New Mexico Geological Society Annual Spring Meeting — Abstracts


Predicting Wildfire Burn Severity and Debris Flow Risk Using Bayesian Statistical Methods

Dan Cadol1 and Abelino Fernandez Leger1

1New Mexico Institute of Mining and Technology, 801 Leroy Place, Socorro, NM, 87801, United States, dan.cadol@nmt.edu

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Most of North America’s freshwater is derived from forests (Collar and Earles, 2023), but climate change and recovery from a century of fire suppression is increasing the risk of larger and more severe forest fires (Parks and Abatzoglou, 2020). Wildfires are well known to set the stage for the generation of debris flows. Severe wildfires reduce infiltration and expose the soil surface to rapid mobilization during high intensity rainfall events (Youberg et al., 2025). The intermountain west relies on forests for surface water supplies, yet post-wildfire debris flows threaten to compromise the water supplied from impacted areas. The San Juan Chama Project delivers more than 100,00 acre-feet of water to municipalities and irrigators in New Mexico. The most recent empirical models developed by researchers at the USGS to predict post-fire debris flow risk require remote sensing inputs to estimate post-fire burn severity conditions (Staley et al., 2018). Our model uses Bayesian statistical methods to better capture the uncertainty of predicting wildfire burn severity. We use vegetation type and percent vegetation cover to predict the statistical distribution of burn severity values expected at any given pixel within the donor watershed area. These burn severity values can then be used to predict the debris flow likelihood in each subbasin. Our results indicate a very high risk of post-fire debris flows in the San Juan-Chama Project donor watersheds and illustrate the need for fire mitigation strategies in the area. We plan to include the spatial clustering patterns from nearby fires and annual fire weather predictors to further refine our simulated burn severity values.

References:

  1. Collar, N. M., & Earles, T. A. (2023). Unique challenges posed by fire disturbance to water supply management and transfer agreements in a headwaters region. Journal of Environmental Management, 339, 117956. https://doi.org/10.1016/j.jenvman.2023.117956
  2. Parks, S. A., & Abatzoglou, J. T. (2020). Warmer and Drier Fire Seasons Contribute to Increases in Area Burned at High Severity in Western US Forests From 1985 to 2017. Geophysical Research Letters, 47(22), e2020GL089858. https://doi.org/10.1029/2020GL089858
  3. Shafer, A. M. Y., Luke A. McGuire, Nina Oakley, Francis K. Rengers, Autym. (2025, February 19). Confronting Debris Flow Hazards After Wildfire. Retrieved April 2, 2025, from https://eos.org/science-updates/confronting-debris-flow-hazards-after-wildfire
  4. Staley, D. M., Tillery, A. C., Kean, J. W., McGuire, L. A., Pauling, H. E., Rengers, F. K., & Smith, J. B. (2018). Estimating post-fire debris-flow hazards prior to wildfire using a statistical analysis of historical distributions of fire severity from remote sensing data. International Journal of Wildland Fire, 27(9), 595. https://doi.org/10.1071/WF17122

Keywords:

Post-fire Debris Flow, Bayesian Statistics, dNBR, Burn Severity, LandFire, San Juan Chama Project

pp. 30

2025 New Mexico Geological Society Annual Spring Meeting
April 25, 2025, Macey Center, Socorro, NM
Online ISSN: 2834-5800