The Lower Rio Grande Valley (LRGV) in South Texas has emerged as a warehouse and transportation center between Central America and the U.S. due to the impact from The North American Free Trade Agreement (NAFTA). According to the Lower Rio Grande Valley Development Council's (LRGVDC) investigation, the area's population has increased by 39.8% in the last 10 years. It is estimate that the population will continue to grow at a rate of approximately 4% per year. The City of Pharr is one of the fast-growing cities in the Valley, which demands larger wastewater treatment capacity in the near future. Risks and uncertainties arise in various aspects of decision analysis with respect to several available expansion options. Finding of the optimal risk-based decision of sewer network expansion with time-varying constraints must be accounted for in long-term planning. In this study, background information has been garnered regarding population projections as well as land use based on the City of Pharr zoning policy. The planning model ran for three five-year periods beginning in 2005 and ending in 2020. Historical population data is used to forecast the population for each time period. The waste stream generated is divided into three distinct sewer sheds: 1) South region, 2) Central region, and 3) North region. The City of Pharr anticipated that most of its growth would be concentrated in the North Region; therefore, Pharr considered building a new wastewater treatment plant in that Region. The other options available to the City of Pharr also include routing of their wastewater to the McAllen wastewater plant on the southern side of McAllen, and expanding the Pharr wastewater plant on the southern side of Pharr. Parameters used in optimization analysis in the second stage would be generally defined as interval numbers in a grey integer-programming model. To identify the optimal risk-based decision, a cost analysis model in conjunction with optimization scheme is prepared for determining the most cost-effective expansion strategy under uncertainty. The outputs would reflect the systematic concerns about integrative uncertainty within this analysis leading to enable decision makers and stakeholders to make risk-informed decisions.