
This is the CAMELS-COL dataset (Catchment Attributes and MEteorology for Large-sample Studies - Colombia) presented in the paper by Jimenez et al., CAMELS-COL: A Large-Sample Hydrometeorological Dataset for Colombia. This dataset provides daily observed streamflow and meteorological time series, along with more than 71 catchment attributes, for 346 river basins across Colombia. The available hydrometeorological time series include:(i) observed streamflow with quality control metadata,(ii) potential evapotranspiration, and(iii) minimum, average, and maximum temperature. The catchment attributes encompass:(i) Catchment information,(ii) Physiographic characteristics,(iii) Hydrometeorological data,(iv) Climatic indices,(v) Hydrological signatures.(vi) Land cover characteristics(vii) Geologic characteristics.(viii) Soil characteristics.(ix) Land Use Capability This dataset follows the same standards as other CAMELS datasets, including those for the United States (https://doi.org/10.5194/hess-21-5293-2017), Chile (https://doi.org/10.5194/hess-22-5817-2018), Great Britain (https://doi.org/10.5194/essd-2020-49), and Brazil (https://doi.org/10.5194/essd-12-2075-2020).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
