Inland waterway transportation network significantly supports the overall freight transportation of the nation. In order to ensure efficient and timely commodity transportation through this network, this study aims at developing a reliable inland waterway transportation network considering the interactions between different transportation entities along with considering the uncertain commodity supply and un-predictable waterway conditions over time. A capacitated, multi-commodity, multi-period, stochastic, two-stage mixed-integer linear programming (MILP) model is pro-posed to capture this stochastic, time variant behavior of the water-depth along any link of the inland waterway under consideration. Additionally, we proposed a parallelized hybrid decomposition algorithm to solve the real-life test instances of this com-plex NP-hard problem. The proposed algorithm is capable of producing high quality solutions within a reasonable amount of time. Further, a case study is demonstrated for the Southeast region of the United States and a number of managerial insights are drawn that magnifies the impact of different key input parameters on the overall inland waterway transportation network under consideration.