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Integrated hydrogeochemical and spatial assessment of groundwater quality using multivariate statistics and GIS: a case study from northeastern Iran

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Publicado en:Environmental Systems Research vol. 14, no. 1 (Dec 2025), p. 19
Autor principal: Tajbakhshian, Maryam
Publicado:
Springer Nature B.V.
Materias:
Iran
Geology
Hydrogeochemistry
Groundwater flow
Surface water
Principal components analysis
Physicochemical properties
Aquifers
Groundwater quality
Environmental policy
Groundwater
Variability
Multivariate analysis
Resource management
Water quality
Precipitation
Hydrogeology
Statistical methods
Aquifer systems
Multivariate statistical analysis
Arid regions
Environmental regulations
Arid zones
Fault lines
Environmental risk
Water sampling
Water analysis
Statistical analysis
Maps
Monitoring
Groundwater recharge
Case studies
Cluster analysis
Permeability
Recharge
Environmental monitoring
Environmental
Acceso en línea:Citation/Abstract
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Resumen:Effective monitoring and assessment of groundwater quality are essential for sustainable resource management in arid regions. This study investigates the hydrogeochemical variability and environmental risks associated with groundwater in the Neyshabur Plain, northeastern Iran, as a semi-arid basin under climatic pressures. To clarify spatial variability, the study distinguishes between groundwater inside the main aquifer, representing extraction zones, and outside areas that mainly serve as recharge regions. This separation improves the interpretation of quality patterns and management strategies. A total of 1137 groundwater samples were analyzed to assess physicochemical parameters, major ion composition, and spatial trends across two hydrogeological domains: inside and outside the main aquifer system. Multivariate statistical methods (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) were applied separately for each zone to identify dominant geochemical processes and classify water types. A customized groundwater quality index (GWQI) was developed based on normalized variable loadings and used to map quality gradients using ordinary kriging in a GIS framework. Hydrochemical facies analysis, ion ratio plots, and spatial GWQI maps revealed that more than 70% of samples inside the aquifer fall into poor or very poor quality classes, driven by evaporative dissolution and over-extraction. In contrast, recharge zones show better quality, dominated by carbonate weathering and shorter residence time. The integrated approach provides a replicable model for groundwater quality monitoring and decision-support in data-scarce arid environments. The findings can inform regional environmental policies by identifying vulnerable zones, supporting zoning-based regulation of groundwater abstraction, and prioritizing recharge interventions for long-term aquifer sustainability.
ISSN:2193-2697
DOI:10.1186/s40068-025-00412-8
Fuente:Publicly Available Content Database