Managing Forests for Snow, Water, and Sustainable Ecosystems

管理森林以实现雪、水和可持续生态系统

• 批准号: 1703663
• 负责人: Jessica Lundquist
• 金额: $ 30万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1703663&HistoricalAwards=false
• 关键词: Managing; Forests; Snow; Water; Sustainable

In western North America, forest management strategies have led to young, dense forests that are more susceptible to drought, insect infestation, and other stressors. Forests cover 30% of the earth's land area and almost 100% of many U.S. mountainous regions. Thus, a change in forest structure has broad ecological impacts, beyond those normally attributed to climate change. The PI has shown forest cover may either increase or decrease the date of the first snowmelt by up to two weeks. As mountainous snowpacks are a natural water storage reservoir, the date of the first snowmelt affects summer river flow. Summer river flow has wide ranging impacts on human, ecosystem, and agricultural water demands. The effect of forest cover may be managed by increasing forest retention and/or opening gaps in the canopy. This research project is developing and testing hydrologic models for mountainous watersheds to determine how forest change relates to the human-ecologic-hydrologic system. Additionally, the researchers on this project are working with stakeholders to help students understand the goals and concerns related to forest-water management and educating undergraduate and graduate students in state-of-the-art spatial data analysis and modeling.Forest managers would like to know what site-specific actions to take for both sustainable water and forest management. Light Detection and Ranging (Lidar) is a remote sensing method that uses light in the form of a pulsed laser to measure distances to the Earth. Lidar imaging, combined with spatially-explicit modeling, represent a break-through in forest structure characterization and its relation to forest-snow interactions. This research project is utilizing and adapting an existing distributed hydrologic model to be used as a tool to assist forest management decisions. Specifically, the project involves modifying the model to better represent complex forest-snow interactions; using high resolution aerial photos combined with forest and snow lidar datasets to extract meaningful model parameters and to check simulated fields; testing model reliability over varying winter weather regimes; testing model transferability between sites with different forests and climate regimes, and working with an advisory team to distribute the model and tools so that they can be applied to any watershed.

在北美西部，森林管理战略导致了年轻、茂密的森林更容易受到干旱、虫害和其他压力因素的影响。森林覆盖了地球陆地面积的30%，几乎覆盖了美国许多山区的100%。 因此，森林结构的变化具有广泛的生态影响，超出了通常归因于气候变化的影响。 PI已经表明，森林覆盖可能会增加或减少第一次融雪的日期长达两周。由于山区积雪是一个天然的蓄水库，第一次融雪的日期会影响夏季的河流流量。 夏季河流流量对人类、生态系统和农业用水有着广泛的影响。森林覆盖的影响可以通过增加森林保有量和/或打开林冠空隙来管理。该研究项目正在开发和测试山区流域水文模型，以确定森林变化与人类-生态-水文系统的关系。 此外，该项目的研究人员正在与利益相关者合作，帮助学生了解与森林水资源管理相关的目标和问题，并对本科生和研究生进行最先进的空间数据分析和建模教育。森林管理人员希望了解为可持续的水资源和森林管理采取的具体措施。光探测和测距（激光雷达）是一种遥感方法，它使用脉冲激光形式的光来测量到地球的距离。激光雷达成像，结合空间显式建模，代表了森林结构表征及其与森林雪相互作用的关系的突破。该研究项目正在利用和调整现有的分布式水文模型，以作为协助森林管理决策的工具。具体而言，该项目涉及修改模型，以更好地表示复杂的森林雪相互作用;使用高分辨率航空照片与森林和雪激光雷达数据集相结合，以提取有意义的模型参数并检查模拟场;测试模型在不同冬季天气状况下的可靠性;测试模型在不同森林和气候状况的地点之间的可移植性，并与咨询团队合作，分发模型和工具，以便它们可以应用于任何流域。

项目成果

Evaluating Wind Fields for Use in Basin‐Scale Distributed Snow Models

评估盆地尺度分布式雪模型中使用的风场

• DOI: 10.1029/2020wr028536
• 发表时间: 2021
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Reynolds, Dylan S.;Pflug, Justin M.;Lundquist, Jessica D.
• 通讯作者: Lundquist, Jessica D.

Snow Depth Variability at the Forest Edge in Multiple Climates in the Western United States

• DOI: 10.1029/2018wr022553
• 发表时间: 2018-11-01
• 期刊: WATER RESOURCES RESEARCH
• 影响因子: 5.4
• 作者: Currier, William Ryan;Lundquist, Jessica D.
• 通讯作者: Lundquist, Jessica D.

Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities

截雪模型：孤立的观测导致许多地表模型缺乏适当的温度敏感性

• DOI: 10.1002/hyp.14274
• 发表时间: 2021
• 期刊: Hydrological Processes
• 影响因子: 3.2
• 作者: Lundquist, Jessica D.;Dickerson‐Lange, Susan;Gutmann, Ethan;Jonas, Tobias;Lumbrazo, Cassie;Reynolds, Dylan
• 通讯作者: Reynolds, Dylan