ارزیابی آسیب‌پذیری کیفی آب‌های زیرزمینی به آلودگی نیترات تحت تأثیر تغییر اقلیم با استفاده از مدل DRASTIC و سامانه اطلاعات جغرافیایی (GIS) در دشت اصفهان

Abstract
Objective: This study aimed to evaluate the vulnerability of groundwater quality in the Isfahan Plain aquifer to nitrate contamination under climate change using the DRASTIC model integrated into a Geographic Information System (GIS) framework.
Method: To achieve this objective, the seven principal DRASTIC parameters, including depth to groundwater, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity, were analyzed. Climate data were derived from CMIP6 global climate models under the RCP4.5 and RCP8.5 scenarios and were subsequently incorporated to adjust the climate-sensitive parameters of the vulnerability model.
Results: The results indicated that the DRASTIC vulnerability index under baseline conditions ranged from 83 to 218, with approximately 23% of the plain classified as having high to very high vulnerability. A correlation coefficient of 0.84 was obtained between the vulnerability index and measured nitrate concentrations, demonstrating the strong predictive capability of the model in identifying contamination-prone areas. Projections for the year 2050 revealed that the vulnerability index is expected to increase by approximately 9% under the RCP4.5 scenario and by 17% under the RCP8.5 scenario. This increase is primarily attributed to reduced precipitation, declining groundwater levels, and decreased natural aquifer recharge.
Conclusion: The findings suggest that climate change is likely to exacerbate nitrate contamination risks and threaten the long-term groundwater quality sustainability of the Isfahan Plain aquifer. Therefore, implementing policies aimed at reducing nitrogen fertilizer application, optimizing cropping patterns, and establishing continuous nitrate monitoring systems in high-risk areas should be prioritized within regional water resources management strategies.
 
English Extended Abstract
Introduction
Groundwater constitutes the principal source of water supply for domestic, agricultural, and industrial purposes in the arid and semi-arid regions of Iran. Over recent decades, rapid agricultural expansion, excessive application of nitrogen-based fertilizers, and continuous population growth have significantly increased nitrate contamination in many aquifer systems. The Isfahan Plain, located in central Iran, is among the country's most important and intensively exploited aquifers.
This aquifer is currently experiencing severe groundwater depletion accompanied by elevated nitrate concentrations. In addition to anthropogenic pressures, climate change has further exacerbated groundwater vulnerability through alterations in precipitation and temperature regimes, thereby affecting groundwater recharge, evapotranspiration rates, and contaminant transport processes.
Assessing the spatial and temporal vulnerability of groundwater resources to nitrate contamination under changing climatic conditions is therefore crucial for sustainable water resources management. Among the available assessment approaches, the DRASTIC model, developed by the U.S. Environmental Protection Agency (EPA), is one of the most widely adopted index-based methods for evaluating intrinsic groundwater vulnerability. When integrated with Geographic Information Systems (GIS), the DRASTIC model provides an effective framework for spatial analysis and the identification of areas susceptible to groundwater contamination.
The present study aims to assess the groundwater quality vulnerability of the Isfahan Plain aquifer to nitrate contamination under both current and projected climate conditions. To this end, the DRASTIC model was implemented within a GIS environment, and its climate-sensitive parameters were modified using projections derived from CMIP6 climate models under the RCP4.5 and RCP8.5 scenarios. The specific objectives of this study are to develop groundwater vulnerability maps for present and future conditions, identify contamination-prone areas, and propose practical management strategies to mitigate nitrate pollution and enhance the long-term protection and sustainability of groundwater resources in the region.
 
Method
The DRASTIC model, originally developed by the U.S. Environmental Protection Agency (EPA), was employed to evaluate the susceptibility of groundwater resources in the Isfahan Plain to nitrate contamination. This widely used index-based approach assesses intrinsic groundwater vulnerability through seven hydrogeological and environmental parameters: depth to groundwater (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of the vadose zone (I), and hydraulic conductivity (C). Each parameter was assigned a specific rating and weight according to its relative contribution to contaminant transport and attenuation processes within the subsurface environment. The overall DRASTIC Index (DI) was calculated using a weighted linear combination of the seven parameters.
The datasets required for model implementation were obtained from various national and regional sources. Groundwater level data were acquired from the Isfahan Regional Water Authority, while historical climatic records were obtained from the Iran Meteorological Organization. Future climate projections were derived from CMIP6 climate models. Soil and aquifer characteristics were extracted from the Natural Resources Organization and FAO databases.
In addition, a Shuttle Radar Topography Mission (SRTM) digital elevation model with a spatial resolution of 30 m was utilized to derive slope and topographic characteristics. All spatial datasets were processed, standardized, converted into raster format, and integrated within the ArcGIS 10.x environment using the Weighted Overlay technique.
To evaluate the potential impacts of climate change on groundwater vulnerability, future precipitation and temperature projections for the 2050 horizon were extracted under the RCP4.5 and RCP8.5 emission scenarios. The projected climatic changes were incorporated into the DRASTIC framework by modifying the climate-sensitive parameters, particularly net recharge (R) and depth to groundwater (D), to represent anticipated changes in recharge conditions and groundwater levels. Consequently, separate vulnerability maps were generated for the baseline period (2010–2020) and for future conditions under both climate scenarios.
Model validation was conducted through statistical comparison between the calculated DRASTIC vulnerability indices and observed nitrate concentrations obtained from 32 monitoring wells distributed throughout the study area. The predictive performance of the model was assessed using Pearson’s correlation coefficient, complemented by spatial correspondence analysis between identified high-vulnerability zones and measured nitrate concentrations.
 
