大都市区洪涝灾害承灾体的时空演化与驱动机制—以上海为例

An integrated understanding of flood risk and its main components (hazard, exposure, and vulnerability) has been widely accepted across academic community and other fields in risk management. Flood risk is increasing in a non-stationarity manner as a result of trends in the three components, due to climate change and socio-economic development. However, most research has focused on the changes in hazard and hydrological component of flood risk. Therefore, a comprehensive understanding of the changes in exposure and vulnerability needs to be elucidated for unravelling the non-stationarity trend of flood risk. This study aims to assess the dynamics and mechanisms of urban exposure and vulnerability and their impacts on the non-stationarity of flood risk. It will use the Pudong metropolitan area in Shanghai as a study case, where the applicant group has a solid foundation of data and knowledge in terms of land use and flood risk. Firstly, this study will investigate the patterns and dynamics of the multiple parameters of urban exposure. A multi-parameter database of historical urban land use will be constructed on the basis of fine-scale land-use data, census data, and building information crawled from real estate databases. A vulnerability model will be constructed based on both existing models and a historical flood database of Shanghai and it will be applied to understand the dynamics in flood vulnerability. The multi-parameter land use data and the vulnerability model will be combined to analyze the dynamics of urban exposure and vulnerability. Secondly, this study will develop and calibrate a multi-parameter cellular automata (MPCA) to simulate the historical changes and predict future scenarios of urban land use. The MPCA model will be coupled with the vulnerability model to comprehensively understand the future scenarios of flood exposure and vulnerability. Lastly, the urban exposure and vulnerability scenarios will be combined with the compound flood hazards of river flood, sea level rise, land subsidence, and climate change scenarios to assess the non-stationarity of flood risk. Such a comprehensive investigation enhances the understanding of the non-stationarity of flood risk and identify the dominant factors. It will also help to promote flood management and resilience in Shanghai and other regions.

全球变化背景下洪涝灾害系统表现出复杂性和动态性，其中快速城市化所伴随的承灾体暴露性与脆弱性变化尚没有得到系统认识。本项研究拟建立城市洪涝灾害承灾体时空演化的模拟模型，揭示承灾体暴露性和脆弱性的动态变化、驱动机制和未来趋势，探讨二者动态变化所导致的洪涝灾害风险动态特征，并以上海浦东新区为例开展实证研究。首先，综合多源数据分析多类型（住宅、商业、工业和其他用地等）城市承灾体的多参数（暴露性参数与脆弱性参数）时空演化和驱动机制。然后，耦合多参数元胞自动机模型、成本价值计算和脆弱性评估模型，建立承灾体价值与脆弱性时空变化的模拟模型，并分析其未来情景。最后，结合未来淹没情景数据研究多要素综合作用下的洪涝灾害风险动态变化，并剖析其对承灾体暴露性和脆弱性变化的响应机制。本研究将促进从承灾体时空演化的角度理解城市洪涝灾害风险的动态特征，并为洪涝灾害风险防范和城市可持续发展提供科学支撑。

全球变化背景下洪涝灾害系统表现出复杂性和动态性，其中快速城市化所伴随的承灾体暴露性与脆弱性变化尚没有得到系统认识。本项目围绕“大都市区洪涝灾害承灾体及其风险评估”这一研究热点开展了系列研究，在承灾体建模、脆弱性动态评估、不确定性分析、风险机理与适应等方面取得了一些成果，包括：1）通过大数据方法构建了城市建筑物脆弱性参数的提取方法，分析了城市化过程中建筑物脆弱性的时空格局；2）构建了社会脆弱性指标体系，系统分析了城市化过程中社会脆弱性的动态变化特征；3）系统分析了洪涝灾害承灾体暴露性格局及其变化，并揭示这对洪涝灾害脆弱性的影响机理；4）开发了一个分析气候变化和社会经济发展情景下洪涝灾害风险变化特征与适应策略的综合研究框架。在项目的支持下，在Global Environmental Change等SCI杂志上发表论文16篇，在科学通报等中文核心期刊发表论文2篇。