06 Mar 2023
 | 06 Mar 2023
Status: this preprint is currently under review for the journal ESSD.

A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2021)

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

Abstract. With the booming big data techniques, large-sample hydrological analysis on streamflow regime is becoming feasible, which could derive robust conclusions on hydrological processes from a big-picture perspective. However, there is not a comprehensive global large-sample dataset for components of the streamflow regime yet. This paper presents a new time series dataset on global streamflow indices calculated from daily streamflow records after data quality control. The dataset contains 79 indices over seven major components of streamflow regime (i.e., magnitude, frequency, duration, changing rate, timing, variability, and recession) of 5548 river reaches globally. The indices time series in the dataset are available until 2021, the lengths of which vary from 30 to 215 years with an average of around 66 years. Restricted-access streamflow data of typical river basins in China are included in the dataset. Compared to existing global datasets, this global dataset covers more indices, especially those characterizing the frequency, duration, changing rate, and recession of streamflow regime. With the dataset, research on streamflow regime will become easier without spending time handling raw streamflow records. This comprehensive dataset will be a valuable resource to the hydrology community to facilitate a wide range of studies, such as studies of hydrological behaviour of a catchment, streamflow regime prediction in data-scarce regions, as well as variations in streamflow regime from a global perspective.

Xinyu Chen et al.

Status: open (until 01 May 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-49', Ionut Cristi Nicu, 13 Mar 2023 reply

Xinyu Chen et al.

Data sets

A global streamflow indices time series dataset Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu

Xinyu Chen et al.


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Short summary
River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are happening more often and destructively 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 the flow characteristics, represented by hydrological indeces. Building such a comprehensive global large-sample dataset is essential.