The western United States is experiencing severe wildfires whose observed impacts, including post-wildfire floods and debris flows, appear to be increasing over time.
Wildfires increase a landscape’s susceptibility to erosion and flood risk by consuming vegetation that stabilizes the soil and shields it from rainfall and by altering the soil’s capacity to absorb water. Post-fire rainfall events can trigger erosion and associated increases in sediment transport, as well as debris flows and non-point source pollution downstream. These post-wildfire watershed responses pose a threat to human communities, water quality, and ecosystems and are expected to increase under future climate conditions.
USGS Science Centers in Northern California, including Western Geographic Science Center, Geology, Minerals, Energy, and Geophysics Science Center, California Water Science Center, and national centers like National Uncrewed Systems Office (NUSO), and National Innovation Center, are partnering with Non-Governmental Organizations, NASA, Pacific Gas and Electric (PG&E) and local State and County entities to study post-wildfire soil infiltration, runoff, and recovery at several sites in northern California that burned during the record-breaking 2020 wildfire season. These studies integrate Uncrewed Aerial Systems (UAS) deployed imagers with field monitoring data (soil organics, microorganisms, soil moisture and water infiltration rates) to characterize fine-grained spatial patterns of soil burn severity that can be related to hydrological and biogeochemical changes, and to quantify post-fire vegetation and soil recovery (Figure 1).
Very high resolution (1-4 cm) UAS imagery was collected at three field monitoring sites in 2021 and 2022, providing true color orthoimagery and digital terrain models for quantifying vegetation changes and soil burn severity immediately after the fires (Figure 2). Multispectral and structural data (Structure from Motion; SfM) were collected in 2021 during the second growing season after the fire to characterize soil and vegetation recovery (Figure 3). Multi-year UAS and field data will be used to track the “return-to-reference” timescales of post-fire infiltration and biogeochemical cycling rates.
Field data collection was undertaken each year (2020-2022) to assess levels of soil burn severity (char depth and color, soil composition, foliage consumed), which provide training and validation data for classifying soil surface and vegetation conditions from the multi-date UAS imagery (Figure 4).
- Overview
The western United States is experiencing severe wildfires whose observed impacts, including post-wildfire floods and debris flows, appear to be increasing over time.
Wildfires increase a landscape’s susceptibility to erosion and flood risk by consuming vegetation that stabilizes the soil and shields it from rainfall and by altering the soil’s capacity to absorb water. Post-fire rainfall events can trigger erosion and associated increases in sediment transport, as well as debris flows and non-point source pollution downstream. These post-wildfire watershed responses pose a threat to human communities, water quality, and ecosystems and are expected to increase under future climate conditions.
USGS Science Centers in Northern California, including Western Geographic Science Center, Geology, Minerals, Energy, and Geophysics Science Center, California Water Science Center, and national centers like National Uncrewed Systems Office (NUSO), and National Innovation Center, are partnering with Non-Governmental Organizations, NASA, Pacific Gas and Electric (PG&E) and local State and County entities to study post-wildfire soil infiltration, runoff, and recovery at several sites in northern California that burned during the record-breaking 2020 wildfire season. These studies integrate Uncrewed Aerial Systems (UAS) deployed imagers with field monitoring data (soil organics, microorganisms, soil moisture and water infiltration rates) to characterize fine-grained spatial patterns of soil burn severity that can be related to hydrological and biogeochemical changes, and to quantify post-fire vegetation and soil recovery (Figure 1).
Very high resolution (1-4 cm) UAS imagery was collected at three field monitoring sites in 2021 and 2022, providing true color orthoimagery and digital terrain models for quantifying vegetation changes and soil burn severity immediately after the fires (Figure 2). Multispectral and structural data (Structure from Motion; SfM) were collected in 2021 during the second growing season after the fire to characterize soil and vegetation recovery (Figure 3). Multi-year UAS and field data will be used to track the “return-to-reference” timescales of post-fire infiltration and biogeochemical cycling rates.
Field data collection was undertaken each year (2020-2022) to assess levels of soil burn severity (char depth and color, soil composition, foliage consumed), which provide training and validation data for classifying soil surface and vegetation conditions from the multi-date UAS imagery (Figure 4).
Sources/Usage: Public Domain.Figure 1. Caption: USGS researchers (Corina Cerovski-Darriau, Kim Perkins) measuring soil moisture, hydrophobicity, and infiltration in 2021, 1 year after a wildfire in California chaparral. Photo cred: C Creamer, USGS
Sources/Usage: Public Domain.Figure 2. A) Post-wildfire 1.2 cm orthoimage draped on a digital terrain model showing a study site that burned in the 2020 LNU Lightning Complex fire, and B) pre-fire lidar canopy height data showing the vegetation structure of the site. Image cred: Joshua von Nonn, USGS.
Sources/Usage: Public Domain.Figure 3. A) USGS UAS pilot Sky Corbett collecting true color imagery from a UAS mounted Ricoh GRII sensor to generate orthoimagery and digital surface models in 2020, and B) Joe Adams calibrating the multispectral MicaSense sensor used to gather information on vegetation and soils in 2022, two years after the fire occurrence. Photo cred: Miguel Villarreal, USGS
Sources/Usage: Public Domain.Figure 4. Field plots used to evaluate fine-scale soil burn serveity to calibrate and validate image classifications from Unoccupied Aerial Systems (UAS). Photograph on the left is from the 1st year after fire, and the photograph on the right is from the second year after fire. Photo cred: Miguel Villarreal, USGS