This study was carried out with the aim of feasibility evaluation of the application of multi-objective game theory and fuzzy programing approaches for settling balance between economic development and environmental impact as well as to facilitate the respective decision-makings in Zemkan basin, west of Iran. The bi-objectives of multi-objective game theory and fuzzy programing approaches are minimizing the destructive effects on the environment (less erosion and sediments) and maximizing the economical incomes resulted from different land uses (more net present value). Satellite images were used for recognition of different land uses and the areas of these land use. In this study, the environmentalists and Zemkan basin users were selected as environmental and economical players, respectively. The results reveal that Nash bargaining solution, which is the result of the multi-objective game theory model, differs from Pareto optimalities, obtained through the classical multi-objective model. Nash bargaining solution offered more satisfactory solutions based on decision-makers’ priorities. In addition, the overall results showed that the results of fuzzy programming approach were very close to the results of the multi-objective game theory model. Therefore, in both methods, the decision variables of semi-closed forest, open forest, non-irrigated agricultural lands and barren rocky lands were eliminated and the ones of rural areas, urban areas, and water body remained unchanged. The innovation of multi-objective game theory and fuzzy programing approaches, which can be understood and interpreted well by decision makers, is setting a kind of balance between economic and environmental concerns in watershed management. The results also show that multi-objective game theory and fuzzy programing approaches can be applied to many other issues concerning the environmental management. The upcoming researches can concentrate on developing a third objective like social concerns and accordingly tri-objective games would be applied instead of bi-objective ones.