A new approach to navigating uncertainty in climate-related hydrologic risk

对未来局部气候的预测具有很大的不确定性。这部分是因为温室气体的未来排放是不确定的（在某种程度上是不可知的），但主要是因为不同的气候模式模拟了给定强迫下天气的定量和定性变化。评估不确定性的传统方法是使用从多个模型得出的越来越大的情景集合。在极端情况下，UKCP09气候预测基于10，000种情景。边界条件、缩小尺度方法、影响模型的选择和模型参数化增加了额外的不确定性。由这些决策导致的传播不确定性已被概念化为“不确定性级联”（Wilby & Dessai 2010 Weather）。将这样的大数据应用于现实世界的风险评估和适应决策以及面对这一“不确定性怪物”的态度可能具有挑战性（货车der Sluijs 2005年《水科学》）。Technol.）是多种多样的导航不确定性的级联是一项压倒性的任务（Smith et al 2018 J. Extreme Events），越来越多的人呼吁采用新的方法来组织气候风险信息，以便更好地与政策需求保持一致（例如Kennel et al. 2016 Science）。其中一种方法开发并使用少量的“故事情节”来降低风险（Clark等人，2016年Curr。爬变更代表）。故事情节是一条看似合理的路径，没有任何先验概率。故事情节的好处是可以进行端到端的定量分析，从而纳入复合风险，这在面对级联的不确定性时很难在概率框架内做到。故事情节也容易让外行人理解，因此为政策竞技场的交流提供了一种自然语言。拟议的概念是导航级联的不确定性，以分析和约束系统组件对干旱风险的气候影响，并制定明确的风险故事情节（详见第1d节）。故事情节的发展将描述与干旱发生有关的气候的全部潜在变化（例如连续干旱冬季的频率变化，以及冬季补给季节开始的延迟）。英国气候预测2018（UKCP18）将包含全球，区域和国家尺度的概率预测以及模拟集合。在这个项目中，利用阅读大学和生态与水文中心主管的专门知识，故事情节方法将应用于这些气候预测，并通过水文模型传播。与Anglian Water合作，这些结果将应用于水资源和水库产量模型，以测试当前的水资源管理计划，并进行干旱风险评估。这项工作有可能通过干旱风险管理计划在盎格鲁地区的政策直接应用，并可以提供广泛的可转让的方法，以帮助更好地管理气候变化对整个英国干旱风险的影响。

Projections of future climate at the local scale are highly uncertain. This is partly because future emissions of greenhouse gases are uncertain (and to a degree unknowable), but largely because different climate models simulate quantitatively and qualitatively different changes in weather for a given forcing. The conventional approach to assessing uncertainty has been to use increasingly large ensembles of scenarios derived from multiple models. At the extreme, the UKCP09 climate projections are based on 10,000 scenarios. Additional uncertainty is added by boundary conditions, downscaling methods, choice of impacts models and model parameterization. The propagating uncertainties that result from these decisions has been conceptualized as the "cascade of uncertainty" (Wilby & Dessai 2010 Weather). It can be challenging to apply such big data to real-world risk assessments and adaptation decisions, and attitudes to confronting this "uncertainty monster" (Van der Sluijs 2005 Water Sci. Technol.) are varied. Navigating the cascade of uncertainty is an overwhelming task (Smith et al 2018 J. Extreme Events), and there are increasing calls for new approaches to organize climate risk information in ways that align better with policy needs (e.g. Kennel et al. 2016 Science). One such approach develops and uses a small number of 'storylines' to characterise risk (Clark et al. 2016 Curr. Clim. Change Rep.). A storyline is a plausible pathway, without any a priori probability attached. Storylines offer the benefit of allowing an end-to-end quantitative analysis and thereby incorporating compound risk, which is difficult to do within a probabilistic framework in the face of the cascade of uncertainty. Storylines are also easy for lay people to understand, and so provide a natural language for communication in the policy arena.This project develops the storyline approach, focusing on future drought risk in the United Kingdom. The proposed concept is to navigate the cascade of uncertainty to analyse and bound the system components contributing to climate influence on drought risk, and develop storylines that crystallize that risk (see details in Section 1d). The storylines will be developed to characterize the full range of potential changes in climate that are relevant to drought occurrence (such as change in the frequency of successive dry winters, and delays to the start of the winter recharge season). UK climate projections 2018 (UKCP18) will contain probabilistic projections, as well as ensembles of simulations, at global, regional, and national scale. In this project, using expertise from supervisors at the University of Reading and the Centre for Ecology & Hydrology, the storyline approach will be applied to these climate projections and propagated through hydrological models. Working with Anglian Water, these results will then be applied to water resources and reservoir yield models in order to stress test current water resource management plans, and develop drought risk assessments. This work has the potential for direct application in policy via drought risk management plans in the Anglian region, and can provide widely transferable methods to help better manage climate change impacts on drought risk across the UK.