Abstract: Nitrogen-based fertilizer industry in United States is undergoing major changes the demand for which is primarily driven by agriculture. Traditionally, this industry sources anhydrous ammonia through imports from Canada and U.S.-Gulf, the latter comprises bulk of imports, or produces domestically to be supplied as is or converted into urea or UAN variations of nitrogen-based fertilizer with various combinations with other minerals. With change in composition of crops and increasing acreage of crops that are fertilizer intensive, there is an increased demand for nitrogen-based fertilizer in order to promote foliar growth as a standalone form, for example Urea, or in combination, for example Di-ammonium phosphate (DAP). Second compelling reason for change in industry is reduction in prices of natural-gas, in part due to oil exploration, that makes it cheaper to produce anhydrous ammonia domestically. Anhydrous ammonia is perquisite for making other types of nitrogen-based fertilizer and highly energy intensive. Thus, lower natural-gas prices provide incentive for domestic firms to either expand existing fertilizer plants or opens up the possibility of new entrants. Many companies/firms have recently announced their plans to expand existing plants or open new units, exerting competitive pressure on an industry that already has lot of surplus capacity but highly competitive in terms of production costs and technology used. It is to be noted that natural-gas prices are volatile; therefore, any commitment to expand or open new plant is subject to volatility in demand, natural-gas prices, and import price of fertilizers. The purpose of this dissertation is to analyze spatial competition among U.S. nitrogen-based fertilizer plants and their respective market boundaries. This dissertation also derives the structure of the supply chain for nitrogen-based fertilizer in the United States (at macro level); and the stochastic spatial-optimization model to account for risk in random variables. Locational information is used to account for spatial nature of problem, and linear and mixed-integer based optimization techniques are applied to arrive at current and most likely future cases. Combination of linear optimization, and mixed-integer, and geographical information systems helps in determining regional areas where competition is expected to be ruinous and most intense; and provide insights on viability of newly announced fertilizer plants that are most likely to be successful and significantly impact the structure of overall supply chain.