NCAR Agreement PWP4: Over-the-Loop Streamflow Forecasting
(1) How can the quality of hydrologic predictions be improved through the implementation of distributed, physically-oriented hydrology models across catchments that lack the necessary information for local-scale calibration and verification? (2) What are the benefits of over-the-loop streamflow forecasting approaches that provide enhanced information relative to the current operational forecast workflow?
Need and Benefit
Reservoir inflow forecasts are used to widely varying degrees by water system managers in determining project releases. For most federal projects that use inflow forecasts, the forecast use practices have evolved to rely on the operational streamflow forecasts produced by the National Weather Service (NWS) River Forecast Centers (RFCs). These forecasts have strengths and limitations in their operational workflow. For instance, forecasters may apply expert knowledge via a hands-on process that involves adjusting the forecast data and conceptual hydrology models at multiple stages (a ‘forecaster in-the-loop' process). This practice often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess controlled variations, and the effort required to make forecasts in this way is an obstacle to expanding forecast service – ie, though adding new forecast locations or more frequent forecast updates, running more complex models, or producing short range ensembles and hindcasts that can support verification. Over-the-loop approaches offer the ability to ameleoriate some of these limitiations and thereby permit objective evaluation of new models, forecast products, and/or data assimilation techniques through robust and reproducible verification.
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Independent Peer Review
The following documents were reviewed by qualified Bureau of Reclamation employees. The findings were determined to be achieved using valid means.
The OverTheLoop Streamflow Forecast Demonstration Project (final, PDF, 504KB)
By Ken Nowak
Research Product completed on May 01, 2017