EAPSI: Connecting Distributed Impacts in Urban Watersheds to In-stream Hydrology and Water Quality Observations through Refined Landscape Metrics for Optimal Stormwater Handling

EAPSI：通过精细的景观指标将城市流域的分布式影响与河流内水文和水质观测联系起来，以实现最佳雨水处理

• 批准号: 1613598
• 负责人: Thomas Epps
• 金额: $ 0.54万
• 依托单位: Epps Thomas H
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1613598&HistoricalAwards=false
• 关键词: EAPSI; Connecting; Distributed; Impacts; Urban

Stormwater moves through urban watersheds via a complex network over pervious surfaces that infiltrate runoff and impervious surfaces that quickly move runoff towards streams. Impervious areas and the degree to which they are connected by drainage pipes have been shown to play the greatest role in shifting streamflow dynamics and water quality in urban streams leading to degraded conditions worldwide. This has spurred the adoption of more natural stormwater handling with green infrastructure practices distributed throughout an urban watershed to handle runoff issues at the source. Because urban land costs are high, guidance is needed to better site these installations in order to maximize their effectiveness to meet local drainage needs and contribute to improvements in stream conditions. This project will explore novel methods of urban drainage assessment that account for natural and piped runoff pathways and identify areas that contribute more to stream degradation based on measures of impervious surface connectivity. Methodology will be explored with the guidance of Dr. Tim Fletcher at University of Melbourne and Dr. David McCarthy at Monash University using established spatial datasets that include impervious areas and their connectivity for comparison and validation. Different flowpath weighting schemes will be explored using runoff and water quality datasets and a temporal analysis will focus on the Little Stringybark experimental watershed to assess how changes in impervious connectivity over time associated with green infrastructure installations relate to observed changes in streamflow and water quality. The connectivity of impervious surfaces in urban watersheds has often been represented as binary while it has been acknowledged that connectivity actually exists on a continuum subject to storm-specific characteristics, antecedent moisture conditions, and variable flowpath disconnection. This project will utilize high-resolution spatial data representing elevation, impervious cover, and stormwater drainage networks to establish a relative connectivity index that provides both a landscape-scale weighted metric of imperviousness and spatially explicit information that identifies critical source areas within the urban watershed more closely tied to in-stream measures. Python scripting will employ a grid-based representation of watershed surface cover and runoff flowpaths that will measure connectivity by investigating weighting schema for different portions of the flowpath that runoff takes across the watershed (overland, impervious, piped, in-stream). These weighting schema will be calibrated to optimize the fit of linear models relating the associated landscape metric to in-stream observations, and differences in parameterization between watersheds will be investigated to assess how effectively they represent physical watershed characteristics and runoff transport mechanisms. This will help validate the methodology and provide guidance to establish a tool that can be used on ungauged watersheds to identify areas within any urban watershed that will be best served by green infrastructure installation to decrease impervious connectivity and impart positive changes in-stream through distributed means. This award under the East Asia and Pacific Summer Institutes program supports summer research by a U.S. graduate student and is jointly funded by NSF and the Australian Academy of Science.

雨水通过一个复杂的网络穿越城市流域，渗透到径流和不透水的表面上，这些表面迅速将径流移向溪流。 不透水的区域及其通过排水管连接的程度已被证明在转移流量动态和水质的城市溪流中发挥了最大作用，导致全球条件下降。 这刺激了采用更自然的雨水处理，其绿色基础设施实践分布在整个城市流域，以处理源头的径流问题。 由于城市土地成本很高，因此需要指导以更好地设置这些装置，以最大程度地提高其有效性，以满足当地排水需求并有助于改善流条件。 该项目将探索城市排水评估的新方法，这些方法可以说明自然和管道径流途径，并确定基于不透水的表面连接度量的溪流降解的领域。 将在墨尔本大学的蒂姆·弗莱彻（Tim Fletcher）和莫纳什大学（Monash University）的戴维·麦卡锡（David McCarthy）博士的指导下，使用既定的空间数据集探讨方法，包括不透水领域及其连接性进行比较和验证。 将使用径流和水质数据集探索不同的流道加权方案，时间分析将集中在小的弦域实验流域，以评估与绿色基础设施安装相关的不透水连通性的变化如何与观察到的流量流和水质的变化有关。 城市流域中不透水表面的连通性通常被表示为二进制，而人们已经承认，连通性实际上存在于连续性上，受风暴特异性特征，先进的水分条件和可变流道断开。 该项目将利用代表高程，不透水覆盖和雨水排水网络的高分辨率空间数据来建立一个相对连通性指数，该指数既可以提供景观尺度的加权度量，又是空间上明确的信息，可以在城市水域内识别更多的关键源区域与河流措施紧密相关。 Python脚本将采用分水岭表面覆盖和径流流道的基于网格的表示，通过研究径流横跨流域（陆上，不透水，管道，流通，流中）的流道的不同部分的加权模式来衡量连通性。 将对这些加权模式进行校准，以优化将相关景观指标与流入观测值相关的线性模型的拟合度，并将研究流域之间的参数化差异，以评估它们如何有效地表示它们代表物理水域特征和径流传输机制。 这将有助于验证该方法，并提供指导以建立可以在未加名的分水岭上使用的工具，以识别任何城市流域内最好通过绿色基础设施安装服务的地区，以降低不透水的连接性，并通过分布式式散发积极变化。 在东亚和太平洋夏季学院计划下的该奖项支持美国研究生的夏季研究，并由NSF和澳大利亚科学院共同资助。