estimated for each 100 x 100 m pixel by simulating 100,000 wildfires under burn conditions that replicated recent severe wildfire events that occurred under conditions where fire suppression was generally ineffective (97th percentile, August weather). We repeated the simulation under milder weather (70th percentile, August weather) to replicate a "wildland fire use scenario" where suppression is minimized to manage fires for fuel reduction. The average BP was calculated for these scenarios to examine variation within and among a number of key designated management units, including forest-urban interface, conservation areas, protected species habitat, municipal watersheds, recreation areas, and others. To quantify risk, we developed a number of loss-benefit functions using fire effects models that relate fire intensity to tree mortality and biomass consumption. We used these relationships to measure the change in highly-valued old forest, designated wildlife conservation areas, aboveground carbon, surface fuels, and other wildland values. The loss-benefit functions were then coupled with BP's for different intensity classes to estimate expected value change (risk) for each pixel. For a subset of the study area we also measured the change in risk from fuels management for selected resources. Estimates of BP, excluding non burnable fuels (water, rock), fro the simulations ranged from 0.00001 to 0.026 within the study area, with a mean value of 0.007. In comparison, the annual burn probability estimated from fire occurrence data within the study area (1910 - 2003) was 0.0022. The estimate from simulations represents the average probability of a random pixel burning from a single large fire that escapes suppression, hence some difference is expected. Variation in BP among designated conservation and fire protection units was relatively large and illustrated spatial differences in wildfire likelihood among highly values resources. For instance, among the 130 different forest-urban interface areas, average BP varied from 0.0001 to 0.02. Average BP for nesting sites used by the endangered Northern spotted owl averaged 0.04 and varied from 0.001 to 0.01. The marginal BP's for high fire intensities was higher for many of the conservation areas compared the surrounding managed forest. Conservation areas that were located on the lee side of non-burnable fuels such as lava flows and lakes showed markedly reduced BP. When wildfire probabilities were combined with habitat loss functions for the Northern spotted owl, we observed expected loss from a random wildfire event ranging from 0.0 to 9.4% with a mean value of 1.5%. Expected loss was strongly correlated with BP for owl habitat, apparently because fires at very low intensities caused understory mortality and reduced stand canopy closure below minimum levels. The effect of simulating strategic fuel treatments on a subunit of the area resulted in significant decrease in expected loss of owl habitat. The effect of changing weather from a severe to mild (97th to 70th) percentile weather resulted in a dramatic 8-fold drop in BP and reduced the average wildfire size. However, the reduction was not uniform with the departures well correlated with specific fuel models. In total, this work demonstrated the application of wildfire spread models to quantitative risk assessment for fuels management on federally-managed lands in the U.S. The analyses revealed spatial variation in BP that is useful in prioritizing fuels treatments and guiding other wildfire mitigation activities. The work also illuminated the conflict between biodiversity conservation efforts on federally-managed lands and the high wildfire risk on fire-prone landscapes.

Capabilities of current wildfire models when simulating topographical flow

NASA Astrophysics Data System (ADS)

Kochanski, A.; Jenkins, M.; Krueger, S. K.; McDermott, R.; Mell, W.

2009-12-01

Accurate predictions of the growth, spread and suppression of wild fires rely heavily on the correct prediction of the local wind conditions and the interactions between the fire and the local ambient airflow. Resolving local flows, often strongly affected by topographical features like hills, canyons and ridges, is a prerequisite for accurate simulation and prediction of fire behaviors. In this study, we present the results of high-resolution numerical simulations of the flow over a smooth hill, performed using (1) the NIST WFDS (WUI or Wildland-Urban-Interface version of the FDS or Fire Dynamic Simulator), and (2) the LES version of the NCAR Weather Research and Forecasting (WRF-LES) model. The WFDS model is in the initial stages of development for application to wind flow and fire spread over complex terrain. The focus of the talk is to assess how well simple topographical flow is represented by WRF-LES and the current version of WFDS. If sufficient progress has been made prior to the meeting then the importance of the discrepancies between the predicted and measured winds, in terms of simulated fire behavior, will be examined.

Short and long-term carbon balance of bioenergy electricity production fueled by forest treatments.

PubMed

Kelsey, Katharine C; Barnes, Kallie L; Ryan, Michael G; Neff, Jason C

2014-01-01

Forests store large amounts of carbon in forest biomass, and this carbon can be released to the atmosphere following forest disturbance or management. In the western US, forest fuel reduction treatments designed to reduce the risk of high severity wildfire can change forest carbon balance by removing carbon in the form of biomass, and by altering future potential wildfire behavior in the treated stand. Forest treatment carbon balance is further affected by the fate of this biomass removed from the forest, and the occurrence and intensity of a future wildfire in this stand. In this study we investigate the carbon balance of a forest treatment with varying fates of harvested biomass, including use for bioenergy electricity production, and under varying scenarios of future disturbance and regeneration. Bioenergy is a carbon intensive energy source; in our study we find that carbon emissions from bioenergy electricity production are nearly twice that of coal for the same amount of electricity. However, some emissions from bioenergy electricity production are offset by avoided fossil fuel electricity emissions. The carbon benefit achieved by using harvested biomass for bioenergy electricity production may be increased through avoided pyrogenic emissions if the forest treatment can effectively reduce severity. Forest treatments with the use of harvested biomass for electricity generation can reduce carbon emissions to the atmosphere by offsetting fossil fuel electricity generation emissions, and potentially by avoided pyrogenic emissions due to reduced intensity and severity of a future wildfire in the treated stand. However, changes in future wildfire and regeneration regimes may affect forest carbon balance and these climate-induced changes may influence forest carbon balance as much, or more, than bioenergy production.

Modelling Spatial Patterns and Drivers of Wildfires in Honduras Using Remote Sensing and Geographic Information Systems

NASA Astrophysics Data System (ADS)

Valdez Vasquez, M. C.; Chen, C. F.; Chiang, S. H.

2016-12-01

Forests in Honduras are one of the most important resources as they provide a wide range of environmental, economic, and social benefits. However, they are endangered as a result of the relentless occurrence of wildfires during the dry season. Despite the knowledge acquired by the population concerning the effects of wildfires, the frequency is increasing, a pattern attributable to the numerous ignition sources linked to human activity. The purpose of this study is to integrate the wildfire occurrences throughout the 2010-2015 period with a series of anthropogenic and non-anthropogenic variables using the random forest algorithm (RF). We use a series of variables that represent the anthropogenic activity, the flammability of vegetation, climatic conditions, and topography. To represent the anthropogenic activity, we included the continuous distances to rivers, roads, and settlements. To characterize the vegetation flammability, we used the normalized difference vegetation index (NDVI) and the normalized multi-band drought index (NMDI) acquired from MODIS surface reflectance data. Additionally, we included the topographical variables elevation, slope, and solar radiation derived from the ASTER global digital elevation model (GDEM V2). To represent the climatic conditions, we employed the land surface temperature (LST) product from the MODIS sensor and the WorldClim precipitation data. We analyzed the explanatory variables through native RF variable importance analysis and jackknife test, and the results revealed that the dry fuel conditions and low precipitation combined with the proximity to non-paved roads were the major drivers of wildfires. Furthermore, we predicted the areas with highest wildfire susceptibility, which are located mainly in the central and eastern regions of the country, within coniferous and mixed forests. Results acquired were validated using the area under the receiver operating characteristic (ROC) curve and the point biserial correlation and both validation metrics showed satisfactory agreement with the test data. Predictions of forest fire risk and its spatial variability are important instruments for proper management and the results acquired can lead to enhanced preventive measures to minimize risk and reduce the impacts caused by wildfires.

