FRACAS: a next generation national Flood Risk Assessment under climate ChAnge Scenarios

FRACAS：气候变化情景下的下一代国家洪水风险评估

• 批准号: NE/E002382/1
• 负责人: Nicholas Reynard
• 金额: $ 23.44万
• 依托单位: HR Wallingford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FE002382%2F1
• 关键词: FRACAS; next; generation; national; Flood

This proposed research will develop the new methodology required to make a step-change in our ability to quantify fluvial flood risk at large scales, incorporating climate change. This will combine existing and emerging technologies, to provide national and regional estimates of flood risk based on gridded models for improved assessment of flood risk to recurrence intervals in excess of 50 years. Linking gridded rainfall, runoff, flood defence performance and flood inundation models will significantly improve our ability to assess flood risk from extreme events and explore the potential impacts of climate change, including new scenarios, as they become available from UKCIPnext. This will include a spatially and temporally consistent gridded rainfall model operating over large spatial domains, a high resolution gridded runoff and flow routing model capable of modelling at the national scale and a continuous system analysis of flood inundation, taking account of defence performance. As each of these models will be run continuously in time, a continuous, linked flood risk analysis system will be developed for the first time. Each model will also be able to use derived future changes in climate to produce predictions of future in flood risk. Moreover there will be an assessment of the model and data uncertainties, as well as estimates of uncertainty due to climate change. These uncertainty assessments will include the propagation of uncertainty through the linked modelling system. The research will utilise many existing sources of data and build upon some established models and techniques, such as the Neyman-Scott Rectangular Pulses (NSRP) stochastic rainfall at the University of Newcastle, the CEH Grid-to-Grid (G2G) model, the RASP system models, and the use ensemble scenario sets to represent uncertainty. At the regional or large basin-scale analyses will include a grid-based (5km) rainfall model linked to a (1km) gridded runoff and routing model and associated knowledge of defence systems and new routines developed to translate rainfall to river levels. Such a modelling system is ultimately applicable at a national scale and this will be demonstrated for river flows. The precipitation for this demonstration will be sourced from observed rainfall datasets, or modelled time series, such as those available from RCMs driven with re-analysis data. The impact of future changes in rainfall, runoff and river levels on flood risk will be assessed within an enhanced version of the HR Wallingford RASP HLMplus model. Scenarios of climate change will be derived from a range of both global (GCMs) and regional climate models (RCMs). There will also be an analysis of the application of multi-ensemble climate scenarios and the generation of probabilistic scenarios of change in future flood risk.

这项拟议的研究将开发新的方法，以提高我们大规模量化河流洪水风险的能力，并纳入气候变化。这将结合现有和新兴技术，基于网格模型提供国家和区域洪水风险估计，以改进对超过 50 年复发间隔的洪水风险评估。将网格降雨、径流、防洪性能和洪水淹没模型联系起来，将显着提高我们评估极端事件造成的洪水风险的能力，并探索气候变化的潜在影响，包括 UKCIPnext 提供的新情景。这将包括在大空间域上运行的空间和时间一致的网格降雨模型、能够在国家尺度上建模的高分辨率网格径流和流量演进模型以及考虑防御性能的洪水淹没的连续系统分析。由于每个模型都将及时连续运行，因此将首次开发出连续、链接的洪水风险分析系统。每个模型还能够利用衍生的未来气候变化来预测未来的洪水风险。此外，还将对模型和数据的不确定性进行评估，并对气候变化造成的不确定性进行估计。这些不确定性评估将包括通过链接的建模系统传播不确定性。该研究将利用许多现有的数据源，并建立在一些已建立的模型和技术的基础上，例如纽卡斯尔大学的 Neyman-Scott 矩形脉冲 (NSRP) 随机降雨、CEH 网格到网格 (G2G) 模型、RASP 系统模型以及使用集合场景集来表示不确定性。在区域或大流域尺度的分析将包括基于网格（5公里）的降雨模型，该模型与网格径流和路径模型（1公里）相关联，以及防御系统的相关知识和开发用于将降雨量转换为河流水位的新例程。这样的建模系统最终适用于全国范围，并将针对河流流量进行论证。该演示的降水量将来自观测的降雨数据集或建模时间序列，例如由再分析数据驱动的 RCM 提供的数据。降雨量、径流和河流水位的未来变化对洪水风险的影响将在 HR Wallingford RASP HLMplus 模型的增强版本中进行评估。气候变化情景将源自一系列全球（GCM）和区域气候模型（RCM）。还将分析多集合气候情景的应用以及未来洪水风险变化的概率情景的生成。