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Abstract Landscapes following wildfire commonly have significant increases in sediment yield and debris flows that pose major hazards and are difficult to predict. Ultimately, post-wildfire sediment yield is governed by processes that deliver sediment from hillslopes to channels, but it is commonly unclear the degree to which hillslope sediment delivery is driven by wet versus dry processes, which limits the ability to predict debris-flow occurrence and response to climate change. Here we use repeat airborne lidar topography to track sediment movement following the 2009 CE Station Fire in southern California, USA, and show that post-wildfire debris flows initiated in channels filled by dry sediment transport, rather than on hillsides during rainfall as typically assumed. We found widespread patterns of 1–3 m of dry sediment loading in headwater channels immediately following wildfire and before rainfall, followed by sediment excavation during subsequent storms. In catchments where post-wildfire dry sediment loading was absent, possibly due to differences in lithology, channel scour during storms did not occur. Our results support a fire-flood model in bedrock landscapes whereby debris-flow occurrence depends on dry sediment loading rather than hillslope-runoff erosion, shallow landslides, or burn severity, indicating that sediment supply can limit debris-flow occurrence in bedrock landscapes with more-frequent fires.
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Predicting post‐fire debris flow grain sizes and depositional volumes in the Intermountain West, United States
Abstract Post‐fire debris flows represent one of the most erosive consequences associated with increasing wildfire severity and investigations into their downstream impacts have been limited. Recent advances have linked existing hydrogeomorphic models to predict potential impacts of post‐fire erosion at watershed scales on downstream water resources. Here we address two key limitations in current models: (1) accurate predictions of post‐fire debris flow volumes in the absence of triggering storm rainfall intensities and (2) understanding controls on grain sizes produced by post‐fire debris flows. We compiled and analysed a novel dataset of depositional volumes and grain size distributions (GSDs) for 59 post‐fire debris flows across the Intermountain West (IMW) collected via fieldwork and from the literature. We first evaluated the utility of existing models for post‐fire debris flow volume prediction, which were largely developed for Southern California. We then constructed a new post‐fire debris flow volume prediction model for the IMW using a combination of Random Forest modelling and regression analysis. We found topography and burn severity to be important variables, and that the percentage of pre‐fire soil organic matter was an essential predictor variable. Our model was also capable of predicting debris flow volumes without data for the triggering storm, suggesting that rainfall may be more important as a presence/absence predictor, rather than a scaling variable. We also constructed the first models that predict the median, 16th percentile, and 84th percentile grain sizes, as well as boulder size, produced by post‐fire debris flows. These models demonstrate consistent landscape controls on debris flow GSDs that are related to land cover, physical and chemical weathering, and hillslope sediment transport processes. This work advances our ability to predict how post‐fire sediment pulses are transported through watersheds. Our models allow for improved pre‐ and post‐fire risk assessments across diverse ranges of watersheds in the IMW.
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- Award ID(s):
- 1848667
- PAR ID:
- 10373156
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Earth Surface Processes and Landforms
- Volume:
- 48
- Issue:
- 1
- ISSN:
- 0197-9337
- Page Range / eLocation ID:
- p. 179-197
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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