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. In addition to facilitating diverse data and model integration while ensuring reproducible computing, CyberWater also enables on-demand access to high-performance computing facilities. 


We would like to get your feedback on the features contained in CyberWater to increase its utility to educators and researchers. We hope to develop an effective and highly useful platform for the user community!

We invite you to a 3-hour virtual meeting that will be held twice to accommodate those teaching classes. The first meeting will be on Thursday, April 8 at 1 PM ET, and the second on Friday, May 21 at 1:00 PM ET. The workshop will consist of brief demos followed by questions and discussion of the features. We would love to have an active and engaged group during these discussions as well as your frank opinion about the utility of the software in your research and teaching. Please register in advance for these meetings. Registration information can be found below. 

Download the workshop agenda here!


April 8, 2021 - 1:00 PM ET

Register in advance for this meeting:

May 21, 2021 - 1:00 PM ET

Register in advance for this meeting:


  • Project Description

    Scientists need to use diverse data and integrate models outside their own disciplines with sufficient model accuracy and predictability. This is currently difficult to accomplish because (1) a vast quantity of diverse data are not readily accessible to models; and (2) diverse models developed individually by different research groups are difficult to share an integrate between disciplines. 

    The goal of this project is to build an open data, open modeling framework software that enables easy and incremental integration of diverse data and models for knowledge discovery and interdisciplinary team-work, as well as reproducible computing and seamless and on-demand access to HPC resources. Our project team includes hydrologists, climate experts, meteorologists, computer scientists and CI experts, from multiple universities and CUAHSI, who collaborate closely to ensure CyberWater will engage the broad communities for domain scientists' benefits. 

  • Project Objectives

    CyberWater can lower the learning curve for modelers with limited skills in computer and technology, and enable them to quickly employ models from other domains. It advances the state-of-the-art by making it possible to quickly, effectively and reliably connect diverse models together to form a comprehensive integrated modeling framework for tackling emerging complex interdisciplinary problems using diverse sources of data. 

    Currently, a large interdisciplinary team must be formed to modify model code to couple the diverse domain models together. The innovations of CyberWater include: 

    1. Significantly reducing model integration complexity, and allowing easy coupling of diverse models without coding.

    2. Facilitating the use of diverse data by automatically ingesting data of heterogeneous types, formats, and access protocols, etc.

    3. Automating the flow from data to model to output visualization in real- or near real-time

    4. Supporting reproducible computing

    5. Enabling high power computing on demand

  • Benefits to the CUAHSI Community
    • Scientists can use the CyberWater framework to greatly simplify their data access, coupled model simulations, reproducible computing, and access to HPC facilities, all of which significantly enhance research productivity.


    • CyberWater will be a valuable education tool to teach and train university students on how to conduct interdisciplinary and reproducible research, thus greatly enhancing university STEM education capability for future workforce.
  • Publications

    An open-data open-model framework for hydrological models’ integration, evaluation and application.

    • Salas, D., Liang, X., Navarro, M., Liang, Y., and Luna, D. An open-data open-model framework for hydrological models’ integration, evaluation and application. Environmental Modelling and Software, 126 (April 2020), 104622. 

    Cyberwater - An open and sustainable framework for diverse data and model integration.

    • Luna, D., Chen, R., Yuan, C., Liang, Y., Liang, X., Bales, J., Castronova, A.M., Demir, I., Hooper, R.P., Krajewski, W.F. and Lin, L., 2019. CyberWater—An open and sustainable framework for diverse data and model integration. AGU Fall Meeting, 2019, pp.IN11B-02.

    Collaborative Research: CyberWater - An open and sustainable framework for diverse data and model integration with provenance and access to HPC.

    • Liang, X., Liang, Y., Luna, D., Chen, R., Cao, Y., Fu, Y., Pamidighantam, S.,Song, F., Bales, J., Castronova, A., Demir, I., Hooper, R., Krajewski, W., Lin, L., Mantilla, R., Zhang, Y., 2020. Collaborative Research: CyberWater - An open and sustainable
  • Workshop Videos

    Watch the videos below to learn more about our project. These lectures were a part of the focus group held virtually in August 2020.

  • Contact/Get Involved

    Please contact Xu Liang ( or Anthony Castronova ( if you would like to be involved or have any questions on the project.


    Xu Liang (University of Pittsburgh), Project lead PI

    Yao Liang (Indiana University - Purdue University Indianapolis), IUPUI PI

    Fengguang Song (Indiana University - Purdue University Indianapolis), IUPUI Co-PI

    Sudhakar Pamidighantam (Indiana University), IUPUI Co-PI

    Dimuthu Upeksha (Indiana University), IUPUI/IU Programmer

    Ibrahim Demir (University of Iowa), Iowa PI

    Witold Krajewski (University of Iowa), Iowa Co-PI

    Ricardo Mantilla (University of Iowa), Iowa Co-PI

    Yang Zhang (North Carolina State University), NC State PI

    Lan Lin (Ball State University), BSU PI

    Anthony Castronova (CUAHSI), CUAHSI PI

    Richard Hooper (Tufts University), Paid Consultant through CUAHSI

    Jennifer Adam (Washington State University), Unpaid Collaborator

    Jonathan L. Goodall (University of Virginia), Unpaid Collaborator

    Nancy Wilkins-Diehr (San Diego Supercomputer Center), Unpaid Consultant

    Ge Sun (U.S. Department of Agriculture), Unpaid Consultant

    Yingping Wang (CSIRO, Australia), Unpaid Consultant

    Dave Meyer (NASA), Unpaid Consultant