gwrefpy

gwrefpy is an open source Python implementation of the Akvifär reference method for detecting deviations in groundwater level time series. The method is described in detail in Strandanger (2024).

User Guide

User guide on installation and the basic concepts.

User guide

Tutorials

Some tutorials on how to use th epackage.

Tutorials

API Reference

Application programming interface (API) reference.

API Reference

Exercises

A collection of gwrefpy exercises.

Exercises

Key Concepts

Key concepts behind gwrefpy and the Akvifär reference method.

Key concepts

GitHub Repository

The source code for gwrefpy is hosted on GitHub.

https://github.com/andersretznerSGU/gwrefpy

Features

• Programmatically fit observation wells to reference wells

• Visualize fits and deviations

• Save your work, share and pick up later with a custom .gwref file format

• Work with live data and update your analysis as new data comes in

Quick Example

Python

In this example an observation well and reference well are fitted and plotted.

# Import the packages
import gwrefpy as gr
import pandas as pd

# Load timeseries data from CSV files
obs_data = pd.read_csv("obs.csv", index_col="date", parse_dates=["date"]).squeeze()
ref_data = pd.read_csv("ref.csv", index_col="date", parse_dates=["date"]).squeeze()

# Create Well objects and add timeseries data
obs = gr.Well(name="12GIPGW", is_reference=False)
obs.add_timeseries(obs_data)

ref = gr.Well(name="45LOGW", is_reference=True)
ref.add_timeseries(ref_data)

# Create a Model object, add wells, and fit the model
model = gr.Model(name="Small Example")
model.add_well([obs, ref])

model.fit(obs_well=obs, ref_well=ref, offset="0D", tmin="2020-01-01", tmax="2020-03-23")

# Plot the results
model.plot_fits(plot_style="fancy", color_style="color", show_initiation_period=True)

Result