| Abstrakt: |
This study reviews five models commonly used in post-fire hydrologic assessments: the Rowe Countryman and Storey ( RCS), United States Geological Survey ( USGS) Linear Regression Equations, USDA Windows Technical Release 55 ( USDA TR-55), Wildcat5, and U.S. Army Corps of Engineers ( USACE) Hydrologic Modeling System ( HEC- HMS). The models are applied to eight diverse basins in the western United States (U.S.) (Arizona, California, Colorado, Montana, and Washington) affected by wildfires and assessed by input parameters, calibration methods, model constraints, and performance. No one model is versatile enough for application to all study sites. Results show inconsistency between model predictions for events across the sites and less confidence with larger return periods (25- and 50-year events) and post-fire predictions. The RCS method performs well, but application is limited to southern California. The USGS linear regression model has wider regional application, but performance is less reliable at the large recurrence intervals and post-fire predictions are reliant on a subjective modifier. Of the three curve number-based models, Wildcat5 performs best overall without calibration, whereas the calibrated TR-55 and HEC- HMS models show significant improvement in pre-fire predictions. Results from our study provide information and guidance to ultimately improve model selection for post-fire prediction and encourage uniform parameter acquisition and calibration across the western U.S. [ABSTRACT FROM AUTHOR] |
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