the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Dec 2021
Global to regional overview of floods fatality: the 1951–2020 period
Abstract. Floods are among the most devastating natural hazards. Human interferences along with climate change cause a lot of human and financial losses every year following the occurrence of floods. In this research, flooding events that have killed more than 10 people in the 1951–2020 period have been studied, analysing the EM-DAT database. The results show that the severity of flood-related deaths is equally distributed worldwide, but present some specific geographical patterns. The flood fatality coefficient, calculated for different countries, identified that Southern, Eastern, and South-Eastern regions of Asia have the deadliest floods in the world. The number of flood events has been increasing since 1951 and peaked in 2007, following a relatively declining trend since then. However, the number of death tolls does not follow a statistically significant trend. An examination of the number of flood events in different decades shows that the highest number of events occurred in the 2001–2010 decade, which corresponds to the largest precipitation anomaly in the world. The most casualties occurred in the decade 1991–2000. However, the lethality of floods has decreased over time, from 412 per flood in 1951–1960 to 67 in the 2011–2020 decade, probably as a consequence of a more resilient environment and better risk reduction strategies. In addition, a direct correlation was found between the number of flood events and the number of casualties with the world’s population.
- Preprint
(9618 KB) - Metadata XML
- BibTeX
- EndNote
Status: closed
-
RC1: 'Comment on nhess-2021-357', Anonymous Referee #1, 04 Jan 2022
General comments
The manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” written by Hamidifar & Nones is a quite interesting approach to the analysis of flood threat on a global scale. The research presented is rather simple – it’s based on the analysis of available data taken from a single source, Emergency Database. However, the information provided and the conclusions drawn may be very useful for many researchers working in different fields of engineering, economy, or social sciences.
The text is written well and the results are presented clearly. In general, the presentation of the findings is understandable. However, there are two drawbacks in my opinion.
- Lack of clearly defined purpose of this analysis. It seems to be obvious for the Authors, but in my opinion, it should be written explicitly in the Introduction.
- The Conclusions should be rewritten. There is an evident lack of broader discussion focused on the importance of the presented findings. A summary of the presented results is not enough for such a paper.
The detailed remarks are presented below.
Detailed remarks
Lines 51 and next
At this part, I would expect a clear definition of the paper's purpose.Lines 71 and next
The presentation of the most severe floods in the World is quite interesting part of the text due to the different reasons, but it's hard to understand the logic behind this detailed discussion of a relatively small category of floods. The paper is not focused only on the phenomena of this kind but tries to discuss the problem broader. Maybe it would be good to present a short overview of different types and discuss the main differences influencing the number of casualties.Line 84
In my opinion, the expression “the great famine that followed” indicates the small weakness of the presented approach. In this study, only the direct fatalities and direct economic losses are taken into account. It's well known that these are not only losses. So this picture of the distribution of the severe flood over the World may be affected by this approach and it may not present the real impacts on the societies, economies, etc.Section “Discussion”
In my opinion, some of the detailed analyses and calculations presented here could be a part of the results. In the discussion, I would like to focus on comparisons of the obtained results with possible causes, explanations, and other results reported in the literature.Lines 194 - 195
In my opinion, the statement “[…] as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase […]” is problematic and basic quotation is not enough in this case. Some additional comments are necessary.Line 202
The conclusion “[…] the number of casualties is directly related to the number of flood events […]” is rather obvious. Maybe it could be better to reformulate this sentence.Line 203
What do the Authors understand as “number of flood events can be reduced”? In my opinion, the losses may be reduced. The number of flood events understood as physical phenomena should not be reduced, because it requires the influence of atmospheric conditions and changes made to the climate. I’m afraid that this is not precise and it should be reformulated.Lines 204 - 207
This passage repeats the well-known ideas of reduction of flood losses by coming back to as natural conditions in the catchment as it is possible. From my experience as a flood hazard modeler, it results that such methods may not be very effective. So, this passage expresses some wishes, but these may not be real, in my opinion.Line 213
I cannot agree that the linkage between the growth of GDP and flooding is in deforestation and rapid urbanization. In my opinion, there might be different mechanisms. The river are economically useful for centuries. The increasing GDP could mean that more people are living near the rivers.Lines 249 – 250
This sentence fits more the section Conclusions.Section “Conclusions”
This section presents a summary of the research, not the real conclusions. I would expect in this section some comments on the further usage of these results, their impact on other areas of engineering and scientific activity, etc.Citation: https://doi.org/10.5194/nhess-2021-357-RC1 -
AC1: 'Reply on RC1', Michael Nones, 06 Jan 2022
Dear Reviewer,
We would like to thank you very much for your comments, which were very helpful to better structure our manuscript, and to drive the key messages.
