基于孕灾环境和承灾体的居民住宅区暴雨内涝灾害损失评估研究

摘要:

本文以合肥市常青街道1000余幢居民住宅为研究对象，首先利用气象、水文、地理信息、社会经济及卫星遥感等多源数据，构建城市内涝数值模型。然后构建四种收入阶层的标准居家模型，针对易受内涝损失的六类财产，尝试利用合成曲线法拟合暴雨内涝中居民住宅损失的水深-损失率曲线。最后使用短时临近预报系统INCA（空间分辨率1公里，更新频次10分钟）驱动城市内涝数值模型，模拟未来6h的积水分布情景，结合已建立的水深-损失率曲线，得到未来6h居民住宅内涝灾害损失的分布图。本研究可根据INCA的更新频次动态预估未来6h内涝造成住宅财产损失的数量、分布情况，预报时间分辨率为小时，空间上精确到住宅楼，为确定防灾减灾的重点区域和重点保护对象等决策提供参考。

Abstract:

This study focuses on over 1,000 residential buildings in Changqing Subdistrict, Hefei City. A urban waterlogging numerical model was constructed using multi-source data, including meteorological, hydrological, geographic information, socio-economic, and satellite remote sensing data. Then, standard household models for four income levels are developed, and the synthetic curve method is applied to fit depth-loss rate curves for six types of properties vulnerable to waterlogging damage. Finally, the short-term forecasting system INCA (with a spatial resolution of 1 km and an update frequency of 10 minutes) is used to drive the urban waterlogging numerical model, simulating water accumulation scenarios for the next 6 hours. By integrating the established depth-loss rate curves, the distribution of residential waterlogging disaster losses over the next 6 hours is obtained. This study dynamically estimates the quantity and distribution of residential property losses caused by waterlogging over the next 6 hours based on INCA's update frequency. The forecast has a temporal resolution of one hour and is spatially precise down to individual residential buildings.