A Scalable Framework for Post Fire Debris Flow Hazard Assessment Using Satellite Precipitation Data

Thumbnail Image

Files

Geophysical Research Letters - 2022 - Orland - A Scalable Framework for Post Fire Debris Flow Hazard Assessment Using.pdf (989.4 KB)
2022gl099850-sup-0001-supporting information si-s01.pdf (81.46 KB)

Links to Files

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022GL099850

Permanent Link

https://doi.org/10.1029/2022GL099850
 http://hdl.handle.net/11603/26184

Collections

UMBC GESTAR II
UMBC Faculty Collection

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0001-8347-3951
 https://orcid.org/0000-0003-2288-0363

Date

2022-09-16

Type of Work

journal articles
Text

Department

Program

Citation of Original Publication

Orland, E., Kirschbaum, D., & Stanley, T. (2022). A scalable framework for post fire debris flow hazard assessment using satellite precipitation data. Geophysical Research Letters, 49, e2022GL099850. https://doi.org/10.1029/2022GL099850

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0

Subjects

Abstract

Wildfire is a global phenomenon that has dramatic effects on erosion and flood potential. On steep slopes, burned areas are more likely to experience significant overland flow during heavy rainfall leading to post fire debris flows (PFDFs). Previous work establishes methods for PFDF hazard assessment, often relying on regional-scale parameterizations with in-situ rainfall measurements to categorize hazard as a function of meteorological and surface properties. We present a globally scalable approach to extend the benefit these models provide to new areas. Our new model relies on publicly available satellite-based inputs with a global extent to provide first order hazard assessments of recently burned areas. Our results show it is possible to identify the conditions relevant for PFDF-initiation processes across a variety of physiographic settings. Improvements to satellite-borne rainfall intensity data and increased availability of PFDF occurrence data worldwide are expected to enhance model skill and applicability further.