Transforming　urban　goods　movement　from　roads　to　underground　is　an　emerging　concept　to　improve　supply　chain　performance　and　alleviate　overcrowded　environments.　Existing　literature　merely　discussed　the　underground　logistics　system　(ULS)　network　design　problem　within　a　simplified　boundary,　whereas　several　critical　system　features　(e.g.,　stochastic　freight　demand　and　co-modality)　were　omitted.　To　bridge　the　knowledge　gaps,　this　paper　proposes　a　reliable　modeling　approach　to　solve　an　urban　surface-underground　integrated　logistics　network　(USUIL)　design　problem　with　a　holistic　consideration　of　cost-benefit　objectives,　road-ULS　modal　split,　and　demand　uncertainties.　To　begin　with,　we　introduce　a　city-wide　hub-and-spoke　USUIL　network　structure　with　a　two-tier　parallel　distribution　process.　Five　major　external　benefits　of　underground　goods　movement　are　formulated　using　real-world　data.　Next,　a　deterministic　model　is　developed　to　optimize　the　network　decisions　including　hub-satellite　location-allocation,　deployment　of　tunnels　and　pipelines,　logistics　service　assignment,　and　flow　routing.　Then,　to　deal　with　the　influences　of　case-wise　demand　uncertainties,　the　model　is　reformulated　into　a　reliable　one　by　incorporating　the　ideas　of　solution　robustness　and　stochastic　equivalents.　A　two-stage　heuristicbased　optimization　tool　that　hybridizes　the　adaptive　immune　genetic　algorithm,　plant　growth　simulation　algorithm,　and　Clarke-Wright　saving　algorithm　was　proposed　to　solve　the　problem.　Finally,　numerical　experiments　are　conducted　on　the　Beijing　city　case　to　validate　the　proposed　method,　and　the　best　network　schemes　obtained　from　different　models　and　scenarios　are　compared.　Results　show　that　a　greater　robust　control　factor　in　our　model　helps　the　network　to　lower　the　integrated　freight　transport　cost　while　improving　the　social-environmental　benefit　at　the　expense　of　deploying　more　facilities.　The　reliable　model　performs　well　in　balancing　the　conservativeness　(i.　e.,　less　capacity　insufficiency　risk)　and　optimality　(i.e.,　less　cost　due　to　redundant　facilities)　of　the　USUIL　network　design　when　faced　with　diverse　demand　cases.