Urban　flood　risk　assessment　plays　a　crucial　role　in　disaster　risk　reduction　and　preparedness.　It　is　essential　to　mitigate　flood　risks　and　establish　a　comprehensive　analysis　of　factors　influencing　flood　risk,　as　well　as　classify　risk　levels,　in　order　to　provide　a　clear　model　for　risk　assessment.　This　article　aims　to　propose　an　efficient　assessment　method　that　can　classify　urban　flood　risk　levels　and　assist　cities　in　flood　risk　management,　particularly　in　identifying　high-risk　areas.　The　study　area　chosen　for　this　method　is　the　municipal　district　of　Fuzhou　City,　located　in　Fujian　Province,　China.　The　proposed　method　utilizes　the　Urban　Flood　Risk　Assessment　Index,　which　is　developed　based　on　the　risk-vulnerability　framework.　It　integrates　the　combinatorial　empowerment　method,　Density-Based　Spatial　Clustering　of　Applications　with　Noise　(DBSCAN),　and　the　K-means　algorithm　to　cluster　the　quantitative　risk　factors,　enabling　a　comprehensive　analysis　of　the　risk　results.　The　findings　demonstrate　that　areas　characterized　by　intense　extreme　rainfall,　lower　elevation,　gradual　slope,　high　runoff　coefficient,　and　high　population　density　tend　to　exhibit　higher　flood　risk.　Moreover,　the　dominant　factors　contributing　to　high　risk　in　different　regions　vary.　The　results　obtained　from　this　method　align　well　with　the　distribution　of　historical　flood　points,　indicating　the　effectiveness　of　the　risk　map　prepared　using　this　approach.　In　comparison　to　the　results　obtained　from　the　single　clustering　method　and　the　TOPSIS　method　used　in　traditional　risk　assessment,　the　proposed　method　can　successfully　identify　high-risk　urban　flood　areas.　Consequently,　this　method　offers　a　valuable　scientific　basis　for　urban　flood　prevention　and　control　planning.　©　2023　The　Author(s).　Published　by　Informa　UK　Limited,　trading　as　Taylor　&　Francis　Group.