Sensitivity analysis to determine the importance of input variables in groundwater stress

This study aims to provide insights into groundwater stress and subsidence in the Varamin plains, located in central Iran. To achieve this, groundwater distributed modeling was simulated, and the groundwater stress index was evaluated accordingly. The area was divided into nine sections based on the intensity and spatial distribution of stresses and subsidence. The study conducted sensitivity analysis to reduce uncertainty, focusing on the importance of abstraction, recharge, and environmental flow at groundwater footprint and stress index equation. The impact of input variables on the groundwater stress index was evaluated using two methods of local and global sensitivity analysis, and the results were compared. A partial correlation criterion was also applied to measure the relationship between stress-dependent variables and three independent variables. The analysis revealed that the correlation analysis and global sensitivity analysis are consistent with each other and differ from the local sensitivity analysis. The abstraction based on global sensitivity analysis and correlation analysis has the greatest impact on stress, while a local sensitivity analysis showed that the reduction in recharge had the greatest effect. The study found that the impact of environmental flow requirements is negligible. Based on the results, the study presented different scenarios for reducing stresses in critical areas and proposed corresponding scenarios to reduce stress in the future management of the plain. A review of three different scenarios for the Varamin plain revealed that recharge is the most effective parameter that correlates with local sensitivity analysis. However, based on the results of the analysis of global sensitivity and correlation coefficient analysis, abstraction has the highest effectiveness.