Where the runoff begins: rethinking the role of impervious area in urban stormwater management

有关分水岭不透水的信息已被广泛用于评估城市化对水文和环境的影响，开发城市水文和水质模型，以及设计从排水收费到绿色基础设施等各种雨水管理战略。流域防渗的描述依赖于总防渗面积和有效防渗面积的概念。这两种措施都是集中和静态的措施，强调不透水的程度，但它们缺乏对各种不透水表面的空间模式的考虑。这种知识差距影响了水文模型的可靠性，这些模型倾向于将透水和不透水表面概念化为两个没有相互作用的集中组件。本项目旨在回答：1)不透水表面的空间非均质性和水文连通性如何影响城市小流域的雨水径流？2)对这一机制的理解如何有助于雨水径流的模拟？该项目将雨水径流的不透水源区(ISA)概念化为恒定成分和动态成分的组合，其水文连通性受透水表面的影响。研究方法强调使用小型无人驾驶飞机系统(UAS)进行土地复盖分类和厘米级空间分辨率的流向分析。利用南得克萨斯州的Corpus Christi作为城市实验室，该项目的工作将包括三个阶段的七项相互关联的研究任务，从空中和地面数据收集开始，过渡到通过综合地理空间-水文框架逐步确定ISA的特征，并最终开发可在不同级别利用遥感数据的新的三要素综合网络模型。该项目的研究结果将在空间上清楚地了解不透水表面对雨水径流过程的影响，并为制定可靠的雨水管理策略提供更好的科学依据。本科生将被纳入研究团队。TAMU-CC是一所主要为少数族裔服务的大学，该项目将为这些项目中的URM本科生和研究生提供各种培训和学习机会，这将满足德克萨斯州水资源和土木工程领域的劳动力需求。该项目团队将参加TAMU-CC的UAS夏令营项目，该项目旨在培训当地高中生，并促进他们对与UAS研究相关的STEM领域的兴趣。该项目的科学数据和工具将通过利用网络地理信息系统和谷歌地球应用编程接口技术开发的互动在线平台传播。项目组将制作一套视频，介绍无人机和遥感在工程水文学和雨水管理中的使用。该项目团队将与科珀斯克里斯蒂市政府合作，加强其雨水教育计划。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Information on watershed imperviousness has been widely used for assessing the hydrologic and environmental impacts of urbanization, developing urban hydrologic and water quality models, and designing stormwater management strategies ranging from drainage charge to green infrastructure across the world. The description of watershed imperviousness has relied on the concepts of total impervious area and effective impervious area. Both of these are lumped and static measures that emphasize the extent of imperviousness, but they lack consideration of the spatial pattern of various impervious surfaces. This knowledge gap affects the reliability of hydrologic models that tend to conceptualize pervious and impervious surfaces as two lumped components with no interactions. This project aims to answer: 1) How do spatial heterogeneity and hydrologic connectivity of impervious surfaces affect stormwater runoff in small urban watersheds? 2) How can the understanding of this mechanism benefit the modeling of stormwater runoff? This project conceptualizes the impervious source area (ISA) of stormwater runoff as a combination of a constant component and a dynamic component with its hydrologic connectivity affected by pervious surfaces. The research methods highlight the use of small uncrewed aircraft systems (UAS) in land cover classification and flow direction analysis with centimeter-level spatial resolution. Using Corpus Christi in south Texas as an urban laboratory, the project efforts will consist of seven interlinked research tasks across three phases, starting with aerial and ground data collection, transitioning into the progressive characterization of ISA through an integrated geospatial-hydrologic framework, and culminating in the development of a new three-component CN model that can utilize remote sensing data at different levels. The findings of this project will lead to a spatially explicit understanding of the effect of impervious surfaces on stormwater runoff processes and provide an improved scientific basis for developing reliable stormwater management strategies. Undergraduate students will be integrated into the research team. TAMU-CC is a predominantly minority serving university and this project will provide URM undergraduate and graduate students in these programs with a variety of training and learning opportunities, which will serve TX workforce needs in the areas of water resources and civil engineering. The project team will participate in TAMU-CC's UAS Summer Camp program that aims to train local high school students and promote their interest in STEM fields related to UAS research. Scientific data and tools of this project will be disseminated through an interactive online platform developed using WebGIS and Google Earth API techniques. The project team will produce a set of videos to introduce the use of UAS and remote sensing in engineering hydrology and stormwater management. The project team will collaborate with the City of Corpus Christi to enhance its stormwater education program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.