RAPID: Analysis of the May 2015 Texas Flood with a Connectivity Framework and High Resolution Topography Data

RAPID：使用连接框架和高分辨率地形数据分析 2015 年 5 月德克萨斯州洪水

• 批准号: 1547200
• 负责人: Paola Passalacqua
• 金额: $ 2.26万
• 依托单位: University of Texas at Austin
• 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: 2015-07-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547200&HistoricalAwards=false
• 关键词: RAPID; Analysis; May; 2015; Texas

After four years of severe drought, central Texas experienced massive flooding on 25-26 May 2015. It is now clear that an event of this magnitude had never been recorded before, with monthly precipitation totals reaching 20 inches at several locations. The 25-26 May event alone contributed 10 inches of rain. The number of rivers in flood was enormous as was the spatial extent of the affected areas spanning the entire central portion of Texas from major city centers such as Austin and Houston to smaller towns such as Wimberley and Bastrop. This proposal seeks immediate acquisition of high-resolution topography data using airborne remote-sensing technology to assess the impact of the Memorial Day Floods. The data will be acquired by the National Center for Airborne Laser Mapping at the University of Houston. Data analysis will be conducted at the University of Texas at Austin. The objective of the proposed research is to quantify the hydrological and sedimentological connectivity between river channel and floodplain during this extreme event and its impact on downstream sediment transport. Such knowledge is fundamental for informing sustainable catchment management through better understanding of where erosion and sedimentation will occur during major storm events. The data collected for this project will immediately be made publically available and shared with the engineering community to aid in assessing the structural damage to bridges and dams impacted by the floods. The data will also be used in a case study to train 46 graduate students at a 2015 Summer Institute that is part of the National Flood Interoperability Experiment.The team will test a hypothesis that channel-floodplain connectivity influences downstream sediment transport, and in particular that high channel-floodplain connectivity resulted in reduced downstream sediment transport due to sediment dispersal and storage on the floodplain. To test this hypothesis, the study targets two contrasting areas: the Lower Trinity River--a major meandering river in Texas where sediment transport is the subject of ongoing research, and an urban setting in downtown Austin. Both experienced major flooding conditions during the May 2015 event, but their floodplains are quite different. Analytical work will use the topography analysis tool GeoNet in conjunction with post-flood fieldwork and enhancement of simulation and forecasting models used in the National Flood Interoperability Experiment. The data will be stored in the NSF-funded OpenTopography repository for access by the community at large. Research results will be disseminated through open-access publications and conference presentations, and the tools used as part of the analysis are available to the community in open-source format.

经过四年的严重干旱，德克萨斯州中部在2015年5月25日至26日经历了巨大的洪水。现在很明显，以前从未记录过这种范围的事件，每月降水总数在几个地点达到20英寸。仅5月25日至26日，仅活动就贡献了10英寸的降雨。洪水中的河流数量是巨大的，从奥斯汀和休斯顿等主要城市中心到温伯利和巴斯特罗普等较小城镇，受影响地区的空间范围也是如此。该提案寻求使用空中遥感技术立即获取高分辨率地形数据，以评估阵亡将士纪念日洪水的影响。数据将由休斯顿大学国家空降激光映射中心收购。数据分析将在德克萨斯大学奥斯汀分校进行。 拟议的研究的目的是在这一极端事件中量化河道和洪泛区之间的水文和沉积学连通性及其对下游沉积物运输的影响。通过更好地理解重大风暴事件期间侵蚀和沉淀将在哪里发生侵蚀和沉积，这种知识是为可持续集水管理提供信息的基础。 该项目收集的数据将立即公开提供，并与工程社区共享，以帮助评估洪水影响的桥梁和大坝的结构损害。 该数据还将在案例研究中使用，以培训2015年夏季研究所的46名研究生，该研究所是国家洪水互操作性实验的一部分。该团队将检验一个假设，即通道 - 置换式连接会影响下游沉积物的运输，尤其是在降低了沉积物造成沉积物造成沉积物的高频道连接中，因此由于沉积物的储备而导致的洪水量和洪水造成的洪水泛滥而导致洪水泛滥和洪水泛滥。 为了检验这一假设，该研究针对了两个对比区域：下三位一体河 - 德克萨斯州的主要蜿蜒河流，那里的沉积物运输是正在进行的研究的主题，也是奥斯汀市中心的城市环境。 在2015年5月的活动中，两者都经历了重大的洪水条件，但它们的洪泛区却大不相同。分析工作将与洪水后的现场工作一起使用地形分析工具Geonet，并增强了国家洪水互操作性实验中使用的模拟和预测模型。 数据将存储在NSF资助的Opentography存储库中，以供整个社区访问。研究结果将通过开放式出版物和会议演讲来传播，并且以开源形式向社区提供了用作分析的一部分的工具。