Statistical models of key components of wildfire risk

Abstract

Fire danger systems have evolved from qualitative indices, to process-driven deterministic models of fire behavior and growth, to data-driven stochastic models of fire occurrence and simulation systems. However, there has often been little overlap or connectivity in these frameworks, and validation has not been common in deterministic models. Yet, marked increases in annual fire costs, losses, and fatality costs over the past decade draw attention to the need for better understanding of fire risk to support fire management decision making through the use of science-backed, data-driven tools. Contemporary risk modeling systems provide a useful integrative framework. This article discusses a variety of important contributions for modeling fire risk components over recent decades, certain key fire characteristics that have been overlooked, and areas of recent research that may enhance risk models.