Satellite-derived aerosol radiative forcing from the 2004 British Columbia wildfires

USGS Publications Warehouse

Guo, Song; Leighton, H.

2008-01-01

The British Columbia wildfires of 2004 was one of the largest wildfire events in the last ten years in Canada. Both the shortwave and longwave smoke aerosol radiative forcing at the top-of-atmosphere (TOA) are investigated using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Clouds and the Earth's Radiant Energy System (CERES) instruments. Relationships between the radiative forcing fluxes (??F) and wildfire aerosol optical thickness (AOT) at 0.55 ??m (??0.55) are deduced for both noontime instantaneous forcing and diurnally averaged forcing. The noontime averaged instantaneous shortwave and longwave smoke aerosol radiative forcing at the TOA are 45.8??27.5 W m-2 and -12.6??6.9 W m-2, respectively for a selected study area between 62??N and 68??N in latitude and 125??W and 145??W in longitude over three mainly clear-sky days (23-25 June). The derived diurnally averaged smoke aerosol shortwave radiative forcing is 19.9??12.1 W m-2 for a mean ??0.55 of 1.88??0.71 over the same time period. The derived ??F-?? relationship can be implemented in the radiation scheme used in regional climate models to assess the effect of wildfire aerosols.

Wildfire in the Critical Zone: Pyro-Geomorphic Feedbacks in Upland Forests

NASA Astrophysics Data System (ADS)

Sheridan, G. J.; Inbar, A.; Metzen, D.; Van der Sant, R.; Lane, P. N. J.; Nyman, P.

2017-12-01

Wildfire often triggers a dramatic geomorphic response, with erosion rates several orders of magnitude greater than background rates. The fact that wildfire is linked to increased soil erosion is well established, but could it also work the other way around? Is it possible that, over time, soil erosion could lead to an increase in wildfire? The proposed mechanism for this is a potential positive feedback between post-fire soil erosion, soil depth, and forest flammability. More fire-related erosion may, over time, lead to less soil water holding capacity, more open vegetation with drier fuels, more fire, and in turn more fire related erosion. These pyro-geomorphic feedbacks may help explain the co-evolved soil-vegetation-fire systems that are observed in the landscape. More broadly, the concept of "wildfire in the critical zone", with a greater emphasis on the interactions between fire, vegetation, hydrology, and geomorphology, may help us understand and predict the trajectory of change as the vegetation-soil-fire system responds and adjusts to the new climate forcing. This presentation will combine an extensive soil, vegetation, and post fire erosion experimental dataset, with conceptual and numerical modelling, to evaluate the significance of the potential pyro-geomorphic feedbacks described above.

Some Wildfire Ignition Causes Pose More Risk of Destroying Houses than Others

PubMed Central

Penman, Trent D.; Price, Owen F.

2016-01-01

Many houses are at risk of being destroyed by wildfires. While previous studies have improved our understanding of how, when and why houses are destroyed by wildfires, little attention has been given to how these fires started. We compiled a dataset of wildfires that destroyed houses in New South Wales and Victoria and, by comparing against wildfires where no houses were destroyed, investigated the relationship between the distribution of ignition causes for wildfires that did and did not destroy houses. Powerlines, lightning and deliberate ignitions are the main causes of wildfires that destroyed houses. Powerlines were 6 times more common in the wildfires that destroyed houses data than in the wildfires where no houses were destroyed data and lightning was 2 times more common. For deliberate- and powerline-caused wildfires, temperature, wind speed, and forest fire danger index were all significantly higher and relative humidity significantly lower (P < 0.05) on the day of ignition for wildfires that destroyed houses compared with wildfires where no houses were destroyed. For all powerline-caused wildfires the first house destroyed always occurred on the day of ignition. In contrast, the first house destroyed was after the day of ignition for 78% of lightning-caused wildfires. Lightning-caused wildfires that destroyed houses were significantly larger (P < 0.001) in area than human-caused wildfires that destroyed houses. Our results suggest that targeting fire prevention strategies around ignition causes, such as improving powerline safety and targeted arson reduction programmes, and reducing fire spread may decrease the number of wildfires that destroy houses. PMID:27598325

Some Wildfire Ignition Causes Pose More Risk of Destroying Houses than Others.

PubMed

Collins, Kathryn M; Penman, Trent D; Price, Owen F

2016-01-01

Many houses are at risk of being destroyed by wildfires. While previous studies have improved our understanding of how, when and why houses are destroyed by wildfires, little attention has been given to how these fires started. We compiled a dataset of wildfires that destroyed houses in New South Wales and Victoria and, by comparing against wildfires where no houses were destroyed, investigated the relationship between the distribution of ignition causes for wildfires that did and did not destroy houses. Powerlines, lightning and deliberate ignitions are the main causes of wildfires that destroyed houses. Powerlines were 6 times more common in the wildfires that destroyed houses data than in the wildfires where no houses were destroyed data and lightning was 2 times more common. For deliberate- and powerline-caused wildfires, temperature, wind speed, and forest fire danger index were all significantly higher and relative humidity significantly lower (P < 0.05) on the day of ignition for wildfires that destroyed houses compared with wildfires where no houses were destroyed. For all powerline-caused wildfires the first house destroyed always occurred on the day of ignition. In contrast, the first house destroyed was after the day of ignition for 78% of lightning-caused wildfires. Lightning-caused wildfires that destroyed houses were significantly larger (P < 0.001) in area than human-caused wildfires that destroyed houses. Our results suggest that targeting fire prevention strategies around ignition causes, such as improving powerline safety and targeted arson reduction programmes, and reducing fire spread may decrease the number of wildfires that destroy houses.

Evaluating alternative fuel treatment strategies to reduce wildfire losses in a Mediterranean area

Treesearch

Michele Salis; Maurizio Laconi; Alan A. Ager; Fermin J. Alcasena; Bachisio Arca; Olga Lozano; Ana Fernandes de Oliveira; Donatella Spano

2016-01-01

The goal of this work is to evaluate by a modeling approach the effectiveness of alternative fuel treatment strategies to reduce potential losses from wildfires in Mediterranean areas. We compared strategic fuel treatments located near specific human values vs random locations, and treated 3, 9 and 15% of a 68,000 ha study area located in Sardinia, Italy. The...

