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Author(s):
Sarah A. Lewis, Peter R. Robichaud, Andrew T. Hudak, Eva K. Strand, Jan U. H. Eitel, Robert E. Brown
Year Published:

Cataloging Information

Topic(s):
Fire Effects
Ecological - Second Order
Aquatic Life
Mapping

NRFSN number: 23819
FRAMES RCS number: 64558
Record updated:

As wildland fires amplify in size in many regions in the western USA, land and water managers are increasingly concerned about the deleterious effects on drinking water supplies. Consequences of severe wildfires include disturbed soils and areas of thick ash cover, which raises the concern of the risk of water contamination via ash. The persistence of ash cover and depth were monitored for up to 90 days post-fire at nearly 100 plots distributed between two wildfires in Idaho and Washington, USA. Our goal was to determine the most ‘cost’ effective, operational method of mapping post-wildfire ash cover in terms of financial, data volume, time, and processing costs. Field measurements were coupled with multi-platform satellite and aerial imagery collected during the same time span. The image types spanned the spatial resolution of 30 m to sub-meter (Landsat-8, Sentinel-2, WorldView-2, and a drone), while the spectral resolution spanned visible through SWIR (short-wave infrared) bands, and they were all collected at various time scales. We that found several common vegetation and post-fire spectral indices were correlated with ash cover (r = 0.6–0.85); however, the blue normalized difference vegetation index (BNDVI) with monthly Sentinel-2 imagery was especially well-suited for monitoring the change in ash cover during its ephemeral period. A map of the ash cover can be used to estimate the ash load, which can then be used as an input into a hydrologic model predicting ash transport and fate, helping to ultimately improve our ability to predict impacts on downstream water resources.

Citation

Sarah A. Lewis SA, Robichaud PR, Hudak AT, Strand EK, Jan U. H. Eitel JUH, and Brown RE. 2021. Evaluating the Persistence of Post-Wildfire Ash: A Multi-Platform Spatiotemporal Analysis. Fire 4(4): 68. https://doi.org/10.3390/fire4040068

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