Predicting Postfire Runoff Using Gridded Curve Number Map Generated from Vegetation Data: A Case Study

Prediction of surface runoff immediately after a wildfire is challenging because it can significantly impact the hydrological parameters of the burned areas due to vegetation reduction. Still, there has been limited research focused on estimating the actual impact of vegetation reduction on increased surface runoff. This paper presents a novel approach to predict postfire surface runoff using the curve number (CN) method, in which the values of CNs were calculated based on the reduction of postfire vegetation. We illustrated the approach using a severely burned watershed after the 2020 Bighorn Fire in Southern Arizona. We developed prefire and postfire gridded CN maps using the latest vegetation map from the LANDFIRE database (LANDFIRE's 2022 map "Existing vegetation type"). We also analyzed and classified (cross-walked) the vegetation types corresponding to the CN values for the broader vegetation types listed in the USDA's 1986 technical release Urban hydrology for small watersheds (TR-55) and the Pima County Regional Flood Control District's 2019 technical report PC-Hydro user guide (PC-Hydro). Since only limited land use classifications for arid regions are available in both manuals, this study reclassified the vegetation types. We developed two new CN tables for more than 70 vegetation types in arid and semiarid regions. These tables quantify the CN values based on vegetation type, canopy cover, and soil hydrologic property. Postfire surface runoff was calculated for the 100 year rainfall event using these tables and the postfire vegetation reduction map. The results showed that areas with high burn severity experienced the most significant increase in CN values ranging from 8 to 20. In contrast, areas with low burn severity had the least increase in CN values (0-4). The peak discharges from the 100 year design rainfall increased at 21 of the 26 subbasin outlets, and the maximum increase is 22%. The comparison of runoff calculated using the grided CN map based on PC-Hydro with the predictions from the United States Geological Survey regression method and the field observations showed good agreements. Therefore, this approach and the revised CN value tables are valuable to hydrologic engineers for predicting postfire surface runoff from watersheds in arid and semiarid regions.