Wildfire potential mapping over the State of Mississippi: A land surface modeling approach

William Cooke, Georgy Mostovoy, Valentine Anantharaj, W. Jolly

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern part of Mississippi. The following three indices were tested and used to simulate spatial and temporal wildfire probability changes: (1) the accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) simulated moisture content of the top 10 cm of soil; and (3) the Keetch-Byram Drought Index (KBDI). These indices were estimated from gridded meterological data and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). The relationships between normalized fire potential index deviations and the probability of at least one fire occurring during the following five consecutive days were evaluated using a 23-year (1986-2008) forest fire record for an evenly spaced grid (0.25°x 0.25°) across the state of Mississippi's coastal plain. Two periods were selected and examined (January-mid June and mid September-December). There was good agreement between the observed and logistic model-fitted fire probabilities over the study area during both seasons. The fire potential indices based on the top 10 cm soil moisture and KBDI had the largest impact on wildfire odds, increasing it by almost 2 times in response to each unit change of the corresponding fire potential index during January-mid-June period and by nearly 1.5 times during mid-September-December. These results suggest that soil moisture-based fire potential indices are good indicators of fire occurrence probability across this region.

Original languageEnglish
Pages (from-to)492-509
Number of pages18
JournalGIScience and Remote Sensing
Volume49
Issue number4
DOIs
StatePublished - Jul 1 2012

Funding

This research was supported by the NASA Applied Sciences Program via grant/ project NNX10AB74G. Valentine Anantharaj was also supported by the National Center for Computational Sciences at the Oak Ridge National Laboratory, USA. The authors greatly appreciate efforts of the NLDAS-2 team for providing high-quality land surface data for the research community, and the efforts of the Mississippi Forestry Commission for continuing to supply wildfire data for research purposes.

FundersFunder number
National Aeronautics and Space AdministrationNNX10AB74G

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