Introducing EStreams - a comprehensive dataset and catalogue of streamflow, hydro-climatic and landscape data for Europe

Large-sample datasets of hydrological variables are crucial for understanding and predicting hydrological variability. We present “EStreams”, an extensive dataset of hydro-climatic variables and landscape descriptors and a catalogue of openly available stream records for 17,130 European catchments.
Introducing EStreams - a comprehensive dataset and catalogue of streamflow, hydro-climatic and landscape data for Europe
Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Unlocking Europe's Hydrological Data

Hydrological data is essential for understanding how rivers behave, predicting floods, and managing water resources. However, accessing this data on a large scale has always been a challenge. While some datasets exist, they often capture only a small portion of the available information, and finding, accessing, and using data from national providers can be complex and time-consuming. This is where our work on EStreams comes in.

Building a Unified Resource

EStreams is the result of a need we identified: to bring together the rich but fragmented hydrological data across Europe into a single, cohesive resource. We wanted to go beyond just collecting data—we aimed to create a platform that allows researchers to access, update, and use this data easily.

Overcoming Challenges

The journey to build EStreams was both exciting and challenging. One of the biggest hurdles was dealing with the diversity of data sources. Different countries have different ways of organizing and sharing their hydrological data, often in their native languages and with varying levels of accessibility. Our goal was to simplify this process for users by creating a detailed catalogue that guides them through accessing the data, regardless of the source.

What EStreams Offers

  • A comprehensive catalogue: Detailed metadata for over 17,000 streamflow gauges across Europe, along with guidance on accessing data from national providers. 
  • Hydro-climatic variables: Data on temperature, precipitation, and other climatic variables. 
  • Landscape descriptors: Detailed information on topography, soil types, vegetation, and land use, crucial for hydrological modeling and analysis.
  • Streamflow indices: Weekly, monthly, seasonal, and annual streamflow indices data across European catchments.

A Dynamic, Evolving Dataset

One thing we wanted to ensure was that EStreams wouldn’t just be a static dataset. With our provided Python scripts, users can easily update the dataset with new data as it becomes available, making it a dynamic and evolving resource.

Empowering Hydrological Research

Creating EStreams wasn’t always easy. We faced challenges related to data accessibility, formatting, and redistribution restrictions. However, the effort was worth it. We believe that EStreams will be a valuable tool for hydrologists, climate scientists, and anyone interested in European water systems.

In short, EStreams represents a new step forward in making hydrological data more accessible and usable.

The dataset is openly available at: https://doi.org/10.5281/zenodo.13154470

The latest version of the code is available at: https://github.com/thiagovmdon/EStreams.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

Water
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences > Water
Research Data
Research Communities > Community > Research Data
Environmental Sciences
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences

Related Collections

With collections, you can get published faster and increase your visibility.

Epidemiological data

This Collection presents a series of articles describing epidemiological datasets spanning diverse populations, ecosystems, and disease contexts. Data are presented without hypotheses or significant analyses, and can be derived from population surveys, health registries, electronic health records, field sampling, or other sources.

Publishing Model: Open Access

Deadline: Dec 22, 2024

Metabolomics

This collection presents a series of articles describing metabolomics datasets, covering data from any organism type, collected via any valid metabolomic technique, and for any application.

Publishing Model: Open Access

Deadline: Nov 28, 2024