Forecasting European Wildfires Today and in the Future

NASA Astrophysics Data System (ADS)

Navarro Abellan, Maria; Porras Alegre, Ignasi; María Sole, Josep; Gálvez, Pedro; Bielski, Conrad; Nurmi, Pertti

2017-04-01

Society as a whole is increasingly exposed and vulnerable to natural disasters due to extreme weather events exacerbated by climate change. The increased frequency of wildfires is not only a result of a changing climate, but wildfires themselves also produce a significant amount of greenhouse gases that, in-turn, further contribute to global warming. I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) is an innovation project funded by the European Commission , which aims to use social media, smartphones and wearables to improve natural disaster management by integrating existing services, both local and European, into a platform that supports the entire emergency management cycle. In order to assess the impact of climate change on wildfire hazards, METEOSIM designed two different System Processes (SP) that will be integrated into the I-REACT service that can provide information on a variety of time scales. SP1 - Climate Change Impact The climate change impact on climate variables related to fires is calculated by building an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CORDEX data. A validation and an Empirical-Statistical Downscaling (ESD) calibration are done to assess the changes in the past of the climatic variables related to wildfires (temperature, precipitation, wind, relative humidity and Fire Weather Index). Calculations in the trend and the frequency of extreme events of those variables are done for three time scales: near-term (2011-2040), mid-term (2041-2070) and long term (2071-2100). SP2 - Operational daily forecast of the Canadian Forest Fire Weather Index (FWI) Using ensemble data from the ECMWF and from the GLAMEPS (multi-model ensemble) models, both supplied by the Finnish Meteorological Institute (FMI), the Fire Weather Index (FWI) and its index components are produced for each ensemble member within a wide forecast time range, from a few hours up to 10 days resulting in a probabilistic output of the FWI for different regions in Europe. This work will improve the currently available information to various wildfire information users such as fire departments, the civil protection, local authorities, etc., where accurate and reliable information in extreme weather situations are vital for improving planning and risk management.

geoKepler Workflow Module for Computationally Scalable and Reproducible Geoprocessing and Modeling

NASA Astrophysics Data System (ADS)

Cowart, C.; Block, J.; Crawl, D.; Graham, J.; Gupta, A.; Nguyen, M.; de Callafon, R.; Smarr, L.; Altintas, I.

2015-12-01

The NSF-funded WIFIRE project has developed an open-source, online geospatial workflow platform for unifying geoprocessing tools and models for for fire and other geospatially dependent modeling applications. It is a product of WIFIRE's objective to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. geoKepler includes a set of reusable GIS components, or actors, for the Kepler Scientific Workflow System (https://kepler-project.org). Actors exist for reading and writing GIS data in formats such as Shapefile, GeoJSON, KML, and using OGC web services such as WFS. The actors also allow for calling geoprocessing tools in other packages such as GDAL and GRASS. Kepler integrates functions from multiple platforms and file formats into one framework, thus enabling optimal GIS interoperability, model coupling, and scalability. Products of the GIS actors can be fed directly to models such as FARSITE and WRF. Kepler's ability to schedule and scale processes using Hadoop and Spark also makes geoprocessing ultimately extensible and computationally scalable. The reusable workflows in geoKepler can be made to run automatically when alerted by real-time environmental conditions. Here, we show breakthroughs in the speed of creating complex data for hazard assessments with this platform. We also demonstrate geoKepler workflows that use Data Assimilation to ingest real-time weather data into wildfire simulations, and for data mining techniques to gain insight into environmental conditions affecting fire behavior. Existing machine learning tools and libraries such as R and MLlib are being leveraged for this purpose in Kepler, as well as Kepler's Distributed Data Parallel (DDP) capability to provide a framework for scalable processing. geoKepler workflows can be executed via an iPython notebook as a part of a Jupyter hub at UC San Diego for sharing and reporting of the scientific analysis and results from various runs of geoKepler workflows. The communication between iPython and Kepler workflow executions is established through an iPython magic function for Kepler that we have implemented. In summary, geoKepler is an ecosystem that makes geospatial processing and analysis of any kind programmable, reusable, scalable and sharable.

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.

Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland-Urban Interfaces in Southern Italy

NASA Astrophysics Data System (ADS)

Elia, Mario; Lafortezza, Raffaele; Lovreglio, Raffaella; Sanesi, Giovanni

2015-09-01

The dramatic increase of fire hazard in wildland-urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures.

Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland-Urban Interfaces in Southern Italy.

PubMed

Elia, Mario; Lafortezza, Raffaele; Lovreglio, Raffaella; Sanesi, Giovanni

2015-09-01

The dramatic increase of fire hazard in wildland-urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures.

Impacts of Wildfires on Land Surface Phenology of Western US Forests

NASA Astrophysics Data System (ADS)

Wang, J.; Zhang, X.

2017-12-01

Land surface phenology (LSP) characterizes seasonal dynamics of vegetation communities within a satellite pixel. The temporal variation of LSP has been widely associated with recent global climate change. However, few studies have focused on the influence of land disturbance, such as wildfire, on LSP variations, which is particularly true at a continental scale. Wildfire has increased in size and severity in the western United States (US) during last few decades. To explore wildfire impacts on LSP in the western US forest, we analyzed the start of growing season (SOS) integrated from the entire forest area, the burned area, and the unburned area, respectively. Specifically, SOS was derived from time series of daily MODIS surface reflectance product at 250 m using a hybrid piecewise logistic detection model. The annual burn perimeters during 2000-2014 were obtained from Monitoring Trends in Burn Severity maps to study the wildfire effect on the SOS in the subsequent years (2001-2015). The wildfire effect was analyzed at three levels: the entire western US, Environmental Protection Agency's Level III ecoregions, and states. Results show that wildfires basically advance SOS but have diverse effects with different regions and years. Comparing SOS in the burned areas with that in surrounding unburned areas from 2001-2015, it was found that the SOS shift was -3.4 days (-: earlier; +: later) on average in the western US forests, and varied from -16.1 to 13.1 days across ecoregions and from -11.4 to 4.3 days across states. Because of the small proportion of annual burned areas (<0.7%) over the entire region, the SOS shift in the burned areas had limited influences on the overall SOS, which caused shifts of -0.06 days over the entire western US, from -0.2 to 0.2 days across ecoregions, and -0.06 to 0.13 days across states. Overall, this study demonstrates that wildfires strongly impact SOS at local areas although the effect in the large region is relatively limited.

