Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5591-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5591-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
03 Dec 2021
Data description paper |
| 03 Dec 2021
| 03 Dec 2021
CCAM: China Catchment Attributes and Meteorology dataset
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Jin Jin
CORRESPONDING AUTHOR
School of Computer Science, Northwestern Polytechnical University,
Xi'an, 710072, China
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Runliang Xia
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Shimin Tian
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Wushuang Yang
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Qixing Liu
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Min Zhu
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Tao Ma
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Chengran Jing
Yellow River Institute of Hydraulic Research, Zhengzhou,
450003, China
Yanning Zhang
School of Computer Science, Northwestern Polytechnical University,
Xi'an, 710072, China
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Cited
16 citations as recorded by crossref.
- Simulation of Gauged and Ungauged Streamflow of Coastal Catchments across Australia M. Bari et al. 10.3390/w16040527
- Catchment characterization: Current descriptors, knowledge gaps and future opportunities L. Tarasova et al. 10.1016/j.earscirev.2024.104739
- Correlation change analysis and NDVI prediction in the Yellow River Basin of China using complex networks and GRNN-PSRLSTM Z. Meng et al. 10.1007/s10661-024-13168-y
- A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. 10.5194/essd-16-1559-2024
- A framework on utilizing of publicly availability stream gauges datasets and deep learning in estimating monthly basin-scale runoff in ungauged regions M. Le et al. 10.1016/j.advwatres.2024.104694
- Caravan - A global community dataset for large-sample hydrology F. Kratzert et al. 10.1038/s41597-023-01975-w
- Identification of unique ecosystem service bundles in farmland - A case study in the Huang-Huai-Hai Plain of China L. Gong et al. 10.1016/j.jenvman.2024.122516
- FOCA: a new quality-controlled database of floods and catchment descriptors in Italy P. Claps et al. 10.5194/essd-16-1503-2024
- BULL Database – Spanish Basin attributes for Unravelling Learning in Large-sample hydrology J. Senent-Aparicio et al. 10.1038/s41597-024-03594-5
- Benchmarking data-driven rainfall-runoff modeling across 54 catchments in the Yellow River Basin: Overfitting, calibration length, dry frequency J. Jin et al. 10.1016/j.ejrh.2022.101119
- A dataset of lake-catchment characteristics for the Tibetan Plateau J. Liu et al. 10.5194/essd-14-3791-2022
- Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs Y. Shen et al. 10.5194/essd-15-2781-2023
- CAMELS‐SE: Long‐term hydroclimatic observations (1961–2020) across 50 catchments in Sweden as a resource for modelling, education, and collaboration C. Teutschbein 10.1002/gdj3.239
- PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia R. Aguayo et al. 10.1038/s41597-023-02828-2
- EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al. 10.1038/s41597-024-03706-1
- Identifying control factors of hydrological behavior through catchment classification in Mainland of China H. Xu et al. 10.1016/j.jhydrol.2024.132206
16 citations as recorded by crossref.
- Simulation of Gauged and Ungauged Streamflow of Coastal Catchments across Australia M. Bari et al. 10.3390/w16040527
- Catchment characterization: Current descriptors, knowledge gaps and future opportunities L. Tarasova et al. 10.1016/j.earscirev.2024.104739
- Correlation change analysis and NDVI prediction in the Yellow River Basin of China using complex networks and GRNN-PSRLSTM Z. Meng et al. 10.1007/s10661-024-13168-y
- A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. 10.5194/essd-16-1559-2024
- A framework on utilizing of publicly availability stream gauges datasets and deep learning in estimating monthly basin-scale runoff in ungauged regions M. Le et al. 10.1016/j.advwatres.2024.104694
- Caravan - A global community dataset for large-sample hydrology F. Kratzert et al. 10.1038/s41597-023-01975-w
- Identification of unique ecosystem service bundles in farmland - A case study in the Huang-Huai-Hai Plain of China L. Gong et al. 10.1016/j.jenvman.2024.122516
- FOCA: a new quality-controlled database of floods and catchment descriptors in Italy P. Claps et al. 10.5194/essd-16-1503-2024
- BULL Database – Spanish Basin attributes for Unravelling Learning in Large-sample hydrology J. Senent-Aparicio et al. 10.1038/s41597-024-03594-5
- Benchmarking data-driven rainfall-runoff modeling across 54 catchments in the Yellow River Basin: Overfitting, calibration length, dry frequency J. Jin et al. 10.1016/j.ejrh.2022.101119
- A dataset of lake-catchment characteristics for the Tibetan Plateau J. Liu et al. 10.5194/essd-14-3791-2022
- Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs Y. Shen et al. 10.5194/essd-15-2781-2023
- CAMELS‐SE: Long‐term hydroclimatic observations (1961–2020) across 50 catchments in Sweden as a resource for modelling, education, and collaboration C. Teutschbein 10.1002/gdj3.239
- PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia R. Aguayo et al. 10.1038/s41597-023-02828-2
- EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al. 10.1038/s41597-024-03706-1
- Identifying control factors of hydrological behavior through catchment classification in Mainland of China H. Xu et al. 10.1016/j.jhydrol.2024.132206
Latest update: 20 Jan 2025
Short summary
CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.
CCAM is proposed to promote large-sample hydrological research in China. The first catchment...
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