This research aims to study a novel approach for waste load allocation (WLA) to meet environmental, economical, and equity objectives, simultaneously. For this purpose, based on a simulation-optimization model developed for Haraz River in north of Iran, the waste loads are allocated according to discharge permit market. The non-dominated solutions are initially achieved through multiobjective particle swarm optimization (MOPSO). Here, the violation of environmental standards based on dissolved oxygen (DO) versus biochemical oxidation demand (BOD) removal costs is minimized to find economical total maximum daily loads (TMDLs). This can save 41% in total abatement costs in comparison with the conventional command and control policy. The BOD discharge permit market then increases the revenues to 45%. This framework ensures that the environmental limits are fulfilled but the inequity index is rather high (about 4.65). For instance, the discharge permit buyer may not be satisfied about the equity of WLA. Consequently, it is recommended that a third party or institution should be in charge of reallocating the funds. It means that the polluters which gain benefits by unfair discharges should pay taxes (or funds) to compensate the losses of other polluters. This intends to reduce the costs below the required values of the lowest inequity index condition. These compensations of equitable fund allocation (EFA) may help to reduce the dissatisfactions and develop WLA policies. It is concluded that EFA in integration with water quality trading (WQT) is a promising approach to meet the objectives.