The　identification　of　pollutant　source　release　history　in　rivers　is　important　for　emergency　response　of　pollution　accidents　and　formulating　remediation　strategies.　Space-time　radial　basis　collocation　method　(RBCM),　as　a　meshless　method　with　strong　applicability,　can　directly　estimate　the　release　history　from　the　concentration　data　measured　at　downstream　observation　sites.　However,　the　uncertainty　of　specific　parameters　in　space-time　RBCM　is　the　main　factor　affecting　the　accuracy　of　estimation.　Therefore,　a　way　to　solve　the　parameters　efficiently　and　accurately　is　essential.　For　this　purpose,　a　new　model　which　combines　space-time　RBCM　and　differential　evolution　algorithm　(DEA)　is　established　to　identify　the　source　release　history.　First　of　all,　efficient　parameter　optimizer　DEA　is　introduced　to　search　the　parameters　that　affect　the　estimation　accuracy　of　space-time　RBCM.　Then,　a　new　loss　function　considering　the　imbalance　configuration　of　RBCM　nodes　is　designed　to　ensure　the　rationality　of　the　parameters　obtained　by　DEA.　The　results　of　numerical　cases　and　real　field　case　show　that　the　proposed　method　can　accurately　estimate　the　real　release　history　with　low　time　consumption.　It　is　also　demonstrated　that　DEA　is　more　efficient　than　k-fold　cross-validation　in　searching　the　optimal　parameters　for　space-time　RBCM,　and　the　parameters　obtained　from　the　new　loss　function　can　make　the　estimated　release　history　more　precise.