Social disorder, accidents, and municipal wildfires

Treesearch

Douglas S. Thomas; David T. Butry; Jeffrey P. Prestemon

2012-01-01

Societal safeguards, established by those who have shared perceptions of the importance of safety and taking preventative measures, reduce the incidence of accidents that harm people and damage property. These safeguards prevent or discourage community members from partaking in careless behaviors that often lead to accidents. Wildland urban interface communities that...

Effects of fire on chaparral soils in Arizona and California and postfire management implications

Treesearch

Leonard F. DeBano

1989-01-01

Wildfires and prescribed burns are common throughout Arizona and California chaparral. Predicting fire effects requires understanding fire behavior, estimating soil heating, and predicting changes in soil properties. Substantial quantities of some nutrients, particularly nitrogen and phosphorus, are lost directly during combustion. Highly available nutrients released...

Potential climate change impacts on fire weather in the United States

Treesearch

Warren E. Heilman; Ying Tang; Lifeng Luo; Shiyuan Zhong; Julie Winkler; Xindi. Bian

2015-01-01

Researchers at Michigan State University and the Forest Service's Northern Research Station worked on a joint study to examine the possible effects of future global and regional climate change on the occurrence of fire-weather patterns often associated with extreme and erratic wildfire behavior in the United States.

Sudden Oak Death mortality and fire: lessons from the basin complex

Treesearch

Chris Lee; Yana Valachovic; Susan Frankel; Katie Palmieri

2010-01-01

Land managers, fire suppression professionals, and research scientists have speculated about the relationship between increased Phytophthora ramorum-caused hardwood mortality and wildfire incidence, severity, and behavior in coastal California. Little quantitative data has emerged to measure the nature of any such relationship. The Basin Complex...

Synoptic backgrounds of the widest wildfire in Mazandaran Province of Iran during December 11-13, 2010

NASA Astrophysics Data System (ADS)

Ghavidel, Yousef; Farajzadeh, Manuchehr; Khaleghi Babaei, Meysam

2016-12-01

In this paper, atmospheric origins of the widest wildfire in Mazandaran province on 11-13th of December, 2010 have been investigated. Data sets of this research include maximum daily temperature (MDT), minimum relative humidity (MRH) of terrestrial stations, dynamic and thermodynamic features of the atmosphere, Gridded data sets of Self-Calibrated Palmer drought severity index (SCPDSI) and global drought dataset standardized precipitation-evapotranspiration index (SPEI) and data related to the time and the extent of the wildfire. The ``environmental to circulation'' approach to synoptic classification has been used to investigate relationships between local-scale surface environment (wildfire) and the synoptic-scale atmospheric circulation conditions. Results of study show that during the 3-day wide wildfire, the average of MDT and the MRH was significantly different from the long-term average. During the aforementioned wildfire, the average of MDT in Mazandaran province was 26 °C and the average of MRH was reported 35 %. The long-term average of MDT and the MRH in Mazandaran province during 3 days of wildfire was 12.3 °C and 68 %, respectively. Therefore, the MDT has a positive abnormality of 13.7 °C and the MRH has a negative abnormality of 33 %. In addition, monthly SCPDSI and SPEI indicated severe drought conditions at December 2010 in Mazandaran. Analysis of SLP maps shows that during the 3-day fire, a pressure center of 1110 hPa on Persian Gulf and a very low-pressure center on Turkey and Asia Minor were created. Normally, this event has caused the pressure gradient and warm and dry air advection from Arabian Peninsula to higher longitudes, particularly Mazandaran province. Consequently, the MDT increased and the wildfire of Mazandaran forest took place in an area of 220 ha. Zonal wind maps signify the weakness of Zonal wind and meridional wind maps show the southern direction of meridional wind flow during the wide wildfire. Moreover, Omega maps prove that during the aforementioned wildfire, the Omega flow has been positive and the warm air flow has subsidence. This made the infusion of warm air and increased the MDT substantially and consequently the wildfire occurrence was facilitated. Temperature advection maps showed that in the level of 1000 hPa, the warm air blowing source is originated from Arabian Peninsula, in the level of 850 hPa from the Arabian Peninsula and Iraq and in the level of 700 and 500 hPa from Ethiopia, Arabian Peninsula and Iraq. The Hybrid-Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model outputs confirm the synoptic mechanisms for the discussed wildfire.

The impact of antecedent fire area on burned area in southern California coastal ecosystems

USGS Publications Warehouse

Price, Owen F.; Bradstock, Ross A.; Keeley, Jon E.; Syphard, Alexandra D.

2012-01-01

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ∼ 0.25).

The impact of antecedent fire area on burned area in southern California coastal ecosystems.

PubMed

Price, Owen F; Bradstock, Ross A; Keeley, Jon E; Syphard, Alexandra D

2012-12-30

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ~ 0.25). Copyright © 2012 Elsevier Ltd. All rights reserved.

Trial by fire: Community Wildfire Protection Plans put to the test

Treesearch

Pamela J. Jakes; Victoria Sturtevant

2013-01-01

Research has found that community wildfire protection planning can make significant contributions to wildfire mitigation and preparedness, but can the planning process and resulting Community Wildfire Protection Plans make a difference to wildfire response and recovery? In case studies conducted in four USA communities with Community Wildfire Protection Plans in place...

Simulated impacts of mountain pine beetle and wildfire disturbances on forest vegetation composition and carbon stocks in the Southern Rocky Mountains

USGS Publications Warehouse

Caldwell, Megan K.; Hawbaker, Todd J.; Briggs, Jenny S.; Cigan, P.W.; Stitt, Susan

2013-01-01

Forests play an important role in sequestering carbon and offsetting anthropogenic greenhouse gas emissions, but changing disturbance regimes may compromise the capability of forests to store carbon. In the Southern Rocky Mountains, a recent outbreak of mountain pine beetle (Dendroctonus ponderosae; MPB) has caused levels of tree mortality that are unprecedented in recorded history. To evaluate the long-term impacts of both this insect outbreak and another characteristic disturbance in these forests, high-severity wildfire, we simulated potential changes in species composition and carbon stocks using the Forest Vegetation Simulator (FVS). Simulations were completed for 3 scenarios (no disturbance, actual MPB infestation, and modeled wildfire) using field data collected in 2010 at 97 plots in the lodgepole pine-dominated forests of eastern Grand County, Colorado, which were heavily impacted by MPB after 2002. Results of the simulations showed that (1) lodgepole pine remained dominant over time in all scenarios, with basal area recovering to pre-disturbance levels 70–80 yr after disturbance; (2) wildfire caused a greater magnitude of change than did MPB in both patterns of succession and distribution of carbon among biomass pools; (3) levels of standing-live carbon returned to pre-disturbance conditions after 40 vs. 50 yr following MPB vs. wildfire disturbance, respectively, but took 120 vs. 150 yr to converge with conditions in the undisturbed scenario. Lodgepole pine forests appear to be relatively resilient to both of the disturbances we modeled, although changes in climate, future disturbance regimes, and other factors may significantly affect future rates of regeneration and ecosystem response.

