Is the whole greater than the sum of its parts? Assessing the combined effect of multiple natural flood management features on downstream flooding.

在英国，河流洪水是一个日益严重的问题，每年都威胁着基础设施和生计。为了减少河流泛滥的影响，通常在河流系统的下游和上游地区采取综合管理措施。这些包括防洪堤和其他类型的工程防御，以防止河流漫顶或减少其在城市地区关键点的破坏性影响。此外，在源头地区采取较小的干预措施有助于减缓河道上游地区的流量，从而减轻下游防洪堤的压力。这些源头干预措施通常选择自然洪水管理特征，这些特征是与自然水文和形态过程一起管理洪水的土地管理技术。这些干预措施提供了一种可能性，以减少径流峰值和管理其timing.The功能和个人的自然洪水管理功能的影响进行了广泛的研究，在最近几年。然而，人们对不同特征如何协同工作、它们对下游的影响有多远以及它们对下游洪水的累积影响知之甚少。通过管理不同支流的时间和贡献，可以优化多个特征的累积效应，以获得最大的下游效益。然而，支流贡献通常难以用洪水预报中使用的常见水文模型来约束。由于不同事件的前期条件和降水强度不同，不同的子集水区/支流可能在不同事件期间被激活到不同程度。因此，一个更好的约束子流域的贡献下游flooding.The项目的目标是量化的贡献，从各种子流域和他们的时间可以通过自然洪水管理干预措施进行调节，解决以下研究问题：1）如何自然洪水管理功能影响旅行和响应时间通过集水区有潜力提高模型predictions. The项目？2)我们能否通过估算支流的相对贡献及其时间来改善下游洪水的预测？该项目结合了实地工作、数值分析和流域建模，以评估水的传播和响应时间，并估计众多自然洪水管理特征对下游洪水的累积影响。来自支流的相对贡献及其时间在控制大洪水方面发挥着重要作用，但这些通常难以用洪水预报中使用的常见水文模型来约束。这样做的一种方法是通过响应时间估计和端元混合分析的基础上，天然示踪剂信号，这可以提供上，下游流量过程的子集水区的贡献的下限。这个博士项目将使用自然溶质的信号来评估支流对下游洪水的贡献，以及它们如何作为先决条件的函数而变化（降雨事件之前集水区的干湿程度如何？），事件特征（降雨量和持续时间？），季节效应（有多少植被？）。为此，现有的模型模拟不同的支流洪水的贡献的相互作用将扩大到包括响应时间和支流的贡献估计。

Flooding from rivers is an increasing problem in the UK which threatens infrastructure and livelihoods every year. To reduce the effect of river flooding, a combination of management interventions in downstream and upstream regions of the river systems is typically used. These consist of flood barriers and other types of engineered defences to prevent overtopping of rivers or reduce their damaging effect at the critical points in urban areas. In addition, smaller interventions in the headwater regions can help to slow down the flow in the upstream regions of the river course, and thus reduce the pressure on the downstream flood barriers. Natural flood management features are often chosen for these headwater interventions, which are land management techniques that work with natural hydrological and morphological processes to manage flooding. These interventions provide a possibility to reduce runoff peaks and manage their timing.The functioning and effect of individual natural flood management features have been studied extensively in recent years. However, less is known about how different features work in concert, how far down stream they have an impact and about their cumulative effect on downstream flooding. By managing the timing and contributions from different tributaries, the cumulative effect of several features together may be optimised for the greatest downstream benefit.However, tributary contributions are often difficult to constrain with common hydrological models used in flood forecasting. Since antecedent conditions and precipitation intensities vary from event to event, different sub-catchments /tributaries may be activated to different degrees during different events. Consequently, a better constraint of sub-catchment contributions to downstream flooding has the potential to improve model predictions.The project aims to quantify how the contributions from various sub-catchments and their timing can be regulated through natural flood management interventions, by addressing the following research questions:1) How do natural flood management features affect travel and response times through the catchment?2) Can we improve the prediction of downstream flooding through the estimation of relative contributions from tributaries and their timing?The project combines field work, numerical analysis and catchment modelling to assess travel and response times of water, and estimate the cumulative effect of numerous natural flood management features on downstream flooding. The relative contributions from tributaries and their timing plays a substantial role in controlling large floods, but these are often difficult to constrain with common hydrological models used in flood forecasting. One way of doing this is through response time estimations and end-member mixing analyses based on natural tracer signals, which can provide upper and lower bounds of sub-catchment contributions on downstream flow processes. This PhD project will use the signals of natural solutes to assess tributary contributions to downstream flooding and how they vary as a function of antecedent conditions (how dry or wet is the catchment before the rain event?), event characteristics (how much does it rain and for how long?), and seasonal effects (how much vegetation is there?). For this purpose, an existing model simulating the interactions of different tributary contribution to flooding will be expanded to incorporate estimates of response times and tributary contributions.