Inexact Management Modeling for Urban Water Supply Systems

Abstract

The water shortage problems have become main obstacles for sustainable socio-economic development of many cities. There was an urgent need to develop effective decision-support tools for supporting water-supply schemes under multiple uncertainties. In this study, an interval-parameter stochastic chance-constrained programming (IPSCCP) model was developed for urban water supply system. It integrated stochastic chance-constrained programming (SCCP) and interval linear programming (ILP) into a general optimization framework. IPSCCP could deal with uncertainties expressed as both discrete intervals and probability distributions; meanwhile, it was also useful for helping analyze the reliability of satisfying system constraints. A multi-layer urban water supply system, including water resources, collection and treatment facilities, reservoirs, and consuming zones, was used to demonstrate the feasibility and applicability of proposed method. The results indicated that IPSCCP was capable of helping understand the effects of uncertainties and was useful for urban water managers to gain an in-depth insight into the tradeoffs between system cost and reliability of constraints satisfaction. The study would be a new attempt in advancing an integrated uncertainty-analysis tool for urban water supply system. It was also suggested that other uncertain approaches are integrated into an IPSCCP framework for reflecting more complex conditions.

Keywords: urban water resources management, stochastic chance-constrained programming, interval linear programming, uncertainty, optimization