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Related Experiment Videos

A methodology for validating numerical ground water models.

Ahmed E Hassan1

  • 1Division of Hydrologic Sciences, Desert Research Institute, 755 E. Flamingo Road, Las Vegas, NV 89119, USA. hassan@dri.edu

Ground Water
|May 27, 2004
PubMed
Summary
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A new general approach enhances ground water model validation by iteratively linking model building, calibration, and evaluation. This method builds confidence in predictions for regulatory acceptance.

Area of Science:

  • Hydrogeology
  • Environmental Modeling
  • Geoscience

Background:

  • Ground water model validation presents significant challenges for modelers and hydrogeologists.
  • Increasing model complexity widens the gap between predictions and validation capabilities.
  • A lack of standardized, adaptable procedures hinders site-specific ground water model validation.

Purpose of the Study:

  • To propose a general validation approach for ground water models, addressing recognized issues in previous studies.
  • To link model building, calibration, evaluation, and validation processes in an iterative framework.
  • To enhance confidence in model predictions for regulatory and public acceptance.

Main Methods:

  • Development of an iterative loop connecting model building, calibration, evaluation, and validation.

Related Experiment Videos

  • Focus on utilizing validation data to reduce model uncertainty and narrow outcome ranges.
  • Adaptable methodology designed for stochastic numerical models (Monte Carlo) but applicable to deterministic models.

    • Main Results:

    • The proposed methodology emphasizes rigorous testing and diverse statistical tools for model checking.
    • It acknowledges that absolute model validity is not theoretically possible or a regulatory necessity.
    • The approach aims to build confidence in model predictions, facilitating acceptance of decisions.

    Conclusions:

    • The developed validation approach provides a structured framework for assessing ground water models.
    • It promotes a shift from seeking absolute validity to building justifiable confidence in model predictions.
    • Application to an underground nuclear test site model in Nevada demonstrates practical utility.