Pastas: Open Source Software for the Analysis of Groundwater Time Series

Area of Science:

• Hydrogeology
• Data Science
• Environmental Science

Background:

• Time series analysis is crucial for understanding groundwater dynamics.
• Analyzing observation well data helps quantify environmental stress impacts.
• Existing tools may lack flexibility or reproducibility for hydrogeological analysis.

Purpose of the Study:

• Introduce Pastas, an open-source Python package for hydrogeological time series.
• Provide a reproducible scientific framework for developing and testing new analysis methods.
• Offer a reliable software tool for groundwater practitioners.

Main Methods:

• Utilizes transfer function noise modeling with predefined response functions (e.g., Gamma function for rainfall).
• Employs a seven-step scripting process for model creation, parameter estimation, and analysis.
• Applies the package to analyze rainfall and evaporation impacts on groundwater levels and well field drawdown.

Main Results:

• Demonstrates the application of Pastas to model groundwater head fluctuations using real-world data.
• Successfully applies batch processing for analyzing multiple observation wells.
• Highlights the reproducibility and transparency of the modeling process through scripts.

Conclusions:

• Pastas provides a robust and accessible platform for hydrogeological time series analysis.
• The package facilitates reproducible research and practical application in groundwater management.
• Open-source availability promotes collaboration and further development in the field.