Understanding geomorphic response to hydrological events: filling the data gaps

我们将改进河流泥沙的管理和洪水风险的建模，方法是开发和应用“泥沙工具包”，从地方到集水区尺度描述河床颗粒大小。-英国的洪水强度正在增加，许多河流正变得更加流动，特别是苏格兰的浮华和多沙系统。我们对地貌系统如何对水文事件作出反应和调整的了解主要来自于从航空照片、激光雷达和地图获得的传统形态测量。我们知道，组成沉积物的性质--特别是大小--是地貌系统的关键要素，控制着沉积物的夹带和流动、洪水期间的河道输送以及支持具有生态和经济意义的重要动植物的能力。然而，关于沉积物性质的数据相对稀少，这主要是因为收集这些数据既昂贵又耗时。国家环保总局已将沙洲到集水区尺度的粒度数据的缺乏确定为一个关键的数据差距，限制了他们预测未来河道侵蚀/沉积模式和模拟洪水风险的能力。因此，获得这类数据是一个关键优先事项。--尽管近年来发展了几种基于图像的颗粒测定方法(包括格雷厄姆/赖斯的方法)，但由于对这些方法的选择和使用的指导有限，以及不愿采用新的/未经证实的技术，从业者对这些方法的理解是片面的。如果这些障碍被克服，基于图像的沉积物表征可以显著提高对地貌系统的理解和管理。在这个项目中，我们将开发一个集成的‘沉积物工具包’，包括软件、文档和指南，用于在多个尺度上基于图像的沉积物表征。它将面向没有图像处理方法专业知识的从业者，并以开放源码许可证发布。利用小型无人机获取各种空间尺度/分辨率的数据的能力，我们将收集各种河流环境的不同数据集。已发表的和原创的(例如，使用运动结构衍生的点云)算法将进行测试，以定义针对不同场景的推荐方法矩阵，包括：正在研究的环境的性质；研究的空间和时间分辨率(例如，条形尺度与集水区尺度)；所需数据的性质(例如，砂砾比例与完整的粒度分布)；场地的可访问性；以及可用的资源(资金/人力/技术)。-该工具包将广泛适用于苏格兰、英国和其他地区的河流。我们将使用阿伯丁郡的迪河作为案例，研究纳入分布式粒度数据如何改善河流管理。2015/16年的洪水在那里造成了严重的侵蚀，破坏了肥沃的土地，并威胁到了基础设施(例如阿伯格尔迪城堡)。我们将估计泥沙夹带阈值，并确定泥沙供应、侵蚀和淤积的潜在区域。将制定管理战略，以降低洪水风险，减轻对基础设施的威胁，并保持水文地貌的完整性(根据水框架指令的要求)。然后，我们将探索在其他环境中的应用，在这些环境中，颗粒大小对于理解地貌调整是至关重要的，例如海滩。

We will improve the management of river sediment and modelling of flood risk by developing and applying a 'sediments toolkit' for the characterisation of river bed grain size at local to catchment scales.-Flood intensity is increasing in the UK and many rivers are becoming more mobile, particularly Scotland's flashy and sediment-laden systems. Our understanding of how geomorphic systems respond and adjust to hydrological events comes principally from traditional morphological measurements, obtained from aerial photographs, LiDAR and maps. We know that the nature of the constituent sediments-especially size-is a critical element of geomorphic systems, controlling, for example, entrainment and mobility of sediment, channel conveyance during floods, and the ability to support ecologically and economically important fauna & flora. However, data on sediment properties is relatively sparse, principally because it is expensive and time-consuming to collect.SEPA have identified the lack of grain-size data at bar to catchment scales as a critical data gap, limiting their ability to predict future patterns of channel erosion/deposition and to model flood risk. Obtaining such data is therefore a key priority.-Despite the development of several image-based grain-sizing methods in recent years (including by Graham/Rice), uptake of these methods by practitioners has been partial owing to limited guidance on their selection and use, and a reluctance to adopt new/unproven technologies. If these obstacles are overcome, image-based sediment characterisation could significantly improve understanding and management of geomorphic systems.In this project, we will develop an integrated 'sediments toolkit' consisting of software, documentation and guidance for image-based sediment characterisation at multiple scales. It will be targeted at practitioners without specialist knowledge of image processing methods and released under an Open Source licence.Utilising the ability of small unmanned aircraft to obtain data over a wide range of spatial scales/resolutions, we will collect a heterogeneous dataset for a variety of river environments. Published and original (e.g. using structure-from-motion derived point clouds) algorithms will be tested to define a matrix of recommended methods for different scenarios, including: the nature of the environment being studied; the spatial and temporal resolution of the study (e.g. bar scale vs catchment scale); the nature of the data required (e.g. proportion of sand/gravel vs complete grain-size distribution); the accessibility of the site; and the resources (financial/human/technological) available.-The toolkit will have wide applicability to rivers in Scotland, the UK and beyond. We will use the River Dee, Aberdeenshire-where the 2015/16 floods caused significant erosion, destroying productive land and threatening infrastructure (e.g. Abergeldie Castle)-as a case study of how the incorporation of distributed grain-size data can improve river management. We will estimate sediment entrainment thresholds and identify potentialzones of sediment supply, erosion and deposition. Management strategies will be designed to reduce flood risk, mitigate threats to infrastructure and maintain hydromorphological integrity (as required by Water Framework Directive, WFD). We will then explore applications in other environments where grain size is of fundamental importance for understanding geomorphic adjustment, such as beaches.