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Predicting Postfire Sediment Yields of Small Steep Catchments Using Airborne Lidar Differencing

  • James J. Guilinger
  • , Efi Foufoula-Georgiou
  • , Andrew B. Gray
  • , James T. Randerson
  • , Padhraic Smyth
  • , Nicolas C. Barth
  • , Michael L. Goulden

Research output: Contribution to journalArticlepeer-review

Abstract

Predicting sediment yield from recently burned areas remains a challenge but is important for hazard and resource management as wildfire impacts increase. Here we use lidar-based monitoring of two fires in southern California, USA to study the movement of sediment during pre-rainfall periods and postfire periods of flooding and debris flows over multiple storm events. Using a data-driven approach, we examine the relative importance of terrain, vegetation, burn severity, and rainfall amounts through time on sediment yield. We show that incipient fire-activated dry sediment loading and pre-fire colluvium were rapidly flushed out by debris flows and floods but continued erosion occurred later in the season from soil erosion and, in ∼9% of catchments, from shallow landslides. Based on these observations, we develop random forest regression models to predict dry ravel and incipient runoff-driven sediment yield applicable to small steep headwater catchments in southern California.

Original languageAmerican English
JournalGeophysical Research Letters
Volume50
Issue number16
StatePublished - Aug 28 2023

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