Results
The DRASTIC model results under baseline climatic conditions (2010–2020) indicated that the groundwater vulnerability index (DI) across the Isfahan Plain ranged from 83 to 218. According to the standard DRASTIC classification, approximately 23% of the study area was classified as high or very high vulnerability. Spatial analysis conducted in the GIS environment revealed a distinct north-to-south decline in vulnerability levels, with the highest indices concentrated in the northern and northeastern sectors of the plain, particularly in the Khorasgan, Dolatabad, and Borkhar regions.
Sensitivity analysis demonstrated that depth to groundwater (D) and net recharge (R) were the most influential parameters affecting groundwater vulnerability, contributing approximately 28% and 24% of the total model variance, respectively. Validation of the model outputs against observed nitrate concentrations from 32 monitoring wells revealed a strong positive correlation (r = 0.84, p < 0.01), indicating a high degree of agreement between the predicted vulnerability patterns and actual groundwater quality conditions. These results confirm the robustness and predictive capability of the DRASTIC model for identifying nitrate-prone areas within the study region.
To assess the potential impacts of climate change, the DRASTIC model was recalculated using temperature and precipitation projections derived from CMIP6 climate models under the RCP4.5 and RCP8.5 scenarios for the mid-century period (2050). The projections indicated an average annual temperature increase of approximately 1.8 °C under RCP4.5 and 3.4 °C under RCP8.5, accompanied by reductions in annual precipitation of 12% and 25%, respectively.
These climatic changes resulted in lower groundwater recharge rates and a progressive decline in groundwater levels, with the depth to groundwater increasing by approximately 0.2–0.4 m yr⁻¹. Consequently, the mean DRASTIC vulnerability index increased by approximately 9% under the RCP4.5 scenario and 17% under the RCP8.5 scenario relative to baseline conditions.
The generated vulnerability maps revealed a substantial expansion of high-risk areas under future climate scenarios. The proportion of the plain classified as highly vulnerable increased from 23% under current conditions to more than 40% under the RCP8.5 scenario. The most pronounced increases were observed in the northern and central parts of the aquifer, where intensive agricultural activities combined with relatively shallow groundwater levels enhance nitrate leaching and contaminant migration. In contrast, the southern portions of the plain exhibited comparatively lower vulnerability due to deeper groundwater tables and the predominance of fine-grained, clay-rich soils that reduce contaminant transport.
Overall, the findings suggest that climate change is likely to not only intensify nitrate contamination risks but also alter the spatial distribution of groundwater vulnerability across the Isfahan Plain aquifer, thereby increasing the complexity of future groundwater management and protection strategies.
 
Conclusion
The findings of this study demonstrate that the integration of the DRASTIC model with GIS, combined with climate change projections, provides a robust and reliable framework for evaluating groundwater vulnerability to nitrate contamination under both current and future environmental conditions.
The Isfahan Plain aquifer, one of the most strategically important groundwater resources in central Iran, exhibited vulnerability levels ranging from moderate to very high, with approximately 23% of the study area classified as highly vulnerable under baseline conditions. The strong correlation observed between the DRASTIC vulnerability index and measured nitrate concentrations (r = 0.84) further confirms the model’s effectiveness in identifying contamination-prone zones.
Future climate projections indicate that groundwater vulnerability is likely to increase substantially by 2050. The average DRASTIC Index is projected to rise by approximately 9% under the RCP4.5 scenario and 17% under the RCP8.5 scenario, primarily as a consequence of reduced groundwater recharge and declining groundwater levels. The projected expansion of highly vulnerable areas, particularly in the northern and central sectors of the plain, highlights the increasing threat of nitrate contamination under future climatic conditions.
These findings underscore the necessity of adopting adaptive and proactive groundwater management strategies to address the combined pressures of climate change and anthropogenic activities. Priority actions should include optimizing nitrogen fertilizer application, promoting the use of slow-release fertilizers, enhancing irrigation management practices, and establishing continuous groundwater quality monitoring networks supported by GIS-based decision-support systems.
Incorporating vulnerability assessments into regional water resources planning can improve the resilience, sustainability, and long-term protection of groundwater resources, thereby supporting water security in arid and semi-arid regions facing increasing environmental stress.