A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)

Chen, Xinyu; Jiang, Liguang; Luo, Yuning; Liu, Junguo

doi:https://doi.org/10.5194/essd-15-4463-2023

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.

https://doi.org/10.5194/essd-15-4463-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 10

Data description paper

|

06 Oct 2023

Data description paper |

| 06 Oct 2023

A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)

Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu

Data sets

A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu https://doi.org/10.57760/sciencedb.07227

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.