Extended Abstract
Introduction

Groundwater is a crucial freshwater source globally, particularly in arid and semi-arid regions like the Ardabil Plain in northwestern Iran, where it sustains domestic, agricultural, and industrial demands (Asadi et al., 2019). However, escalating population, intensified land use, and climate variability increasingly strain both the quantity and quality of groundwater resources (Danielopol et al., 2003). The quality of groundwater is shaped by natural influences such as geological formations, rainfall, and evaporation, alongside human-induced impacts including pollution infiltration and overextraction (Lan et al., 2023). Degradation of groundwater quality can threaten public health, agriculture, and ecosystems (Kupa et al., 2024), highlighting the need for consistent monitoring and evaluation.
Numerous investigations have identified significant water quality threats across Iran. In central and southern plains like Beheshtabad, seasonal contamination—especially in the rainy period—impairs drinking water due to pollutant wash-off entering aquifers (Gharahi & Zamani-Ahmadmahmoodi, 2020). Ardabil province, similarly, has exhibited low Groundwater Quality Index (GWQI) values with elevated concentrations of TDS, sulfate, and chloride, raising concerns over water safety (Azizi et al., 2018). Related studies in Isfahan and Rafsanjan have also pointed to heightened salinity and sodium content as key limitations for potable and agricultural uses (Hosseininia & Hassanzadeh, 2023). Hydrogeochemical tools such as Piper diagrams have revealed controlling processes like rock weathering and Na-SO4 dominance, particularly in areas such as northern Isfahan (Rezaei & Hassani, 2018). Additionally, incorporating Water Quality Indices (WQIs) with GIS techniques has proven effective for agricultural water quality zoning, as demonstrated in the Isfahan desert, where considerable quality challenges were mapped (Zamani et al., 2018).
Groundwater contamination results from both human activities—particularly agricultural runoff containing fertilizers and pesticides (Basharat et al., 2023; Jibitha & Joseph, 2023)—and natural factors such as mineral dissolution from local lithology. Industrial waste contributes toxic elements including arsenic and cadmium (Kayastha et al., 2022; Khelfi, 2019), while landfill leachate and urban waste exacerbate pollution levels (Hou et al., 2024; Jibitha & Joseph, 2023). Geogenic factors, especially in areas with gypsum or salt deposits, can also lead to elevated hardness and salinity levels (Basharat et al., 2023). Coastal regions face additional risks from seawater intrusion. While anthropogenic impacts often dominate, natural contributions are also significant and must be addressed.
This study presents a detailed assessment of groundwater quality in the Ardabil Plain by integrating multivariate statistical methods—Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA)—with the Iran-specific IRWQIGT index, designed to evaluate drinking water suitability. This comprehensive framework allows for spatial differentiation of water quality patterns and identification of major hydrogeochemical drivers, offering a clearer understanding of aquifer health in the region.

Materials and Methods
Study Area

The Ardabil Plain, encompassing around 1,500 km² in Ardabil province, is underlain by Quaternary alluvial deposits that serve as key aquifers. The semi-arid climate features warm, dry summers and cold, wet winters. Agriculture (particularly grains, potatoes, and fruit orchards) and livestock farming form the region’s economic backbone. Sampling locations and regional maps are illustrated in Figure 1 of the main article.
Data Collection and Parameters
Groundwater quality data were obtained from 26 operational wells monitored by the Ardabil Regional Water Organization. These samples were collected in spring 1403 (spring 2024) in accordance with Iranian EPA standards (2016). Measured parameters included: Electrical Conductivity (EC), sulfate (SO₄), pH, Total Dissolved Solids (TDS), calcium (Ca), magnesium (Mg), nitrate (NO₃), lead (Pb), cadmium (Cd), arsenic (As), bicarbonate (HCO₃), sodium (Na), potassium (K), and chloride (Cl). An ionic balance test was performed to ensure data reliability; wells with a balance error above ±5% were excluded, leaving 26 wells for analysis.
Statistical Analysis and IRWQIGT Index
Data analysis was conducted using Python. Descriptive statistics were computed, followed by HCA (using Ward’s linkage and Euclidean distance) and PCA to detect patterns and key influencing factors in the water quality dataset. To evaluate drinking suitability, the IRWQIGT index was applied, which consists of:
1. Parameter Selection and Weighting – Ten key parameters were assigned weights based on their relative importance in drinking water (Table 3).
2. Sub-index Value Determination – Standardized curves were used to derive sub-index values for each parameter.
3. Final Index Computation – The overall index was calculated via the weighted geometric mean.

Results and Discussion

Descriptive Statistics and Spatial Variation
Table 4 details the descriptive statistics of the water quality parameters. Spatial variation across the Ardabil Plain (Figure 2) revealed that high-range parameters (EC, TDS, SO₄, Cl, HCO₃) were elevated in the south. Mid-range ions (Ca, Mg, K, Na, NO₃) also peaked in southern areas, with high nitrate likely linked to agricultural leaching. Heavy metals and pH displayed regional variability; Cd levels were higher in the north, suggesting localized contamination.
Hierarchical Cluster Analysis (HCA)
HCA grouped the 26 wells into three clusters (Figure 3). Cluster 1 (wells 1–16) exhibited low salinity and covered most of the northern and central plain. Clusters 2 and 3, composed of high-salinity wells predominantly located in the south, differed in chemical composition, reflecting distinct hydrogeochemical conditions (Figure 4).
Principal Component Analysis (PCA)
Two main components explained 75% of the variance. PC1, associated with salinization and mineralization, had strong loadings for EC, TDS, SO₄, Na, Cl, and divalent cations, as well as Pb—suggesting both natural sources and possible contamination. PC2, representing anthropogenic inputs, showed high contributions from K, Cd, As, and a negative correlation with pH—indicating pollution from fertilizers and industrial activities. Figure 5 displays the PCA score plot, showing clear spatial distinctions aligned with regional zoning.
IRWQIGT Zonation
According to Figure 6, the IRWQIGT-based classification showed that 50% of the area was of "poor" quality, and 27% was "very poor," predominantly in the south and southeast. Only 4% in the northern area was rated "very good." This spatial trend reflects worsening water quality towards the southern part of the plain.

Conclusion

Ardabil Plain's groundwater quality is influenced by combined natural hydrogeochemical processes (primarily salinization and mineralization) and anthropogenic activities. While natural processes are primary drivers, increasing human impacts, especially from agriculture (elevated nitrate, potassium) and potential industrial/urban pollution (heavy metal contamination), are significant concerns. A substantial portion of the aquifer, especially in southern/southeastern areas, has poor to very poor water quality, posing health risks if used untreated for drinking and limiting agricultural suitability. Given growing water demand and limited surface water, protecting the Ardabil Plain aquifer is crucial. Integrated water resource management, continuous monitoring, and a thorough understanding of hydrogeochemical processes are essential for sustainable groundwater utilization.