Optimising NFM in headwater catchments to protect downstream communities

优化源头流域的 NFM 以保护下游社区

• 批准号: NE/R004587/1
• 负责人: David Milledge
• 金额: $ 36.52万
• 依托单位: Durham University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FR004587%2F1
• 关键词: Optimising; NFM; headwater; catchments; protect

Natural flood risk management (NFM) describes methods of modifying hillslope and catchment runoff through the modification of landscapes to restore natural hydrological behaviour which limits downstream flood risk. This proposal is for a focussed study of NFM benefits associated with wider ecosystem restoration work which is under way across the uplands of the UK. Headwaters comprise 60-80% of the length of most river systems and high slopes and high rainfall mean that they are important areas of hillslope runoff production. Across the UK there are communities which are prone to flash flooding from steep upland catchments. These headwater catchments are relatively small catchments and are areas where extensive upland restoration is occurring and so they are locations where positive impacts of NFM measures are likely to be observed. Vulnerable communities in headwaters are often small and dispersed with land values that rarely justify hard engineering flood defences through standard cost-benefit approaches. If relatively low cost upland restoration approaches can mitigate risk to communities such as this then it will be possible to provide some protection to communities where funding precludes hard engineering approaches.This project will work with project partners Moors for the Future and Greater Manchester, Merseyside and Cheshire Environment Agency who have existing funded NFM work in the southern Pennines to undertake a series of field experiments. These will assess the potential impact of various forms of gully blocking, restoration of Sphagnum cover on moorlands, and establishment of upland woodlands on hillslope runoff production and channel flow. It will also assess the longer term evolution of woodland and gully blocking approaches through the study of mature woodland and well established gully blocked systems. This is an important consideration since investment in NFM works requires confidence in the long term impact of the restoration on runoff and knowledge of any ongoing maintenance costs for the interventions.Installation of NFM schemes to mitigate flood risk requires careful planning and prediction of potential impacts. This project will develop conceptually sophisticated but computationally simple models which can run multiple scenarios in order to assess the catchment wide impacts on runoff of NFM measures implemented to a variety of designs and in a variety of spatial configurations.The model will be developed (with input from project partner CH2M and input from potential users such as EA) and validated using data from the Glossop Brook catchment in Derbyshire which has a history of major flash flooding impacting households in the town of Glossop. The modelling approach will then be used to assess possible NFM interventions in the upland catchments draining to 21 communities at risk on the eastern edge of Greater Manchester. In each of these catchments we will model the optimum configuration of upland restoration measures for NFM benefit.The project will also work with partners (Environment Agency, Natural Resources Wales, Scottish Environmental Protection Agency, International Union the Conservation for Nature) to identify existing headwater flow records across the UK which relate to areas of significant upland restoration. At these sites we will model expected impacts and interrogate the available flow data for evidence of these effects on runoff.The project will work with its range of project partners which span England, Wales and Scotland and which comprise regulators, land managers and industry to develop guidelines to optimise future implementation of NFM measures in headwater catchments across upland Britain.

自然洪水风险管理（NFM）描述了通过修改景观来恢复限制下游洪水风险的自然水文行为，从而修改山坡和集水区径流的方法。这项建议是一个集中的研究NFM的好处与更广泛的生态系统恢复工作，这是正在进行的整个高地的英国。河源占大多数河流系统长度的60-80%，高坡度和高降雨量意味着它们是山坡径流产生的重要区域。在英国各地，有一些社区容易受到陡峭高地集水区的山洪暴发的影响。这些源头集水区相对较小，是正在进行大规模高地恢复的地区，因此，它们是可能观察到NFM措施产生积极影响的地点。上游的脆弱社区往往规模小，分散，土地价值很少能证明通过标准的成本效益方法进行硬工程防洪是合理的。如果相对低成本的高地恢复方法可以减轻风险的社区，如这将是可能的，以提供一些保护社区的资金排除硬工程的approaches.This项目将与项目合作伙伴摩尔人的未来和大曼彻斯特，默西塞德郡和柴郡环境局谁现有的资助NFM工作在南部奔宁山脉进行了一系列的实地实验。这些研究将评估各种形式的沟渠堵塞、高沼地泥炭藓覆盖的恢复以及高地林地的建立对山坡径流和河道流量的潜在影响。它还将通过研究成熟的林地和完善的沟道阻塞系统，评估林地和沟道阻塞方法的长期演变。这是一个重要的考虑因素，因为NFM工程的投资需要对恢复对径流的长期影响有信心，并了解干预措施的任何持续维护成本。安装NFM方案以减轻洪水风险需要仔细规划和预测潜在影响。该项目将开发概念复杂但计算简单的模型，这些模型可以运行多种情景，以评估在各种设计和各种空间配置中实施的NFM措施对径流的全流域影响。（项目合作伙伴CH 2 M的投入和潜在用户（如EA）的投入）并使用来自德比郡Glossop Brook集水区的数据进行验证，该集水区具有影响Glossop镇家庭的重大山洪暴发的历史。然后，该建模方法将用于评估可能的NFM干预措施在高地集水区排水到21个社区在大曼彻斯特东部边缘的风险。在每个集水区，我们将模拟高地恢复措施的最佳配置，以实现NFM效益。该项目还将与合作伙伴（环境署，威尔士自然资源部，苏格兰环境保护局，国际自然保护联盟）合作，以确定英国各地与重要高地恢复地区相关的现有源头流量记录。在这些地点，我们将模拟预期的影响，并询问现有的流量数据，以获得这些影响对径流的证据。该项目将与其范围内的项目合作伙伴，包括英格兰，威尔士和苏格兰的监管机构，土地管理者和行业制定指导方针，以优化未来在英国高地的源头流域实施NFM措施。

项目成果

Rainfall intensity and catchment size control storm runoff in a gullied blanket peatland

• DOI: 10.1016/j.jhydrol.2022.127688
• 发表时间: 2022-03
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: D. Edokpa;D. Milledge;T. Allott;J. Holden;E. Shuttleworth;M. Kay;A. Johnston;G. Millin-Chalabi;Matt Scott-Campbell;David A Chandler;Jamie L. Freestone;M. Evans

Blanket Peat Restoration: Numerical Study of the Underlying Processes Delivering Natural Flood Management Benefits

• DOI: 10.1029/2020wr029209
• 发表时间: 2020-12
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Salim Goudarzi;D. Milledge;J. Holden;M. Evans;T. Allott;E. Shuttleworth;M. Pilkington;J. Walker

A Generalized Multistep Dynamic (GMD) TOPMODEL

• DOI: 10.1029/2022wr032198
• 发表时间: 2023-01
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Salim Goudarzi;D. Milledge;Joseph Holden

Restoration of blanket peat moorland delays stormflow from hillslopes and reduces peak discharge

• DOI: 10.1016/j.hydroa.2018.100006
• 发表时间: 2019-01
• 期刊: Journal of Hydrology X
• 影响因子: 4
• 作者: E. Shuttleworth;M. Evans;M. Pilkington;T. Spencer;J. Walker;D. Milledge;T. Allott