Articles | Volume 15, issue 10
https://doi.org/10.5194/essd-15-4463-2023
© Author(s) 2023. 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-15-4463-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Oct 2023
Data description article |
| 06 Oct 2023
| 06 Oct 2023
A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)
Xinyu Chen
School of Environmental Science and Engineering, Southern
University of Science and Technology, Shenzhen, 518055, China
School of Environmental Science and Engineering, Southern
University of Science and Technology, Shenzhen, 518055, China
Yuning Luo
State Key Laboratory of Hydrology-Water Resources and Hydraulic
Engineering, and College of Hydrology and Water Resources, Hohai University,
Nanjing, 210098, China
Junguo Liu
School of Environmental Science and Engineering, Southern
University of Science and Technology, Shenzhen, 518055, China
Henan Provincial Key Lab of Hydrosphere and Watershed Water
Security, North China University of Water Resources and Electric Power,
Zhengzhou, 450046, China
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Total article views: 5,525 (including HTML, PDF, and XML)
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Cited
19 citations as recorded by crossref.
- Historical simulation performance evaluation and monthly flow duration curve quantile-mapping (MFDC-QM) of the GEOGLOWS ECMWF streamflow hydrologic model J. Sanchez Lozano et al. https://doi.org/10.1016/j.envsoft.2024.106235
- Power System Planning Considering Extreme Weather Events and Stability Criteria P. Gutiérrez et al. https://doi.org/10.1109/ACCESS.2026.3672869
- Coherent changes in global high and low flows Q. Huang et al. https://doi.org/10.1016/j.hydroa.2025.100212
- Explaining spatial variation and catchment characteristics thresholds in streamflow response A. Amorim Brandão et al. https://doi.org/10.1016/j.jhydrol.2026.135492
- A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. https://doi.org/10.5194/essd-16-1559-2024
- Permutation Entropy and Its Niche in Hydrology: A Review D. Mihailović https://doi.org/10.3390/e27060598
- Influence of individual streamflow gauging stations: a hybrid approach based on complex networks and copulas D. Muthuvel et al. https://doi.org/10.1016/j.jhydrol.2025.134164
- Climate drives observational changes in hydrological extremes across most global regions N. Wang et al. https://doi.org/10.1016/j.xinn.2025.101171
- Evaluating Rainfall-Runoff Generation Mechanisms of Deep Learning Models Using a Process-Based Rainfall-Runoff Model T. Duong et al. https://doi.org/10.1007/s11269-025-04231-5
- Long-term basin trends confirm a record 2022–2024 hydrological drought and water-storage losses in western Amazonia G. De la Cruz et al. https://doi.org/10.1016/j.ejrh.2025.102951
- Technical note: Streamflow seasonality using directional statistics W. Berghuijs et al. https://doi.org/10.5194/hess-29-2851-2025
- China’s nationwide streamflow decline driven by landscape changes and human interventions K. Wang et al. https://doi.org/10.1126/sciadv.adu8032
- EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al. https://doi.org/10.1038/s41597-024-03706-1
- Where to build altimetry-based stage-discharge rating curves? Insights from Sentinel-3 Y. Zhao & L. Jiang https://doi.org/10.1080/15481603.2025.2530802
- Past and future change in global river flows L. Gudmundsson et al. https://doi.org/10.1038/s43017-025-00745-z
- Global risk pooling mitigates financial risk from drought in hydropower-dependent countries R. Cuppari et al. https://doi.org/10.1038/s41467-025-67082-z
- Attribution of streamflow and its seasonal variation to dual nature-society drivers using CMIP6 data and hydrological models M. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133314
- Hidden flux partitioning in the global water cycle G. Rau et al. https://doi.org/10.1038/s44221-025-00548-y
- Mapping pan-Arctic riverine particulate organic carbon from space (1985 to 2022) X. Sun et al. https://doi.org/10.1126/sciadv.ady6314
19 citations as recorded by crossref.
- Historical simulation performance evaluation and monthly flow duration curve quantile-mapping (MFDC-QM) of the GEOGLOWS ECMWF streamflow hydrologic model J. Sanchez Lozano et al. https://doi.org/10.1016/j.envsoft.2024.106235
- Power System Planning Considering Extreme Weather Events and Stability Criteria P. Gutiérrez et al. https://doi.org/10.1109/ACCESS.2026.3672869
- Coherent changes in global high and low flows Q. Huang et al. https://doi.org/10.1016/j.hydroa.2025.100212
- Explaining spatial variation and catchment characteristics thresholds in streamflow response A. Amorim Brandão et al. https://doi.org/10.1016/j.jhydrol.2026.135492
- A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. https://doi.org/10.5194/essd-16-1559-2024
- Permutation Entropy and Its Niche in Hydrology: A Review D. Mihailović https://doi.org/10.3390/e27060598
- Influence of individual streamflow gauging stations: a hybrid approach based on complex networks and copulas D. Muthuvel et al. https://doi.org/10.1016/j.jhydrol.2025.134164
- Climate drives observational changes in hydrological extremes across most global regions N. Wang et al. https://doi.org/10.1016/j.xinn.2025.101171
- Evaluating Rainfall-Runoff Generation Mechanisms of Deep Learning Models Using a Process-Based Rainfall-Runoff Model T. Duong et al. https://doi.org/10.1007/s11269-025-04231-5
- Long-term basin trends confirm a record 2022–2024 hydrological drought and water-storage losses in western Amazonia G. De la Cruz et al. https://doi.org/10.1016/j.ejrh.2025.102951
- Technical note: Streamflow seasonality using directional statistics W. Berghuijs et al. https://doi.org/10.5194/hess-29-2851-2025
- China’s nationwide streamflow decline driven by landscape changes and human interventions K. Wang et al. https://doi.org/10.1126/sciadv.adu8032
- EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al. https://doi.org/10.1038/s41597-024-03706-1
- Where to build altimetry-based stage-discharge rating curves? Insights from Sentinel-3 Y. Zhao & L. Jiang https://doi.org/10.1080/15481603.2025.2530802
- Past and future change in global river flows L. Gudmundsson et al. https://doi.org/10.1038/s43017-025-00745-z
- Global risk pooling mitigates financial risk from drought in hydropower-dependent countries R. Cuppari et al. https://doi.org/10.1038/s41467-025-67082-z
- Attribution of streamflow and its seasonal variation to dual nature-society drivers using CMIP6 data and hydrological models M. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133314
- Hidden flux partitioning in the global water cycle G. Rau et al. https://doi.org/10.1038/s44221-025-00548-y
- Mapping pan-Arctic riverine particulate organic carbon from space (1985 to 2022) X. Sun et al. https://doi.org/10.1126/sciadv.ady6314
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are occurring more often and are more destructive in many places worldwide. To deal with such issues, hydrologists endeavor to understand the features of extreme events as well as other hydrological changes. One key approach is analyzing flow characteristics, represented by hydrological indices. Building such a comprehensive global large-sample dataset is essential.
River flow is experiencing changes under the impacts of climate change and human activities. For...
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