8 posts tagged with "AWS"

Technological advances are evolving water prediction capabilities at a ludicrous pace. From revolutionary machine learning algorithms to dramatic advances in computational hardware, the potential for making accurate hydrologic predictions has never been higher. To meet this new potential, the hydrologic community continuously generates models and approaches based on cutting edge research that could potentially benefit operational systems. However, many of these innovations lack a path to operational deployment.

The NextGen Research Datastream (NRDS) provides a mechanism by which these ideas can be refined and make their way into operations.

Developed by Lynker and the Alabama Water Institute (a Cooperative Institute for Research to Operations in Hydrology partnership), the NRDS facilitates the actualization a research idea from the community in a scalable and deployable numerical prediction system. To evaluate each of these modeling concepts, NRDS deploys prototype models to generate a continuous “datastream”. These outputs can then be evaluated and made more accurate. This cycle of streamlined deployment and iterative design lets these prototypes mature into a product that can be picked up by an operational forecasting team.

To enable this process to be done rapidly and smoothly, the entire system is designed with reproducibility and iterative improvement as core principles. The NRDS is an automated numerical prediction system generating regular stream flow forecasts that uses the NextGen Water Resources Modeling Framework (NextGen) as the core modeling engine and NextGen In A Box (NGIAB) as the simulation environment. This system generates forecasts across the contiguous United States (CONUS) on CIROH's operational cyberinfrastructure backbone: the research-to-operations (R2O) Hybrid Cloud (R2OHC) platform, with deployment on the AWS cloud. What makes the NRDS exciting is that the entire system is open-sourced, reproducible, publicly browsable, and potentially editable by anyone in the hydrologic community.

AI, DevOps and the Future of Cloud Infrastructure​

AWS re:Invent did not disappoint! I spent the first week of December at Amazon Web Services' flagship conference in Las Vegas. The event delivered cutting-edge technical insights, showcased the rapid evolution of cloud computing and AI, and provided countless opportunities to connect with industry leaders.

The energy across all five conference venues was more vibrant than I ever imagined it would be.

Last week, at the invitation and expert coordination of James Halgren, teams from RTI International (Sam Lamont and Matt Denno) and the University of Calgary (Darri Eythorsson, Cyril Thebault, and Martyn Clark) met at AWI for an intensive working session focused on weaving recent CIROH research into AWI’s fork of the NOAA Office of Water Prediction (OWP) Next Generation Water Resources Modeling Framework (nicknamed “NextGen”). James took the lead in developing the agenda, lining up the right scientific and technical expertise and ensuring that the week targeted the most critical software integration challenges. Throughout the visit, the RTI and UCalgary teams collaborated closely with AWI software engineers Quinn Lee, Josh Cunningham, hydrologic scientist Sifan A. Koriche, and James himself. The days were filled with whiteboards, deep technical conversations, and strategic planning around the future of NextGen water prediction. This recap captures the key themes and the momentum that carried through the week.

The recent DevCon 2025 event showcased not just cutting-edge development practices, but also demonstrated how modern DevOps principles and cloud infrastructure can seamlessly support large-scale technical workshops. Our team had the privilege of providing IT infrastructure and support for over 200 attendees, creating a robust learning environment through an exemplary public-private partnership.

CIROH's Research Cyberinfrastructure and DevOps team.
Left to right, top to bottom:
Manjila Singh, Arpita Patel, Nia Minor, Trupesh Patel, James Halgren; Benjamin Lee.

Last week, I had the incredible opportunity to co-present a keynote at the CIROH Developers Conference (DevCon 2025), which attracted over 200 attendees. This presentation, which I presented alongside Dan Ames, focused on "CIROH HydroInformatics and Research Cyberinfrastructure." It was a fantastic experience to share insights into the powerful tools and technologies that CIROH engineers, students, researchers have been developing to advance hydrological research and operations.

Pennsylvania State University (PSU) researchers have been leveraging CIROH Cyberinfrastructure to tackle complex hydrological modeling challenges. This post highlights their innovative approach using the Wukong computing platform in conjunction with Amazon S3 bucket storage to efficiently process and analyze large-scale environmental datasets. 🚀

This month, we are excited to showcase two case studies that utilized our cyberinfrastructure tools and services. These case studies demonstrate how CIROH's cyberinfrastructure is being utilized to support hydrological research and operational advancements.

1. ngen-datastream and NGIAB​

We're excited to share some recent developments and updates from CIROH's Research CyberInfrastructure team:

Cloud Infrastructure​

• CIROH's Google Cloud Account is now fully operational and managed by our team. You can find more information here.
• We're in the process of migrating our 2i2c JupyterHub to CIROH's Google Cloud account.
• We've successfully deployed the Google BigQuery API (developed by BYU and Google) for NWM data in our cloud. To access this API, please contact us at ciroh-it-support@ua.edu. Please refer to NWM BigQuery API to learn more.