Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions, and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011-2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, 3, and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within one year, while four years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understory or minimally recovered. Relative to using a pixel-based Normalized Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.

Following wildfire, mountainous areas of the western United States are susceptible to enhanced runoff and erosion and an increased vulnerability to debris flow during intense rainfall. Convective storms that can generate debris flows in recently burned areas may occur during or immediately after the wildfire, leaving insufficient time for development and implementation of risk mitigation strategies. We present a method for estimating post-fire debris-flow hazards prior to wildfire using historical data to define the range of potential fire severity for a given location based on the statistical distribution of severity metrics obtained from remote sensing. Estimates of debris-flow likelihood, magnitude and triggering rainfall threshold based upon the statistically simulated fire severity data provide hazard predictions consistent with those calculated from fire severity data collected after wildfire. Simulated fire severity data also produce hazard estimates that replicate observed debris-flow occurrence, rainfall conditions, and magnitude at a monitored site in the San Gabriel Mountains of southern California. Future applications of this method should rely upon a range of potential fire severity scenarios for improved pre-fire estimates of debris-flow hazard. The method presented here is also applicable to modeling other post-fire hazards, such as flooding and erosion risk, and for quantifying historic trends in fire severity in a changing climate. This release contains the data used to derive the historical distributions of fire severity, including a) the data used to derive a Weibull cumulative distribution function to historical measures of the differenced normalized burn ratio for fires >= 4 square kilometers (1000 acres) that burned between 2001 and 2014 in the western United States, b) the shape and scale parameters for the Weibull cumulative distribution function for every class of existing vegetation type, and the statistics describing goodness-of-fit of the Weibull distribution to these data, and c) the data used to determine the BARC4 threshold defining the break between pixels burned at low and moderate or high severity.

Following wildfire, mountainous areas of the western United States are susceptible to enhanced runoff and erosion and an increased vulnerability to debris flow during intense rainfall. Convective storms that can generate debris flows in recently burned areas may occur during or immediately after the wildfire, leaving insufficient time for development and implementation of risk mitigation strategies. We present a method for estimating post-fire debris-flow hazards prior to wildfire using historical data to define the range of potential fire severity for a given location based on the statistical distribution of severity metrics obtained from remote sensing. Estimates of debris-flow likelihood, magnitude and triggering rainfall threshold based upon the statistically simulated fire severity data provide hazard predictions consistent with those calculated from fire severity data collected after wildfire. Simulated fire severity data also produce hazard estimates that replicate observed debris-flow occurrence, rainfall conditions, and magnitude at a monitored site in the San Gabriel Mountains of southern California. Future applications of this method should rely upon a range of potential fire severity scenarios for improved pre-fire estimates of debris-flow hazard. The method presented here is also applicable to modeling other post-fire hazards, such as flooding and erosion risk, and for quantifying historic trends in fire severity in a changing climate. This release contains the data used to derive the historical distributions of fire severity, including a) the data used to derive a Weibull cumulative distribution function to historical measures of the differenced normalized burn ratio for fires >= 4 square kilometers (1000 acres) that burned between 2001 and 2014 in the western United States, b) the shape and scale parameters for the Weibull cumulative distribution function for every class of existing vegetation type, and the statistics describing goodness-of-fit of the Weibull distribution to these data, and c) the data used to determine the BARC4 threshold defining the break between pixels burned at low and moderate or high severity.

Wildfire can substantially alter the hydrologic response of watersheds to rainfall, and debris-flow activity is the among the most destructive consequences of these events. To assist federal, state, and local agencies in planning for postfire hazards, the U.S. Geological Survey conducts debris-flow hazard assessments for recent wildfires.This item holds the postfire debris-flow hazard assessment for the Johnson fire event that began on or near 2024-07-25. Contents: Shapefiles.zip Zip archive of hazard modeling results. Includes shapefiles for the fire perimeter, stream segments, catchment basins, and outlet points. jon2024-field-descriptions.txt Descriptions of the shapefile data fields. jon2024-median-thresholds.csv Table of median rainfall thresholds as calculated over the stream segments and catchment basins. jon2024-metadata.txt Auxiliary metadata about the fire event and implementation of the hazard assessment. Methods: The hazard assessment was designed to implement: * The "M1" debris-flow likelihood model of Staley and others (2017) * The "emergency" potential sediment volume model of Gartner and others (2014) * The debris-flow combined hazard classification scheme of Cannon and others (2010) The assessment was produced by USGS personnel running the beta version of the ocelote package. Operational personnel may have also modified stream network delineation and modeling parameters in order to ensure quality. The beta version is represented by the ocelote commits prior to the v1.0.0 release. The ocelote source repository can be found here: https://code.usgs.gov/ghsc/lhp/ocelote References: Cannon, S. H., Gartner, J. E., Rupert, M. G., Michael, J. A., Rea, A. H., and Parrett, C. (2010). Predicting the probability and volume of postwildfire debris flows in the intermountain western United States. Bulletin, 122(1-2), 127-144. Gartner, J. E., Cannon, S. H., and Santi, P. M. (2014). Empirical models for predicting volumes of sediment deposited by debris flows and sediment-laden floods in the transverse ranges of southern California. Engineering Geology, 176, 45-56. Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and Youberg, A. M. (2017). Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States. Geomorphology, 278, 149-162.

