Recent　advances　have　significantly　enhanced　dynamic　early　warning　systems　for　rainfall-induced　landslides　by　integrating　rainfall　thresholds　with　susceptibility　mapping.　However,　there　is　still　room　for　optimizing　these　models　for　regional-scale　applications.　This　study　introduces　a　dynamic　early　warning　model　in　Anxi　County,　Fujian　Province,　China-a　region　prone　to　rainfall-induced　landslides.　First,　historical　landslide　data　and　their　controlling　factors　were　analyzed　for　the　study　area,　and　an　optimal　landslide　susceptibility　map　was　produced　by　integrating　an　information　value　model　with　a　logistic　regression　model.　Second,　based　on　the　theory　of　effective　rainfall,　the　regional　rainfall　threshold　model　was　established　according　to　the　indices　of　daily　and　hourly　rainfall,　and　the　model＇s　accuracy　was　evaluated.　Third,　the　more　effective　E-D　(daily　index)　and　EE-D　(hourly　index)　models　were　coupled　with　the　landslide　susceptibility　map　for　landslide　dynamic　early　warning.　The　model＇s　validation　results　show　its　significant　predictive　capabilities,　with　the　hourly　model　proving　more　accurate　for　short-duration　rainfall　events.　This　study　provides　valuable　insights　for　local　authorities　on　dynamic　early　warning　for　rainfall-induced　landslides　and　offers　guidance　for　refining　dynamic　early　warning　systems　in　similar　regions.