A risk index for characterising flow pattern in soils using dye tracer distributions

Area of Science:

• Environmental Science
• Hydrogeology
• Soil Physics

Background:

• Assessing groundwater vulnerability to pollutants is crucial for environmental protection.
• Existing methods may not fully capture the complex dynamics of contaminant transport.
• Extreme value theory provides a framework for analyzing extreme events, applicable to contaminant plumes.

Purpose of the Study:

• To define and validate a novel risk index for groundwater vulnerability.
• To utilize Pareto distribution and dye tracer experiments for risk assessment.
• To investigate the index's properties using Monte Carlo simulations and real-world data.

Main Methods:

• Definition of a risk index based on the form parameter of the Pareto distribution.
• Estimation of the index using data from dye tracer experiments.
• Monte Carlo simulations employing Gaussian random fields to model contaminant pathways.
• Application to three soil profiles from Brilliant Blue tracer experiments at ETH Zurich.

Main Results:

• A single soil profile can be reasonably characterized by the proposed risk index.
• The Pareto distribution effectively models extreme value behavior in contaminant transport.
• High variability in dye tracer profiles necessitates a minimum of 15 profiles for robust soil characterization.

Conclusions:

• The novel risk index offers a promising approach to quantifying groundwater vulnerability.
• The method, grounded in extreme value theory, provides valuable insights into pollutant transport.
• Sufficient sampling (≥15 profiles) is essential for reliable risk assessment in heterogeneous soils.