Wildfire can substantially alter the hydrologic response of watersheds to rainfall, and debris-flow activity is the among the most destructive consequences of these events. To assist federal, state, and local agencies in planning for postfire hazards, the U.S. Geological Survey conducts debris-flow hazard assessments for recent wildfires.This item holds the postfire debris-flow hazard assessment for the Shelly fire event that began on or near 2024-07-03. Contents: Shapefiles.zip Zip archive of hazard modeling results. Includes shapefiles for the fire perimeter, stream segments, catchment basins, and outlet points. shl2024-field-descriptions.txt Descriptions of the shapefile data fields. shl2024-median-thresholds.csv Table of median rainfall thresholds as calculated over the stream segments and catchment basins. shl2024-metadata.txt Auxiliary metadata about the fire event and implementation of the hazard assessment. Methods: The hazard assessment was designed to implement: * The "M1" debris-flow likelihood model of Staley and others (2017) * The "emergency" potential sediment volume model of Gartner and others (2014) * The debris-flow combined hazard classification scheme of Cannon and others (2010) The assessment was produced by USGS personnel running the beta version of the ocelote package. Operational personnel may have also modified stream network delineation and modeling parameters in order to ensure quality. The beta version is represented by the ocelote commits prior to the v1.0.0 release. The ocelote source repository can be found here: https://code.usgs.gov/ghsc/lhp/ocelote References: Cannon, S. H., Gartner, J. E., Rupert, M. G., Michael, J. A., Rea, A. H., and Parrett, C. (2010). Predicting the probability and volume of postwildfire debris flows in the intermountain western United States. Bulletin, 122(1-2), 127-144. Gartner, J. E., Cannon, S. H., and Santi, P. M. (2014). Empirical models for predicting volumes of sediment deposited by debris flows and sediment-laden floods in the transverse ranges of southern California. Engineering Geology, 176, 45-56. Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and Youberg, A. M. (2017). Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States. Geomorphology, 278, 149-162.

Wildfire can substantially alter the hydrologic response of watersheds to rainfall, and debris-flow activity is the among the most destructive consequences of these events. To assist federal, state, and local agencies in planning for postfire hazards, the U.S. Geological Survey conducts debris-flow hazard assessments for recent wildfires.This item holds the postfire debris-flow hazard assessment for the Snag fire event that began on or near 2024-08-05. Contents: Shapefiles.zip Zip archive of hazard modeling results. Includes shapefiles for the fire perimeter, stream segments, catchment basins, and outlet points. sng2024-field-descriptions.txt Descriptions of the shapefile data fields. sng2024-median-thresholds.csv Table of median rainfall thresholds as calculated over the stream segments and catchment basins. sng2024-metadata.txt Auxiliary metadata about the fire event and implementation of the hazard assessment. Methods: The hazard assessment was designed to implement: * The "M1" debris-flow likelihood model of Staley and others (2017) * The "emergency" potential sediment volume model of Gartner and others (2014) * The debris-flow combined hazard classification scheme of Cannon and others (2010) The assessment was produced by USGS personnel running the beta version of the ocelote package. Operational personnel may have also modified stream network delineation and modeling parameters in order to ensure quality. The beta version is represented by the ocelote commits prior to the v1.0.0 release. The ocelote source repository can be found here: https://code.usgs.gov/ghsc/lhp/ocelote References: Cannon, S. H., Gartner, J. E., Rupert, M. G., Michael, J. A., Rea, A. H., and Parrett, C. (2010). Predicting the probability and volume of postwildfire debris flows in the intermountain western United States. Bulletin, 122(1-2), 127-144. Gartner, J. E., Cannon, S. H., and Santi, P. M. (2014). Empirical models for predicting volumes of sediment deposited by debris flows and sediment-laden floods in the transverse ranges of southern California. Engineering Geology, 176, 45-56. Staley, D. M., Negri, J. A., Kean, J. W., Laber, J. L., Tillery, A. C., and Youberg, A. M. (2017). Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States. Geomorphology, 278, 149-162.

