Sequential analysis of hydrochemical data for watershed characterization.

Area of Science:

• Hydrogeology
• Geochemistry
• Environmental Science

Background:

• Understanding watershed hydrogeology is crucial for water resource management.
• Characterizing groundwater flow paths and water quality is essential for assessing anthropogenic impacts.

Purpose of the Study:

• To present an integrated methodology for watershed hydrogeology characterization.
• To utilize hydrochemical data combined with statistical, geochemical, and spatial techniques.
• To differentiate natural hydrochemical processes from anthropogenic influences.

Main Methods:

• Hierarchical cluster analysis for sample classification.
• Principal Component Analysis (PCA) for identifying sources of variation.
• PHREEQC modeling for quantitative hydrochemical evolution analysis.
• Spatial analysis of seasonal water chemistry changes.

Main Results:

• Hydrochemical clusters show geological basis and correspond to topographic flowpaths.
• Fractured rock aquifers can be modeled as equivalent porous media at the watershed scale.
• PCA identified natural weathering (Ca, Mg, SO4, HCO3) and anthropogenic impacts (pH, NO3, Cl).
• Seasonal analysis improved characterization of vertical hydraulic conductivity variability.

Conclusions:

• The integrated method effectively characterizes watershed hydrogeology using traditional data.
• The approach provides a robust framework for differentiating natural and anthropogenic water chemistry signatures.
• This methodology enhances the understanding of watershed-scale aquifer behavior and water quality dynamics.