Potential influence of wildfire in modulating climate-induced forest redistribution in a central Rocky Mountain landscape

USGS Publications Warehouse

Campbell, John L.; Shinneman, Douglas

2017-01-01

IntroductionClimate change is expected to impose significant tension on the geographic distribution of tree species. Yet, tree species range shifts may be delayed by their long life spans, capacity to withstand long periods of physiological stress, and dispersal limitations. Wildfire could theoretically break this biological inertia by killing forest canopies and facilitating species redistribution under changing climate. We investigated the capacity of wildfire to modulate climate-induced tree redistribution across a montane landscape in the central Rocky Mountains under three climate scenarios (contemporary and two warmer future climates) and three wildfire scenarios (representing historical, suppressed, and future fire regimes).MethodsDistributions of four common tree species were projected over 90 years by pairing a climate niche model with a forest landscape simulation model that simulates species dispersal, establishment, and mortality under alternative disturbance regimes and climate scenarios.ResultsThree species (Douglas-fir, lodgepole pine, subalpine fir) declined in abundance over time, due to climate-driven contraction in area suitable for establishment, while one species (ponderosa pine) was unable to exploit climate-driven expansion of area suitable for establishment. Increased fire frequency accelerated declines in area occupied by Douglas-fir, lodgepole pine, and subalpine fir, and it maintained local abundance but not range expansion of ponderosa pine.ConclusionsWildfire may play a larger role in eliminating these conifer species along trailing edges of their distributions than facilitating establishment along leading edges, in part due to dispersal limitations and interspecific competition, and future populations may increasingly depend on persistence in locations unfavorable for their establishment.

The increasing wildfire and post-fire debris-flow threat in western USA, and implications for consequences of climate change

USGS Publications Warehouse

Cannon, Susan H.; DeGraff, Jerry

2009-01-01

In southern California and the intermountain west of the USA, debris flows generated from recently-burned basins pose significant hazards. Increases in the frequency and size of wildfires throughout the western USA can be attributed to increases in the number of fire ignitions, fire suppression practices, and climatic influences. Increased urbanization throughout the western USA, combined with the increased wildfire magnitude and frequency, carries with it the increased threat of subsequent debris-flow occurrence. Differences between rainfall thresholds and empirical debris-flow susceptibility models for southern California and the intermountain west indicate a strong influence of climatic and geologic settings on post-fire debris-flow potential. The linkages between wildfires, debris-flow occurrence, and global warming suggests that the experiences in the western United States are highly likely to be duplicated in many other parts of the world, and necessitate hazard assessment tools that are specific to local climates and physiographies.

The economics of fuel management: Wildfire, invasive plants, and the dynamics of sagebrush rangelands in the western United States

Treesearch

Michael H. Taylor; Kimberly Rollins; Mimako Kobayashi; Robin J. Tausch

2013-01-01

In this article we develop a simulation model to evaluate the economic efficiency of fuel treatments and apply it to two sagebrush ecosystems in the Great Basin of the western United States: the Wyoming Sagebrush Steppe and Mountain Big Sagebrush ecosystems. These ecosystems face the two most prominent concerns in sagebrush ecosystems relative to wildfire: annual grass...

Using cellular automata to simulate forest fire propagation in Portugal

NASA Astrophysics Data System (ADS)

Freire, Joana; daCamara, Carlos

2017-04-01

Wildfires in the Mediterranean region have severe damaging effects mainly due to large fire events [1, 2]. When restricting to Portugal, wildfires have burned over 1:4 million ha in the last decade. Considering the increasing tendency in the extent and severity of wildfires [1, 2], the availability of modeling tools of fire episodes is of crucial importance. Two main types of mathematical models are generally available, namely deterministic and stochastic models. Deterministic models attempt a description of fires, fuel and atmosphere as multiphase continua prescribing mass, momentum and energy conservation, which typically leads to systems of coupled PDEs to be solved numerically on a grid. Simpler descriptions, such as FARSITE, neglect the interaction with atmosphere and propagate the fire front using wave techniques. One of the most important stochastic models are Cellular Automata (CA), in which space is discretized into cells, and physical quantities take on a finite set of values at each cell. The cells evolve in discrete time according to a set of transition rules, and the states of the neighboring cells. In the present work, we implement and then improve a simple and fast CA model designed to operationally simulate wildfires in Portugal. The reference CA model chosen [3] has the advantage of having been applied successfully in other Mediterranean ecosystems, namely to historical fires in Greece. The model is defined on a square grid with propagation to 8 nearest and next-nearest neighbors, where each cell is characterized by 4 possible discrete states, corresponding to burning, not-yet burned, fuel-free and completely burned cells, with 4 possible rules of evolution which take into account fuel properties, meteorological conditions, and topography. As a CA model, it offers the possibility to run a very high number of simulations in order to verify and apply the model, and is easily modified by implementing additional variables and different rules for the evolution of the fire spread. We present and discuss the application of the CA model to the "Tavira wildfire" in which approximately 24,800ha were burned. The event took place in summer 2012, between July 18 and 21, and spread in the Tavira and São Brás de Alportel municipalities of Algarve, a province in the southern coast of Portugal. [1] DaCamara et. al. (2014), International Journal of Wildland Fire 23. [2] Amraoui et. al. (2013), Forest Ecology and Management 294. [3] Alexandridis et. al. (2008), Applied Mathematics and Computation 204.

Forecasting and visualization of wildfires in a 3D geographical information system

NASA Astrophysics Data System (ADS)

Castrillón, M.; Jorge, P. A.; López, I. J.; Macías, A.; Martín, D.; Nebot, R. J.; Sabbagh, I.; Quintana, F. M.; Sánchez, J.; Sánchez, A. J.; Suárez, J. P.; Trujillo, A.

2011-03-01

This paper describes a wildfire forecasting application based on a 3D virtual environment and a fire simulation engine. A novel open-source framework is presented for the development of 3D graphics applications over large geographic areas, offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community. The application includes a remote module that allows simultaneous connections of several users for monitoring a real wildfire event. The system is able to make a realistic composition of what is really happening in the area of the wildfire with dynamic 3D objects and location of human and material resources in real time, providing a new perspective to analyze the wildfire information. The user is enabled to simulate and visualize the propagation of a fire on the terrain integrating at the same time spatial information on topography and vegetation types with weather and wind data. The application communicates with a remote web service that is in charge of the simulation task. The user may specify several parameters through a friendly interface before the application sends the information to the remote server responsible of carrying out the wildfire forecasting using the FARSITE simulation model. During the process, the server connects to different external resources to obtain up-to-date meteorological data. The client application implements a realistic 3D visualization of the fire evolution on the landscape. A Level Of Detail (LOD) strategy contributes to improve the performance of the visualization system.

