CAMELS-CL is a catchment database that relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of Chile, a region where in situ measurements are scarce. The dataset includes 516 catchments and provides boundaries, daily streamflow records and basin-averaged daily time series of precipitation (from one national and three global datasets), maximum, minimum and mean temperatures, potential evapotranspiration (PET; from two datasets), and snow water equivalent. We calculated hydro-climatological indices using these time series, and leveraged diverse data sources to extract topographic, geological and land cover features. Relying on publicly available reservoirs and water rights data for the country, we estimated the degree of anthropic intervention within the catchments. To facilitate the use of this dataset and promote common standards in large-sample studies, we computed most catchment attributes introduced by Addor et al. (2017) in their Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset (doi:10.5065/D6G73C3Q), and added several others.
CAMELS-CL can be visualised from https://camels.cr2.cl.
Reference: Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817-5846, https://doi.org/10.5194/hess-22-5817-2018, 2018.
This research emerged from the collaboration with many colleagues at the Center for Climate and Resilience Research (CR2, CONICYT/FONDAP/15110009). Camila Alvarez-Garreton was funded by FONDECYT postdoctoral grant no. 3170428. Pablo Mendoza received additional support from FONDECYT postdoctoral grant no. 3170079. Mauricio Zambrano-Bigiarini thanks FONDECYT 11150861 for financial support. The development of CR2MET was supported by the Chilean Water Directorate (DGA), through National Water Balance Updating Project DGA-2319, and by FONDECYT grant no. 3150492. This study is a contribution to the Large-sample Hydrology working group of the Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS).
- Datasets description
- A platform to provide comments, request information and report issues
- Examples
- Codes for computing catchment attributes
- Current applications
- Future work
In this link, you can provide comments, report bugs and errors, request for specific information (e.g., scripts, examples, data sources) and suggest for examples to be published in the repository.
Informing about bugs and errors found while using the dataset is critical for generating improved versions of the dataset. One of the main sources of errors is streamflow gauge locations (see discussion in Alvarez-Garreton et al., (2018)), therefore, if a better location (based on field data) is provided we can update all the information for the corresponding catchment.
- Load and visualise data for single catchment: github example
- Load and visualise data for several catchments
The codes for computing catchment attributes were obtained from Nans Addor Github. These codes were used for computing the CAMELS dataset for the US (Addor et al., 2017)