This data release includes time-series data from two monitoring stations in a small drainage basin burned in the 2014 Silverado Fire, Orange County, California. One station (upper station) is located in the headwaters of the study area (33 45’39.10”N, 117 35’17.48”W, WGS84). The other station (lower station) is located at the outlet of the study area (33 45’04.61”N, 117 35’12.54”W). The data were collected between November 15, 2014 and January 14, 2016. The data include continuous 1-minute time series of rainfall and soil water content recorded at the both stations and intermittent (during rain storms) 50-Hz time series of flow-induced ground vibrations recorded by geophones at the lower station. The soil water content measurements were made at 2 depths below the ground surface (5 and 10 cm) between 2014-11-15 and 2015-04-24, and 4 depths below the ground surface (5, 10, 15, and 20 cm) between 2015-04-24 and 2016-01-14. The ground vibrations were measured by two 4.5 Hz vertical axis geophones (Geospace SNG 11D/PC902/OPEN-30m) located approximately 3 m from the channel bank and separated by 11.8 m in the streamwise direction. Details of this study are described in the journal article: McGuire, L.A., Rengers, F.K., Kean, J.W., Staley, D.M., and Mirus B.B., (2017), Incorporating spatially heterogeneous infiltration capacity into hydrologic models with applications for simulating post-wildfire debris flow initiation, Hydrologic Processes.

This data release includes time-series data from two monitoring stations in a small drainage basin burned in the 2014 Silverado Fire, Orange County, California. One station (upper station) is located in the headwaters of the study area (33 45’39.10”N, 117 35’17.48”W, WGS84). The other station (lower station) is located at the outlet of the study area (33 45’04.61”N, 117 35’12.54”W). The data were collected between November 15, 2014 and January 14, 2016. The data include continuous 1-minute time series of rainfall and soil water content recorded at the both stations and intermittent (during rain storms) 50-Hz time series of flow-induced ground vibrations recorded by geophones at the lower station. The soil water content measurements were made at 2 depths below the ground surface (5 and 10 cm) between 2014-11-15 and 2015-04-24, and 4 depths below the ground surface (5, 10, 15, and 20 cm) between 2015-04-24 and 2016-01-14. The ground vibrations were measured by two 4.5 Hz vertical axis geophones (Geospace SNG 11D/PC902/OPEN-30m) located approximately 3 m from the channel bank and separated by 11.8 m in the streamwise direction. Details of this study are described in the journal article: McGuire, L.A., Rengers, F.K., Kean, J.W., Staley, D.M., and Mirus B.B., (2017), Incorporating spatially heterogeneous infiltration capacity into hydrologic models with applications for simulating post-wildfire debris flow initiation, Hydrologic Processes.

This data release includes time-series data from a monitoring site located in a small drainage basin in the Arroyo Seco watershed in Los Angeles County, CA, USA (N3788964 E389956, UTM Zone 11, NAD83). The site was established after the 2009 Station Fire and recorded a series debris flows in the first winter after the fire. The data include three types of time-series: (1) 1-minute time series of rainfall, soil water content, channel bed pore pressure and temperature, and flow stage recorded by radar and laser distance meters (ArroyoSecoContinuous.csv); (2) 10-Hz time series of flow stage recorded by the laser distance meter during rain storms (ArroyoSecoStormLaser.csv), and (3) 2-second time series of rainfall and channel bed pore pressure and temperature during rain storms (ArroyoSecoStormPressureRain.csv). The laser and radar distance meters are suspended above the pore pressure sensor mounted in the bedrock of the channel. The equations for converting the distance measurements into flow stage above the pressure sensor (or stage of the stationary bed surface during times of no flow) are given by the equations Stage_laser (meters) = 2.107 meters – Distance_laser (meters), and Stage_radar (meters) = 2.156 meters – Distance_radar (feet)*0.3048 Details of this study are described in the journal article: Kean, J. W., D. M. Staley, and S. H. Cannon (2011), In situ measurements of post-fire debris flows in southern California: Comparisons of the timing and magnitude of 24 debris-flow events with rainfall and soil moisture conditions, J. Geophys. Res., 116, F04019, doi:10.1029/2011JF002005.

This data release includes time-series data from a monitoring site located in a small drainage basin in the Arroyo Seco watershed in Los Angeles County, CA, USA (N3788964 E389956, UTM Zone 11, NAD83). The site was established after the 2009 Station Fire and recorded a series debris flows in the first winter after the fire. The data include three types of time-series: (1) 1-minute time series of rainfall, soil water content, channel bed pore pressure and temperature, and flow stage recorded by radar and laser distance meters (ArroyoSecoContinuous.csv); (2) 10-Hz time series of flow stage recorded by the laser distance meter during rain storms (ArroyoSecoStormLaser.csv), and (3) 2-second time series of rainfall and channel bed pore pressure and temperature during rain storms (ArroyoSecoStormPressureRain.csv). The laser and radar distance meters are suspended above the pore pressure sensor mounted in the bedrock of the channel. The equations for converting the distance measurements into flow stage above the pressure sensor (or stage of the stationary bed surface during times of no flow) are given by the equations Stage_laser (meters) = 2.107 meters – Distance_laser (meters), and Stage_radar (meters) = 2.156 meters – Distance_radar (feet)*0.3048 Details of this study are described in the journal article: Kean, J. W., D. M. Staley, and S. H. Cannon (2011), In situ measurements of post-fire debris flows in southern California: Comparisons of the timing and magnitude of 24 debris-flow events with rainfall and soil moisture conditions, J. Geophys. Res., 116, F04019, doi:10.1029/2011JF002005.