Evaluating Noah‐MP Simulated Runoff and Snowpack in Heavily Burned Pacific‐Northwest Snow‐Dominated Catchments.
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| Title: | Evaluating Noah‐MP Simulated Runoff and Snowpack in Heavily Burned Pacific‐Northwest Snow‐Dominated Catchments. |
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| Authors: | Abolafia‐Rosenzweig, Ronnie1 (AUTHOR) abolafia@ucar.edu, He, Cenlin1 (AUTHOR), Chen, Fei1 (AUTHOR), Zhang, Yongxin1 (AUTHOR), Dugger, Aubrey1 (AUTHOR), Livneh, Ben2 (AUTHOR), Gochis, David3 (AUTHOR) |
| Source: | Journal of Geophysical Research. Atmospheres. 5/16/2024, Vol. 129 Issue 9, p1-21. 21p. |
| Subject Terms: | *Land cover, *Runoff, *Snowmelt, Leaf area index, Snowpack augmentation, Snow accumulation |
| Geographic Terms: | Idaho, Washington (State) |
| Abstract: | 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. Plain Language Summary: Western U.S. fire activity has been increasing in recent decades and is expected to continue to increase in coming decades. Fires remove vegetation and alter soils which in turn alters terrestrial hydrology. Fire effects on hydrology are particularly significant over snowy catchments that serve as natural water towers for major western U.S. rivers. Sophisticated models often neglect or underrepresent fire effects on land surface properties, and thus are susceptible to larger errors after fires. This study compares runoff and snow simulations from a widely used land surface model (LSM) with observations to quantify fire‐induced changes in model accuracy over two snow dominated catchments in the Pacific Northwest. Simulations persistently underestimate enhanced spring runoff and annual runoff anomalies in post‐fire years. These underestimates are consistent with observed enhancements in post‐fire snow accumulation and melt, which the model mostly failed to capture. The finding that post‐fire model errors are consistent with previously published fire impacts on hydrology supports that fire is an important error source in LSM simulations that should be accounted for. Key Points: Noah‐MP underestimates annual runoff anomalies relative to observations following fires in the Pacific‐NorthwestIn post‐fire years, Noah‐MP fails to simulate deeper snowpacks that ablate faster and the associated enhanced spring runoffInforming the model with satellite‐observed vegetation characteristics (including fire effect) did not resolve post‐fire model deficiencies [ABSTRACT FROM AUTHOR] |
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| Database: | GreenFILE |
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