Susceptibility of catchments to INTense RAinfall and flooding (SINATRA)

集水区对强降雨和洪水的敏感性 (SINATRA)

• 批准号: NE/K00896X/1
• 负责人: Hannah Cloke
• 金额: $ 163.3万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FK00896X%2F1
• 关键词: Susceptibility; catchments; INTense; RAinfall; flooding

Project SINATRA responds to the NERC call for research on flooding from intense rainfall (FFIR) with a programme of focused research designed to advance general scientific understanding of the processes determining the probability, incidence, and impacts of FFIR.Such extreme rainfall events may only last for a few hours at most, but can generate terrifying and destructive floods. Their impact can be affected by a wide range factors (or processes) such as the location and intensity of the rainfall, the shape and steepness of the catchment it falls on, how much sediment is moved by the water and the vulnerability of the communities in the flood's path. Furthermore, FFIR are by their nature rapid, making it very difficult for researchers to 'capture' measurements during events. The complexity, speed and lack of field measurements on FFIR make it difficult to create computer models to predict flooding and often we are uncertain as to their accuracy. To address these issues, NERC launched the FFIR research programme. It aims to reduce the risks from surface water and flash floods by improving our identification and prediction of the meteorological (weather), hydrological (flooding) and hydro-morphological (sediment and debris moved by floods) processes that lead to FFIR. A major requirement of the programme is identifying how particular catchments may be vulnerable to FFIR, due to factors such as catchment area, shape, geology and soil type as well as land-use. Additionally, the catchments most susceptible to FFIR are often small and ungauged.Project SINATRA will address these issues in three stages: Firstly increasing our understanding of what factors cause FFIR and gathering new, high resolution measurements of FFIR; Secondly using this new understanding and data to improve models of FFIR so we can predict where they may happen - nationwide and; Third to use these new findings and predictions to provide the Environment Agency and over professionals with information and software they can use to manage FFIR, reducing their damage and impact to communities. In more detail, we will:1. Enhance scientific understanding of the processes controlling FFIR, by-(a) assembling an archive of past FFIR events in Britain and their impacts, as a prerequisite for improving our ability to predict future occurrences of FFIR.(b) making real time observations of flooding during flood events as well as post-event surveys and historical event reconstruction, using fieldwork and crowd-sourcing methods.(c) characterising the physical drivers for UK summer flooding events by identifying the large-scale atmospheric conditions associated with FFIR events, and linking them to catchment type.2. Develop improved computer modelling capability to predict FFIR processes, by-(a) employing an integrated catchment/urban scale modelling approach to FFIR at high spatial and temporal scales, modelling rapid catchment response to flash floods and their impacts in urban areas.(b) scaling up to larger catchments by improving the representation of fast riverine and surface water flooding and hydromorphic change (including debris flow) in regional scale models of FFIR.(c) improving the representation of FFIR in the JULES land surface model by integrating river routing and fast runoff processes, and performing assimilation of soil moisture and river discharge into the model run.3. Translate these improvements in science into practical tools to inform the public more effectively, by-(a) developing tools to enable prediction of future FFIR impacts to support the Flood Forecasting Centre in issuing new 'impacts-based' warnings about their occurrence.(b) developing a FFIR analysis tool to assess risks associated with rare events in complex situations involving incomplete knowledge, analogous to those developed for safety assessment in radioactive waste management.In so doing SINATRA will achieve NERC's science goals for the FFIR programme.

Sinatra项目对NERC的呼吁进行了对洪水泛滥（FFIR）的研究的呼吁，该计划旨在提高对确定FFIR的概率，发病率和影响的过程的一般科学理解。极端的降雨事件最多只能持续几个小时，但可以产生恐怖和破坏性的洪水。它们的影响可能会受到广泛的因素（或过程）的影响，例如降雨的位置和强度，其流域的形状和陡度落在，水被水以及洪水路径中社区的脆弱性移动了多少沉积物。此外，FFIR本质上是迅速的，因此研究人员很难在事件期间“捕获”测量。 FFIR上的复杂性，速度和缺乏现场测量使得难以创建计算机模型来预测洪水，并且通常不确定它们的准确性。为了解决这些问题，NERC启动了FFIR研究计划。它的目的是通过改善我们对气象（天气），水文（洪水）和水型（洪水泛滥和碎屑）的识别和预测来降低地表水和山洪的风险，从而降低了我们的气象（天气），水文（洪水）和水力形态学（沉积物和碎屑）。该计划的主要要求是确定由于集水区，形状，地质和土壤类型以及土地利用等因素，特定的集水区如何容易受到FFIR的影响。此外，最容易受到FFIR的流域通常很小且不受欢迎。项目Sinatra将在三个阶段解决这些问题：首先，我们对哪些因素引起FFIR并收集新的，高分辨率的FFIR测量；其次，使用这种新的理解和数据来改善FFIR的模型，以便我们可以预测它们在全国范围内发生的情况以及；第三使用这些新发现和预测为环境机构和专业人士提供他们可以用来管理FFIR的信息和软件，从而减少了他们对社区的损害和影响。更详细地说，我们将：1。增强对控制FFIR的过程的科学理解，by-（a）组装过去的FFIR事件的档案及其影响及其影响，作为提高我们预测FFIR未来发生的能力。（b）对实时的洪水事件进行实时观察，并在事件发生后进行了暑期和历史事件的夏季进行临床和临床效果。通过识别与FFIR事件相关的大规模大气条件，并将其与集水型型相关联，洪水事件。2。 （a）开发改进的计算机建模能力以预测FFIR过程，在高空间和时间尺度上使用集成的集水区/城市尺度建模方法对FFIR进行FFIR，建模对山洪泛滥的快速集水区响应及其在城市地区的影响。（b）通过提高较大的集水区和水范围的水平变化（包括较大的水流量表）（b），将水或水范围的变化（包括）变化（ （c）通过整合河流路线和快速径流过程，并将土壤水分和河流排放量同化为模型运行3。 （a）开发工具，将这些改进的这些改进转化为实用工具，以更有效地向公众告知公众，以预测FFIR的影响，以支持洪水预测中心发出新的“基于影响的”警告。将实现FFIR计划的NERC科学目标。

项目成果

Diagnosing links between atmospheric moisture and extreme daily precipitation over the UK

诊断英国大气湿度和极端每日降水之间的联系

• DOI: 10.1002/joc.4547
• 发表时间: 2015
• 期刊: International Journal of Climatology
• 作者: Allan R

Characterising flash flood response to intense rainfall and impacts using historical information and gauged data in Britain

• DOI: 10.1111/jfr3.12187
• 发表时间: 2018-01-01
• 期刊: JOURNAL OF FLOOD RISK MANAGEMENT
• 影响因子: 4.1
• 作者: Archer, D. R.;Fowler, H. J.
• 通讯作者: Fowler, H. J.

Do floods cause more loss of life from the peak or from their rate of rise

洪水造成的生命损失是从高峰期还是上涨率增加？

• 发表时间: 2014
• 期刊: BHS Circulation
• 作者: Archer DR

Atmospheric precursors for intense summer rainfall over the United Kingdom

• DOI: 10.1002/joc.6431
• 发表时间: 2020-01
• 期刊: International Journal of Climatology
• 作者: R. Allan;S. Blenkinsop;H. Fowler;Adrian J. Champion

Advances in understanding large-scale responses of the water cycle to climate change

• DOI: 10.1111/nyas.14337
• 发表时间: 2020-04-04
• 期刊: ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
• 影响因子: 5.2
• 作者: Allan, Richard P.;Barlow, Mathew;Zolina, Olga
• 通讯作者: Zolina, Olga