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Evaluating the factors responsible for post-fire water quality response in forests of the western USA

September 3, 2019

Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first five post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain post-fire streamwater responses observed in those watersheds. Increased post-fire total nitrogen and phosphorus loading were proportional to the catchment extent of moderate and high burn severity. Post-fire dissolved metal concentrations increased in catchments with < 2% pre-fire soil organic matter. In contrast, in catchments with > 2% soil organic matter, post-fire dissolved metal concentrations decreased compared to pre-fire conditions. Where post-fire normalized difference vegetation index (NDVI), a remote sensing indicator of live green vegetation, was low, total metal concentrations increased by 25% on average and by > 100% in some cases. When pre-fire soil field capacity exceeded 17%, there was a 750% median increase in total metals export to streams. Overall, the current analysis identified burn severity, post-fire vegetation cover, and several soil properties as the key variables explaining extended post-fire water quality response across a broad range of conditions found in the western US.

Publication Year 2019
Title Evaluating the factors responsible for post-fire water quality response in forests of the western USA
DOI 10.1071/WF18191
Authors Ashley J. Rust, Samuel Saxe, John E. McCray, Charles C. Rhoades, Terri S. Hogue
Publication Type Article
Publication Subtype Journal Article
Series Title International Journal of Wildland Fire
Index ID 70205841
Record Source USGS Publications Warehouse
USGS Organization WMA - Integrated Modeling and Prediction Division
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