Increased wildfire activity (e.g. number of starts, area burned, fire behaviour) across the western United States in recent decades has heightened interest in resolving climate–fire relationships. Macroscale climate–fire relationships were examined in forested and non-forested lands for eight Geographic Area Coordination Centers in the western United States, using area burned derived from the Monitoring Trends in Burn Severity dataset (1984–2010). Fire-specific biophysical variables including fire danger and water balance metrics were considered in addition to standard climate variables of monthly temperature, precipitation and drought indices to explicitly determine their optimal capacity to explain interannual variability in area burned. Biophysical variables tied to the depletion of fuel and soil moisture and prolonged periods of elevated fire-danger had stronger correlations to area burned than standard variables antecedent to or during the fire season, particularly in forested systems. Antecedent climate–fire relationships exhibited inter-region commonality with area burned in forested lands correlated with winter snow water equivalent and emergent drought in late spring. Area burned in non-forested lands correlated with moisture availability in the growing season preceding the fire year. Despite differences in the role of antecedent climate in preconditioning fuels, synchronous regional fire activity in forested and non-forested lands suggests that atmospheric conditions during the fire season unify fire activity and can compound or supersede antecedent climatic stressors. Collectively, climate–fire relationships viewed through the lens of biophysical variables provide a more direct link to fuel flammability and wildfire activity than standard climate variables, thereby narrowing the gap in incorporating top-down climatic factors between empirical and process-based fire models.

http://www.pyrogeographer.com/uploads/1/6/4/8/16481944/abatzoglou_kolden_2013_ijwf.pdf

Relationships between climate and macroscale area burned in the western United States

https://www.fs.fed.us/rm/pubs_other/rmrs_2011_thompson_m002.pdf

Uncertainty and risk in wildland fire management: a review.

Risk analysis evolved out of the need to make decisions concerning highly stochastic events, and is well suited to analyse the timing, location and potential effects of wildfires. Over the past 10 years, the application of risk analysis to wildland fire management has seen steady growth with new risk-based analytical tools that support a wide range of fire and fuels management planning scales from individual incidents to national, strategic interagency programs. After a brief review of the three components of fire risk – likelihood, intensity and effects – this paper reviews recent advances in quantifying and integrating these individual components of fire risk. We also review recent advances in addressing temporal dynamics of fire risk and spatial optimisation of fuels management activities. Risk analysis approaches have become increasingly quantitative and sophisticated but remain quite disparate. We suggest several necessary and fruitful directions for future research and development in wildfire risk analysis.

https://www.fs.fed.us/rm/pubs_other/rmrs_2013_miller_c001.pdf

A review of recent advances in risk analysis for wildfire management

The degree of accuracy in model predictions of rate of spread in wildland fires is dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data. On the basis of a compilation of 49 fire spread model evaluation datasets involving 1278 observations in seven different fuel type groups, the limits on the predictability of current operational models are examined. Only 3% of the predictions (i.e. 35 out of 1278) were considered to be exact predictions according to the criteria used in this study. Mean percent error varied between 20 and 310% and was homogeneous across fuel type groups. Slightly more than half of the evaluation datasets had mean errors between 51 and 75%. Under-prediction bias was prevalent in 75% of the 49 datasets analysed. A case is made for suggesting that a ?35% error interval (i.e. approximately one standard deviation) would constitute a reasonable standard for model performance in predicting a wildland fire's forward or heading rate of spread. We also found that empirical-based fire behaviour models developed from a solid foundation of field observations and well accepted functional forms adequately predicted rates of fire spread far outside of the bounds of the original dataset used in their development. We examined error statistics of operational wildland fire spread models.We compiled 49 fire spread model evaluation datasets involving 1278 observations.Mean percent error varied between 20 and 310% and was homogeneous across fuel type groups.The analysis suggests that a ?35% error interval is a reasonable standard for model adequacy.

http://www.firescience.gov/projects/09-S-03-1/project/09-S-03-1_CruzAlexander_2013_EMS_UncerModeledROS.pdf

Uncertainty associated with model predictions of surface and crown fire rates of spread

The BehavePlus Fire Modeling System is among the most widely used systems for wildland fire prediction. It is designed for use in a range of tasks including wildfire behaviour prediction, prescribed fire planning, fire investigation, fuel hazard assessment, fire model understanding, communication and research. BehavePlus is based on mathematical models for fire behaviour, fire effects and fire environment. It is a point system for which conditions are constant for each calculation, but is designed to encourage examination of the effect of a range of conditions through tables and graphs. BehavePlus is successor to BEHAVE, which was developed in 1977 and became available for field application in 1984. It was updated to BehavePlus in 2002. Updates through version 5 have added features and modelling capabilities. It is becoming increasingly difficult to expand the system. A redesign will address the need for consolidation with other systems and make it easier to incorporate new research results. This paper describes the development history and application of BehavePlus. The design, features and modelling foundation of the current system are described. Considerations for the next generation are presented.

/pdf/current-status-and-future-needs-of-the-behaveplus-fire-4bliohdj1j.pdf

Current status and future needs of the BehavePlus Fire Modeling System

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis is used to characterize the seasonal trend in ERC, autocorrelation of residuals, and daily standard deviation and stochastically generate artificial time series of afternoon fuel moisture. Daily wind speed and direction are sampled stochastically from joint probabilities of historical wind speed and direction for the date range of the fire simulation period. Hundreds or thousands of fire growth simulations are then performed using the synthetic fire weather sequences. The performance of these methods is evaluated in terms of the number of ensemble member simulations, one- versus two-dimensional fire spread simulations, and comparison with results from 91 fires occurring from 2007 to 2009. Simulations were found to be in consistent agreement with observations, but trends indicate that the ensemble average of simulated fire sizes were consistently larger than actual fires whereas the farthest extent burned by fires was underestimated.

https://www.fs.fed.us/rm/pubs_other/rmrs_2011_finney_m001.pdf

A Method for Ensemble Wildland Fire Simulation

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.

/pdf/developing-the-us-wildland-fire-decision-support-system-89inu92dne.pdf

Developing the US Wildland Fire Decision Support System

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 several command line programs linked together: (1) FVS with the Parallel Processor (PPE) and Fire and Fuels (FFE) extensions that pauses the simulation during each cycle and transfers data to and from other system components; (2) a component to create the spatial landscape file with fuel model logic to select fuel models not available in FFE; and (3) a command line version of FlamMap utilizing the Minimum Travel Time fire growth method and Treatment Optimization Model to identify treatments, simulate wildfires, and evaluate the performance of the fuel treatments. Simulations were performed for three study areas: Sanders County in western Montana, the Stanislaus National Forest in California, and the Blue Mountains in eastern Oregon utilizing the Inland Empire, Western Sierra, and Blue Mountain FVS variants. Several limitations of FVS were identified during the project. Understory vegetation important for fuel modeling is not simulated in FVS, and the cap of 10,000 stands in PPE limited the size of the analysis areas. This simulation system required a large time commitment for data development, multiprocessor computer hardware to perform the simulations, and a range of technical expertise that is more specialized than land management agencies are currently staffed to handle. The system was successful in meeting the project’s requirements. The research nature of this simulation system suggests it is probably not practical to run in most places for operational planning uses.

https://www.fs.fed.us/rm/pubs/rmrs_p054/rmrs_p054_027_039.pdf

Robert C. Seli

Papers

A Method for Ensemble Wildland Fire Simulation

Developing the US Wildland Fire Decision Support System

Incorporating landscape fuel treatment modeling into the Forest Vegetation Simulator