Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.
Abstract
Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.H41A1423S
- Keywords:
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- 1816 Estimation and forecasting;
- HYDROLOGY;
- 1860 Streamflow;
- HYDROLOGY;
- 1873 Uncertainty assessment;
- HYDROLOGY;
- 1880 Water management;
- HYDROLOGY