RAPID: Patterns of Fluvial Sedimentation and Geomorphic Change Following an Extreme Flood Event

RAPID：极端洪水事件后河流沉积和地貌变化的模式

• 批准号: 1615154
• 负责人: Allan James
• 金额: $ 4.93万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1615154&HistoricalAwards=false
• 关键词: RAPID; Patterns; Fluvial; Sedimentation; Geomorphic

NATIONAL SCIENCE FOUNDATIONGEOGRAPHY SPATIAL SCIENCES (GSS) PROGRAMABSTRACT1615154Allan JamesJohn KupferUniversity of South CarolinaThis rapid-response research project will delineate and quantify the effects of large floods that occurred in early October 2015 on numerous rivers and streams in South Carolina. Extreme flooding generates considerable erosion and sedimentation and provides an excellent opportunity to study how a severe flood can modify channels and floodplains. The ephemeral data collected soon after the flooding ended will improve basic understanding of sediment transport and deposition dynamics during these large, rare floods as well as their importance in the sedimentary record. In particular, the duration of stream power above a threshold value will help predict where and how much bank and floodplain erosion will occur and when the rates of change in stream power will coincide with patterns of sedimentation. Project findings will enhance basic understanding of the magnitude and nature of geomorphic adjustments to large floods. They will help guide policy makers at city, county, state and federal levels and at local watershed associations, and they will enable research scientists to develop more effective watershed management plans for urban streams. The project also will guide the development of graduate and undergraduate students from underrepresented groups in science and engineering and will build STEM capacity by incorporating undergraduate and graduate students into the research process through their involvement in field-based data collection and analytical procedures.The researchers will investigate the use of longitudinal variations in unit stream power and stream gradient index (SGI) as potential indicators for reach-scale changes in sediment flux that identify sites that are vulnerable to future flooding. Using state-of-the-art mapping techniques including global positioning systems (GPS), unmanned aerial vehicles (UAVs), and light detection and ranging (LiDAR), the investigators will map and measure channel adjustments to test theories, explain patterns, and develop predictive models of river erosion and sedimentation. While modern mapping technologies will help identify, locate, and recognize patterns of channel and floodplain change, UAVs will acquire low-altitude aerial imagery, which will be used with "structure-from-motion" (SfM) photogrammetric techniques to develop high-resolution, large-scale maps of selected sites. Spatial patterns of erosion and sedimentation measured by these methods will be compared with patterns predicted by analysis of stream power to test theories based on the duration of critical power and spatial changes in stream power. Improvement in the ability to predict channel erosion and deposition and subsequent changes in flood stages has enormous socioeconomic implications that will help guide future flood-mitigation efforts.

地理学空间科学（GSS）计划战略1615154南卡罗来纳大学的艾伦·詹姆斯·约翰·库普弗这个快速反应研究项目将描述和量化2015年10月初发生的大洪水对南卡罗来纳州众多河流和溪流的影响。 极端洪水会产生相当大的侵蚀和沉积，并提供了一个很好的机会来研究严重的洪水如何改变渠道和洪泛区。洪水结束后不久收集的短暂数据将提高对这些大型罕见洪水期间沉积物输运和沉积动力学及其在沉积记录中的重要性的基本了解。 特别是，超过阈值的流功率的持续时间将有助于预测在哪里和多少银行和河漫滩侵蚀将发生，以及流功率的变化率何时将与沉积模式相一致。 项目研究结果将增进对大洪水地貌调整的规模和性质的基本了解。 它们将帮助指导市、县、州和联邦各级以及地方流域协会的决策者，并使研究科学家能够为城市河流制定更有效的流域管理计划。 该项目还将指导来自理工科代表性不足群体的研究生和本科生的发展，并将通过让本科生和研究生参与实地数据收集和分析程序，将他们纳入研究过程，以建立STEM能力。研究人员将调查单位水流功率和水流梯度指数（SGI）纵向变化的使用情况。作为沉积物通量范围变化的潜在指标，确定未来易受洪水影响的地点。 使用最先进的测绘技术，包括全球定位系统（GPS），无人机（UAV）和光探测和测距（LiDAR），调查人员将绘制和测量河道调整，以测试理论，解释模式，并开发河流侵蚀和沉积的预测模型。 虽然现代测绘技术将有助于识别、定位和识别河道和洪泛区变化的模式，但无人机将获得低空航空图像，这些图像将与“运动恢复结构”（SfM）摄影测量技术一起使用，以开发选定地点的高分辨率、大比例尺地图。将通过这些方法测量的侵蚀和沉积的空间模式与通过分析流功率预测的模式进行比较，以测试基于临界功率持续时间和流功率空间变化的理论。 提高预测河道侵蚀和沉积以及洪水阶段后续变化的能力具有巨大的社会经济意义，这将有助于指导未来的防洪工作。