EGU2020-12069
https://doi.org/10.5194/egusphere-egu2020-12069
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Ensemble Streamflow Assimilation with Coupled WRF-Hydro and DART

Seong Jin Noh1, James McCreight2, Moha El Gharamti2, Tim Hoar2, Arezoo Rafieeinasab2, and Benjamin Johnson2
Seong Jin Noh et al.
  • 1Kumoh National Institute of Technology, Department of Civil Engineering, Gumi-si, Korea, Republic of (seongjin.noh@gmail.com)
  • 2National Center for Atmospheric Research, Boulder, CO, USA

The Data Assimilation Research Testbed (DART) has been coupled with the community WRF-Hydro modeling system with the intent of providing efficient and flexible support for assimilating a wide range of streamflow and soil moisture observations and delivering an ensemble of model states useful for quantifying streamflow uncertainties. The coupled framework, named Hydro-DART, is used to study and assess the flooding consequences of Hurricane Florence over the Carolinas during August-September 2018 period.
Several extensions to earlier versions of Hydro-DART have been explored. These include: (1) a multi-configuration ensemble in which different ensemble members are run with different physical parameters (e.g., Manning's roughness and channel geometry) in order to create additional ensemble variability, (2) a variable transform, anamorphosis, which is introduced such that bounded quantities (e.g., streamflow) are transformed to a Gaussian space prior to the Kalman update as a way to avoid non-physical state updates, (3) a spatially-correlated noise, which is introduced to represent uncertainty of input forcings (e.g., overland and subsurface fluxes) in a physically meaningful way, and (4) an along-the-stream localization, which considers precipitation correlation length scale, rather than physical proximity. Hourly streamflow gauge data, from the flood-affected area, is used to test the impact of these extensions on the overall prediction accuracy. Analyses and hindcasts are compared to those based on the nudging assimilation currently employed in the National Water  Model (NWM) operations. Standard streamflow forecast metrics are also supplemented by a wavelet-based event timing error metric.

How to cite: Noh, S. J., McCreight, J., El Gharamti, M., Hoar, T., Rafieeinasab, A., and Johnson, B.: Ensemble Streamflow Assimilation with Coupled WRF-Hydro and DART, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12069, https://doi.org/10.5194/egusphere-egu2020-12069, 2020.

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