Preprints
https://doi.org/10.5194/hess-2023-268
https://doi.org/10.5194/hess-2023-268
11 Dec 2023
 | 11 Dec 2023
Status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

A Comprehensive Framework for Stochastic Calibration and Sensitivity Analysis of Large-Scale Groundwater Models

Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva

Abstract. We introduce a comprehensive and robust theoretical framework and operational workflow that can be employed to enhance our understanding, modeling and management capability of complex heterogeneous large-scale groundwater systems. Our framework encapsulates key components such as the three-dimensional nature of groundwater flows, river-aquifer interactions, probabilistic reconstruction of three-dimensional spatial distributions of geomaterials and associated properties across the subsurface, multi-objective optimization for model parameter estimation through stochastic calibration, and informed global sensitivity analysis. By integrating these components, we effectively consider the inherent uncertainty associated with subsurface system characterizations as well as their interactions with surface water bodies. The approach enables us to identify parameters impacting diverse system responses. By employing a coevolutionary optimization algorithm, we ensure efficient model parameterization, facilitating simultaneous and informed optimization of the defined objective functions. Additionally, estimation of parameter uncertainty naturally leads to quantification of uncertainty in system responses. The methodology is designed to increase our knowledge of the dynamics of large-scale groundwater systems. It also has the potential to guide future data acquisition campaigns through the informed global sensitivity analysis. We demonstrate the effectiveness of our proposed methodology by applying it to the largest groundwater system in Italy. The system considered faces multiple challenges, including groundwater contamination, sea water intrusion, and water scarcity. Our study offers a promising modeling strategy applicable to large-scale subsurface systems and valuable insights into groundwater flow patterns that can then inform effective system management.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-268', Anonymous Referee #1, 14 Jan 2024
    • AC1: 'Reply on RC1', Monica Riva, 27 Feb 2024
  • RC2: 'Comment on hess-2023-268', Anonymous Referee #2, 01 Feb 2024
    • AC2: 'Reply on RC2', Monica Riva, 27 Feb 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-268', Anonymous Referee #1, 14 Jan 2024
    • AC1: 'Reply on RC1', Monica Riva, 27 Feb 2024
  • RC2: 'Comment on hess-2023-268', Anonymous Referee #2, 01 Feb 2024
    • AC2: 'Reply on RC2', Monica Riva, 27 Feb 2024
Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva
Andrea Manzoni, Giovanni Michele Porta, Laura Guadagnini, Alberto Guadagnini, and Monica Riva

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Short summary
We introduce a comprehensive methodology that combines multi-objective optimization, Global Sensitivity Analysis and three-dimensional groundwater modeling to analyze subsurface flow dynamics across large-scale domains. In this way, we effectively consider the inherent uncertainty associated with subsurface system characterizations and their interactions with surface water bodies. We demonstrate the effectiveness of our proposed approach by applying it to the largest groundwater system in Italy.