Data description paper
08 Sep 2020
Data description paper | 08 Sep 2020
CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil
Vinícius B. P. Chagas et al.
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20 citations as recorded by crossref.
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- Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management L. Slater et al. 10.5194/hess-25-3897-2021
- Spatial and temporal patterns of propagation from meteorological to hydrological droughts in Brazil A. Bevacqua et al. 10.1016/j.jhydrol.2021.126902
- CCAM: China Catchment Attributes and Meteorology dataset Z. Hao et al. 10.5194/essd-13-5591-2021
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
- Process Controls on Flood Seasonality in Brazil V. Chagas et al. 10.1029/2021GL096754
- Data‐Driven Worldwide Quantification of Large‐Scale Hydroclimatic Covariation Patterns and Comparison With Reanalysis and Earth System Modeling N. Ghajarnia et al. 10.1029/2020WR029377
- Machine learning models for streamflow regionalization in a tropical watershed R. Ferreira et al. 10.1016/j.jenvman.2020.111713
- CABra: a novel large-sample dataset for Brazilian catchments A. Almagro et al. 10.5194/hess-25-3105-2021
- LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe C. Klingler et al. 10.5194/essd-13-4529-2021
- PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020) H. Llauca et al. 10.3390/w13081048
Discussed (final revised paper)
Latest update: 01 Dec 2022