Due to the increasing contamination and resource-scarcity issues, environmental systems management is essential to socio-economic development. However, formulating relevant policies and strategies is often associated with a variety of complexities. It is necessary for decision makers to identify desired management plans to reflect multiobjective features that involve a trade-off between environmental protection and economic development. Moreover, these complexities will be further intensified by multiple formats of uncertainties existent in the related factors and parameters, as well as their interrelationships. Therefore, efficient system analysis techniques for supporting multiobjective environmental systems management under such complexities are required. In this dissertation research, a set of two-stage fractional programming methods were developed for managing environmental systems under uncertainty, including (a) a twostage fractional programming method for managing multiobjective waste management systems, (b) a two-stage chance-constrained fractional programming method for sustainable water quality management under uncertainty, and (c) a dynamic chanceconstrained two-stage fractional programming method for planning regional energy systems in the province of British Columbia, Canada. The proposed multiobjective optimization methods could address the conflicts between two objectives (e.g. economic and environmental effects) without the demand of subjectively setting a weight for each objective. Economic penalties were taken into consideration as corrective measures against any arising infeasibility caused by a particular realization of uncertainty, such that a linkage to pre-regulated policy targets was established. Furthermore, the methods facilitated an in-depth analysis of the interactions between economic cost and system efficiency. The developed methods could provide desired decision alternatives for managing environmental systems under various conditions.