Dear Reviewer,

Thank you very much for your helpful feedback! Please see our response below. We will submit a revised version of the manuscript once the feedback from all reviewers is available.

Thank you and best regards,

Florian Roth (on behalf of all authors)

Line 28: Thank you for this advice. The risk and recovery product looks very promising for flood mapping validation. Unfortunately, there is currently no data available for the Pakistan flood, which is why we selected the rapid mapping data.

Line 33: We will clarify in the revised version that we are showing the extent of the study sites provided by the CEMS rapid mapping data.

Line 45: The internal low sensitivity masking used by our algorithm is described in detail by the cited publication (Bauer-Marschallinger et al., 2022), and we will add details on the exclusion methods to the manuscript.

Line 48: Thank you for pointing us towards this publication. The GFM exclusion layers fundamentally differ from the described methods/layers of this publication. Following a similar approach of Zhao et al., 2021, we implemented a time-series-based masking per pixel, but the layers are produced individually based on statistical parameters or external datasets. The layers will be part of a future scientific publication, and are already publicly accessible via the product definition document of the Global Flood Monitoring service (cited in the paper under Global Flood Monitoring).

Line 73: The 4th area of interest (Shanghar) is 2 days apart from a Sentinel-1 acquisition, but is currently missing in Table 1. For completion, we will add the area to Table 1, but keep the analysis to be focused on the other three areas to rely on temporally close reference data.

Line 87: Thank you for bringing this up. Since Sentinel-1 observed the situation before Spot, and the flood surface was still growing at this point in time, the underestimation is more likely related to the time difference of the acquisitions. To double-check this and to analyse the relationship with vegetation, we will add land cover data to provide more context.

Figure 4: Thank you for this comment. The validation is limited to areas showing a valid result from both the Sentinel-1 flood mapping and the optical reference data. Consequently, cloud-covered areas are excluded. We will add the information about the coverage of the validation!

Line 89: Thank you for putting this into the correct context and pointing us towards two useful publications (Schumann et al., 2022 and Dasgupta et al., 2022). Optical observations are not able to detect flood under dense vegetation. In the case of Shikarpur, we assumed advantages of optical observations for detecting flood close to sparse vegetation, but we have not fully communicated this in the paper. However, as you mentioned, the differences are more likely to be related to the time difference between Sentinel-1 and Spot (please see comment on line 87).

Line 91: See comment on line 89.

Line 99: Thank you for your advice. We will include a zoomed subset to ease the interpretation of the confusion maps.

Line 100: The areas of overestimation mostly correspond to cropland, which occasionally shows fast backscatter changes due to different agricultural activities. Low-backscatter over vegetation appearing with water-like signature can occur due to ploughing in case of agricultural fields or attenuation of the signal within the vegetation (Vreugdenhil et al., 2018, Harfenmeister et al., 2019). A more speculative explanation is that the flood surface changed between the two satellite observations due to manipulation of local dams in reaction to the flood threat.

Line 101: Thank you for pointing this out. You are correct, the time difference can generally only correspond to an increased or decreased flood surface. Our interpretation of the overestimation can be seen in the comment for line 100.

Figure 7: We will add a scale bar to the figure.

Line 114: We agree!

Line 140: As this large flood is not covered by a single Sentinel-1 overpass, each orbit covers different parts of the event, at different times. To allow an estimate of the progress of the flooded area over time, we decided to base the analysis on a single orbit, which covers about the same area at each overpass.

Dear Dr. Jin,

Thank you for your interest and your comment on our manuscript.

When looking at the first Sentinel-1 scenes covering this outstandingly large flood event happening in Pakistan, we decided on presenting the abilities of our flood mapping algorithm for the event. The main goal was to quickly share our results with the scientific and other interested communities, while providing details on the performance of the algorithm. This was the reason why we went for the pre-print option and made the data publicly available, while the event was still on going. As our algorithm is included in the Copernicus Emergency Management Service's (CEMS) Global Flood Monitoring (GFM) component, it contributed to the data used by DG Echo and other users for emergency response. Additionally, the topic was taken up by EUMETSAT in their article on flood and drought monitoring.

The used algorithm itself is presented in detail in a dedicated methodology paper (Bauer-Marschallinger et al., 2022). For this study, we focused on applying the algorithm on a large-scale event and showing how to describe the impact of this kind of event based on flood mapping results. This is why we do not present the full methodology in this topical paper.

Please let us point you to some relevant links to this topic:

Methodology paper: https://www.mdpi.com/2072-4292/14/15/3673/htm

GFM Product Definition Document: https://extwiki.eodc.eu/GFM/PDD

EUMETSAT article: https://www.eumetsat.int/features/towards-better-flood-and-drought-monitoring

DG Echo map: https://erccportal.jrc.ec.europa.eu/ercmaps/ECDM_20220902_SW_Pakistan.pdf

Thank you and best regards,

Florian Roth (on behalf of all authors)

Dear reviewer,

Thank you for your comments. We have summarized your suggestions into 6 points and have prepared related answers, which you can find below. The corresponding changes in the manuscript will be part of the next revised version.

Thank you and best regards,

Florian Roth (on behalf of all authors)

Extended description of hydrology, climate and land use: 

To extend the context of this study, we will provide more details within the description of the study area (Section 2). As some of the discussions relate to the local land cover types, this change would additionally benefit a better understanding of the detected differences to the reference data.

Emphasize limitations of evaluation:

We agree with emphasizing the known limitations of the evaluation and presenting some details of potential implications of these. Since the comparable small area covered by the reference is mentioned in the description of the evaluation (Section 3), we will extend the explanations there.

More details on the differences of the two sensors:

Thank you for pointing this out. We will extend the description of the evaluation (Section 3) by some details on the differences of Spot and Sentinel-1.

Applications of the flood mapping algorithm in flood management and disaster :

To discuss some of the potential applications of flood mapping results, we will mention and link some literature on this topic in the introduction of the manuscript (Section 1). Thereby, we will focus on work on the use in the context of flood forecasting and early warning systems.

Discuss the significance of near-real-time applications:

As this study should present the near-real-time capabilities of our algorithm, we support the suggestion of discussing the significance of a short reaction time for flood management and disaster response. 

Add future developments and improvements to the algorithm:

As mentioned in the conclusion section of the manuscript, we plan to publish a deeper analysis of the algorithm’s performance based on globally distributed events. Consequently, additional insights on the needed improvements of the algorithm will be part of that study. However, we will add already known developments of the algorithm to the conclusion.