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Predicting large wildfires across western North America by modeling seasonal variation in soil water balance

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  • Richard Waring
  • Nicholas Coops

Abstract

A lengthening of the fire season, coupled with higher temperatures, increases the probability of fires throughout much of western North America. Although regional variation in the frequency of fires is well established, attempts to predict the occurrence of fire at a spatial resolution >10 km 2 have generally been unsuccessful. We hypothesized that predictions of fires might be improved if depletion of soil water reserves were coupled more directly to maximum leaf area index (LAI max ) and stomatal behavior. In an earlier publication, we used LAI max and a process-based forest growth model to derive and map the maximum available soil water storage capacity (ASW max ) of forested lands in western North America at l km resolution. To map large fires, we used data products acquired from NASA’s Moderate Resolution Imaging Spectroradiometers (MODIS) over the period 2000–2009. To establish general relationships that incorporate the major biophysical processes that control evaporation and transpiration as well as the flammability of live and dead trees, we constructed a decision tree model (DT). We analyzed seasonal variation in the relative availability of soil water (fASW) for the years 2001, 2004, and 2007, representing respectively, low, moderate, and high rankings of areas burned. For these selected years, the DT predicted where forest fires >1 km occurred and did not occur at ~100,000 randomly located pixels with an average accuracy of 69 %. Extended over the decade, the area predicted burnt varied by as much as 50 %. The DT identified four seasonal combinations, most of which included exhaustion of ASW during the summer as critical; two combinations involving antecedent conditions the previous spring or fall accounted for 86 % of the predicted fires. The approach introduced in this paper can help identify forested areas where management efforts to reduce fire hazards might prove most beneficial. Copyright The Author(s) 2016

Suggested Citation

  • Richard Waring & Nicholas Coops, 2016. "Predicting large wildfires across western North America by modeling seasonal variation in soil water balance," Climatic Change, Springer, vol. 135(2), pages 325-339, March.
  • Handle: RePEc:spr:climat:v:135:y:2016:i:2:p:325-339
    DOI: 10.1007/s10584-015-1569-x
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    References listed on IDEAS

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    1. Peterman, Wendy & Bachelet, Dominique & Ferschweiler, Ken & Sheehan, Timothy, 2014. "Soil depth affects simulated carbon and water in the MC2 dynamic global vegetation model," Ecological Modelling, Elsevier, vol. 294(C), pages 84-93.
    2. Philip E Higuera & John T Abatzoglou & Jeremy S Littell & Penelope Morgan, 2015. "The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-21, June.
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    Cited by:

    1. Mathys, A.S. & Coops, N.C. & Simard, S.W. & Waring, R.H. & Aitken, S.N., 2018. "Diverging distribution of seedlings and mature trees reflects recent climate change in British Columbia," Ecological Modelling, Elsevier, vol. 384(C), pages 145-153.
    2. Gupta, Rajit & Sharma, Laxmi Kant, 2019. "The process-based forest growth model 3-PG for use in forest management: A review," Ecological Modelling, Elsevier, vol. 397(C), pages 55-73.

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