Uncertainty Assessments of Flood Inundation Impacts: Using spatial climate change scenarios to drive ensembles of distributed models for extremes

英国探索性气候变化研究表明，极端事件和相关洪水风险的频率可能会增加。鉴于在目前的气候条件下，洪水每年造成的损失超过10亿英镑，气候变化对洪水风险管理产生了重大影响。为了评估这些后果，在一系列温室气体排放情景下，水文和洪水淹没模型与大气模式的降水预估相结合，以产生未来洪水预测。然而，这些基于模型的输入降水场的有效性和不确定性是关键问题，因为它们可能构成水文和水力建模模糊的主要来源。此外，不确定性与水文和淹没模型本身有关，例如，模型能够表示主要的物理过程，并能够唯一地识别将影响未来预测的有效模式因素（参数和任何其他模式变量）。由于所有模型组成部分的非线性相互作用将影响与水文影响评估相关的总不确定性，因此需要对这些不确定性进行全面评估。因此，一个关键和令人兴奋的挑战是描述和量化从气候到水文到洪水淹没模型的不确定性的起源和传播。该项目旨在开发一种新颖的整体建模方法来实现这一目标。我们的重点区域将是塞文河集水区，因为关注当前和未来的洪水风险。具体来说，我们将：(1)通过分析两种对比方法产生的降水场，量化与气候变化水文影响评估相关的“高端”不确定性，并评估这些不确定性如何影响洪水和淹没预测的性质；(2)以完全耦合和动态的方式评估洪水淹没预测的级联建模框架之间和内部的所有不确定性；(3)使用不确定性分析的新技术，包括全球敏感性分析和新的有效的功能相似采样方法，使建模级联中的不确定性的有效评估。(4)评估塞文河流域在未来100年各种气候、土地利用和土壤湿度情景下可能发生的洪水灾害变化。该项目将提供一个有洞察力的科学方法，可用于未来的研究评估，并将英国科学推向一个令人兴奋的、社会和政治上重要的国际研究领域的前沿。

Exploratory climate change studies for the UK indicate that an increase in the frequency of extreme events and associated flood risk is likely. Given that floods cause damage of over £1bn per year under present climatic conditions, climate change bears significant consequences for flood risk management. In order to evaluate these consequences, hydrological and flood inundation models are forced with projections of precipitation from atmospheric models for a range of Greenhouse gas emission scenarios to produce future flood predictions. However the validity and uncertainty of these model-based input precipitation fields are of key concern, as they potentially constitute a major source of ambiguity for hydrological and hydraulic modelling. Additionally, uncertainty is associated with the hydrological and inundation models themselves, such as for example the models ability to represent the dominating physical processes and to uniquely identify effective model factors (parameters and any other model variables) that will shape future forecasts. As the non-linear interaction of all model components will influence the total uncertainty associated with hydrological impact assessments these need to be comprehensively assessed. Therefore, a key and exciting challenge is to describe and quantify the origin and propagation of uncertainty from climate to hydrological to flood inundation models. This project aims to develop a novel holistic modelling approach for doing this. Our region of focus will be the River Severn catchment because of concerns about current and future flood risk. Specifically we will: (1) Quantify the 'top-end' uncertainties associated with climate change hydrological impact assessments by analyzing precipitation fields produced by two contrasting methods and assess how these affect the nature of flood and inundation predictions (2) Evaluate all uncertainties between and within a cascade modeling framework for flood inundation predictions in a fully coupled and dynamic way (3) Use novel techniques of uncertainty analysis including global sensitivity analysis and a new efficient functional similarity sampling approach to enable an effective evaluation of the uncertainties in the modeling cascade. (4) Assess the likely flood hazard change for the River Severn catchment over the next 100 years for various climate, landuse and soil moisture scenarios This project will deliver an insightful scientific methodology which can be used in future research assessments and catapult UK science to the forefront of an exciting, socially, and politically important international research area.