This study aims to demonstrate this potential by employing HEAVEN to assimilate streamflow data from USGS stations into a conceptual hydrologic model to enhance its capability to forecast hurricane-induced floods across multiple locations within three watersheds in the Southeastern United States. The results show that this data assimilation approach significantly improves hydrologic model’s ability to forecast extreme river flows.

Overall, this paper is very interesting and well written. It demonstrates the scientific value of HEAVEN in extreme river flow simulation and forecasting. I have some minor comments before publication.

In the abstract, the authors can add some quantitative results to show how much this data assimilation approach significantly improves hydrologic model’s ability to forecast extreme river flows.

How the different sources of uncertainties are considered in HEAVEN should be mentioned.

It would be better to introduce figure 2 in the beginning of section 2.4.

In figure 4, the validation accuracy in terms of R is higher than that during calibration in Savanah, but the validated RMSE is also higher than the latter. Why?

In figures 6-7, Streamflow forecast improved by data assimilation during peak flow conditions across the USGS stations are demonstrated. The POI ranges from 0-100%. Is there any negative value?

It would be better to draw a scatter plot to demonstrate the streamflow forecast skills during peak flow conditions with/without data assimilation.