Rapid response tools and datasets for post-fire erosion modeling: linking remote sensing and process-based hydrological models to support post-fire remediation

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Conference Paper/Presentation

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Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern to both resource managers and the public. To respond to this threat, interdisciplinary Burned Area Emergency Response (BAER) Teams are formed to assess potential erosion and flood risks. These teams are under tight deadlines, as remediation plans and treatments must be developed and implemented before the first major storms in order to be effective. One of the primary sources of information for making these decisions is a soil burn severity map derived from Remote Sensing data (typically Landsat) that reflects fire induced changes in vegetative cover and soil properties. Slope, soils, land cover and climate are also important parameters that need to be considered when accessing risk. Many modeling tools and datasets have been developed to assist BAER teams, but process-based and spatially-explicit empirical models are currently under-utilized relative to simpler, lumped models because they are both more difficult to set up and require spatially-explicit inputs such as digital elevation models, soils, and land cover. We are working to increase the use of models by preparing spatial data sets before the fire season that can be rapidly combined with soil burn severity maps and then used to quickly run more accurate, process-based models for spatially explicit predictions of post-fire erosion and runoff.

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© Author(s) 2014

Publication Title

Proceedings from Pecora 19

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Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.