Iranian Water Research Journal

Iranian Water Research Journal

Prioritization of Underground Dam Axes in the Shahrekord Watershed using Multi-Criteria Ranking method

Document Type : Original Article

Authors
Department of Water Engineering, Faculty of Agriculture, Shahrekord University, Shahrekord, CHB, Iran
Abstract
Extended Abstract
Introduction:
The Shahrekord plain faces chronic water scarcity, especially during dry seasons, and increasing dependence on groundwater resources to meet domestic, agricultural, and industrial demands. However, uncontrolled groundwater extraction has resulted in declining water tables and reduced aquifer sustainability, highlighting the urgent need for alternative water management strategies. Among the available solutions, subsurface dams have gained attention as an effective and environmentally friendly technique for controlling subsurface flow, enhancing groundwater recharge, and improving water storage capacity in alluvial aquifers. The successful implementation of subsurface dams critically depends on the proper selection of suitable locations, which requires a comprehensive evaluation of multiple hydrogeological, environmental, and socio-economic factors. Accordingly, the main objective of this study is to identify suitable sites and prioritize potential locations for subsurface dam construction within the Shahrekord Plain watershed using an integrated GIS and Multi-Criteria Decision-Making (MCDM) framework.

Materials and Methods
This research adopted a structured two-stage methodological framework. In the first stage, a GIS-based suitability analysis was conducted to identify potential locations suitable for subsurface dam construction. As a result of this process, 12 candidate dam axes were identified as suitable for further analysis. Detailed information regarding this stage is presented in the previous paper. In the second stage, the Analytical Hierarchy Process (AHP) was employed as the MCDM tool to prioritize the selected axes. The decision hierarchy was structured into main criteria, including groundwater quantity/quality, reservoir characteristics, axis conditions, and socio-economic factors, each further subdivided into relevant sub-criteria. Pairwise comparison matrices were developed based on expert judgment, field observations, and a literature review, and consistency ratios were checked to ensure the logical reliability of the comparisons. The weights of criteria were calculated using the geometric mean method. To address uncertainty and potential bias in expert weighting, five different decision scenarios were defined. In Scenario 1, all main criteria were assigned equal importance, representing a neutral decision perspective. In Scenarios 2 to 5, each scenario emphasized one dominant criterion by assigning it a higher relative weight compared to the other criteria, allowing for sensitivity analysis of the decision model. For each scenario, a composite suitability index was calculated for all 12 candidate axes by aggregating standardized criterion values using weighted linear combination methods. Hydrogeological parameters, surface runoff, recharge conditions, soil permeability, and socio-economic indicators were collected and analyzed.

Results and Discussion
The results of the multi-scenario AHP-GIS analysis revealed that although some variations occurred in rankings across different weighting scenarios, the overall prioritization pattern remained relatively stable, indicating the robustness of the decision model. Among the 12 candidate axes, Axis 54 consistently ranked as the most suitable site for subsurface dam construction in all scenarios. This high ranking was mainly attributed to its favorable hydrogeological and geomorphological characteristics, including relatively thick alluvial deposits, substantial subsurface flow availability, moderate slopes, and minimal environmental constraints. Furthermore, its limited negative impact on downstream water users strengthened its environmental and socio-economic acceptability. In contrast, Axis 65 consistently ranked as the least suitable option across all scenarios. The main limiting factors for this site included relatively steep topographic gradients, insufficient aquifer thickness, lower permeability of subsurface materials, and reduced groundwater storage capacity. Sensitivity analysis of the five scenarios indicated that groundwater quantity-related criteria had the greatest influence on site prioritization outcomes, followed by reservoir characteristics such as sediment thickness, permeability, and storage capacity. Socio-economic criteria, including accessibility, agricultural water demand, and proximity to settlements, also played a significant role in refining the final rankings. Water quality parameters were particularly important in excluding areas potentially affected by salinity sources, evaporitic formations, or anthropogenic contamination. The integration of GIS with AHP proved to be a powerful approach for managing complex spatial decision problems. The scenario-based approach further enhanced model reliability by demonstrating that the final ranking was not overly sensitive to minor changes in weighting assumptions.

Conclusion:
This study demonstrated that integrating GIS-based spatial analysis with the AHP provides an effective and reliable framework for identifying and prioritizing subsurface dam sites in complex hydrogeological environments. Applying this methodology in the Shahrekord watershed led to the identification of 12 suitable candidate axes and their evaluation under five different decision-making scenarios. The results consistently identified Axis 54 as the most suitable location, while Axis 65 was determined to be the least suitable due to its unfavorable structural and hydraulic characteristics. Overall, the findings indicated that hydrogeological parameters, particularly groundwater availability and aquifer storage characteristics, were the dominant factors influencing site suitability for subsurface dams. The proposed approach offers a transferable decision-support framework that can be applied to other arid and semi-arid regions.
Keywords
Subjects

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  • Receive Date 24 June 2026
  • Revise Date 22 July 2026
  • Accept Date 22 July 2026
  • Publish Date 22 June 2026