This　study　presents　a　novel　decision-support　framework　for　the　bioethanol　supply　chain　network　planning　and　management　under　uncertainties.　Under　the　holistic　framework,　the　most　suitable　sites　for　biorefineries　are　first　screened　out　by　adopting　a　GIS-based　multi-criteria　decision-making　approach.　Then,　a　mixed-integer　linear　programming　model　combined　with　quantile-based　scenario　analysis　is　developed　to　determine　the　strategic　planning　(i.e.　locations　and　size　of　biorefineries)　and　tactical　management　(i.e.　biomass　purchasing,　feedstock　transportation,　bioethanol　production,　and　product　delivery)　under　uncertainties.　The　model　can　effectively　search　for　reliable　solutions　under　uncertainties　and　achieve　tradeoff　solutions　with　the　consideration　of　decision　makers＇　risk　tolerance.　The　proposed　framework　is　demonstrated　through　a　case　study　in　China.　It　is　suggested　to　build　seven　biorefineries　with　a　capacity　of　100　million　liters　in　Zhumadian　city.　Utilizing　41%　of　local　agricultural　residues　could　satisfy　the　bioethanol　requirement　in　the　transportation　sector　under　the　E20　policy.　However,　the　estimated　production　cost　of　bioethanol　in　Zhumadian　is　very　high,　about　1.11　$/L,　which　makes　it　lose　cost　advantage　in　the　fuel　market.　Thus,　currently,　effective　subsidies,　mandatory　energy　substitution　policies,　along　other　environmental　regulatory　measures　are　desired　to　promote　the　bioethanol　industry　development.