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

Elijah Orland; Dalia Kirschbaum; Thomas Stanley

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NASA NTRS · 20220015050

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

Elijah Orland·Dalia Kirschbaum·Thomas Stanley

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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.

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Wildfire Debris Flows Mass Wasting Remote Sensing Machine Learning IMERG

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Elijah Orland, Dalia Kirschbaum, Thomas Stanley. 2022-09-16. A Scalable Framework for Post Fire Debris Flow Hazard Assessment Using Satellite Precipitation Data. https://ntrs.nasa.gov/citations/20220015050

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