چكيده به لاتين
In this study, Multi-Pollutant Waste Load Allocation (MPWLA) models considering uncertainties have been developed in a river-reservoir system in multi-objective frameworks. Furthermore, game theory approaches such as leader-follower and Nash bargaining have been applied to resolve the conflicts among stakeholders involved in water resources management. To achieve the optimal MPWLA programs, the CE-QUAL-W2 as 2D hydrodynamic and water quality simulation model (WQSM) is coupled with the Particle Swarm Optimization (or Multi-Objective Particle Swarm Optimization) algorithm. To tackle the high computational burden, imposed by coupling the numerical WQSM in an optimization framework, data-driven surrogate models are employed. Artificial Neural Network (ANN) models are developed based on some input variable selection techniques as a substitute for the original WQSM in a repetitive adaptive pattern. Fuzzy membership functions are employed to deal with the uncertainties and address the imprecision and fuzziness in defining objective functions. To achieve social and economic development along with environmental conservation and equilibrate between conflicting goals of various stakeholders, Stackelberg game and Nash bargaining theory in deterministic and uncertain frameworks, are applied. To deal with the sequential decision system in Stackelberg game and prioritize the leader’s decision over followers’, the Stackelberg game is abstracted as a Bi-level Programming Problem (BLPP) and solved with a hierarchical PSO. The proposed methodologies have been implemented in Behesht-Abad river-reservoir system with a high density of fish farms located in the central part of Iran, Chaharmahal-Bakhtiari province.
The results indicate that the optimal MPWLA programs have led to water quality enhancement in various monitoring points along with the Behesht-Abad river-reservoir system. Applying the Stackelberg game with the superiority of the leader has led to higher environmental fines, less fish production capacities, and consequently better water quality in comparison with the Nash bargaining game. Furthermore, the Fuzzy Stackelberg and Nash bargaining games result in lower environmental fines, higher fish production capacities, and consequently higher water quality violations in comparison with the deterministic framework of each game. The Carleston index in Stackelberg game is improved highly compared with the Fuzzy and deterministic Nash bargaining, fuzzy Stackelberg, and also the current condition.
