Development of a Fuzzy-Boundary Interval Programming Method for Water Quality Management Under Uncertainty

This study develops a fuzzy-boundary interval programming (FBIP) method for tackling dual uncertainties expressed as crisp intervals and fuzzy-boundary intervals. An interactive algorithm and a vertex analysis approach are proposed for solving the FBIP model and solutions with α-cut levels have been generated. FBIP is applied to planning water quality management of Xiangxi River in the Three Gorges Reservoir Region, China. Biological oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP) are selected as water quality indicators to determine the pollution control strategies. Results reveal that the highest discharge of BOD is observed at the Baishahe chemical plant, among all point and nonpoint sources; crop farming is the main nonpoint source with the excessive nitrogen loading due to too much uses of livestock manures and chemical fertilizers; phosphorus discharge derives mainly from point sources (i.e. chemical plants and phosphorus mining companies). Abatement of pollutant discharges from industrial and agricultural activities is critical for the river pollution control; however, the implementation of management practices for pollution control can have potentials to affect the local economic income. These findings can help generate desired decisions for identifying various industrial and agricultural activities in association with both maximizing economic income and mitigating river-water pollution.