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.
Nowadays, water allocation is a major problem in water resources planning and management considering water limitation and scarcity, population growth, agriculture and industrial uses, and food security (Dinar et al., 1997). There are many goals, stakeholders, and researchers are trying to improve allocation criteria. Among these criteria, economic issues are important parts in which researchers beneft from multi-objective optimization to deal with the problem (Guo et al., 2014; Roozbahani et al., 2015). In addition, water demand varies per nation due to variations in hydrological parameters (Wang et al., 2016). For example, climate change has raised certain plants and animals’ water needs. Economic growth and decreasing precipitation have limited human water availability (Yao et al., 2019). So, water scarcity problems arise as demand for water hits the limits of fnite supply. Water allocation especially in water transfer projects implemented to overcome such a crisis often results in water conficts among water users and stakeholders. Therefore, confict resolution is an essential component of water resource management, particularly in the case of water transfer systems, and various quantitative and qualitative methods have been proposed for it. Game theory provides a framework for studying the strategic actions of individual decision-makers to develop more broadly acceptable solutions to confict resolution (Madani, 2010).
According to the high costs of fulflling the water needs of the province and transferring water from the Dez branch to this province, the purpose of this study was to optimize the allocation of water resources to diferent sectors to maximize the proft from water allocation. The optimization model performed with and without considering the water transfer and taking into account the priority of users from the strategic management and water value perspectives. Without considering water transfer due to fewer constraints and non-prioritization of uses, the overall amount of water is higher, but in the other two states having more constraints and allocating some water to the aquifer recharge, its value has reduced to half.
The amount of water allocated to the plains other than Sharifaabad plain has decreased by assigning weights to the model. Water allocated to the drinking and industrial sectors has increased due to water transfer. It is clear from the results of the confict analysis that according to the conditions, all sectors choose the water value-frst scenario. By implementing this scenario a signifcant allocation has been made to industry and agriculture, and 94.6% to the drinking sector. It should be noted that the drinking sector plays a more important role than other sectors, and it is necessary to satisfy drinking water needs. Finally, to compare the results of this study with the real situation of the study area in 2021, statistical data show that total precipitation is less than in the past years and total discharge has been decreased. So, based on the slope of the total discharge line in Fig. 4, it could comply with the estimation.