The lost summer: Community experiences of large wildfires in Trinity County, California

Treesearch

Emily J. Davis; Cassandra Moseley; Pamela Jakes; Max Nielsen-Pincus

2011-01-01

As wildfires are increasing in scale and duration, and communities are increasingly located where these wildfires are occurring, we need a clearer understanding of how large wildfires affect economic and social well being. These wildfires can have complex impacts on rural public lands communities. They can threaten homes, public health, and livelihoods. Wildfires can...

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.

Experimental & Numerical Modeling of Non-combusting Model Firebrands' Transport

NASA Astrophysics Data System (ADS)

Tohidi, Ali; Kaye, Nigel

2016-11-01

Fire spotting is one of the major mechanisms of wildfire spread. Three phases of this phenomenon are firebrand formation and break-off from burning vegetation, lofting and downwind transport of firebrands through the velocity field of the wildfire, and spot fire ignition upon landing. The lofting and downwind transport phase is modeled by conducting large-scale wind tunnel experiments. Non-combusting rod-like model firebrands with different aspect ratios are released within the velocity field of a jet in a boundary layer cross-flow that approximates the wildfire velocity field. Characteristics of the firebrand dispersion are quantified by capturing the full trajectory of the model firebrands using the developed image processing algorithm. The results show that the lofting height has a direct impact on the maximum travel distance of the model firebrands. Also, the experimental results are utilized for validation of a highly scalable coupled stochastic & parametric firebrand flight model that, couples the LES-resolved velocity field of a jet-in-nonuniform-cross-flow (JINCF) with a 3D fully deterministic 6-degrees-of-freedom debris transport model. The validation results show that the developed numerical model is capable of estimating average statistics of the firebrands' flight. Authors would like to thank support of the National Science Foundation under Grant No. 1200560. Also, the presenter (Ali Tohid) would like to thank Dr. Michael Gollner from the University of Maryland College Park for the conference participation support.

Modelling Carbon Emissions in Calluna vulgaris-Dominated Ecosystems when Prescribed Burning and Wildfires Interact.

PubMed

Santana, Victor M; Alday, Josu G; Lee, HyoHyeMi; Allen, Katherine A; Marrs, Rob H

2016-01-01

A present challenge in fire ecology is to optimize management techniques so that ecological services are maximized and C emissions minimized. Here, we modeled the effects of different prescribed-burning rotation intervals and wildfires on carbon emissions (present and future) in British moorlands. Biomass-accumulation curves from four Calluna-dominated ecosystems along a north-south gradient in Great Britain were calculated and used within a matrix-model based on Markov Chains to calculate above-ground biomass-loads and annual C emissions under different prescribed-burning rotation intervals. Additionally, we assessed the interaction of these parameters with a decreasing wildfire return intervals. We observed that litter accumulation patterns varied between sites. Northern sites (colder and wetter) accumulated lower amounts of litter with time than southern sites (hotter and drier). The accumulation patterns of the living vegetation dominated by Calluna were determined by site-specific conditions. The optimal prescribed-burning rotation interval for minimizing annual carbon emissions also differed between sites: the optimal rotation interval for northern sites was between 30 and 50 years, whereas for southern sites a hump-backed relationship was found with the optimal interval either between 8 to 10 years or between 30 to 50 years. Increasing wildfire frequency interacted with prescribed-burning rotation intervals by both increasing C emissions and modifying the optimum prescribed-burning interval for minimum C emission. This highlights the importance of studying site-specific biomass accumulation patterns with respect to environmental conditions for identifying suitable fire-rotation intervals to minimize C emissions.

The estimation of territiry predeposition to wildfires

NASA Astrophysics Data System (ADS)

Panchenko, Ekaterina; Dukarev, Anatoly

2010-05-01

Wildfires have significant environmental effects. The indirect damages because of fires are an emission of various combustion products such as aerosols, greenhouse gases and carcinogen. Analysis of smoke emission show that from 1 ha burning area emitted aerosols from 0.2 to 1 ton. The aim of our research is to estimate biomass burning emission: Biomass Burning Emission=BA x FL x CE x EF, where BA is Burned Area (ha); FL is forest litter cover (cm); CE is Combustion Efficiency (0-1), depends on a class of fire danger; EF is Emission Factor (kg emitted / kg dry-mass burnt). Consequently for estimation of biomass burning emission it is necessary to analyze of territory predisposition to wildfires and give characteristic of combustion material types for detection fire hazard, for prognosis fire origin and extension. Prognosis of occurrence of wildfires and definition of emissions is possible by means of data of depth forest litter, types of vegetation and type of landscapes including concrete weather conditions (seasons, length of arid period, current temperature, wind speed and its direction). The investigated object is the territory Tomskii district near to the city of Tomsk (56° 31 N-85°08 E) - with the population more than 500 thousand people. The conducted analysis of investigated territory and the calculation will be basic prognostic model for researching wildfires.

The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems.

PubMed

Jensen, Daniel; Reager, John T; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

2018-01-01

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the US Forest Service's historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25-degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This result is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability.

The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems

NASA Astrophysics Data System (ADS)

Jensen, Daniel; Reager, John T.; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

2018-01-01

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service’s historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship’s utility for the future development of national-scale predictive capability.

Database of in-situ field measurements for estimates of fuel consumption and fire emissions in Siberia

NASA Astrophysics Data System (ADS)

Kukavskaya, Elena; Conard, Susan; Buryak, Ludmila; Ivanova, Galina; Soja, Amber; Kalenskaya, Olga; Zhila, Sergey; Zarubin, Denis; Groisman, Pavel

2016-04-01

Wildfires show great variability in the amount of fuel consumed and carbon emitted to the atmosphere. Various types of models are used to calculate global or large scale regional fire emissions. However, in the databases used to estimate fuel consumptions, data for Russia are typically under-represented. Meanwhile, the differences in vegetation and fire regimes in the boreal forests in North America and Eurasia argue strongly for the need of regional ecosystem-specific data. For about 15 years we have been collecting field data on fuel loads and consumption in different ecosystem types of Siberia. We conducted a series of experimental burnings of varying fireline intensity in Scots pine and larch forests of central Siberia to obtain quantitative and qualitative data on fire behavior and carbon emissions. In addition, we examined wildfire behavior and effects in different vegetation types including Scots pine, Siberian pine, fir, birch, poplar, and larch-dominated forests; evergreen coniferous shrubs; grasslands, and peats. We investigated various ecosystem zones of Siberia (central and southern taiga, forest-steppe, steppe, mountains) in the different subjects of the Russian Federation (Krasnoyarsk Kray, Republic of Khakassia, Republic of Buryatia, Tuva Republic, Zabaikalsky Kray). To evaluate the impact of forest practices on fire emissions, burned and unburned logged sites and forest plantations were examined. We found large variations of fuel consumption and fire emission rates among different vegetation types depending on growing conditions, fire behavior characteristics and anthropogenic factors. Changes in the climate system result in an increase in fire frequency, area burned, the number of extreme fires, fire season length, fire season severity, and the number of ignitions from lightning. This leads to an increase of fire-related emissions of carbon to the atmosphere. The field measurement database we compiled is required for improving accuracy of existing biomass burning models and for use by air quality agencies in developing regional strategies to mitigate negative smoke impacts on human health and environment. The research was supported by the Grant of the President of the Russian Federation MK-4646.2015.5, RFBR grant # 15-04-06567, and the NASA LCLUC Program.

