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

These data support results presented in the manuscript by Abolafia-Rosenzweig et al., "Evaluating Noah-MP simulated runoff and snowpack in heavily burned Pacific-Northwest snow-dominated catchments"

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 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 vegetation fraction do not consistently improve the model ability to simulate hydrologic responses to fire disturbances.

本数据集支持Abolafia-Rosenzweig等人在其手稿《评估Noah-MP模拟的太平洋西北部重度烧毁积雪流域的径流和雪pack》中提出的结果。

摘要
陆地水文学因火灾而改变，尤其在积雪主导的流域中。然而，火灾对流域水文学的影响常在陆地表面模型（LSM）模拟中遭到忽视。近几十年来，美国西部野火活动不断增加，预计至少在未来三十年内将持续增加，因此评估在操作LSM中忽略火灾影响是否是显著的误差来源，并在其他不确定性来源中产生可感知的信号，显得尤为重要。我们对一种广泛应用的先进LSM（Noah-MP）在太平洋西北部两个具有代表性的火灾影响积雪主导流域的径流和雪pack模拟中进行评估：华盛顿州的Andrew's Creek和爱达荷州的Johnson Creek。这两个流域在美国所有西部火灾影响流域中被选中，因为它们是积雪主导的，并且在一次火灾事件中超过50%的区域被烧毁，而该事件之外的区域燃烧程度极低，这使得可以对火灾前后两个不同的时期进行分析。在模拟径流和雪pack方面，模型技能在火灾前后年份间存在显著的转变。在两个研究流域中，模拟在火灾后年份未能捕捉到早春径流和年径流效率的提升，导致在12年的火灾后分析期间，年径流异常持续被低估。火灾后的增加积雪积累和融化有助于这些流域春季径流和年径流效率的观测值，但未被模型模拟。使用卫星观测的土地覆盖分类、叶面积指数和植被分数来指导模拟，并不能一致性地提高模型对火灾干扰水文响应的模拟能力。