Assessment of wildland fire impacts on watershed annual water yield [electronic resource] : Analytical framework and case studies in the United States
- Washington, D.C. : United States. Dept. of Energy. Office of Science, 2016.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- 35 pages : digital, PDF file
- Additional Creators:
- Oak Ridge National Laboratory
United States. Department of Energy. Office of Science
United States. Department of Energy. Office of Scientific and Technical Information
- More than 50% of water supplies in the conterminous United States originate on forestland or rangeland and are potentially under increasing stress as a result of larger and more severe wildfires. Little is known, however, about the long-term impacts of fire on annual water yield and the role of climate variability within this context. We here propose a framework for evaluating wildland fire impacts on streamflow that combines double-mass analysis with new methods (change point analysis, climate elasticity modeling, and process-based modeling) to distinguish between multiyear fire and climate impacts. The framework captures a wide range of fire types, watersheds characteristics, and climate conditions using streamflow data, as opposed to other approaches requiring paired watersheds. The process is illustrated with three case studies. A watershed in Arizona experienced a +266% increase in annual water yield in the 5 years after a wildfire, where +219% was attributed to wildfire and +24% to precipitation trends. In contrast, a California watershed had a lower (–64%) post-fire net water yield, comprised of enhanced flow (+38%) attributed to wildfire offset (–102%) by lower precipitation in the post-fire period. Changes in streamflow within a watershed in South Carolina had no apparent link to periods of prescribed burning but matched a very wet winter and reports of storm damage. As a result, the presented framework is unique in its ability to detect and quantify fire or other disturbances, even if the date or nature of the disturbance event is uncertain, and regardless of precipitation trends.
- Published through SciTech Connect.
Ecohydrology 10 2 ISSN 1936-0584 AM
Dennis W. Hallema; Ge Sun; Peter V. Caldwell; Steven P. Norman; Erika C. Cohen; Yongqiang Liu; Eric J. Ward; Steven G. McNulty.
- Funding Information:
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