Data description paper
12 Oct 2020
Data description paper | 12 Oct 2020
CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain
Gemma Coxon et al.
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25 citations as recorded by crossref.
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- CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia K. Fowler et al. 10.5194/essd-13-3847-2021
- Incorporating Uncertainty Into Multiscale Parameter Regionalization to Evaluate the Performance of Nationally Consistent Parameter Fields for a Hydrological Model R. Lane et al. 10.1029/2020WR028393
- Knowledge gaps in our perceptual model of Great Britain's hydrology T. Wagener et al. 10.1002/hyp.14288
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- Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface H. McMillan et al. 10.1002/hyp.14481
- Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks A. Sun et al. 10.1029/2021WR030394
- Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. 10.1016/j.jhydrol.2021.127261
- GRQA: Global River Water Quality Archive H. Virro et al. 10.5194/essd-13-5483-2021
- Advancing flood warning procedures in ungauged basins with machine learning Z. Rasheed et al. 10.1016/j.jhydrol.2022.127736
- PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020) H. Llauca et al. 10.3390/w13081048
- WITHDRAWN: Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. 10.1016/j.hydroa.2021.100109
- TOSSH: A Toolbox for Streamflow Signatures in Hydrology S. Gnann et al. 10.1016/j.envsoft.2021.104983
- Theoretical and empirical evidence against the Budyko catchment trajectory conjecture N. Reaver et al. 10.5194/hess-26-1507-2022
- Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G. Papacharalampous et al. 10.1016/j.gsf.2022.101349
- A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
- LamaH | Large-Sample Data for Hydrology: Big data für die Hydrologie und Umweltwissenschaften C. Klingler et al. 10.1007/s00506-021-00769-x
- How is Baseflow Index (BFI) impacted by water resource management practices? J. Bloomfield et al. 10.5194/hess-25-5355-2021
- Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models T. Lees et al. 10.5194/hess-25-5517-2021
- Continental-scale streamflow modeling of basins with reservoirs: Towards a coherent deep-learning-based strategy W. Ouyang et al. 10.1016/j.jhydrol.2021.126455
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
- CCAM: China Catchment Attributes and Meteorology dataset Z. Hao et al. 10.5194/essd-13-5591-2021
- CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil V. Chagas et al. 10.5194/essd-12-2075-2020
Discussed (final revised paper)
Latest update: 09 Dec 2022