Developing adaptation policies to climate change for groundwater resources exploitation in dispute resolution

Population growth has increased the exploitation of groundwater resources and caused an imbalance between the recharge and discharge of the resources. Therefore, developing approaches to improve or rehabilitate aquifers is important for their sustainable utilization. The present study aims to develop optimal exploitation policies in various hydrological periods to achieve aquifer stability in Hashtgerd Plain, Iran. Three climate models, i.e., CAS-ESM2-0, ACCESS-CM2, and BCC-CSM2-MR, were examined under three emission scenarios of RCP 2.6, RCP 4.5, and RCP 8.5 to evaluate the future status of the aquifer. The MODFLOW numerical model was used to simulate groundwater fluctuation in the aquifer due to high exploitations and climate change. The results showed that in the most optimistic scenario, there will be a drop of 7.8 m, and in the most pessimistic scenario, there will be a drop of 9.7 m in the aquifer. Various strategies were selected to simulate adaptation to climate change based on aquifer decline. The combination of three strategies of reducing the groundwater withdrawal by 15%, supplying drinking water from surface water, and artificial recharge, showed the highest increase in groundwater level in the aquifer. Moreover, Nash asymmetric game theory was used between the two players, the government and the water users (farmers), in order to balance groundwater resources and minimize the discrepancy between the stakeholders. The aquifer utility function and the cost of implementing balancing strategies for the government, social satisfaction, and economic costs for farmers were selected as the performance indices in the game model. The game model was optimized to maximize the indicators for both players. The results showed that a scenario that included reducing the aquifer withdrawal by 5%, artificial recharge, and supplying drinking water from surface resources was the first priority of balancing with equal results for both players. The results showed that the optimal governance index ranged from 0.6 to 0.66 in different climatic scenarios, while the farmers’ index was 0.73 for scenario S12 and 0.43 for scenario S13.