ipylar 1.0.7

Python utilities for the LAR model (Land Atmospheric Reservoir)

PyLAR

Python utilities for the LAR model

PyLAR is a python package and datasets intended to test and use the LAR (Land-Atmospheric and Reservoir) model. The LAR model is intended to describe the changes in the water storage in large river basin around the world, including atmospheric processes as a critical component of the basin water budget.

For the science behind the LAR model please refer to the following paper:

Juan F. Salazar, Rubén D. Molina, Jorge I. Zuluaga, and Jesus D. Gomez-Velez (2024), Wetting and drying trends in the land–atmosphere reservoir of large basins around the world, Hydrology and Earth System Sciences, HESS, 28, 2919–2947, 2024, doi.org/10.5194/hess-28-2919-2024.

All the notebooks and data required to reproduce the results of this paper, and other papers produced by our group, are available in the dev directory in this repository.

Downloading and Installing PyLAR

PyLAR is available at the Python package index and can be installed using:

$ sudo pip install ipylar

as usual this command will install all dependencies and download some useful data, scripts and constants.

NOTE: If you don't have access to sudo, you can install PyLAR in your local environmen (usually at ~/.local/). In that case you need to add to your PATH environmental variable the location of the local python installation. Add to ~/.bashrc the line export PATH=$HOME/.local/bin:$PATH

Quickstart

To start using PyLAR, you should first obtain data for a large river basin. We have provided with the package a dataset especially prepared for the Amazonas Basin we will use in this quickstart.

You must start by importing the package:

import ipylar as lar

Create a basin:

amazonas = lar.Basin(key='amazonas',name='Amazonas')

Once created, you should read the timeseries for the basin and load it into the pandas dataframe amazonas.data. The present version of PyLAR includes sample data. You may read the sample data using:

amazonas.read_basin_data()

Once the data is loaded you can perform operations on the data, for instance, you can plot it:

fig = amazonas.plot_basin_series()

Tutorials

We have prepared a set of basic tutorials for illustrating the usage of some of the tools including in PyLAR. The tutorials can be ran in Google Colab.

What's new

For a detailed list of the newest characteristics of the code see the file What's new.

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This package has been designed and written by Jorge I. Zuluaga, Ruben D. Molina, Juan F. Salazar and Jesus D. Gomez-Velez (C) 2024