Streamflow data assimilation for hydrologic river routing: advances and challenges
Abstract
River routing is one of the most important operations in real-time hydrologic forecasting. Among the various routing methods, hydrologic routing is widely used for parsimony and minimal data and computational requirements. Due to simplifying assumptions, however, hydrologic river routing such as the Muskingum method is subject to potentially significant errors from structural and parametric uncertainties. If informative observations of the river such as streamflow are available in real time, they may be used to update the model states and/or parameters for improved accuracy. In this presentation, we discuss the latest advances, experiences gained, and science issues and challenges in streamflow data assimilation focusing on hydrologic river routing. The results from variational assimilation with a distributed hydrologic routing model for the Upper Trinity River in the Dallas-Fort Worth area will be provided to illustrate the impacts of dual state-parameter updating on short-range streamflow forecasts. We will also discuss the benefits and challenges of streamflow DA regarding timing and volumetric errors of river routing.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H31J1853N
- Keywords:
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- 1847 Modeling;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY;
- 1910 Data assimilation;
- integration and fusion;
- INFORMATICS