Land use changes, landscape modifications and changing climate have resulted in local to regional flood risk increases in recent decades. As an alternative to traditional engineering approaches, there has been a movement towards catchment-based flood risk management, a subset of which is natural flood management (NFM). NFM aims to enhance flood resilience through the slowing and storing of runoff and flow, based on the restoration and augmentation of hydrological and morphological catchment features. However, despite research highlighting their potential benefits, there is a limited quantity of robust and science-based empirical evidence on how these structures function in the landscape and their efficacy in reducing flood hazards. To address this knowledge gap and contribute to the growing NFM evidence base, this study evaluates the efficacy of offline water storage ponds for flow attenuation. Two contrasting pond sites in the Tone and Parrett catchment headwaters (SW-England) were monitored from April 2018 to December 2020 for channel flow, pond volume, and rainfall. Field-scale, high resolution (1.61 cm spatial support) digital elevation models from Structure-from-Motion and manual surveys were collected to quantify pond dynamics and connectivity. A comprehensive, storm definition methodology was developed for event separation, to enable quantification of the impact of pond behaviour on stream flow, across storm hydrographs. Results show that where offline ponds function as designed, with direct pond filling from the channel, peak flow attenuation can reach 7% (maximum event AEP of 83%). Smaller events, where pond filling occurs directly from rainfall or runoff display only a maximum of 3% peak flow reduction (event AEP from 83% –>99%). The ability of ponds to attenuate flow is heavily reliant on sufficient structural conditions for ponds to fill directly from the channel and to drain slowly following event peaks. This study provides an empirical database for future NFM applications, including key criteria for future design and for use as observational data in modelling applications, by upscaling the efficacy of ponds to reduce flood impacts at larger scales.

中文翻译：

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评估离线蓄水池对自然洪水管理的功效

近几十年来，土地利用变化、景观改造和气候变化导致局部到区域的洪水风险增加。作为传统工程方法的替代方案，已经转向基于流域的洪水风险管理，其中的一个子集是自然洪水管理 (NFM)。NFM 旨在通过减缓和储存径流和流量来增强洪水恢复力，基于水文和形态集水特征的恢复和增强。然而，尽管研究强调了它们的潜在好处，但关于这些结构如何在景观中发挥作用以及它们在减少洪水灾害方面的功效的可靠和基于科学的经验证据数量有限。为了解决这一知识差距并为不断增长的 NFM 证据库做出贡献，本研究评估了离线蓄水池对流量衰减的功效。从 2018 年 4 月到 2020 年 12 月，对 Tone 和 Parrett 集水区源头 (SW-England) 中两个对比鲜明的池塘地点进行了河道流量、池塘容积和降雨量监测。收集了来自运动结构和手动调查的现场规模、高分辨率（1.61 厘米空间支持）数字高程模型，以量化池塘动态和连通性。为事件分离开发了一种全面的风暴定义方法，以量化池塘行为对风暴水文过程线中溪流的影响。结果表明，在离线池塘按设计运行的情况下，从渠道直接填充池塘，峰值流量衰减可以达到 7%（最大事件 AEP 为 83%）。较小的活动，其中池塘填充直接来自降雨或径流，仅显示最大 3% 的峰值流量减少（事件 AEP 从 83% -> 99%）。池塘减弱流量的能力在很大程度上依赖于足够的结构条件，以使池塘能够直接从河道注水并在事件高峰后缓慢排水。本研究为未来 NFM 应用提供了一个经验数据库，包括未来设计的关键标准以及用作建模应用中的观测数据，通过提升池塘的功效以减少更大规模的洪水影响。