The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain)

Cortès, Maria; Turco, Marco; Llasat-Botija, Montserrat; Llasat, Maria Carmen

doi:https://doi.org/10.5194/nhess-18-857-2018

Articles | Volume 18, issue 3

https://doi.org/10.5194/nhess-18-857-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Damage of natural hazards: assessment and mitigation

https://doi.org/10.5194/nhess-18-857-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 3

Research article

|

16 Mar 2018

Research article |

| 16 Mar 2018

The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain)

Maria Cortès, Marco Turco, Montserrat Llasat-Botija, and Maria Carmen Llasat

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Final revised paper (published on 16 Mar 2018)
Supplement to the final revised paper
Preprint (discussion started on 07 Aug 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review for the article “The relationship between precipitation and insurance data for flood damages in a region of the Mediterranean (Northeast Spain)” by Maria Cortès et al.', Anonymous Referee #1, 24 Aug 2017
- AC1: 'Answers to reviewer #1', Maria Cortès, 24 Nov 2017
RC2: 'Review', Anonymous Referee #2, 18 Sep 2017
- AC2: 'Answers to reviewer #2', Maria Cortès, 24 Nov 2017
RC3: 'Review', Anonymous Referee #3, 06 Oct 2017
- AC3: 'Answers to reviewer #3', Maria Cortès, 24 Nov 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (24 Nov 2017) by Thomas Thaler

AR by Maria Cortès on behalf of the Authors (24 Nov 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (29 Nov 2017) by Thomas Thaler

RR by Anonymous Referee #2 (07 Dec 2017)

RR by Anonymous Referee #1 (12 Dec 2017)

Suggestions for revision or reasons for rejection

Review on the article “The relationship between precipitation and insurance data for surface water floods in a region of the Mediterranean (Northeast Spain)” by Maria Cortès et al.

General comments
The manuscript improved remarkably in the updated version. However, some weak points remain in the manuscripts.
While the hydrologic process that is investigated now has been defined more strictly (surface water floods), the differentiation between “flash floods” remain unclear. Are these two terms used synonymously?
As in the first version the focus laid on floods in general and now the focus is on surface water floods, I am wondering how the authors created the subset of claims affected exclusively by this type of floods from the whole set of flood losses.
The main goal and the research question remain unclear. For me, it is not clear whether the main aim is to search for a threshold, or to forecast losses, etc. I highly recommend to sharpen the research question.
It is not clearly described, how precipitation in Fig. 2 is calculated. Is the value for precipitation an average over Catalonia or it is the maximum value of all meteorological stations in Catalonia? The method for combining pairs of precipitation values and claims has to be described in more detail, especially in regards to the spatial reference unit at which aggregation of both variables was made. In Fig. 2 it is not clear if the units for precipitation are in [mm] or in [mm/h] (valid also for Fig. 4, 6 and 7).
The authors state that exact data on the value and location of assets exposed are not available (p. 30, ln. 2). However, in chapter 2.2 they state that the claims are aggregated on postcode level. Since the number of rainfall gauging stations is relatively dense in the lowland areas, the minimal spatial reference unit for analysing pairs of records should be the postcode area. Precipitation can be interpolated between stations to cover postcode areas without rainfall gauging stations. However, the mountain regions might be better excluded from the analysis. This corresponds with a statement that coastal areas are the most affected by flood events.
In chapter 2.2. (p. 2, ln 15.) the authors write that they compare the maximum of precipitation measured in a basin with losses aggregated at basin level. As some basins have a relatively heterogeneous topography and a remarkably aerial size, and as the main focus is on surface water floods, this assumption for correlation might be misleading. An intensive precipitation event captured by one of the rainfall stations can be restricted to a few kilometres and may not be representative for the whole basin. Thus, instead of the maximum precipitation an average over the whole basin might be more relevant when correlating precipitation with losses aggregated over the whole basin. The focus on the MAB underlines this. Another option is to focus on smaller spatial reference units as the post code areas, as proposed above. Furthermore, the paper could also be more sophisticated if it focuses on MAB only.
Regarding the calculation of the hit rate and false alarm rate, it would be very useful to define more clearly what has been count as a hit and what has been count as a false alarm. Furthermore, it has to be defined how the validation metrics are calculated and on which sample (how was the validation sample extracted from the whole data set and how many records it contains).

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RR by Anonymous Referee #3 (13 Dec 2017)

ED: Reconsider after major revisions (further review by editor and referees) (20 Dec 2017) by Thomas Thaler

AR by Maria Cortès on behalf of the Authors (19 Jan 2018) Author's response Manuscript

ED: Publish subject to minor revisions (review by editor) (30 Jan 2018) by Thomas Thaler

AR by Maria Cortès on behalf of the Authors (09 Feb 2018) Author's response Manuscript

ED: Publish as is (12 Feb 2018) by Thomas Thaler

AR by Maria Cortès on behalf of the Authors (13 Feb 2018)

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Short summary

The aim of this study is to develop and evaluate a methodology to estimate surface water flood damages from heavy precipitation in the Mediterranean region of study. The relationship between precipitation and insurance data has been assessed, using logistic regression models, to assess the probability of large monetary damages in relation to heavy precipitation events. Results show that our model is able to simulate the probability of a damaging event as a function of precipitation.