Search

Sustainable urban stormwater management presents challenges due to uncertainties and conflicting stakeholder preferences. In this regard, our research introduces a comprehensive framework that integrates self-organization map (SOM) and many-objective robust decision-making (MORDM) methods to bridge the knowledge gap between deep uncertainty and conflict resolution. To do so, first, MORDM generates optimal strategies for the implementation of low-impact development (LID) practices and quantifies their robustness under different uncertain scenarios. Then, the results are integrated into the SOM framework, wherein multi-dimensional decision space can be classified and stakeholders are enabled to navigate their satisfaction to reach a subset of robust strategies. Finally, to determine the most suitable management strategy, a novel game theory-based group multicriteria decision-making (GT-GMCDM) method is employed, which can effectively consider stakeholders' conflicts in the selection process. Results from applying the proposed methodology in District 10 of Tehran municipality, Iran, demonstrate that the selected alternative can reduce TSS contamination load and runoff volume (RV) by 30% and 27%, respectively. Indeed, findings prove that in addition to improving stormwater quality and quantity, the suggested methodology can simultaneously consider stakeholders' preferences and find a reliable strategy. This study also offers valuable insights into robust stormwater management, with a focus on ensuring the sustainability of urban environments. [ABSTRACT FROM AUTHOR]

This paper proposes a new framework to optimize the allocation of water resources considering two perspectives of water value and strategic management which is one of the novelties of this study. After identifying agricultural, industrial, and domestic water demands, a water allocation model is developed to maximize the net benefit of water delivered to each sector. Based on the characteristics of the study area which is the Namak Lake basin, water transfer from Dez tributaries can be considered as an uncertainty depending on the climate and political issues. So, the model is initially performed without considering water transfer and then water transfer is considered to enhance the flexibility. In addition, the initial model does not assign the weights to the plain. In the novel model, weights derived from questionnaires are applied to reflect experts' opinions and consider the priorities of the plains. Transferred water is then allocated from the strategic management perspective and the water value perspective (six possible combinations of perspectives and scenarios), and eleven independent variables are considered in the model. Also, GMCR + , the new version of the Graph Model for Conflict Resolution, is applied to visualize the possible scenarios and equilibrium states based on the status quo of the conflict. Based on the results, the first scenario of water value perspective is chosen which results in a significant water allocation to the industry and agriculture sectors (approximately 94% and 96%, respectively). Also, 94.6% of potable water is satisfied compared to the initial water needs. [ABSTRACT FROM AUTHOR]

Determining the optimized policies in the exploitation of groundwater water resources is a complicated issue, especially when there are several different managers with conflicting goals. The current study presents a new multi-purpose method to reach a compromise among different stakeholders by determining optimal social policies and sustainable hydro-environmental management of underground water resources. This method simultaneously considers qualitative and quantitative simulation and optimization, stakeholders' preferences, and uncertainty analysis. In this study, the recharge was determined and incorporated in MODFLOW groundwater current model and MT3DMS pollution transfer model by using the hydrological model SWAT. In addition, DREAM (zs) algorithm (derived from algorithms based on Markov chain Monte Carlo) was used to examine the uncertainty of MODFLOW model parameters. The optimal head and TDS rate were determined in the studied aquifer by linking the model with MOPSO. Then, the Pareto frontier derived from the previous step, was utilized to determine the allocation rate of groundwater resources among a set of non-dominated solutions using Social Choice Rules (SCR) including Condorcet, Median Voting Rule (MVR), and Fallback Bargaining (FB) including unanimity fallback bargaining and fallback bargaining with impasse. The results showed that almost all the selected methods of conflict resolution in this research behaved similarly, and their results were not significantly different from each other. However, the comparison of these methods indicated that the MVR with the minimum reduction in withdrawal discharge and the maximum elevation in response to optimal allocation policies had the best performance. The amount of water extracted from the study area is about 540 million m3/year, which reaches 395 million m3/year. [ABSTRACT FROM AUTHOR]

In this paper, a new methodology is proposed for waste load allocation in river systems using the decision support system (DSS) for the graph model for conflict resolution II (GMCRII), multi-criteria decision making (MCDM) analysis and the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Minimization of total treatment and penalty costs and minimization of biological oxygen demand violation of standards at the check point are considered as the main objectives of this study. At first, the water quality along the river was simulated using the Streeter-Phelps (S-P) equation coupled with the MOPSO model. Thereby a trade-off curve between the objectives is obtained and a set of non-dominated solutions is selected. In the next step, the best alternative is chosen using MCDM techniques and the GMCRII DSS package and non-cooperative stability definitions. The applicability and efficiency of the methodology are examined in a real-world case study of the Sefidrud River in the northern part of Iran. [ABSTRACT FROM AUTHOR]

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]