T111 Advancements in the Science and Management of Wildfire Impacts on the Critical Zone (Posters)

Monday, 16 October 2023
8:00 AM - 5:30 PM
Hall B

SIMULATING SOIL BURN SEVERITY FOR PRE-FIRE ASSESSMENTS OF POST-FIRE DEBRIS-FLOW HAZARDS

Paper number: T111-2
Program: Technical Sessions
Time: 8:00 AM – 5:30 PM

Authors

Abstract

Trends of increasing wildfire size and severity, and continued development of the wildland-urban interface, place people, property, and infrastructure at risk to direct (e.g., burning) and indirect (e.g, post-fire flows) impacts from wildfire. Land managers, local government agencies and emergency planners need information to help inform decisions to plan for and reduce risks from post-fire flows before a fire starts. Pre-fire assessments of post-fire hazards can provide information, yet they pose challenges. One such challenge is creating synthetic soil burn severity (SBS) data, which is a critical input for post-fire hydrologic and geomorphic models. Soil burn severity, which quantifies the effects of fire on soil properties that are relevant for erosion and runoff, is sometimes ingested into models as a classified variable (i.e., low, moderate, high) and/or a continuous variable (i.e., differenced normalized burn ratio, dNBR). Fire behavior models can provide estimates of classified SBS but do not provide estimates of dNBR. Recently a statistical method was developed utilizing vegetation type and historic soil burn severity data to simulate continuous and classified SBS. This method provides an important step forward, but the results can be too uniform relative to observed burn severity patterns, making it difficult to identify and prioritize at-risk areas. We modified this method by incorporating fuels information such as simulated burn probability and cumulative flame length derived using Fsim, a wildfire-risk simulation model, with the vegetation data. Simulated SBS maps derived from fuels-modified vegetation data provided more realistic burn patterns. A debris-flow likelihood model that utilized synthetic SBS data derived from the fuels-modified vegetation data performed better, relative to observations, compared to a model using the unmodified method. Results from pre-wildfire assessments using this modified method will help land managers, local government agencies and emergency planners identify areas at greater risks from post-fire debris flows, prior to a wildfire, which allows time for planning and implementing mitigation measures.

Geological Society of America Abstracts with Programs. Vol. 55, No. 6

doi: 10.1130/abs/2023AM-390023

© Copyright 2023 The Geological Society of America (GSA), all rights reserved. Permission is hereby granted to the author(s) of this abstract to reproduce and distribute it freely, for noncommercial purposes. Permission is hereby granted to any individual scientist to download a single copy of this electronic file and reproduce up to 20 paper copies for noncommercial purposes advancing science and education, including classroom use, providing all reproductions include the complete content shown here, including the author information. All other forms of reproduction and/or transmittal are prohibited without written permission from GSA Copyright Permissions.