RUI: Measurement and modeling of rainfall interception loss from Georgia Southern University's urban forest.

RUI：佐治亚南方大学城市森林降雨拦截损失的测量和建模。

• 批准号: 1518726
• 负责人: John Van Stan
• 金额: $ 21.46万
• 依托单位: Georgia Southern University Research and Service Foundation, Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-15 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1518726&HistoricalAwards=false
• 关键词: RUI; Measurement; modeling; rainfall; interception

Forest canopy can reduce precipitation reaching the ground by up to 50% through interception, storage, and evaporation of droplets from leaf and bark surfaces. This process, called "interception loss," impacts run-off, recharge, flood flashiness, erosion, etc., and cost of stormwater management. It is not well understood how canopy structure affects interception loss, particularly in urban forests. This research addresses this by monitoring interception loss variables for a common SE US tree species (the loblolly pine) across a natural-to-urban gradient in forest structure. Interception loss variables monitored include rainwater stored in and evaporated from the canopy, passing through the canopy (throughfall), and draining down the stem (stemflow) as well as air temperature, humidity, wind speed/direction, pressure, and incoming solar radiation during and after rainfall. These measurements will be related to new, high-resolution, non-destructive laser-scanning (LiDAR) techniques to address 2 questions: 1) how do stand structural changes ranging from natural conditions to common urban conditions affect interception loss processes; and 2) Will LiDAR-measured canopy structures and interception loss processes improve estimation and prediction of hydrologic processes and, thereby, improve water management and planning? The hypothesis is that, because tree stand conditions affect branching and leaf structures, interception loss and its underlying variables will vary in response to storm conditions. Inclusion of these responses in common models will have predictive value for water management concerning shifts in storm conditions . This is an RUI (Research at Undergraduate Institutions) project that will train undergraduate students in cutting-edge hydrologic science and be incorporated into educational outreach efforts reaching thousands of K-12 students, undergraduate students, high school teachers, and community members. Georgia Southern University (GSU) has a substantial African American student population (25.7% and 26.4% of undergraduates in 2012 and 2013), so the project will provide research experiences to underrepresented groups. Project data will be used to develop management practices on the GSU campus. Forest canopy rainfall interception loss (I) is documented to exert significant influence on run-off, recharge, flood flashiness, erosion and the cost of stormwater management infrastructure. However, it is not well understood how the forest canopy structure controls the components of I (storage, S, and evaporation, E), particularly in urban forests. No existing study has: 1) compared S and E behavior along a natural-urban forest continuum of differing canopy architecture or 2) incorporated terrestrial LiDAR (TLiDAR) measured canopy structures and the interaction of these structures with S and E dynamics into common I models. This study will do this along a natural-to-urban forest structure gradient on the Georgia Southern University (GSU) campus using a regionally dominant species (Pinus taeda, loblolly pine). The study will couple existing biometeorological monitoring methods (meteorological, stemflow, and throughfall measurements) with novel terrestrial LiDAR techniques (LaserBark and L-Architect) to compare S and E in urban forests with directly, non-destructively measured canopy structural metrics. This addresses two questions: 1) how do across- and within-storm dynamics of S and E vary for 2 urban forest structures, and how does this compare to natural tree stands, and 2) to what extent can inclusion of directly-measured canopy structures in urban stands alter I outputs, parameters, and even parameterizations for the most commonly used models (i.e., the Gash- and Rutter-type)? These findings will advance nearly all hydrologic models that simulate or include forest interception processes. Six undergraduates supported by this proposal will receive substantial research experiences spanning the breadth of research activities (including field instrument training, installation, and maintenance; data collection and processing; modeling and model evaluation; manuscript preparation; and presentation at national meetings) in a timely and critical subfield of water resource management. Data will also be used to improve: 1) the L-Architect model, which is being incorporated into Computree, a tool used by the Office National des Forêts (France) for national improvement of forest inventories; and 2) the sustainable irrigation practices currently employed on the GSU campus.

森林冠层可以通过拦截，存储和叶片和树皮表面的液滴蒸发来减少高达50％的降水量。这个过程称为“拦截损失”，影响雨水管理的径流，充值，洪水闪烁，侵蚀等和成本。尚不充分了解冠层结构如何影响拦截损失，尤其是在城市森林中。这项研究通过监测森林结构中自然界梯度的普通se树（Loblolly Pine）的截距损失变量来解决这一问题。监测的截距损失变量包括存储在树冠中并蒸发的雨水，穿过冠层（通过秋天），并在降雨期间和之后排干茎（茎流）以及空气温度，湿度，风速/方向，压力，压力，压力和传入的太阳辐射。这些测量结果将与新的高分辨率，非破坏性激光扫描（LIDAR）技术有关，以解决2个问题：1）从自然条件到常见的城市条件的结构变化如何影响拦截损失过程； 2）激光盖的树冠结构和拦截损失过程是否会改善水文过程的估计和预测，从而改善水的管理和计划？假设是，由于树木支架的条件会影响分支和叶片结构，因此拦截损失及其基本变量会随着暴风雨条件而有所不同。将这些响应纳入共同模型将具有有关风暴条件下的转移的水管理的预测价值。这是一项RUI（本科机构的研究）项目，该项目将培训本科生的尖端水文科学，并将其纳入教育外展工作中，以涉及成千上万的K-12学生，本科生，高中老师和社区成员。佐治亚州南部大学（GSU）拥有大量的非裔美国学生人口（2012年和2013年的本科生的25.7％和26.4％），因此该项目将为代表性不足的群体提供研究经验。项目数据将用于开发GSU校园的管理实践。森林冠层降雨拦截损失（I）已记录在径流，补给，洪水闪烁，侵蚀和雨水管理基础设施的成本上产生重大影响。但是，尚不清楚森林冠层结构如何控制I（存储，S和蒸发，E）的组成部分，尤其是在城市森林中。没有现有的研究具有：1）比较了沿天然城市的森林连续体的S和E行为，或者2）2）掺入的陆地激光雷达（Tlidar）测量的冠层结构，以及这些结构与S和E动力学与常见I模型的相互作用。这项研究将沿着佐治亚州南部大学（GSU）校园的自然界森林结构梯度（使用区域优势物种（Pinus taeda，loblory pine）来做到这一点。该研究将将现有的生物气象监测方法（气象，干液和遍布测量值）与新颖的陆地痛技术（Laserbark和L-Architect）与直接，非破坏性测量的冠层结构度量进行比较。这解决了两个问题：1）S and E的跨和内部动力学在2个城市森林结构中如何变化，以及与自然树的架子相比，以及2）在多大程度上可以在多大程度上纳入Urban Stand中直接测量的冠层结构，改变了I的i输出，参数，甚至是最常用的模型（即Gash-和gash-和gash-e和Rutter-toctepepe）？这些发现将进步几乎所有模拟或包括森林拦截过程的氢化模型。该提案支持的六名大学生将在及时且关键的水资源管理子领域中获得跨越研究活动（包括现场仪器培训，安装和维护；数据收集和处理；模型和模型评估；手稿准备；以及在国家会议上的介绍）的大量研究经验。数据还将用于改进：1）将L-Architect模型纳入Computree，该模型是Computree，该工具由办公室国家使用的工具（法国）用于全国性的森林库存改善； 2）GSU校园目前采用的可持续灌溉实践。