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CUAHSI’s data services and software provide solutions to support many different workflows and use cases, and all aspects of the data management life cycle, from collecting, storing, and analyzing data, to sharing, publishing, and citing data, thereby enabling reproducibility in the water sciences.

Explore the topics below to learn more about how CUAHSI’s services and products can support your work, or contact us at email hidden; JavaScript is required to learn more.

Data Discovery


CUAHSI’s HydroClient data portal provides access to more than 100 data sources, including over 5 million unique time series, from federal agencies, university researchers, volunteer science groups, and others through a single map interface, with all data returned to the user in the same format. Use HydroClient to search for, preview, and download time series data like streamflow measurements, meteorological data, repeated grab sample results, and soil moisture measurements. To learn more, check out the HydroClient User Guide.


The HydroShare data repository enables discovery of multiple types of water data including time series data, GIS data, models and more, and makes data available in a citable manner.

Data Storage & Publication

The benefits of publishing your data with CUAHSI include:

  • Data Discoverability: data can be discovered in a domain-specific repository among hundreds of other data sources and through Google Database Search.
  • Data access control: keep data private, limit sharing to selected colleagues, or make data publicly available.
  • Access free tools developed by the hydrologic community for managing and analyzing data.
  • Increased project sustainability: data and models are stored in one of CUAHSI’s data repositories.
  • Data can be easily cited: at the completion of your project, formally publish your data by obtaining a Digital Object Identifier.
  • Support: CUAHSI staff provide assistance and long-term infrastructure support, including regular data back-ups.

Contact email hidden; JavaScript is required with questions about archiving and publishing data with CUAHSI, and to discuss which repository is best suited for your data.

CUAHSI’s Data Repositories:

Analysis & Modeling Tools

Model Domain Subsetter

The CUAHSI Model Domain Subsetter is a collaborative effort for publishing and sharing static domain datasets for CONUS hydrologic models such as the National Water Model and Parflow. This service enables researchers to execute large scale models at local and regional scales.


HydroShare modeling functionality has been developed to support the collaborative modeling needs of the hydrologic community and make it easier to share research products. Learn more about how HydroShare supports collaborative modeling here.


The CUAHSI JupyterHub is a cloud computing service that enables researchers to execute scientific code and explore, modify, and interact with data inside a remote execution environment using Python and/or R programming languages. JupyterHub is integrated with HydroShare and the Hydrologic Information System data repositories, making it easy to leverage community datasets, collaborate, and disseminate research workflows.


The CyberWater project creates a new cyberinfrastructure with an open data, open modeling framework software. The goal of this project is to reduce the user time and effort needed for hydrologic modeling studies, thereby expediting fundamental knowledge discoveries. CyberWater also enables on-demand access to high-performance computing facilities.

Cloud Computing

CUAHSI develops, maintains, and hosts cloud computing software to support scientific research and education in the water sciences. Our systems interoperate with data repositories such as the Hydrologic Information System (HIS) and HydroShare. Our goal is to provide tools for analysis, publication, and replication of scientific models and workflows that can be used for research, education, and other water-resources applications.

We’ve developed a suite of cloud computing services to improve the way we conduct scientific analysis, water science education, and reproducible science. These efforts build off the widely used open source Jupyter project to provide a free to use cloud computing service to the community.

Learn more about the cloud computing services we offer:

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