CAMELS-DE 🌊

A Python package for working with the CAMELS-DE dataset.

About 🐪

CAMELS-DE provides access to hydrometeorological time series data and catchment attributes for 1582 catchments in Germany. This package offers a simple interface for loading, analyzing, and visualizing data from the CAMELS-DE dataset.

Installation

pip install camelsde

Usage

[!IMPORTANT] The package requires the CAMELS-DE dataset to be downloaded and extracted.

CAMELS-DE can be downloaded from Zenodo: 10.5281/zenodo.13837553

• The package uses polars for reading csv files efficiently, but the functions return pandas DataFrames at the moment.
• Gauging station point locations and catchment polygons are returned as geopandas GeodataFrames.
• Interactive time series plots are created using plotly.

Setting the CAMELS-DE Dataset Path

The package will look for the dataset in the following order:

1. path argument passed to the CAMELS_DE class constructor.
2. User-configured permanent path (if set).
3. CAMELSDE_PATH environment variable (if set)

You can set a permanent path to your CAMELS-DE dataset in following ways:

from camelsde import CAMELS_DE, set_camels_path

# Option 1: Temporarily override the path for a specific instance
camelsde = CAMELS_DE(path="/path/to/your/CAMELS_DE_v1_0_0")

# Option 2: Set a permanent path that will be remembered across sessions
set_camels_path("/path/to/your/CAMELS_DE_v1_0_0")

camelsde = CAMELS_DE()  # Now this will use the permanent path

The permanent path is stored in a configuration file in your user config directory, which makes it available across all future Python sessions.

Basic Usage Examples

from camelsde import CAMELS_DE

# Initialize (uses the configured path or default)
camelsde = CAMELS_DE()

# Load static attributes
attributes = camelsde.load_static_attributes()

# Load specific attributes
hydro_attrs = camelsde.load_static_attributes(static_attribute="hydrology")

# Load specific columns across all static attribute files
attributes2 = camelsde.load_static_attributes(columns=["gauge_name", "gauge_elev", "area", "NSE_lstm", "NSE_hbv"])

# Load specific columns and apply filtering
attributes3 = camelsde.load_static_attributes(columns=["gauge_name", "gauge_elev", "area", "NSE_lstm", "NSE_hbv"], filters={"NSE_lstm": (">=", 0.9), "area": [ (">=", 50), ("<=", 100)]})

# Load specific gauge ID
gauge_data = camelsde.load_static_attributes(gauge_id="DE110000")

# Load timeseries data
ts_data = camelsde.load_timeseries(gauge_id="DE110000")

# Plot timeseries with Plotly
camelsde.plot_timeseries(gauge_id="DE110000", columns=["precipitation", "discharge_spec_obs", "discharge_spec_sim_lstm"])

# Load geospatial data (returns a geopandas GeoDataFrame)
catchments = camelsde.load_geopackage(layer="catchments")
stations = camelsde.load_geopackage(layer="gauging_stations")

Dataset

This package works with the CAMELS-DE v1.0.0 dataset, which is publicly available at:

• CAMELS-DE Dataset on Zenodo

The dataset needs to be downloaded and extracted before using this package.

Citation

If you use this package or the CAMELS-DE dataset in your research, please cite both the data description paper and the dataset itself:

• Dataset: CAMELS-DE v1.0.0
• Data description paper: CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany

License

This package is distributed under the CC0 1.0 Universal License. See the LICENSE file for more information.