Wildfire in the United Kingdom: status and key issues

Treesearch

Julia McMorrow

2011-01-01

This paper reviews the status of wildfire risk in the United Kingdom and examines some of the key issues in U.K. wildfire management. Wildfires challenge the resources of U.K. Fire and Rescue Services (FRSs), especially in dry years, yet FRSs are poorly equipped and trained to deal with wildfire. A brief geography of U.K. wildfires is presented using fire statistics...

A conceptual framework for coupling the biophysical and social dimensions of wildfire to improve fireshed planning and risk mitigation

Treesearch

Jeff Kline; Alan A. Ager; Paige Fischer

2015-01-01

The need for improved methods for managing wildfire risk is becoming apparent as uncharacteristically large wildfires in the western US and elsewhere exceed government capacities for their control and suppression. We propose a coupled biophysical-social framework to managing wildfire risk that relies on wildfire simulation to identify spatial patterns of wildfire risk...

The Challenges to Coupling Dynamic Geospatial Models

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

Goldstein, N

2006-06-23

Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanizationmore » and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.« less

Predicting soil quality indices with near infrared analysis in a wildfire chronosequence.

PubMed

Cécillon, Lauric; Cassagne, Nathalie; Czarnes, Sonia; Gros, Raphaël; Vennetier, Michel; Brun, Jean-Jacques

2009-01-15

We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066-3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.

Thermogravimetric analysis of forest understory grasses

Treesearch

Thomas Elder; John S. Kush; Sharon M. Hermann

2011-01-01

Forest understory grasses are of significance in the initiation, establishment and maintenance of fire, whether used as a management tool or when occurring as wildfire. The fundamental thermal properties of such grasses are critical to their behavior in fire situations and have been investigated in the current work by the application of thermogravimetric analysis (TGA...

Dynamic Data Driven Applications Systems (DDDAS)

DTIC Science & Technology

2012-05-03

response) – Earthquakes, hurricanes, tornados, wildfires, floods, landslides, tsunamis, … • Critical Infrastructure systems – Electric-powergrid...Multiphase Flow Weather and Climate Structural Mechanics Seismic Processing Aerodynamics Geophysical Fluids Quantum Chemistry Actinide Chemistry...Alloys • Approach and Objectives:  Consider porous SMAs:  similar macroscopic behavior but mass /weight is less, and thus attractive for

The Mack Lake fire.

Treesearch

Albert J. Simard; Donald A. Haines; Richard W. Blank; John S. Frost

1983-01-01

Describes the Mack Lake Fire near Mio, Michigan. Few documented wildfires have exceeded its average spread rate (2 mi/h) and energy release rate (8,800 Btu/ft/sec). The extreme behavior resulted from high winds, low humidity, low fuel moisture and jack pine fuels. Horizontal roll vortices may have contributed to the death of one firefighter.

Responses of dead forest fuel moisture to climate change

Treesearch

Yongqiang Liu

2016-01-01

Forest fuel moisture is an important factor for wildland fire behavior. Predicting future wildfire trends and controlled burned conditions is essential to effective natural resource management, but the associated effects of forest fuel moisture remain uncertain. This study investigates the responses of dead forest fuel moisture to climate change in the...

What kind of cutting and thinning can prevent crown fires?

Treesearch

Mick Harrington

2008-01-01

Many land managers are attempting to lessen the probability of severe wildfire behavior and impacts, especially near communities, by manipulating canopy and surface fuel characteristics. Various interest groups have questioned the value of fuels treatments. In reality, apart from fire exposure when a real fire went through a treated stand, effectiveness of fuel...

Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile

NASA Astrophysics Data System (ADS)

Cuchiara, G. C.; Rappenglück, B.; Rubio, M. A.; Lissi, E.; Gramsch, E.; Garreaud, R. D.

2017-10-01

On January 4, 2014, during the summer period in South America, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. On that day the biomass-burning plume was transported by low-intensity winds towards the metropolitan area of Santiago and impacted the concentration of pollutants in this region. In this study, the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) is implemented to investigate the biomass-burning plume associated with these wildfires nearby Santiago, which impacted the ground-level ozone concentration and exacerbated Santiago's air quality. Meteorological variables simulated by WRF/Chem are compared against surface and radiosonde observations, and the results show that the model reproduces fairly well the observed wind speed, wind direction air temperature and relative humidity for the case studied. Based on an analysis of the transport of an inert tracer released over the locations, and at the time the wildfires were captured by the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS), the model reproduced reasonably well the transport of biomass burning plume towards the city of Santiago de Chile within a time delay of two hours as observed in ceilometer data. A six day air quality simulation was performed: the first three days were used to validate the anthropogenic and biogenic emissions, and the last three days (during and after the wildfire event) to analyze the performance of WRF/Chem plume-rise model within FINNv1 fire emission estimations. The model presented a satisfactory performance on the first days of the simulation when contrasted against data from the well-established air quality network over the city of Santiago de Chile. These days represent the urban air quality base case for Santiago de Chile unimpacted by fire emissions. However, for the last three simulation days, which were impacted by the fire emissions, the statistical indices showed a decrease in the model performance. While the model showed a satisfactory evidence that wildfires plumes that originated in the vicinity of Santiago de Chile were transported towards the urban area and impacted the air quality, the model still underpredicted some pollutants substantially, likely due to misrepresentation of fire emission sources during those days. Potential uncertainties may include to the land use/land cover classifications and its characteristics, such as type and density of vegetation assigned to the region, where the fire spots are detected. The variability of the ecosystem type during the fire event might also play a role.

Coupling chemical transport model source attributions with positive matrix factorization: application to two IMPROVE sites impacted by wildfires.

