近年来，城市洪涝事件频发，对人民的生命和财产安全造成了严重影响。客观、准确的风险评估对于提升城市洪涝灾害防控水平至关重要，以宜昌市2020年6月末遭受的洪涝灾害为例进行城市洪涝灾害影响因子分析及风险评估。首先，基于RS遥感技术利用哨兵二号雷达影像提取和对比灾前、灾后水体形成淹没区范围并通过随机采样获取淹没点数据；然后，从致涝、孕涝、承涝和恢复能力4个方面选取16个指标，使用随机森林模型计算各指标贡献率并依据排序结果优化指标体系；最后，使用XGBoost模型对优化后的指标体系赋权并对宜昌市的洪涝灾害风险进行评估。结果显示：（1）在宜昌市洪涝灾害影响因素中，地形地貌及河流分布的影响>社会经济因素>气象因素；（2）高风险地区的范围与长江、清江、沮漳河、黄柏河、渔洋河等主要河系的分布关系十分密切，对于以上主要河系的水位线监测应保持高度敏感并制定针对性的应急管理措施；（3）低风险、较低风险和中风险地区占研究区域总面积的71.8%，但只包含8%的淹没点；而高风险地区仅占研究区域总面积的7.32%，但却包含81.33%的淹没点，表明高风险区域内洪涝灾害事件集中；（4）使用小尺度历史灾害事件对评估模型的验证结果显示，72%的验证点落在高风险及较高风险区，高达92%的验证点落在中高风险区。上述验证结果显示了该评估模型的有效性，其评估结果与宜昌市实际情况相符，研究解决了城市洪涝灾害风险难以精细化、定量化评估的部分问题并为城市洪涝风险管理、防灾减灾和区域规划提供科学参考。

In recent years, flooding events happened frequently and severely affected people’s lives and property. Objective and accurate risk assessment is vital for urban flood risk prevention and emergency management. This paper takes the flood event happened in Yichang City in late June 2020 as an example to analyze the influencing factors of urban flooding and conduct risk assessment. Firstly, based on RS remote sensing technology, we extracted the inundation area of water bodies before and after flooding using Sentinel II radar images and conducted random sampling. Then, initially selected 16 basic indicators from four different perspectives: flood-causing, flood-pregnant, flood-bearing and recovery capability. Finally, the XGBoost model was used to assign weights to the optimized indicators and carry out risk assessment. The assessment results show that: (1) among the factors influencing flood risk in Yichang, the influence of topography and river distribution > socio-economic factors > meteorological factors; (2) the scope of high-risk areas is closely related to the distribution of major river systems such as the Yangtze River, Qingjiang River, Fuzhan River, Huangbai River and Yuyang River. The relative departments in Yichang should be highly sensitive to the water level of these river systems and make the essential emergency management measures; (3) the low-risk to medium-risk areas account for 71.8% of the total area of the region, but only contain 8% of the flood hazard sites; while the high-risk area only accounts for 7.32% of the total area, but contains 81.33% of the flood hazard sites, indicating a high flooding intensity in this area; (4) the assessment results of the model are verified to be consistent with the actual situation in Yichang City by using small-scale historical disaster data, the verification results show that 72% of the validation points fall into the high to higher-risk areas, and up to 92% of the validation points fall into the medium-high risk areas. This study solves the difficulty of quantitative assessment of flood risk at fine scales, and provides a useful reference for urban flood risk management, disaster prevention and mitigation efforts and regional planning.