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In this research, a dual-inexact fuzzy stochastic programming (DIFSP) methodwas developed for supporting the planning of water and farmland usemanagement system considering the non-point source pollution mitigation underuncertainty. The random boundary interval (RBI) was incorporated into DIFSPthrough integrating fuzzy linear programming (FLP) and chance-constrainedprogramming (CCP) approaches within an interval linear programming (ILP)framework. This developed method could effectively tackle the uncertaintiesexpressed as intervals and fuzzy sets. Moreover, the lower and upper boundsof RBI are continuous random variables, and the correlation existing betweenthe lower and upper bounds can be tackled in RBI through the jointprobability distribution function. And thus the subjectivity of decisionmaking is greatly reduced, enhancing the stability and robustness of obtainedsolutions. The proposed method was then applied to solve a water and farmlanduse planning model (WFUPM) with non-point source pollution mitigation. Thegenerated results could provide decision makers with detailed watersupply–demand schemes involving diversified water-related activities underpreferred satisfaction degrees. These useful solutions could allow morein-depth analyses of the trade-offs between humans and environment, as wellas those between system optimality and reliability. In addition, comparativeanalyses on the solutions obtained from ICCP (Interval chance-constraintsprogramming) and DIFSP demonstrated the higher application of this developedapproach for supporting the water and farmland use system planning

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