The NextGen Research DataStream (NRDS): A Reproducible Numerical Prediction System for Accelerating Research to Operations in Hydrology
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.