Articles | Volume 25, issue 11
https://doi.org/10.5194/nhess-25-4317-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
INSYDE-content: a synthetic, multi-variable flood damage model for household contents
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- Final revised paper (published on 04 Nov 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 12 May 2025)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-1413', Anonymous Referee #1, 03 Jun 2025
- AC1: 'Reply on RC1', Anna Rita Scorzini, 03 Jul 2025
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RC2: 'Comment on egusphere-2025-1413', Anonymous Referee #2, 22 Jun 2025
- AC2: 'Reply on RC2', Anna Rita Scorzini, 03 Jul 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (14 Jul 2025) by Philip Ward
AR by Anna Rita Scorzini on behalf of the Authors (05 Aug 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (07 Aug 2025) by Philip Ward
RR by Anonymous Referee #2 (15 Aug 2025)
RR by Anonymous Referee #1 (22 Aug 2025)
ED: Reconsider after major revisions (further review by editor and referees) (03 Sep 2025) by Philip Ward
AR by Anna Rita Scorzini on behalf of the Authors (15 Sep 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (18 Sep 2025) by Philip Ward
RR by Anonymous Referee #1 (26 Sep 2025)
ED: Publish as is (01 Oct 2025) by Philip Ward
AR by Anna Rita Scorzini on behalf of the Authors (02 Oct 2025)
Manuscript
This paper provides a detailed description of the development of an expert based flood content damage model called INSYDE. It seems to be a follow up paper on the structure damage version of INSYDE, a model that seems to have found quite widespread use in the literature. The paper is well written and describes the development process well. The methods are solid but not very innovative and have been around in the grey literature for a long time (e.g. US Army Corps of Engineers). This paper goes in quite some detail describing the methods and adds much needed validation and is therefore definitely a useful addition to the scientific literature. That being said I have concerns about the validation results and more importantly the analysis of the results.
Figure 4 shows that for detached and semi-detached houses the variation in observed damages is much larger than the variation in predicted damages. My first impression is that the model always roughly predicts the same damage regardless of the circumstances (the blue dots are a nearly horizontal line). I think it may not be so bad because the log-log scale masks some of the variation. However, more information is required so readers can actually tell the model performance. For example, I currently cannot see if the variation in observed values is just based on some large outliers or whether there is some more fundamental problem whereby the observed losses have much more variation than the modelled losses. Also is there even any correlation between modelled and observed losses? I understand that there is unexplained uncertainty in the model predictions as indicated by the uncertainty ranges in figure 4. However, if the model typically predicts more or less the same mean how do I know such a complicated model adds any value compared to a simple mean value as prediction?
Also very common error metrics are missing such as Mean Absolute Error, correlation coefficient or R2, so it's nearly impossible to assess how the model is doing from the information presented in the paper. Not all these metrics are needed but at least more information. Table 4 only gives an aggregated comparison, so basically gives a bias value. In one region there seems to be some bias but the authors do not really explain where this bias might be coming from. Lastly, I would expect an in depth analysis and discussion of the model performance in the paper based on the validation. That analysis is missing, making the validation not very useful in its current form.
Some of the input variables for the model validation seem sampled whereas others seem observed and the current text is very unclear about what is sampled and what is observed. This makes it even more difficult to interpreted the validation results.
The word “to” in the title doesn’t read well, maybe you can replace it with “for”? Or another solution..