PubMed

Sturtz, Timothy M; Schichtel, Bret A; Larson, Timothy V

2014-10-07

Source contributions to total fine particle carbon predicted by a chemical transport model (CTM) were incorporated into the positive matrix factorization (PMF) receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in the Multilinear Engine (ME-2). The methodology provides the ability to separate features that would not be identified using PMF alone, without sacrificing fit to observations. The hybrid model was applied to IMPROVE data taken from 2006 through 2008 at Monture and Sula Peak, Montana. It was able to separately identify major contributions of total carbon (TC) from wildfires and minor contributions from biogenic sources. The predictions of TC had a lower cross-validated RMSE than those from either PMF or CTM alone. Two unconstrained, minor features were identified at each site, a soil derived feature with elevated summer impacts and a feature enriched in sulfate and nitrate with significant, but sporadic contributions across the sampling period. The respective mean TC contributions from wildfires, biogenic emissions, and other sources were 1.18, 0.12, and 0.12 ugC/m(3) at Monture and 1.60, 0.44, and 0.06 ugC/m(3) at Sula Peak.

Quantifying O3 Impacts in Urban Areas Due to Wildfires Using a Generalized Additive Model.

PubMed

Gong, Xi; Kaulfus, Aaron; Nair, Udaysankar; Jaffe, Daniel A

2017-11-21

Wildfires emit O 3 precursors but there are large variations in emissions, plume heights, and photochemical processing. These factors make it challenging to model O 3 production from wildfires using Eulerian models. Here we describe a statistical approach to characterize the maximum daily 8-h average O 3 (MDA8) for 8 cities in the U.S. for typical, nonfire, conditions. The statistical model represents between 35% and 81% of the variance in MDA8 for each city. We then examine the residual from the model under conditions with elevated particulate matter (PM) and satellite observed smoke ("smoke days"). For these days, the residuals are elevated by an average of 3-8 ppb (MDA8) compared to nonsmoke days. We found that while smoke days are only 4.1% of all days (May-Sept) they are 19% of days with an MDA8 greater than 75 ppb. We also show that a published method that does not account for transport patterns gives rise to large overestimates in the amount of O 3 from fires, particularly for coastal cities. Finally, we apply this method to a case study from August 2015, and show that the method gives results that are directly applicable to the EPA guidance on excluding data due to an uncontrollable source.

Does Wildfire Open a Policy Window? Local Government and Community Adaptation After Fire in the United States.

PubMed

Mockrin, Miranda H; Fishler, Hillary K; Stewart, Susan I

2018-05-15

Becoming a fire adapted community that can coexist with wildfire is envisioned as a continuous, iterative process of adaptation, but it is unclear how communities may pursue adaptation. Experience with wildfire and other natural hazards suggests that disasters may open a "window of opportunity" leading to local government policy changes. We examined how destructive wildfire affected progress toward becoming fire adapted in eight locations in the United States. We found that community-level adaptation following destructive fires is most common where destructive wildfire is novel and there is already government capacity and investment in wildfire regulation and land use planning. External funding, staff capacity, and the presence of issue champions combined to bring about change after wildfire. Locations with long histories of destructive wildfire, extensive previous investment in formal wildfire regulation and mitigation, or little government and community capacity to manage wildfire saw fewer changes. Across diverse settings, communities consistently used the most common tools and actions for wildfire mitigation and planning. Nearly all sites reported changes in wildfire suppression, emergency response, and hazard planning documents. Expansion in voluntary education and outreach programs to increase defensible space was also common, occurring in half of our sites, but land use planning and regulations remained largely unchanged. Adaptation at the community and local governmental level therefore may not axiomatically follow from each wildfire incident, nor easily incorporate formal approaches to minimizing land use and development in hazardous environments, but in many sites wildfire was a focusing event that inspired reflection and adaptation.

Organizing knowledge for tutoring fire loss prevention

NASA Astrophysics Data System (ADS)

Schmoldt, Daniel L.

1989-09-01

The San Bernardino National Forest in southern California has recently developed a systematic approach to wildfire prevention planning. However, a comprehensive document or other mechanism for teaching this process to other prevention personnel does not exist. An intelligent tutorial expert system is being constructed to provide a means for learning the process and to assist in the creation of specific prevention plans. An intelligent tutoring system (ITS) contains two types of knowledge—domain and tutoring. The domain knowledge for wildfire prevention is structured around several foci: (1) individual concepts used in prevention planning; (2) explicitly specified interrelationships between concepts; (3) deductive methods that contain subjective judgment normally unavailable to less-experienced users; (4) analytical models of fire behavior used for identification of hazard areas; (5) how-to guidance needed for performance of planning tasks; and (6) expository information that provides a rationale for planning steps and ideas. Combining analytical, procedure, inferential, conceptual, and expositional knowledge into a tutoring environment provides the student and/or user with a multiple perspective of the subject matter. A concept network provides a unifying framework for structuring and utilizing these diverse forms of prevention planning knowledge. This network structure borrows from and combines semantic networks and frame-based knowledge representations. The flexibility of this organization facilitates an effective synthesis and organization of multiple knowledge forms.

Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA

NASA Astrophysics Data System (ADS)

DeLong, Stephen B.; Youberg, Ann M.; DeLong, Whitney M.; Murphy, Brendan P.

2018-01-01

Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.

Future inhibition of ecosystem productivity by increasing wildfire pollution over boreal North America

NASA Astrophysics Data System (ADS)

Yue, X.; Strada, S.; Unger, N.

2017-12-01

Biomass burning is an important source of tropospheric ozone (O3) and aerosols, which can affect vegetation photosynthesis through stomatal uptake (for O3) and light scattering and meteorological variations (for aerosols). Climate change will significantly increase wildfire activity in boreal North America by the midcentury, while little is known about the impacts of enhanced emissions on the terrestrial carbon budget. Here, combining site-level and satellite observations and a carbon-chemistry-climate model, we estimate the impacts of fire emitted O3 and aerosols on net primary productivity (NPP) over boreal North America. Fire emissions are calculated based on an ensemble projection from 13 climate models. In the present day, wildfire enhances surface O3 by 2 ppbv (7%) and aerosol optical depth (AOD) at 550 nm by 0.03 (26%) in the summer. By midcentury, boreal area burned is predicted to increase by 66%, contributing more O3 (13%) and aerosols (37%). Fire O3 causes negligible impacts on NPP because ambient O3 concentration is far below the damaging thresholds. Fire aerosols reduce surface solar radiation but enhance atmospheric absorption, resulting in enhanced air stability and intensified regional drought. The domain of this drying is confined to the North in the present day, but extends southward by 2050 due to increased fire emissions. Consequently, wildfire aerosols enhance NPP by 72 Tg C yr-1 in the present day but decrease NPP by 118 Tg C yr-1 in the future, mainly because of the soil moisture perturbations. Our results suggest that future wildfire may accelerate boreal carbon loss, not only through direct emissions, but also through the biophysical impacts of fire aerosols.

Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA

USGS Publications Warehouse

DeLong, Stephen B.; Youberg, Ann M.; DeLong, Whitney M.; Murphy, Brendan P.

2018-01-01

Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.