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Post-fire flooding and debris flows are often triggered by increased overland flow resulting from wildfire impacts on soil infiltration capacity and surface roughness. Increasing wildfire activity and intensification of precipitation with climate change make improving understanding of post-fire overland flow a particularly pertinent task. Hydrologic signatures, which are metrics that summarize the hydrologic regime of watersheds using rainfall and runoff time series, can be calculated for large samples of watersheds relatively easily to understand post-fire hydrologic processes. We demonstrate that signatures designed specifically for overland flow reflect changes to overland flow processes with wildfire that align with previous case studies on burned watersheds. For example, signatures suggest increases in infiltration-excess overland flow and decrease in saturation-excess overland flow in the first and second years after wildfire in the majority of watersheds examined. We show that climate, watershed and wildfire attributes can predict either post-fire signatures of overland flow or changes in signature values with wildfire using machine learning. Normalized difference vegetation index (NDVI), air temperature, amount of developed/undeveloped land, soil thickness and clay content were the most used predictors by well-performing machine learning models. Signatures of overland flow provide a streamlined approach for characterizing and understanding post-fire overland flow, which is beneficial for watershed managers who must rapidly assess and mitigate the risk of post-fire hydrologic hazards after wildfire occurs.
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Importance of subsurface water for hydrological response during storms in a post-wildfire bedrock landscape
Abstract Wildfire alters the hydrologic cycle, with important implications for water supply and hazards including flooding and debris flows. In this study we use a combination of electrical resistivity and stable water isotope analyses to investigate the hydrologic response during storms in three catchments: one unburned and two burned during the 2020 Bobcat Fire in the San Gabriel Mountains, California, USA. Electrical resistivity imaging shows that in the burned catchments, rainfall infiltrated into the weathered bedrock and persisted. Stormflow isotope data indicate that the amount of mixing of surface and subsurface water during storms was similar in all catchments, despite higher streamflow post-fire. Therefore, both surface runoff and infiltration likely increased in tandem. These results suggest that the hydrologic response to storms in post-fire environments is dynamic and involves more surface-subsurface exchange than previously conceptualized, which has important implications for vegetation regrowth and post-fire landslide hazards for years following wildfire.
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- PAR ID:
- 10446758
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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ABSTRACT Rising temperatures and shifting fire regimes in the western United States are pushing fires upslope into areas of deep winter snowpack, where we have little knowledge of the likely hydrologic impacts of wildfire. We quantified differences in the timing and magnitude of stormflow responses to summer rainstorms among six catchments of varying levels of burn severity and seasonal snowpack cover for years 1–3 after the 2020 Cameron Peak fire. Our objectives were to (1) examine whether responsiveness, magnitude, and timing of stormflow responses to rainfall vary between burned and unburned catchments and between snow zones, and (2) identify the factors that affect these responses. We evaluated whether differences in storm hydrograph peak flow, total flow, stage rise, and lag to peak time differed by snow zone and burn category using generalised linear models. Additional predictors in these models are the maximum 60‐min rainfall intensity for each storm, the cumulative potential water deficit prior to the storm, and the year post‐fire. These models showed that the high snow zone (HSZ) has higher total stormflow than the low snow zone (LSZ), likely due to the higher soil moisture content in that area. In both snow zones, the biggest driver of the magnitude of the stormflow response was MI60. Burn category did not have a clear impact on stormflow response in the HSZ, but it did impact stage rise at the severely burned catchment in the LSZ. This was the only site that had widespread overland flow post‐fire. These results demonstrate that the stormflow responses to fire vary between snow zones, indicating a need to account for elevation and snow persistence in post‐fire risk assessments.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41467-023-39095-z
