CAREER: Sedimentary signatures of large riverine floods to constrain risk and build resiliency

职业：利用大型河流洪水的沉积特征来限制风险并增强抵御能力

• 批准号: 2236920
• 负责人: Samuel Munoz
• 金额: $ 71.84万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236920&HistoricalAwards=false
• 关键词: CAREER; Sedimentary; signatures; large; riverine

Rivers represent critical economic corridors and refuges for biodiversity, but infrastructure and ecosystems in floodplains remain vulnerable to flooding and erosion. This project will improve flood hazard assessments for lowland rivers by understanding and harnessing fluvial dynamics, thus improving the safety and sustainability of river management science. A research plan focusing on observing and simulating floodplain sedimentation to improve flood hazard assessments is coupled with an education and outreach plan that broadens participation in geomorphology and redefines rivers as dynamic features that provide beneficial services to people and ecosystems. The research tests hypotheses describing controls on fluvial sedimentation that are critical for predicting and managing the accumulation of pollutants and sediments for floodplain management and restoration. A diverse geoscience workforce and public engagement are critical for the long-term move towards equitable and sustainable river management, and this project is expressly designed to broaden participation in Earth sciences through immersive research experiences for community college students and to elevate public awareness of fluvial dynamics through K-12 initiatives.The traditional paradigm in lowland river and floodplain management relies almost exclusively on systematic stream gage data as the key dataset informing flood hazard assessments, while largely neglecting the geomorphic dynamics and resulting sedimentary records preserved in floodplains. This project builds on the PI’s prior work in the development and application of alluvial stratigraphic records by harnessing recent advances in hydraulic modeling to constrain flood hazard assessments via robust paleoflood estimates. The research objectives are to (1) establish a long-term observatory to monitor floodplain sedimentation, (2) develop hydraulic model simulations on modern and theoretical floodplain geometries, and (3) integrate models and observations of sedimentation to link streamflow to sedimentation patterns in a dynamic alluvial setting. The research plan leverages state-of-the-art hydraulic modeling with an observational network of environmental sensors and sediment cores to test a series of hypotheses describing the landscape controls on alluvial sedimentation patterns, and then it applies the findings to constrain flood hazard assessments through high precision paleoflood estimates. This research is integrated with an education and outreach plan designed to (1) attract, motivate, and train community college students in geoscience research through an established internship program, and (2) develop a platform for raising public awareness of dynamic fluvial processes through K-12 initiatives. This award is co-funded by the Geomorphology & Land-use Dynamics and Hydrologic Sciences programs.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.

河流是重要的经济走廊和生物多样性的避难所，但洪泛区的基础设施和生态系统仍然容易受到洪水和侵蚀的影响。该项目将通过了解和利用河流动力学，改善对低地河流的洪水灾害评估，从而提高河流管理科学的安全性和可持续性。一项研究计划的重点是观察和模拟洪泛区沉积，以改善洪水灾害评估，同时还有一项教育和宣传计划，扩大对地貌学的参与，并将河流重新定义为人类和生态系统提供有益服务的动态特征。该研究测试了描述河流沉积控制的假设，这些假设对于预测和管理污染物和沉积物的积累以进行河漫滩管理和恢复至关重要。多样化的地球科学工作队伍和公众参与对于长期实现公平和可持续的河流管理至关重要，该项目旨在通过社区大学生的沉浸式研究体验来扩大对地球科学的参与，并通过K提高公众对河流动力学的认识，12.低地河流和洪泛区管理的传统模式几乎完全依赖于系统的河流水位计数据，将其作为洪水灾害评估的关键数据集，而在很大程度上忽略了地貌动力学和由此产生的沉积记录保存在洪泛平原。该项目建立在PI先前在冲积地层记录的开发和应用方面的工作基础上，利用水力建模的最新进展，通过强大的古生物学估计来约束洪水灾害评估。研究目标是：（1）建立一个长期观测站，以监测洪泛区的沉积情况;（2）开发现代和理论洪泛区几何形状的水力模型模拟;以及（3）整合沉积模型和观测结果，将水流与动态冲积环境中的沉积模式联系起来。该研究计划利用最先进的水力建模与环境传感器和沉积物岩心的观测网络来测试一系列描述冲积沉积模式的景观控制的假设，然后将研究结果应用于通过高精度的古植被估计来约束洪水灾害评估。这项研究与教育和推广计划相结合，旨在（1）通过既定的实习计划吸引，激励和培训社区大学生进行地球科学研究，（2）通过K-12计划开发一个平台，提高公众对动态河流过程的认识。 该奖项由地貌学、土地利用动力学和水文科学项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。