The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, which was burned during the Waldo Canyon fire in the summer of 2012. The ensemble consists of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network. This ensemble of instruments was used to calculate stream channel characteristics derived from light detection and ranging (lidar) data. These data were leveraged to predict mean channel velocities based on Manning's equation, which were needed to compute the kinematic celerity and uncertainties and include water level, cross-sectional area, mean-channel velocity, and discharge. Surface velocity, stage, and precipitation time-series data collected during the field deployment on 10 August, 2015 were used to validate this novel method for predicting flood wave velocities and travel times as a function of stream discharge.

The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, which was burned during the Waldo Canyon fire in the summer of 2012. The ensemble consists of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network. This ensemble of instruments was used to calculate stream channel characteristics derived from light detection and ranging (lidar) data. These data were leveraged to predict mean channel velocities based on Manning's equation, which were needed to compute the kinematic celerity and uncertainties and include water level, cross-sectional area, mean-channel velocity, and discharge. Surface velocity, stage, and precipitation time-series data collected during the field deployment on 10 August, 2015 were used to validate this novel method for predicting flood wave velocities and travel times as a function of stream discharge.

This data release contains rainfall data from the 2020 Archie Creek, Holiday Farm, and Riverside Fire’s. These are gages identified in the parent OR_field_observations.csv release and used to calculate peak rainfall intensity-durations. The csv files here are organized by the station name and followed by the year of data collection. The locations of the stations, dates of deployment, interval, and unit of rainfall measurement are available in gage_locations.csv in the parent data release. All rainfall data are reported as a cumulative total. The Archie1, Archie2, Archie3, Holiday1, Holiday2, Holiday3, Holiday4, and Oregon Rain 4 rain gages are non-telemetered. These gages were deployed following the fires within the first few months of the 2020 water year. These rainfall data files are the raw output of the HOBO data logger file that have been converted to a csv using HOBO software version 3.7.25. These are tipping bucket gages where each bucket tip represents 0.2 mm of rainfall. The column headers for the non-telemetered gages are: #: Number of data logs recorded. Date Time, GMT-07:00: Time stamp of when data event was recorded [m/d/yyyy H:M:S]. Event, units (Sensor IDs): Bucket tip. OregonRain4 additionally includes a temperature recording column Temp, °C (LGR S/N: 10741450, SEN S/N: 10741450, LBL: temp), which describes the temperature recorded for the timestamp in degrees C. The D7564, E6414, F0379, F9895, HGNO3, LNEO3, RWXO3, TCFO3, and WPKO3 gages are telemetered, and rainfall data were downloaded from MESOWEST (https://mesowest.utah.edu/). MESOWEST only allows for rainfall data to be downloaded at a maximum of 365 days at a time, and rainfall data associated with these telemetered gages span multiple years. The multiple years of data for each gage were combined and adjusted so that our cumulative rainfall data starts at a value of 0 at the start of our downloaded data. These data are reported in inches. The column headers for these telemetered gages are: date: Time stamp of when data event was recorded [m/d/yyyy H:M]. precip: Cumulative total of rainfall in inches.

Spatial data used in the study "Characterization and Evaluation of Controls on Post-Fire Streamflow Response Across Western U.S. Watersheds".

Spatial data used in the study "Characterization and Evaluation of Controls on Post-Fire Streamflow Response Across Western U.S. Watersheds".

The consequence of the 1996 Buffalo Creek wildfire disturbance and a subsequent high-intensity summer convective rain storm (~100 mm h-1) was the deposition of a sediment superslug in the Spring Creek basin (26.8 km2) of the Front Range Mountains in Colorado. Changes in the superslug near the confluence of Spring Creek with the South Platte River were monitored by cross-section surveys at 18 nearly equally-spaced cross sections along a 1500 m study reach for 18 years (1996-2014) to understand the evolution and internal stratigraphy of this type of disturbance in response to different geomorphic processes. These data consist of 18 Excel files (one for each cross section) containing worksheets corresponding to each channel cross-section survey (about 25-31). Worksheets contain the basic survey information (dates, instruments, reference pin elevations, foresight, distances from reference pins, and elevations).

The consequence of the 1996 Buffalo Creek wildfire disturbance and a subsequent high-intensity summer convective rain storm (~100 mm h-1) was the deposition of a sediment superslug in the Spring Creek basin (26.8 km2) of the Front Range Mountains in Colorado. Changes in the superslug near the confluence of Spring Creek with the South Platte River were monitored by cross-section surveys at 18 nearly equally-spaced cross sections along a 1500 m study reach for 18 years (1996-2014) to understand the evolution and internal stratigraphy of this type of disturbance in response to different geomorphic processes. These data consist of 18 Excel files (one for each cross section) containing worksheets corresponding to each channel cross-section survey (about 25-31). Worksheets contain the basic survey information (dates, instruments, reference pin elevations, foresight, distances from reference pins, and elevations).

