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.本数据集支撑Abolafia-Rosenzweig等人题为"重度焚烧的太平洋西北部积雪主导流域中Noah-MP模型模拟径流与积雪"（Evaluating Noah-MP simulated runoff and snowpack in heavily burned Pacific-Northwest snow-dominated catchments）的手稿中的研究结果。 摘要 火灾会改变陆地水文过程，在积雪主导流域中这一效应尤为显著。然而，陆面模型（Land Surface Model, LSM）的模拟往往未考虑火灾对流域水文的影响。近数十年来，美国西部野火活动愈发频繁，且预计至少在未来三十年仍将持续加剧，因此亟需评估业务化陆面模型中忽略火灾影响这一做法是否会成为显著的误差来源，并在其他不确定性因素中产生可被观测到的信号。 本研究针对太平洋西北部两处受火灾影响的典型积雪主导流域——华盛顿州的安德鲁溪（Andrew’s Creek）与爱达荷州的约翰逊溪（Johnson Creek），评估了当前广泛使用的先进陆面模型Noah-MP在径流与积雪储量模拟中的表现。这两处流域从全美西部受火灾影响的流域中筛选而出，原因在于其均为积雪主导型流域，且在单次火灾事件中过火面积超过50%，该事件外几乎无额外过火，这使得研究可以清晰区分火灾前后的水文响应时段。 研究发现，在模拟径流与积雪储量时，模型在火灾前后年份的模拟能力存在统计学意义上的显著变化。在两处研究流域中，模型均未能复现火灾后年份早春径流与年度径流效率的提升现象，导致在火灾后12年的分析时段内，持续低估了年度径流异常值。火灾后积雪积累与消融过程的增强，会带来研究流域内春季径流与年度径流效率的实测提升，但这一过程未被模型纳入考量。 通过卫星观测的土地覆盖分类、叶面积指数（Leaf Area Index）与植被占比信息优化模型模拟，并未持续提升模型模拟水文响应对火灾扰动的能力。