This　paper　studies　a　stochastic　inventory　routing　problem　with　alternative　handling　modules　and　limited　capital　budget,　under　partial　distributional　information　(i.e.,　the　mean　and　covariance　matrix　of　customer　demands).　The　objective　is　to　maximize　the　service　level,　i.e.,　the　probability　of　jointly　ensuring　no　stockout　and　respecting　the　warehouse　capacities　for　all　customers　at　the　end　of　each　period.　A　novel　distributionally　robust　chance　constrained　formulation　is　proposed.　The　sample　average　approximation　method　and　a　model-based　hierarchical　approach　based　on　problem　analysis　are　developed.　Computational　results　show　that　the　latter　approach　is　more　efficient.　We　also　draw　some　managerial　insights.