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Urbanization growth leads to shifting hydrological factors which in turn represent a challenge for urban stormwater management. In this situation, policy strategies can be employed by governments to incentivize stakeholders to use green infrastructure for effective runoff management. This study presents a novel framework evaluating the application of Low-Impact Development (LID) practices for runoff quality and quantity management from a socio-economic point of view. The proposed framework investigates the potential of cooperative game theory to find a fair allocation based on the concept of justice. In this regard, first, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was coupled with the Storm Water Management Model (SWMM) to find optimal runoff management scenarios considering minimization of runoff volume, peak flow, Total Suspended Solid (TSS) load, and costs of LIDs implementation. In the next step, in order to conflict resolution, stakeholders' preferences and interactions were incorporated into the cooperative game theory to determine management scenarios' worth of coalition. In the third step, benefits are allocated among stakeholders by defining three different sharing rules. Then, to select the most capable runoff management scenario, social choice methods of Condorcet choice, Borda scoring, and median voting rule support cooperative game decisions. The proposed methodology is explored in District 10 of Tehran municipality in Iran. According to the findings, solutions with stricter plans for runoff management correspond to more worth of coalition. In addition, the higher worth of coalition, the higher the reduction of peak flow, TSS load, and the total runoff volume. The results also reveal that the Borda scoring procedure tends to select scenarios with less reduction in TSS load, runoff volume, and peak flow in comparison with the others, and as expected, the minimum value for the worth of coalition. Additionally, the cooperative game targets a management scenario with the highest worth of coalition and the maximum value for the reduction in runoff volume, peak flow, and TSS removal. Our framework warrants runoff volume, TSS load, and peak flow can be reduced by 32.8, 31.9, and 32.7 percent, respectively. This framework, in addition to incentivize the stakeholders for implementing runoff management strategies, can effectively consider their conflict of interests in the decision-making process. [Display omitted] • Urban runoff quality and quantity are managed using cooperative game theory. • The coupled simulation-optimization model is applied to find optimal solutions. • Three allocation systems are applied to share the benefits among stakeholders. • Social choice theories support game theory for selecting the best scenario. [ABSTRACT FROM AUTHOR]

Allocating water to organizational stakeholders poses a vital challenge to water managers. Organizations which benefit from water as the primary factor input attempt to achieve their objectives using cost-effective and quick-return strategies, such as increasing the water rights. In such circumstances, lack of water probably results in the conflict. Recognizing the management approaches, organizational priorities, and the stakeholders' influence power can play a dominant role in analyzing the future of such conflicts. In this paper, we analyzed the conflict of water allocation in Ilam dam among organizational stakeholders. We defined the strategies based on the background of the game and organizational objectives. The influence power of stakeholders and the numerical weights of strategies were quantified based on the expert judgment method. The relative priorities of strategies were then calculated for each state of the conflict. We used the GMCR + model to study the actions of stakeholders. Results suggest that the Jihad Agriculture Organization and the Water and Wastewater Company withdraw more water; hence, there exists no water to meet the environmental water right. In this case, the participation of the third party, such as the Governorship and the Justice can change the future of the conflict, and result in moving to the optimal state. However, results from Inverse GMCR analysis demonstrate that Justice is the most influential third party that can move the conflict towards a desired equilibrium (optimal case). [ABSTRACT FROM AUTHOR]