EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A new process-oriented ensemble hydrological prediction system for flood prediction and water management in the US Pacific Northwest

Andy Wood1,2, Josh Sturtevant3, Naoki Mizukami2, and Guoqiang Tang1
Andy Wood et al.
  • 1National Center for Atmospheric Research (NCAR), Climate and Global Dynamics, Boulder, USA
  • 2National Center for Atmospheric Research (NCAR), Research Applications Laboratory, Boulder, USA
  • 3Lynker, Boulder, USA

Water-related applications and decisionmaking for flood forecasting and seasonal water management commonly rely on hydrologic modeling and forecasting that must provide accurate information over large domains as well as at local watershed scales.  We present progress on an experimentally operational hydrologic forecasting system being developed in a project between NCAR and the US Army Corps of Engineers to increase situational awareness in the US Columbia River basin of the Pacific Northwest, where myriad management concerns include flood risk mitigation, hydropower generation, navigation, water supply, recreation, fisheries and environmental management. The components of the system arise from process-oriented hydrologic modeling, analysis and prediction research that has been developed over the last decade in a collaboration between NCAR, federal US water agencies, and several academic institutions. In particular, a calibrated, watershed-based SUMMA hydrologic model and MizuRoute channel routing model are run in both retrospective and real time modes to provide 3-hourly timestep ensemble flood forecasts for short to medium range lead times, as well as ensemble seasonal streamflow and water supply forecasts up to a 1-year lead time. A 36-member meteorological forcing analysis is used to initialize the model states, while ensemble meteorological forecasts from GEFS, sub-seasonal-to-seasonal (S2S) climate forecasts and ESP are used to drive future flow predictions. We present the current status of the system, which runs in real time at NCAR, and discuss different elements of the forecast approach, including model calibration, ensemble initialization, data assimilation, downscaling of NWP, S2S climate forecast use, post-processing, and hindcasting. We also discuss project links to a related streamflow forecasting testbed initiative through the new NOAA Cooperative Institute for Research to Operations in Hydrology (CIROH)

How to cite: Wood, A., Sturtevant, J., Mizukami, N., and Tang, G.: A new process-oriented ensemble hydrological prediction system for flood prediction and water management in the US Pacific Northwest, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8578,, 2023.