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Wildfire Probability Mapping Based on Regional Soil Moisture Models

A South Central CSC FY 2017 Funding Opportunity Project
Principal Investigator
Tyson Ochsner

Dates

Start Date
2017-08
End Date
2022-02-03
Release Date
2017

Summary

Wildfires scorched 10 million acres across the United States in 2015, and for the first time on record, wildfire suppression costs topped $2 billion. Wildfire danger modeling is an important tool for understanding when and where wildfires will occur, and recent work by our team in the South Central United States has shown wildfire danger models may be improved by incorporating soil moisture information. Advancements in wildfire danger modeling may increase wildfire preparedness, and therefore decrease loss of life, property, and habitat due to wildfire. Still, soil moisture—an important determinant of wildfire risk—is not currently used for wildfire danger assessments because data are generally unavailable at the appropriate scales [...]

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BlackForestFire_CO_USDA.jpg
“Black Forest Fire in Colorado; Credit: USDA”
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Project Extension

parts
typeTechnical Summary
valueObjectives/justification: A record 10 million acres were consumed by wildfires across the United States in 2015 and wildfire potential is projected to increase in this century with warmer and drier climate conditions. Soil moisture influences wildfire activity because of its influence on vegetation characteristics and live fuel moisture. However, soil moisture is not currently used operationally for wildfire prediction because data are unavailable at the appropriate scales of space and time. This project will (1) develop effective soil moisture models for South Central river basins using digital soil maps, gridded climate data, and satellite vegetation indices; (2) quantify the relationships between modeled soil moisture and wildfire probability; and (3) develop and distribute soil moisture and wildfire probability maps for the Red River (RR) and Rio Grande (RG) basins. Background: High spatial variability of soil properties complicates spatial predictions of soil moisture; however, existing soil survey information can be linked with distributed climate data to improve soil moisture estimates. Soil moisture exerts strong influence on vegetation properties and subsequently on wildfire occurrence. Procedures/Methods: We will integrate existing soil and climate data to model the fraction of available water (FAW) present in the root zone at daily time steps and 250-m spatial resolution with a novel approach utilizing existing drought indices re-scaled to track available in situ soil moisture data. We will then demonstrate how the newly generated FAW maps, along with traditional meteorological variables, can be used to develop dynamic fire probability maps in the RR and RG basins. Expected Products and Information/ Technology Transfer: Products generated will include soil moisture models, FAW and wildfire data sets for the 2000-2016 period, and selected maps of FAW and wildfire probability along with peer-reviewed manuscripts and presentations and a website for distribution. Personnel/Cooperators/Partners: Our interdisciplinary research team is comprised of soil scientists, hydrologists, climatologists, and ecologists from Oklahoma State University, USGS, and USDA-ARS, with additional cooperators including USDA Climate Hubs, OK-FIRE, USFS, The Nature Conservancy, New Mexico State University, Texas A&M Forest Service, and support from the Southern Rockies, Desert, Great Plains, and Gulf Coast Prairie LCCs.
projectStatusCompleted

Budget Extension

annualBudgets
year2017
totalFunds40985.0
totalFunds40985.0

Black Forest Fire in Colorado; Credit: USDA
Black Forest Fire in Colorado; Credit: USDA

Map

Spatial Services

ScienceBase WMS

Communities

  • National and Regional Climate Adaptation Science Centers
  • South Central CASC

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Additional Information

Identifiers

Type Scheme Key
RegistrationUUID NCCWSC cfdc69ad-1154-4962-b56c-3614b6e73cda
StampID NCCWSC SC17-OT1092

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