Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5315-2021
https://doi.org/10.5194/hess-25-5315-2021
Research article
 | 
29 Sep 2021
Research article |  | 29 Sep 2021

Ensemble streamflow data assimilation using WRF-Hydro and DART: novel localization and inflation techniques applied to Hurricane Florence flooding

Mohamad El Gharamti, James L. McCreight, Seong Jin Noh, Timothy J. Hoar, Arezoo RafieeiNasab, and Benjamin K. Johnson

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Cited articles

Abbaszadeh, P., Moradkhani, H., and Yan, H.: Enhancing hydrologic data assimilation by evolutionary particle filter and Markov chain Monte Carlo, Adv. Water Resour., 111, 192–204, 2018. a, b, c
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Short summary
The article introduces novel ensemble data assimilation (DA) techniques for streamflow forecasting using WRF-Hydro and DART. Model-related biases are tackled through spatially and temporally varying adaptive prior and posterior inflation. Spurious and physically incorrect correlations, on the other hand, are mitigated using a topologically based along-the-stream localization. Hurricane Florence (2018) in the Carolinas, USA, is used as a test case to investigate the performance of DA techniques.