The CAMELS-CL dataset - links to files
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PANGAEA
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| Autores principales: | , , , , , , , , , , , |
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| Formato: | Dataset Open Access |
| Lenguaje: | en |
| Publicado: |
PANGAEA
2018
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| _version_ | 1867168195265167360 |
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| author | Alvarez-Garreton, Camila Mendoza, Pablo A Boisier, Juan Pablo Addor, Nans Galleguillos, Mauricio Zambrano-Bigiarini, Mauricio Lara, Antonio Puelma, Cristóbal Cortes, Gonzalo Garreaud, Rene McPhee, James Ayala, Alvaro |
| author_facet | Alvarez-Garreton, Camila Mendoza, Pablo A Boisier, Juan Pablo Addor, Nans Galleguillos, Mauricio Zambrano-Bigiarini, Mauricio Lara, Antonio Puelma, Cristóbal Cortes, Gonzalo Garreaud, Rene McPhee, James Ayala, Alvaro |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | CAMELS-CL relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of 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 http://camels.cr2.cl --- 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). |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_894885 |
| institution | PANGAEA |
| language | en |
| publishDate | 2018 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | The CAMELS-CL dataset - links to files Alvarez-Garreton, Camila Mendoza, Pablo A Boisier, Juan Pablo Addor, Nans Galleguillos, Mauricio Zambrano-Bigiarini, Mauricio Lara, Antonio Puelma, Cristóbal Cortes, Gonzalo Garreaud, Rene McPhee, James Ayala, Alvaro Chile_CAMELS; File content; File format; File name; File size; Uniform resource locator/link to file CAMELS-CL relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of 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 http://camels.cr2.cl --- 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). |
| title | The CAMELS-CL dataset - links to files |
| topic | Chile_CAMELS; File content; File format; File name; File size; Uniform resource locator/link to file |
| url | https://doi.org/10.1594/PANGAEA.894885 |