Evaluating Noah-MP simulated runoff and snowpack in heavily burned Pacific-Northwest snow-dominated catchments

Terrestrial hydrology is altered by fires, particularly in snow-dominated catchments. However, fire impacts on catchment hydrology are often neglected from land surface model (LSM) simulations. Western U.S. wildfire activity has been increasing in recent decades and is projected to continue increasing over at least the next three decades, and thus it is important to evaluate if neglecting fire impacts in operational land surface models (LSMs) is a significant error source that has a noticeable signal among other sources of uncertainty. We evaluate a widely used state-of-the-art LSM (Noah-MP) in runoff and snowpack simulations at two representative fire-affected snow-dominated catchments in the Pacific Northwest: Andrew's Creek in Washington and Johnson Creek in Idaho. These two catchments are selected across all western U.S. fire-affected catchments because they are snow-dominated and experienced more than 50% burning in a single fire event with minimal burning outside of this event, which allows analyses of distinct pre- and post-fire periods. There are statistically significant shifts in model skills from pre-to post-fire years in simulating runoff and snowpack. At both study catchments, simulations miss enhancements in early-spring runoff and annual runoff efficiency during post-fire years, resulting in persistent underestimates of annual runoff anomalies throughout the 12-year post-fire analysis periods. Enhanced post-fire snow accumulation and melt contributes to observed but unmodeled increases of spring runoff and annual runoff efficiency at these catchments. Informing simulations with satellite observed land cover classifications, leaf area index, and green fraction do not consistently improve the model ability to simulate hydrologic responses to fire disturbances.

To Access Resource:

Questions? Email Resource Support Contact:

  • opensky@ucar.edu
    UCAR/NCAR - Library

Resource Type publication
Temporal Range Begin N/A
Temporal Range End N/A
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links

Related Dataset #1 : Evaluating Noah-MP simulated runoff and snowpack in heavily burned Pacific-Northwest snow-dominated catchments

Related Dataset #2 : Snowmelt Timing Maps Derived from MODIS for North America, Version 2, 2001-2018

Related Dataset #3 : Shuttle Radar Topography Mission (SRTM) Non-Void Filled

Related Dataset #4 : MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006

Related Dataset #5 : MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006

Related Dataset #6 : MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250m SIN Grid V006

Additional Information N/A
Resource Format PDF
Standardized Resource Format PDF
Asset Size N/A
Legal Constraints

Copyright 2024 American Geophysical Union (AGU).


Access Constraints None
Software Implementation Language N/A

Resource Support Name N/A
Resource Support Email opensky@ucar.edu
Resource Support Organization UCAR/NCAR - Library
Distributor N/A
Metadata Contact Name N/A
Metadata Contact Email opensky@ucar.edu
Metadata Contact Organization UCAR/NCAR - Library

Author Abolafia-Rosenzweig, Ronnie
He, Cenlin
Chen, Fei
Zhang, Yongxin
Dugger, A.
Livneh, B.
Gochis, D.
Publisher UCAR/NCAR - Library
Publication Date 2024-05-16T00:00:00
Digital Object Identifier (DOI) Not Assigned
Alternate Identifier N/A
Resource Version N/A
Topic Category geoscientificInformation
Progress N/A
Metadata Date 2025-07-10T20:02:06.382580
Metadata Record Identifier edu.ucar.opensky::articles:27188
Metadata Language eng; USA
Suggested Citation Abolafia-Rosenzweig, Ronnie, He, Cenlin, Chen, Fei, Zhang, Yongxin, Dugger, A., Livneh, B., Gochis, D.. (2024). Evaluating Noah-MP simulated runoff and snowpack in heavily burned Pacific-Northwest snow-dominated catchments. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7h999cz. Accessed 09 August 2025.

Harvest Source