Quantifying the effectiveness of natural flood management in lowland

量化低地自然洪水管理的有效性

• 批准号: 2105474
• 金额: --
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2105474
• 关键词: Quantifying; effectiveness; natural; flood; management

Further calls for the inclusion of natural solutions in flood alleviation schemeswere made following the severe floods in Cumbria, December 2015. NaturalFlood Management (NFM) has emerged over the last decade as a very usefuland sustainable approach. It involves the adoption of a multitude of measuresthat mitigate flooding by restoring or enhancing natural processes in upstreamcatchment areas. Evidence of the effectiveness of NFM in flood riskmanagement is limited. Therefore, the overall aim of this project is to monitora range of NFM interventions and evaluate their functioning in space and time.This will provide the information needed by numerical modellers to assesstheir effectiveness at a range of scales. More specifically the objectives of thisproject would be to: (1) monitor the functioning of NFM interventions bothindividually and in combination for a range of event magnitudes and antecedent conditions; (2) define floodhydrograph metrics and determine the potential of interventions to mitigate specific flood characteristics (e.g.peak flow, peak level, flood duration, rate of rise); (3) consult numerical modellers to translate measurements ofhydraulic and hydrological intervention functioning into useable parameters (e.g. roughness and storage indices);(4) interpret and communicate measurements of intervention functioning to a wide range of stakeholders; and (5)consider the sustainability of interventions and their potential in mitigating future environmental change. Thisproject benefits from the unique opportunity to monitor the effectiveness of interventions being implemented aspart of the first Thames Basin NFM trial in the Evenlode catchment. This is a 5 year trial (2016 to 2021) beingco-ordinated by the Evenlode Catchment Partnership. The potential of using citizen science to enhance themonitoring of interventions will be considered. This project will compliment previous NFM modelling studiesand benefit from alignment with current initiatives. A range of novel monitoring techniques will be used tomonitor intervention functioning (e.g. Unmanned Aerial Vehicle (UAV) photography and a remote controlledsurveying boat).

2015年12月坎布里亚郡发生严重洪灾后，人们进一步呼吁将自然解决方案纳入防洪计划。自然洪水管理（NFM）在过去十年中作为一种非常有用和可持续的方法出现。它涉及采取多种措施，通过恢复或加强上游集水区的自然进程来减轻洪水。NFM在洪水风险管理中的有效性的证据是有限的。因此，本项目的总体目标是监测一系列非森林管理干预措施，并评估其在空间和时间上的作用，这将为数值建模者提供所需的信息，以评估其在一系列尺度上的有效性。更具体地说，本项目的目标是：（1）监测NFM干预措施在一系列事件量级和先前条件下的单独和组合功能;（2）定义洪水过程线指标，并确定干预措施缓解特定洪水特性的潜力（如洪峰流量、洪峰水位、洪水持续时间、上涨率）;（3）咨询数值模拟人员，将水力和水文干预功能的测量结果转化为可用参数（如粗糙度和储存指数）;（4）解释并向广泛的利益攸关方通报干预措施运作的测量结果;（5）考虑干预措施的可持续性及其在缓解未来环境变化方面的潜力。该项目受益于独特的机会，以监测干预措施的有效性正在实施的一部分，第一泰晤士河流域NFM试验在Evenlode集水区。这是一项为期5年的试验（2016年至2021年），由Evenlode流域合作伙伴关系协调。将考虑利用公民科学来加强对干预措施的监测的潜力。该项目将补充以前的NFM建模研究，并受益于与当前举措的一致性。一系列新的监测技术将用于监测干预功能（例如无人机摄影和遥控测量船）。