This　paper　develops　an　interval　multi-stage　robust　programming　model　for　regional　low-carbon　electric　power　system　planning　with　energy-water　nexus.　The　model　integrates　interval　programming　and　multi-stage　stochastic　programming　to　handle　uncertainties　with　different　probability　distribution　information.　In　addition,　under　the　framework　of　robust　programming,　the　optimal　solutions　could　provide　tradeoff　information　between　system　cost　and　decision　maker＇s　risk　preference.　The　hybrid　programming　method　is　tailored　for　a　case　study　of　Shandong　Province,　China　to　validate　its　applicability　and　provide　useful　managerial　insights,　where　energy-water　interactions　are　gain　great　concerns.　The　model　helps　to　make　robust　strategies　associated　with　risk　control　for　capacity　expansion,　carbon　capture　and　storage　(CCS)　technology　retrofitting,　power　generation,　imported　electricity,　and　water　allocation　for　electricity　generation,　with　the　goal　of　minimizing　total　cost.　Besides,　considering　the　variation　of　water　resource　conditions　and　environmental　policies　under　climate　change,　the　impacts　of　water　resource　availability　and　carbon　emission　caps　on　regional　electric　power　system　planning　are　explored　and　discussed.　It　is　found　that　stricter　carbon　emission　cap　policy　would　facilitate　the　investment　on　CCS　devices　but　have　little　impact　on　the　installed　capacity　structure,　meanwhile　it　would　increase　water　consumption　per　power　generation.　However,　scarcer　water　resource　situation　would　promote　the　development　of　renewable　energy　generation,　and　limit　the　investment　on　CCS　technology.　(C)　2019　Elsevier　Ltd.　All　rights　reserved.