Title: Review of methods for developing probabilistic risk assessments
Author: Weinstein, D. A.; Woodbury, P.B.;
Source: In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 285-302
Publication Series: General Technical Report (GTR)
Description: We describe methodologies currently in use or those under development containing features for estimating fire occurrence risk assessment. We describe two major categories of fire risk assessment tools: those that predict fire under current conditions, assuming that vegetation, climate, and the interactions between them and fire remain relatively similar to their condition during recent history, and those that anticipate changes in fire risk as climate and vegetation communities change through time. Three types of models have proven useful for predicting fire under current conditions: (1) biophysical models that predict fire from vegetation type, fuel load, and climate; (2) statistical models; and (3) fire behavior models. Programs such as LANDFIRE have great promise for using biophysical properties to estimate risk. Statistical models that use historical data to predict fire probabilities if landscape-fire relationships continue to remain relatively unchanged, are gaining interest as more data become available. Fire behavior models are producing accurate predictions of the ways individual fires will move across the landscape. For longer periods, fire risk needs to be evaluated by models that predict the ways vegetation communities will change over time because these changes will alter fire probabilities. We identified models capable of being used to track changes in vegetation and the resulting effect on changes in fire frequency. Risk systems need to be designed to track changes in fire susceptibility as the climate changes, using models such as MAPSS. Prediction of fire occurrence is just the first part of a complete analysis of risks associated with fire. Fire occurrence risk needs to be combined with models that determine the risk of the effects of fire. Models that predict mortality, fuel consumption, smoke production, and soil heating caused by prescribed fire or wildfire should be used, as well as those capable of evaluating second order effects, such as changes in site productivity, animal use, insects, and disease. Fire must be looked at in the context of other stresses, such as invasive insects and pathogens, encroaching urbanization, and loss of critical habitat. There are interactions among stresses that play a role in affecting the frequency and intensity of fire, and fire, in turn, can affect the probability of those stresses. Consequently, risk evaluation systems need to be created that can simultaneously estimate the probability of other major stresses influencing ecosystem development.
Keywords: Fire prediction, fire susceptibility, modeling, risk assessment, wildfire
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
- You may send email to firstname.lastname@example.org to request a hard copy of this publication. (Please specify exactly
which publication you are requesting and your mailing address.)
XML: View XML
Weinstein, D.A.; Woodbury, P.B. 2010. Review of methods for developing probabilistic risk assessments. part 1: modeling fire. In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 285-302.
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility