| Summary: | Specialization: Transportation Engineering Degree: Master of Science Abstract: The Mackenzie River shipping corridor is one of the most important transportation corridors in the Northwest Territories (NWT), an area of Canada that is rich in natural resources. The corridor is the main means of transporting goods to many communities in the NWT. It is also considered to be a potential shipping route for delivering heavy equipment to Alberta’s oil sands, one of the largest hydrocarbon deposits in the world. The route, however, presents uncertainties and challenges in the delivery of goods due to shallow and variable water levels, and navigational hazards. Moreover, the route’s capacity to move goods has not been realized due to low demand in the area. Better understanding of the route’s capacity and reliability may enable greater utilization of this transportation corridor. The current study designs a network representation of the transportation corridor that can be used to understand route capacity and reliability issues. This research addresses two questions: i) what data are required to build a shipping network representation for the Mackenzie River corridor, and ii) how can the network representation be built using available data sources? To answer the first question, datasets used in inland and maritime freight transportation literature were identified, and then the datasets relating to the Mackenzie River inland water transportation system were gathered and organized. The data were taken from different published and unpublished reports, as well as other data sources, such as Water Survey of Canada (WSC)’s water level data and GNWT Geomatics’s shape files. The data include spatial features of the Mackenzie River freight transportation system, water level, freight operators and their operations, and freight demand. Spatial features of the freight transportation system consist of the Mackenzie River and its adjacent channels, landing locations at communities, danger zones, navigational hazards, and other ...
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