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Programs for calibration-based Monte Carlo simulation of recharge areas
J Jeffrey Starn1, Amvrossios C Bagtzoglou
1University of Connecticut, Department of Civil and Environmental Engineering, Storrs, CT 06269, USA. jjstarn@usgs.gov
Ground Water
|October 5, 2011
Summary
This study introduces Python scripts for Monte Carlo simulations to improve groundwater recharge area accuracy. The method enhances well capture zone reliability by incorporating parameter uncertainties from model calibration.
Area of Science:
- Hydrogeology
- Computational Modeling
Background:
- Groundwater flow models are crucial for simulating recharge areas to wells and springs.
- Uncertainties in model parameters like hydraulic conductivity and recharge affect the accuracy of simulated recharge areas.
- Particle tracking is a common method for simulating these areas, but its reliability is often questioned due to parameter errors.
Purpose of the Study:
- To develop and present Python scripts (GEN_LHS and MCDRIVER_LHS) for running Monte Carlo simulations.
- To quantify the uncertainty in simulated groundwater recharge areas by incorporating parameter variability.
- To calculate the probability of particles reaching a well's contributing area considering parameter errors.
Main Methods:
- Utilizing Latin hypercube sampling within a Monte Carlo simulation framework.
- Randomly varying key model parameters, including hydraulic conductivity and recharge rates, across numerous simulations.
- Employing parameter sets derived from nonlinear regression calibration, including optimal parameters, standard deviations, and correlation matrices.
- Implementing acceptance criteria to filter out unrealistic parameter sets.
Main Results:
- Monte Carlo simulation provides a robust measure of variability in modeled particle paths.
- The developed scripts enable probabilistic assessment of well capture zones.
- The method uniquely integrates calibration-derived parameter statistics for more realistic uncertainty analysis.
Conclusions:
- The described Monte Carlo approach enhances the reliability of simulated groundwater recharge areas.
- This method offers a more accurate understanding of well capture zone variability by accounting for parameter uncertainties.
- The Python scripts provide a practical tool for modelers to assess and improve the accuracy of groundwater flow model outputs.
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