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A wildfire risk assessment framework for land and resource management

Posted date: June 07, 2018
Publication Year: 
2013
Authors: Scott, Joe H.; Thompson, Matthew P.Calkin, Dave E.
Publication Series: 
General Technical Report (GTR)
Source: Gen. Tech. Rep. RMRS-GTR-315. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 83 p.

Abstract

Wildfires can result in significant, long-lasting impacts to ecological, social, and economic systems. It is necessary, therefore, to identify and understand the risks posed by wildland fire, and to develop cost-effective mitigation strategies accordingly. This report presents a general framework with which to assess wildfire risk and explore mitigation options, and illustrates a process for implementing the framework. Two key strengths of the framework are its flexibility - allowing for a multitude of data sources, modeling techniques, and approaches to measuring risk - and its scalability, with potential application for project, forest, regional, and national planning. The specific risk assessment process we introduce is premised on three modeling approaches to characterize wildfire likelihood and intensity, fire effects, and the relative importance of highly valued resources and assets that could be impacted by wildfire. The spatial scope of the process is landscape-scale, and the temporal scope is short-term (that is, the temporal dynamics of succession and disturbance are not simulated). We highlight key information needs, provide guidance for use of fire simulation models and risk geo-processing tools, and demonstrate recent applications of the framework across planning scales. The aim of this report is to provide fire and land managers with a helpful set of guiding principles and tools for assessing and mitigating wildfire risk.

Citation

Scott, Joe H.; Thompson, Matthew P.; Calkin, David E. 2013. A wildfire risk assessment framework for land and resource management. Gen. Tech. Rep. RMRS-GTR-315. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 83 p.