Reanalysis　datasets　can　provide　alternative　and　complementary　meteorological　data　sources　for　hydrological　studies　or　other　scientific　studies　in　regions　with　few　gauge　stations.　This　study　evaluated　the　accuracy　of　two　reanalysis　datasets,　the　China　Meteorological　Assimilation　Driving　Datasets　for　the　Soil　and　Water　Assessment　Tool　(SWAT)　model　(CMADS)　and　Climate　Forecast　System　Reanalysis　(CFSR),　against　gauge　observations　(OBS)　by　using　interpolation　software　and　statistical　indicators　in　Northeast　China　(NEC),　as　well　as　their　annual　average　spatial　and　monthly　average　distributions.　The　reliability　and　applicability　of　the　two　reanalysis　datasets　were　assessed　as　inputs　in　a　hydrological　model　(SWAT)　for　runoff　simulation　in　the　Hunhe　River　Basin.　Statistical　results　reveal　that　CMADS　performed　better　than　CFSR　for　precipitation　and　temperature　in　NEC　with　the　indicators　closer　to　optimal　values　(the　ratio　of　standard　deviations　of　precipitation　and　maximum/minimum　temperature　from　CMADS　were　0.92,　1.01,　and　0.995,　respectively,　while　that　from　CFSR　were　0.79,　1.07,　and　0.897,　respectively).　Hydrological　modelling　results　showed　that　CMADS　+　SWAT　and　OBS　+　SWAT　performed　far　better　than　CFSR　+　SWAT　on　runoff　simulations.　The　Nash-Sutcliffe　efficiency　(NSE)　of　CMADS　+　SWAT　and　OBS　+　SWAT　ranged　from　0.54　to　0.95,　while　that　of　CFSR　+　SWAT　ranged　from　-0.07　to　0.85,　exhibiting　poor　performance.　The　CMADS　reanalysis　dataset　is　more　accurate　than　CFSR　in　NEC　and　is　a　suitable　input　for　hydrological　simulations.