Debris Flow, Precipitation, and Volume Measurements in the Grizzly Creek Burn Perimeter June 2021-September 2022 https://doi.org/10.5066/P9Z7RROL This data release contains data summarizing observations within and adjacent to the Grizzly Creek Fire, which burned from 10 August to 18 December 2020. This monitoring data summarizes precipitation, observations of debris flows, and the volume of sediment eroded during debris flows triggered during the summer monsoonal period in 2021 and 2022. Summary rainfall data 2021 (1a_Storm_matrix_2021_gr1mmhr.csv) are provided in a comma-separated value (CSV) file. These data represent the maximum measured rainfall intensities during the monsoon months of 2021 (June-Sept). The columns in the csv file are: Date (m/dd/yy), Name (11 columns have unique gage names), Max 15 min (this is the maximum 15-minute rainfall intensity in mm/h for the unique gauge), Maximum Value for All Gages (this is the maximum rainfall intensity for all of the gauges in units of either mm/h or in/15 min), Peak 15-minute Intensity (in/15 min) (this is the total inches of rainfall in 15 minutes), Debris Flow (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response). Note that we only display gauges that record data sufficient to produce a 15-minute rainfall intensity. Gauges with longer recording rates (e.g., 1 hour) cannot be used to compute the 15-minute rainfall intensity and are not displayed in this table. A null value (‘n/a’) populates the entries where the rain gauge did not measure a 15-minute rainfall intensity greater than 1 mm/hr. Time series rainfall data from the gauges are provided in the child item: Precipitation Data Grizzly Creek Burn Perimeter. Summary rainfall data 2022 (1b_Storm_matrix_2022_gr1mmhr.csv) are provided in a comma-separated value (CSV) file. These data represent the maximum measured rainfall intensities during the monsoon months of 2022 (June-Sept). The columns in the csv file are: Date (m/dd/yy), Name (7 columns have unique gage names), Max 15 min (this is the maximum 15-minute rainfall intensity in mm/h), Peak 15-minute Intensity (in/15 min) (this is the total inches of rainfall in 15 minutes), Debris Flow (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response). Note that we only display gauges that record data sufficient to produce a 15-minute rainfall intensity. Gauges with longer recording rates (e.g., 1 hour) cannot be used to compute the 15-minute rainfall intensity and are not displayed in this table. A null value (‘n/a’) populates the entries where the rain gauge did not measure a 15-minute rainfall intensity greater than 1 mm/hr. Time series rainfall data from the gauges are provided in the child item: Precipitation Data Grizzly Creek Burn Perimeter. Debris Flow Observation data 2021 (2a_All_Verification_2021.csv) are provided in a comma-separated value (CSV) file. The columns in the csv file are: Year (yyyy), State, Fire Name, Fire_ID (index for the fire developed during the USGS debris flow hazard assessment), Fire_SegID (a specific index assigned by the USGS debris flow hazard assessment to the channel segment that produced the debris flow), Site Name (the name of the nearest milemarker on interstate 70), ObservationDate_mmddyyyy, ObservationLatitude_DD, ObservationLongitude_DD, DebrisFlowResponse (this can be 0 indicating no debris flow response, or 1 indicating a debris flow response), SourceOfObservation (name of the observer), StormDate_mmddyyyy, GaugeName, GaugeLatitude_DD, GaugeLongitude_DD, GaugeDist_km (distance from watershed of the debris flow observation to the nearest rain gage in km), StormAccum_mm (the total rainfall during a storm in millimeters), StormDuration_hr (the total duration of a storm in hours), Peak_I15_mm/h (the maximum 15 minute rainfall intensity in mm/h), Peak_I30_mm/h (the maximum 30 minute rainfall intensity in mm/h), Peak_I60_mm/h (the maximum 60 minute rainfall intensity in

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 Hill fire event that began on or near 2024-07-16. Contents: Shapefiles.zip Zip archive of hazard modeling results. Includes shapefiles for the fire perimeter, stream segments, catchment basins, and outlet points. hil2024-field-descriptions.txt Descriptions of the shapefile data fields. hil2024-median-thresholds.csv Table of median rainfall thresholds as calculated over the stream segments and catchment basins. hil2024-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.

After wildfires occurred in the western United States during 2020, in-stream water quality monitors and automatic samplers were deployed in four burned watersheds and one unburned watershed. In-stream water temperature, turbidity, and fluorescent dissolved organic matter (fDOM) were measured at high frequency, and the fDOM data were corrected for temperature and turbidity effects. Automatic samplers were triggered during storm events, which captured turbid conditions in the wildfire affected streams. Laboratory experiments with storm event samples informed site-specific turbidity correction coefficients for fDOM data. An iterative solver approach also was developed to verify turbidity correction coefficients. This data release contains laboratory experiment data, as well as in-stream water temperature, turbidity, uncorrected fDOM, temperature-corrected fDOM, and temperature- and turbidity-corrected fDOM data. An example of the iterative solver code is also provided.