the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 May 2025
INSYDE-content: a synthetic, multi-variable flood damage model to household contents
Abstract. This paper introduces INSYDE-content, a novel, probabilistic multi-variable synthetic flood damage model designed to analyze physical damage to household contents on a component-by-component basis. The model addresses a critical gap in current modeling tools, which often overlook the significance of household contents in overall damage assessments. Developed through an expert-based approach and grounded in the scientific and technical literature, INSYDE-content leverages desk-based data to characterize model features, including uncertainty treatment arising from incomplete input data. A sensitivity analysis and a benchmark test against observed losses demonstrate the robust performance of the model and highlight the contribution of different features to damage mechanisms affecting house contents. While in this study INSYDE-content is tailored for illustrative purposes to the hazard, vulnerability and exposure characteristics of Northern Italy, the model is highly adaptable, allowing for its application to different regional contexts through appropriate customization.
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Supplement
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-1413', Anonymous Referee #1, 03 Jun 2025
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..
Citation: https://doi.org/10.5194/egusphere-2025-1413-RC1 - 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
The paper presents a new model for estimating flood damage to houshold contents. In contrast to damage to residential buildings, damaged household items are neglected in many (scientific) flood damage models or are estimated using simple approaches such as a lumped share of the estimated building damage. In practical loss estimation applications such as cost-benefit-analysis, where a loss estimation for all sectors and damage types is needed, further approaches exist, e.g. specific stage-damage functions for contents. These approaches are often not well documented or published. With INSYDE-contents the authors propose a detailed flood damage assessment of household contents based on 11 typical household items, their mean replacement values and the estimated number of damaged items, which depends on characteristics of the flood event and the affected buildings. The paper also adds insights on the model's performance and validation using two real world data sets. So, I think the paper and the model presented provide a valuable contribution to the scientific literature on flood loss modelling. Still, the paper could be further improved with regard to the following aspects:
- Introduction (line 44 - 59): While it is acknowledged that the authors present the relevant literature, not many insights about the existing approaches are provided. Please be clearer about the weaknesses and strengths of the models mentioned. And discuss later in the paper, what your model contributes in comparison to the existing approaches.
- Methodology: Since the model development is an important part of the whole paper, I think it should be presented in more detail. It doesn't become clear in my view, why these 11 items (lines 100-102) were selected. Later, the sampling procedure that led to 60 buildings and the sample itself could be better described. Furthermore, Table 3 and the analyses behind it, should be better explained. A lot of material is presented in the Supplement, but I would prefer to see at least one example how the damage function was derived for one item in the main text. Along the same lines, the methods in section 2.2 could benefit from some more details on the data and the methods used. Altogether, I think the paper could benefit from a flow chart or another image showing the different stages of the model development and evaluation as well as the data sets involved.
- Table 1: The equation for SA is given as SA = F(SA; NF). Do you mean FA as independent variable here?
- Table 1: Why do you use FA (instead of SA) in the equation for HU?
- line 176/177: rephrase ("by the same authors" is a bit confusing here)
- Table 3: As already mentioned above, the rationales and analyses behind the equations in Table 3 need more explanation.
- lines 217: "total actualized losses" - please check term
- Figure 2: This figure and the methods behind it need more explanation in my view. Also, the two data sets should be better described in the paper (briefly, but still in more detail than is currently the case).
- Figure 4: These results should be analyzed and discussed in much more detail. How come that the estimates for (semi-)detached house do not show much variability (in contrast to the estimates for apartments)? The authors should present more indepth analysis of these results, including common metrics for errors or model performance (RMSE, MAE etc.), and they should discuss potential weaknesses of their model. How could the model be further improved to better capture the variability of the observed damage/claims?
In general, I think that the results could be better interpreted and discussed. In a merged section "results and discussion" there's always the risk that the discussion is too short. The authors should expand theirs.
Supplement 1 is very helpful and detailed. It will enable others to apply the model, too, which is much appreciated.
Citation: https://doi.org/10.5194/egusphere-2025-1413-RC2 - AC2: 'Reply on RC2', Anna Rita Scorzini, 03 Jul 2025
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