A dual-inexact fuzzy stochastic model for water resources management and non-point source pollution mitigation under multiple uncertainties

摘要

In this research, a dual-inexact fuzzy stochastic programming (DIFSP) method was developed for support-ing the planning of water and farmland use management system considering the non-point source pollution mitiga-tion under uncertainty. The random boundary interval (RBI) was incorporated into DIFSP through integrating fuzzy linear programming (FLP) and chance-constrained programming (CCP) approaches within an interval linear programming (ILP) framework. This developed method could effectively tackle the uncertainties expressed as intervals and fuzzy sets. Moreover, the lower and upper bounds of RBI are continu-ous random variables, and the correlation existing between the lower and upper bounds can be tackled in RBI through the joint probability distribution function. And thus the sub-jectivity of decision making is greatly reduced, enhancing the stability and robustness of obtained solutions. The pro-posed method was then applied to solve a water and farm-land use planning model (WFUPM) with non-point source pollution mitigation. The generated results could provide de-cision makers with detailed water supply–demand schemes involving diversi?ed water-related activities under preferred satisfaction degrees. These useful solutions could allow more in-depth analyses of the trade-offs between humans and en-vironment, as well as those between system optimality and reliability. In addition, comparative analyses on the solutions obtained from ICCP (Interval chance-constraints program-ming) and DIFSP demonstrated the higher application of this developed approach for supporting the water and farmland use system planning.