Hydropower　energy　model　(HEM)　facilitates　the　construction　and　efficiency　of　the　energy　system,　including　the　enhancement　of　power　generation　and　the　efficient　utilization　of　water　energy.　Runoff　uncertainty　has　influenced　HEM　accuracy,　resulting　in　reduced　energy　production　efficiency.　To　address　this　issue,　a　dynamic　multi-scenario　hydropower　energy　model　considering　runoff　uncertainty　(DMS-HEM)　is　presented　in　this　paper.　First,　a　library　of　probability　distribution　functions　is　constructed　considering　runoff　characteristics.　A　dynamic　selection　mechanism　based　on　kolmogorov-smirnov　(KS)　test　is　designed　to　select　distribution　probability　function　of　reservoir　from　the　library.　Second,　the　initial　runoff　scenarios　set　is　generated　based　on　the　selected　distribution　probability　function　by　Latin　hypercube　sampling　method.　A　fast　predecessor　elimination　technique　based　on　probability　distance　is　used　to　obtain　runoff　scenarios　set.　Third,　a　dynamic　multi-scenario　hydropower　energy　model　is　established　according　to　runoff　scenarios　set,　with　the　constraint　of　guaranteed　output.　Annual　power　generation　and　water　disposal　are　the　optimization　objective　functions　of　the　model.　Finally,　three　algorithms　are　used　to　solve　DMS-HEM　and　HEM.　The　experimental　results　show　that　DMS-HEM　can　reduce　water　disposal　volume　and　increase　energy　generation　effectively.　©　2023　IEEE.