Erosion and runoff have been observed to increase following fire. Land managers and Burned Area Emergency Rehabilitation (BAER) teams must be able to estimate these post-fire changes. Studies of post-fire erosion on burned watersheds show that the concentrations of sediment eroded from burned rangeland and forested hillslopes in the southwestern United States can be extremely high. Since wildfire primarily impacts soils and vegetation cover on hillslopes, it is appropriate to assume that changes in hillslope conditions will result in changes in runoff peak, volume and sediment yield. The AGWA (Automated Geospatial Watershed Assessment www.tucson.ars.ag.gov/agwa) hydrologic modeling tool employs both an empirical model (SWAT) and a more process-based model (KINEROS2). In order to study how these models should be modified to provide land managers with a means to assess the impact of fire, the models were applied on two burned watersheds. Analysis of data from the Marshall Gulch watershed near Tucson, Arizona, indicates that changes in runoff volume are small compared to changes in peak runoff. The application of the KINEROS2 model to burned conditions at the Starmer Canyon near Los Alamos, New Mexico shows a pattern of change over time that is consistent with watershed recovery. Calibrated hillslope roughness values are consistent with independent estimates for roughness under bare conditions following the fire to roughness consistent with forested conditions three years later. The modeling also indicated that increasing hillslope roughness over time accounts for much of the change in runoff response. Some of the physical changes following fire that have been identified to contribute to changes in hydrologic response include (DeBano et al. 1998):

Abstract:There have been many studies of hydrologic processes and scale. However, some researchers have found that predictions from hydrologic models may not be improved by attempting to incorporate the understanding of these processes into hydrologic models. This paper quantifies the effect of simplifying watershed geometry and averaging the parameter values on simulations generated using the KINEROS2 model. Furthermore, it examines how these changes in model input effect model output. The model was applied on a small semiarid rangeland watershed in which runoff is generated by the infiltration excess mechanism. The study concludes that averaging input parameter values has little effect on runoff volume and peak in simulating runoff. However, geometric simplification does have an effect on runoff peak and volume, but it is not statistically significant. In contrast, both averaging input parameter values and geometric simplification have an effect on model-predicted sediment yield.

Rapid post-fire watershed assessment to identify potential trouble spots for erosion and flooding can potentially aid land managers and Burned Area Emergency Rehabilitation (BAER) teams in deploying mitigation and rehabilitation resources. These decisions are inherently complex and spatial in nature and require a distributed hydrological modeling approach. The extensive data requirements and the task of building input parameter files have presented obstacles to the timely and effective use of complex distributed rainfallrunoff and erosion models by BAER teams and resource managers. Geospatial tools and readily-available digital sources of pre-fire land cover, topography, and soils combined with rainfall-runoff and erosion models can expedite assessments if properly combined, provided a post-fire burn-severity map is available. The AGWA (Automated Geospatial Watershed Assessment) hydrologic modeling tool was developed to utilize nationally available spatial data sets and both empirical (SWAT) and more process-based (KINEROS2) distributed hydrologic models (see: www.tucson.ars.ag.gov/agwa). Through an intuitive interface the user selects an outlet from which AGWA delineates and discretizes the watershed using a Digital Elevation Model (DEM). The watershed model elements are then intersected with soils and land cover data layers to derive the requisite model input parameters. The chosen model is then run, and the results are imported back into AGWA for graphical display. AGWA can difference results from pre-and post-fire model simulations and display the change on the modeled watershed. This allows managers to identify potential problem areas where mitigation activities can be focused. An overview of AGWA and an application of it to the 2003 Aspen fire north of Tucson, Arizona are discussed herein.

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