Evaluating predictive models of critical live fuel moisture in the Santa Monica Mountains, California

Article

<< Previous

Next >>

Contents Vol 17(1)

doi:10.1071/WF07017

Evaluating predictive models of critical live fuel moisture in the Santa Monica Mountains, California

Philip E. Dennison ^A ^D, Max A. Moritz ^B, Robert S. Taylor ^C

^A Department of Geography and Center for Natural and Technological Hazards, University of Utah, 260 S Central Campus Drive, Salt Lake City, UT 84112, USA.
^B Environmental Science, Policy, and Management Department, Center for Fire Research and Outreach, University of California, Berkeley, CA 94720, USA.
^C National Park Service, Santa Monica Mountains National Recreation Area, 401 W Hillcrest Drive, Thousand Oaks, CA 91360, USA.
^D Corresponding author. Email: dennison@geog.utah.edu





	PDF (476 KB) $25



	Export Citation

Print

International Journal of Wildland Fire 17(1) 18–27 http://dx.doi.org/10.1071/WF07017
Submitted: 8 February 2007 Accepted: 5 June 2007 Published online: 14 February 2008

Abstract

Large wildfires in the Santa Monica Mountains of southern California occur when low levels of live and dead fuel moisture coincide with Santa Ana wind events. Declining live fuel moisture may reach a threshold that increases susceptibility to large wildfires. Live fuel moisture and fire history data for the Santa Monica Mountains from 1984 to 2005 were used to determine a potential critical live fuel moisture threshold, below which large fires become much more likely. The ability of live fuel moisture, remote sensing, and precipitation variables to predict the annual timing of 71 and 77% live fuel moisture thresholds was assessed. Spring precipitation, measured through the months of March, April, and May, was found to be strongly correlated with the annual timing of both live fuel moisture thresholds. Large fires in the Santa Monica Mountains only occurred after the 77% threshold was surpassed, although most large fires occurred after the less conservative 71% threshold. Spring precipitation has fluctuated widely over the past 70 years but does not show evidence of long-term trends. Predictive models of live fuel moisture threshold timing may improve planning for large fires in chaparral ecosystems.

Keywords: chamise, chaparral, precipitation, wildfire danger.