Data for: Modeling Postfire Recovery of Snow Albedo and Forest Structure to Understand Drivers of Decades of Reduced Snow Water Storage and Advanced Snowmelt Timing
Sponsor
NASA Terrestrial Hydrology Program Grant #80NSSC19K0002
Document Type
Dataset
Publication Date
2024
Abstract
Forest fires darken snow albedo and degrade forest structure, ultimately reducing peak snow-water storage, and advancing snowmelt timing for up to 15 years following fire. Todate, no volumetric estimates of watershed-scale postfire effects on snow-water storage and snowmelt timing have been quantified over decades of postfire recovery. Using postfire parameterizations in a spatially-distributed snow mass and energy balance model, SnowModel, we estimated postfire recovery of forest fire effects on snow-water equivalent (SWE) and snowmelt timing over decades following fire. Using this model, we quantified volumetric recovery of forest fire effects on snow hydrology across a chronosequence of eight sub-alpine forests burned between 2000 and 2019 in the Triple Divide of western Wyoming.We found that immediately following fire, forest fire effects reduced snow-water storage by 6.8% (sd = 11.2%) and advanced the snow disappearance date by 31 days (sd = 9 days). Across the 15-year recovery following fire, forest fire effects reduced snow-water storage by 4.5% (sd = 11.4%). Postfire effects on snow hydrology generally recovered over time, but still persisted beyond15-years following fire due to the observed postfire shift from forest to open meadow. Estimates of postfire reductions on peak SWE summed over the entire15-year postfire recovery period were eighteen times greater than the immediate losses in the first winter following fire alone. These lasting effects of forest fires on snow hydrology decades following fire highlight the importance of postfire parameterizations for more accurate watershed-scale volumetric estimates of forest fire effects on snow-water resources.
Rights
This work is marked with CC0 1.0 Universal
DOI
10.15760/esm-data.5
Recommended Citation
Anton Surunis & Kelly Gleason. "Data for: Modeling Postfire Recovery of Snow Albedo and Forest Structure to Understand Drivers of Decades of Reduced Snow Water Storage and Advanced Snowmelt Timing" (2024) [dataset] https://doi.org/10.15760/esm-data.5
outputs-20240720T005209Z-001.zip (773717 kB)
snowmodel_input-20240720T005359Z-001.zip (15596 kB)
Description
The input data folder of the repository includes the input data (meteorological forcing data [.dat], land cover and topography rasters [.asc], and snow-water equivalent assimilation data [.dat]) and parameterized code (.f) for three SnowModel instantiations (a base model, a postfire forest structure degradation model, and a postfire forest structure degradation and snow albedo decay model). The script folder includes the R scripts (.R) used to prepare and process the input data and analyze the model outputs. The outputs folder includes all the data used to produce the figures and tables in the associated journal article (extracted snow-water equivalent and energy balance values [.csv], March/April/May 1st snow-water equivalent rasters [.tif] , peak snow-water equivalent rasters [.tif], and snow disappearance data rasters [.tif]).