This table provides all the source websites that were used in the dataset for this journal article

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions

Wildfire effects on Stream discharge and suspended sediments. This dataset is associated with the following publication: Beyene, M.T., S.G. Leibowitz, and M.J. Pennino. Parsing Weather Variability and Wildfire Effects on the Post-Fire Changes in Daily Stream Flows: A Quantile-Based Statistical Approach and Its Application. WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 57(10): e2020WR028029, (2021).

Wildfire effects on Stream discharge and suspended sediments. This dataset is associated with the following publication: Beyene, M.T., S.G. Leibowitz, and M.J. Pennino. Parsing Weather Variability and Wildfire Effects on the Post-Fire Changes in Daily Stream Flows: A Quantile-Based Statistical Approach and Its Application. WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 57(10): e2020WR028029, (2021).

This dataset provides annual forest fire burned area and daily hotspot products developed using data acquired from the Advanced Very-High-Resolution Radiometer (AVHRR) instruments carried aboard two NOAA polar-orbiting satellites (NOAA-11 and NOAA-14). The fire products were generated over 12 fire seasons (1st May - 31st October) from 1989-2000 across North America at 1-km resolution and subset to the ABoVE spatial domain of Alaska and Canada.

This data release contains model input and output data associated with a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]) where specific descriptions of the data can be found. The input data are derived from pre- and post-fire aerial LiDAR acquired in June 2010 and May 2012 respectively, for a small basin in the Jemez Mountains, northern, New Mexico. Data were process (analyzed?) to represent forest canopy characteristics pre- and post-fire. These characteristics include, (1) canopy closure, (2) edginess to the north, (3) edginess to the south, (4) leaf area index, (5) maximum tree height, (6) mean distance to canopy, (7) mean tree height, and (8) total gap area. Output includes Snow Water Equivalent (SWE) estimates from the SnowPALM model for pre- and post-fire conditions on a daily timestep between the 1st of September 1981 to the 31st of August 2018. All data are in a gridded format where the lower left hand corner is located at 3979325 north, and 371710 east in UTM Zone 13N with a map datum of NAD83. The grid is comprised of 1000 rows by 1100 columns with a grid cell size of 1m for a total domain size of 1.0km x 1.1km.

This data release contains model input and output data associated with a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]) where specific descriptions of the data can be found. The input data are derived from pre- and post-fire aerial LiDAR acquired in June 2010 and May 2012 respectively, for a small basin in the Jemez Mountains, northern, New Mexico. Data were process (analyzed?) to represent forest canopy characteristics pre- and post-fire. These characteristics include, (1) canopy closure, (2) edginess to the north, (3) edginess to the south, (4) leaf area index, (5) maximum tree height, (6) mean distance to canopy, (7) mean tree height, and (8) total gap area. Output includes Snow Water Equivalent (SWE) estimates from the SnowPALM model for pre- and post-fire conditions on a daily timestep between the 1st of September 1981 to the 31st of August 2018. All data are in a gridded format where the lower left hand corner is located at 3979325 north, and 371710 east in UTM Zone 13N with a map datum of NAD83. The grid is comprised of 1000 rows by 1100 columns with a grid cell size of 1m for a total domain size of 1.0km x 1.1km.

The impact of wildfire on water availability is a critical issue in the western United States. Because actual evapotranspiration (ETa) constitutes the largest loss in the terrestrial water budget, it has been suggested that fire-induced ETa reduction is a primary driver of elevated post-fire discharge. Ten gaged watersheds with burns exceeding 5% of their total contributing drainage area were selected from California, Oregon, Montana, Utah, New Mexico, and Colorado. Continuous daily stream gage data were compiled, and 30-meter ETa estimates were calculated with the Operational Simplified Surface Energy Balance (SSEBop) model. Fire-induced ETa shifts were quantified with statistical tests that compared pre and post-fire monthly ETa in burned and unburned pixels; the dampening effect of scale was also evaluated by repeating tests on all pixels from the entire basin. As streamflow data are point measurements that aggregate a large spatial area, additional statistical methods were required to isolate the effect of fire from climate on baseflow and runoff. Key findings include a) significant fire-induced ETa reductions were only distinguishable in basin-scale monthly datasets when at least 73% of the basin burned, b) the effect of wildfire disturbance on streamflow magnitude was seasonably variable, c) streamflow was modified in basins with as little as 6% burned drainage area; however, shifts only persisted beyond the fifth post-fire year where more than three-quarters of the basin was fire-impacted, and d) surplus water from ETa reduction was sufficient to account for boosted fire-induced streamflow. Where fire-induced streamflow increases were not significantly correlated with ETa anomaly, other fire-impacted landscape processes may have contributed to modified runoff generation and routing. Where fire reduced ETa but streamflow shifts were not detected, compensatory ETa pathways may have consumed the excess water before it reached the gage. Findings suggest that water providers with small source-water collection areas have higher relative risk for fire-induced hydromodification than providers with larger or more diversified supply portfolios. Results also illustrate the tendency of overarching climate signals to mask or artificially boost the apparent effect of landscape disturbance on streamflow at the basin outlet.

This dataset represents percent area burned in each burn severity class for wildfires within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies for each year for 1984-2018.The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. See: https://catalog.data.gov/dataset/monitoring-trends-in-burn-severity-burned-area-boundaries-feature-layer-27201 and https://www.mtbs.gov/product-descriptions