Uncertainty estimation of pathlines in ground water models

Area of Science:

• Hydrogeology
• Groundwater Modeling
• Computational Fluid Dynamics

Background:

• Estimating uncertainty in groundwater flow pathlines is crucial for accurate resource management and risk assessment.
• Existing methods often simplify aquifer properties, limiting their applicability to complex hydrogeological settings.
• Spatially variable hydraulic conductivity and transmissivity fields introduce significant uncertainty in particle tracking.

Purpose of the Study:

• To develop and validate a novel method for estimating pathline location uncertainty in 2D steady-state groundwater flow.
• To reformulate existing semianalytical first-order theory to incorporate nonuniform recharge and aquifer thickness.
• To apply the method for uncertainty estimation of pumping well catchment zones.

Main Methods:

• Utilizes a reformulated semianalytical first-order theory to estimate the lateral second moment (variance) of particle location.
• Accounts for spatial variability using an isotropic exponential covariance function of log-transformed hydraulic conductivity/transmissivity.
• Employs advective transport and backtracking with reversed velocity fields for well catchment analysis; developed the PPPath postprocessing code.

Main Results:

• The proposed method successfully estimates pathline uncertainty, even with nonuniform recharge and aquifer thickness.
• Application to pumping well catchments, using results from Monte Carlo simulations, shows good correspondence.
• The PPPath code effectively postprocesses pathline computations from groundwater models like MODFLOW.

Conclusions:

• The developed method provides a robust framework for quantifying pathline uncertainty in heterogeneous aquifers.
• This approach enhances the reliability of groundwater model predictions, particularly for well capture zone delineation.
• The methodology is practical and applicable to real-world aquifer systems.