Spatial and temporal distribution characteristics of escaped prescribed fires in California
Abstract
Prescribed fires are one of the most efficient and affordable measures to control the intensity of growing wildfires in California. However, the escaped prescribed fires have the risk of becoming large wildfires, which would cause significant damage to lives, ecosystems and properties and pose challenges to fire management agencies, landowners and the public. Thus, it is essential to look into the temporal and spatial distributions of escaped prescribed fires in the records for the reference of the future burn window selection. To this end, we cleaned the escaped prescribed fire data from CAL FIRE, MTBS, and PFIRS by removing the duplicates and cross-validating the records. Several geostatistics methods, such as kernel density estimation and spatial correlation calculation, were adopted to investigate contributing environmental factors and the spatial patterns of escaped prescribed fires. The results showed that the escaped prescribed fires mostly occurred in October and November, while covering the largest area in June. Among 27 CAL FIRE administrative units, prescribed fires in Mendocino Unit have the highest escape rate, reaching about 25%. Based on the spatial correlation, prescribed fires are prone to escape in the regions with tree cover from 30% to 60% and shrub cover from 30% to 50%. Montane Conifer Forest & Woodland, Xeric Chaparral, and Ruderal Grassland & Meadow are the three vegetation types with the highest coverage in the previous escaped prescribed fire perimeters. Regarding the relationship between climate conditions and the escaped prescribed fires, the temperature was a significant correlation factor, compared with precipitation and vapor pressure deficit. These results shed light on the periods, regions and environmental conditions in which prescribed fires were prone to escape in the record, and it is a valuable reference for window selection in future California prescribed burning projects.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMNH15F0511L