标题： FlowsDT：用于导航城市洪水动态的地理空间数字孪生 显示英文标题

标题： FlowsDT: A Geospatial Digital Twin for Navigating Urban Flood Dynamics

摘要： 全球各地的社区日益面临由气候变化、城市扩张和环境退化加剧的洪水灾害。 应对这些挑战需要实时洪水分析、精确的洪水预测以及与利益相关者的稳健风险沟通，以实施有效的缓解策略。 水动力模型和数字孪生的最新进展为在街道和地下室层面进行高分辨率洪水建模和可视化提供了新的机会。 聚焦于美国德克萨斯州的加尔维斯顿市，一个屏障岛，本研究创建了一个由一维-二维耦合水动力模型支持的地理空间数字孪生（GDT），以增强城市对暴雨和河流洪水的韧性。 研究目标包括：（1）开发一个包含地形、水文和基础设施的GDT（FlowsDT-Galveston）；（2）使用历史洪水事件和社会感知数据验证该孪生；（3）在2年、10年、25年、50年和100年重现期降雨情景下模拟超本地洪水条件；以及（4）识别不同情景下的高风险区域。 本研究采用PCSWMM创建城市景观的动态虚拟副本和精确的洪水建模。 通过整合LiDAR数据、土地覆盖和雨水管道几何形状，该模型可以在不同历史和设计风暴中，在四维环境中模拟洪水深度、范围、持续时间和速度。 结果表明，从2年到100年洪水，淹没超过1英尺的建筑物增加了5.7%。 超过1英尺的路面淹没增加了6.7%从2年到100年的洪水。 所提出的模型可以支持加尔维斯顿的主动洪水管理和城市规划；并有助于灾害韧力建设，指导可持续基础设施的发展。 该框架可以扩展到其他面临类似挑战的社区。 显示英文摘要

摘要： Communities worldwide increasingly confront flood hazards intensified by climate change, urban expansion, and environmental degradation. Addressing these challenges requires real-time flood analysis, precise flood forecasting, and robust risk communications with stakeholders to implement efficient mitigation strategies. Recent advances in hydrodynamic modeling and digital twins afford new opportunities for high-resolution flood modeling and visualization at the street and basement levels. Focusing on Galveston City, a barrier island in Texas, U.S., this study created a geospatial digital twin (GDT) supported by 1D-2D coupled hydrodynamic models to strengthen urban resilience to pluvial and fluvial flooding. The objectives include: (1) developing a GDT (FlowsDT-Galveston) incorporating topography, hydrography, and infrastructure; (2) validating the twin using historical flood events and social sensing; (3) modeling hyperlocal flood conditions under 2-, 10-, 25-, 50-, and 100-year return period rainfall scenarios; and (4) identifying at-risk zones under different scenarios. This study employs the PCSWMM to create dynamic virtual replicas of urban landscapes and accurate flood modeling. By integrating LiDAR data, land cover, and storm sewer geometries, the model can simulate flood depth, extent, duration, and velocity in a 4-D environment across different historical and design storms. Results show buildings inundated over one foot increased by 5.7% from 2- to 100-year flood. Road inundations above 1 foot increased by 6.7% from 2- to 100-year floods. The proposed model can support proactive flood management and urban planning in Galveston; and inform disaster resilience efforts and guide sustainable infrastructure development. The framework can be extended to other communities facing similar challenges.