پتانسیل‌سنجی مناطق مستعد آلودگی منابع آب زیرزمینی (مطالعه موردی: حوضه آبخیز رازآور)

Karstic areas are at risk of groundwater contamination due to their high permeability. One of the areas facing this problem is the Razavar basin between Kurdistan and Kermanshah provinces. Given the importance of the issue, this study has identified areas susceptible to groundwater contamination in the Razavar basin. In this research, the 1:100,000 digital geological map layer of the region, the 30-meter SRTM elevation model, and Sentinel 1 satellite images were used as the most important research data. The most important research tools were ArcGIS, TerrSet, and Google Earth Engine. Also, in this research, the AHP, WLC, and OWA analysis models were used to identify areas susceptible to groundwater pollution. Based on the results obtained from the WLC model, 15.9 and 30.5 percent of the basin are in the very high and high vulnerability potential classes, respectively. In addition, based on the results obtained from the OWA model, 12.1 and 27.3 percent of the basin are in the very high and high vulnerability potential classes, respectively. The results of the spatial analysis of the pollution-prone areas also showed that, in a general trend, the middle areas of the Razavar basin have a high potential for groundwater pollution due to the type of lithology, proximity to the river and main roads, as well as the low altitude and slope.
 
Extended Abstract
 
Introduction
Groundwater resources, particularly karst aquifers, play a crucial role in supplying water for domestic, agricultural, and industrial purposes. However, characteristics such as high secondary porosity, complex networks of fractures, joints, and underground conduits, high flow velocities, and short residence times increase the vulnerability of these resources to contamination. In karst environments, pollutants originating from domestic and industrial wastewater and agricultural runoff can rapidly infiltrate aquifers, thereby threatening groundwater quality. The Razavar Watershed, located between Kamyaran and Kermanshah, is considered one of the areas in the Zagros region susceptible to groundwater contamination due to its karst formations, high density of settlements, agricultural and industrial activities, and inadequate wastewater collection and treatment systems. Despite the importance of these resources, comprehensive studies on the vulnerability and contamination potential of aquifers in this watershed remain limited and have mainly focused on water-quality assessment or cross-sectional analyses. Therefore, this study aimed to assess the contamination potential and identify areas susceptible to groundwater contamination in the Razavar Watershed. To this end, hydrogeological, geological, and land-use data were integrated to evaluate different zones in terms of their degree of vulnerability and contamination potential, and an aquifer vulnerability map was subsequently developed. The results of this assessment can provide a scientific basis for identifying critical areas, prioritizing protective measures, and strengthening groundwater monitoring and sustainable management programs in the Razavar Watershed.
 
Methodology
In this study, a 1:100,000-scale geological map, a 30-m SRTM digital elevation model (DEM), and Sentinel-1 satellite imagery were used to identify areas vulnerable to groundwater contamination. Data processing was performed using ArcGIS, TerrSet, and Google Earth Engine. Eight parameters, including lithology, distance from faults, elevation, slope, distance from settlements, major roads, and rivers, and land use, were selected for vulnerability assessment and standardized on a scale from 0 to 1. Subsequently, the criteria were weighted based on expert judgment using the Analytic Hierarchy Process (AHP), and the resulting weights were applied to the thematic layers in Expert Choice. The weighted layers were then integrated in TerrSet using two multi-criteria decision-making methods, Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA), to generate vulnerability maps. The simultaneous application of these two methods was intended to compare the results and increase confidence in identifying areas susceptible to groundwater contamination.
 
Results and Discussion
The results of weighting the criteria using the Analytic Hierarchy Process (AHP) showed that distance from rivers and lithology, with weights of 0.212 and 0.178, respectively, were the most important factors influencing the groundwater contamination potential in the Razavar Watershed. The integration of the thematic layers using the WLC and OWA methods indicated that the central parts of the watershed had the highest contamination potential due to susceptible lithology, proximity to rivers and major roads, as well as lower elevation and slope. Quantitative results showed that, under the WLC method, areas with high and very high contamination potential covered 712 km², equivalent to 46.3% of the watershed area, whereas under the OWA method, these areas covered 606 km², equivalent to 39.4%. In contrast, areas with low and very low contamination potential were estimated at 396 km² (25.8%) using WLC and 402 km² (26.2%) using OWA. Overall, both methods revealed a similar spatial pattern and identified a substantial proportion of the Razavar Watershed as being exposed to relatively high groundwater contamination potential.
 
Conclusion
The results showed that the Razavar Watershed has a high potential for groundwater vulnerability, with more than 40% of its area falling within the high and very high vulnerability classes. The central parts of the watershed, particularly areas adjacent to rivers and major roads and those characterized by lower elevation and slope, exhibited the greatest sensitivity. This spatial pattern is influenced by geological characteristics, land use, and the density of human activities. Accordingly, strengthening the monitoring of industrial and agricultural activities, managing waste and land-use changes, continuously monitoring water quality, and regularly updating vulnerability maps are among the most important measures for reducing contamination risks and protecting groundwater resources. In addition, restricting development in sensitive zones and increasing local community awareness can contribute to the sustainable management of groundwater resources. Nevertheless, limitations such as the accuracy of elevation and geological data, the inability of the WLC and OWA models to fully capture the complexity of the hydrogeological characteristics of the karst aquifer, and the exclusion of seasonal and climatic variations should be taken into account when interpreting the results.