Caravan-Qual (lite): A global scale integration of water quality observations into a large sample hydrology dataset
Authors/Creators
Description
Caravan-Qual is an open access dataset that brings water quality to the research paradigm of large sample hydrology (LSH), integrating daily water quality data from 100 constituents with catchment attributes, meteorological forcing and co-located streamflow observations.
The dataset is currently under submission at Scientific Data. A preprint can be found here.
We envisage the dataset to facilitate research into topics including:
- Spatio-temporal analysis of river water quality dynamics at regional to global scales.
- Investigation of the relationships between (constituent-specific) water quality responses and hydrological, meteorological and catchment characteristics.
- The development and evaluation of process-based, hybrid and data-driven water quality models across diverse hydrological and climatic conditions.
Please note that, due to data storage restrictions, only monthly weather data is stored on Zenodo (in Caravan-Qual_weather_monthly.zarr.zip) and is stored seperately to the daily water quality data and catchment attributes (in Caravan-Qual_lite.zarr.zip). All water quality data (combined with streamflow observations with a 10km distance threshold) are also provided as .csv files.
The 'full' Caravan-Qual dataset (i.e., including daily weather data) and the auxilliary data required for extending the dataset can be accessed here. The most up-to-date developments are documented on Caravan-Qual's GitHub page. The original Caravan paper can be accessed here, while developments and community extensions are documented on Caravan's GitHub page.
Files
wqms-csv.zip
Files
(1.6 GB)
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Additional details
Related works
- Continues
- Journal article: 10.1038/s41597-023-01975-w (DOI)
- Dataset: 10.5281/zenodo.15529786 (DOI)
Funding
Software
- Repository URL
- https://github.com/SustainableWaterSystems/Caravan-Qual
- Programming language
- Python , Shell
- Development Status
- Active