A Sequential Fuzzy Model with General-Shaped Parameters for Water Supply-Demand Analysis

Fuzzy programming model has been widely used in water resources management, but its applicability has been significantly restricted in dealing with triangular or trapezoidal shaped fuzzy sets due to intrinsic complexity in converting fuzzy constraints into their deterministic forms. In this study, a novel superiority-inferiority-based sequential fuzzy programming (SISFP) model was proposed for supporting water supply-demand analysis under uncertainty. The SISFP method could transform fuzzy objective function and constraints with general-shaped fuzzy coefficients into their crisp equivalent by using fuzzy superiority and inferiority measures. The water supply-demand management system in Tianjin Binhai New Area, China, consisting of five sources of water, five water users at three districts (i.e. Tanggu, Hanggu, and Dagang), was used for methodology demonstration. The proposed model could effectively address the complex nature of fuzzy characterization of water-transfer safety factor, wastewater reclamation rate, the net benefits derived from water, and water-saving rate of the system; and also take demand management measures into consideration. The obtained solutions have sought a well balance among the water availability, water demand, adoption of water-saving measures, and benefit/cost of each water users. The advantage and necessity of SISFP in dealing with general-shaped fuzzy parameters were further verified by comparing to fuzzy models with both deterministic and specially-shaped fuzzy parameters.