In the revised version we addressed all your comments in detail, and our point-by-point answers can be found in the following.
General comments
The manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” written by Hamidifar & Nones is a quite interesting approach to the analysis of flood threat on a global scale. The research presented is rather simple – it’s based on the analysis of available data taken from a single source, Emergency Database. However, the information provided and the conclusions drawn may be very useful for many researchers working in different fields of engineering, economy, or social sciences.
Thank you very much for your encouraging words. We are aware that our analysis is intrinsically affected by the reduced data analysed, and we stressed this concept in the manuscript to avoid misunderstandings.
The text is written well and the results are presented clearly. In general, the presentation of the findings is understandable. However, there are two drawbacks in my opinion.
Lack of clearly defined purpose of this analysis. It seems to be obvious for the Authors, but in my opinion, it should be written explicitly in the Introduction.
The Conclusions should be rewritten. There is an evident lack of broader discussion focused on the importance of the presented findings. A summary of the presented results is not enough for such a paper.
The detailed remarks are presented below.
We revised the manuscript following your comments, improving both the Introduction and the Discussion to better pinpoint the current state-of-art and the novelty of our work. The Conclusions were expanded to provide readers with more insights on the findings, rather than just presenting them.
Detailed remarks
Lines 51 and next
At this part, I would expect a clear definition of the paper's purpose.
Thank you for your comments. We have added a few new sentences to emphasize the aims of the study.
Lines 71 and next
The presentation of the most severe floods in the World is quite interesting part of the text due to the different reasons, but it's hard to understand the logic behind this detailed discussion of a relatively small category of floods. The paper is not focused only on the phenomena of this kind but tries to discuss the problem broader. Maybe it would be good to present a short overview of different types and discuss the main differences influencing the number of casualties.
To provide readers with more details on the study rationale, the following sentence has been added to the text according to the reviewer’s comment. “While coastal and flash floods are the most catastrophic disasters that cause the most deaths worldwide, river flood has the highest frequency among all types of floods and therefore has the greatest impact on human society in terms of loss of life and economic.”
As discussed in the manuscript, in the long term, most casualties are caused by relatively “small” events, which were quite frequent during the study period. On the other part, very extreme events can cause significant losses, but are very rare. To corroborate the information provided in Figure 1, we analysed in detail these six events, pointing out their major characteristics.
Line 84
In my opinion, the expression “the great famine that followed” indicates the small weakness of the presented approach. In this study, only the direct fatalities and direct economic losses are taken into account. It's well known that these are not only losses. So this picture of the distribution of the severe flood over the World may be affected by this approach and it may not present the real impacts on the societies, economies, etc.
Thank you very much for the comments. As you also pointed out, in the present study, the focus is on direct losses that occurred immediately after the flood and due to flood flow or flooding surrounding the rivers. Clearly, the number of indirect deaths from flooding may increase over time. For example, years after the flood, people may die due to psychological problems caused by the loss of life and property caused to themselves or their relatives, which cannot be closely examined. In this work, only quantitative and direct data were analyzed and indirect losses were not the subject of the present study. We improved the text to clarify our aims, and to acknowledge that indirect and cascading effects of floods were not considered in the present study.
Section “Discussion”
In my opinion, some of the detailed analyses and calculations presented here could be a part of the results. In the discussion, I would like to focus on comparisons of the obtained results with possible causes, explanations, and other results reported in the literature.
The Discussion section has been revised and some new explanations have been added to the text, aiming to better compare our study with literature evidence and similar works.
We also revised the Results section, to highlight that this section was focused on presenting the outcomes in terms of death tolls and fatality coefficient as derived from the EM-DAT database, while possible drivers (e.g., precipitation anomalies) and co-causes (e.g., population density) were analysed in the Discussion.
Lines 194 - 195
In my opinion, the statement “[…] as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase […]” is problematic and basic quotation is not enough in this case. Some additional comments are necessary.
The text has been revised as follow: “For example, Tellman et al. (2021) used satellite imagery to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018, and concluded that as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase”.
Line 202
The conclusion “[…] the number of casualties is directly related to the number of flood events […]” is rather obvious. Maybe it could be better to reformulate this sentence.
We revised this sentence, which now reads “…the number of casualties increases with the number of flood events…”.
Line 203
What do the Authors understand as “number of flood events can be reduced”? In my opinion, the losses may be reduced. The number of flood events understood as physical phenomena should not be reduced, because it requires the influence of atmospheric conditions and changes made to the climate. I’m afraid that this is not precise and it should be reformulated.
It seems that a misunderstanding happened here. Our purpose was not to reduce rainfall, as we are completely aware that natural phenomena cannot be changed. When rainfall occurs, some of the rainwater flows as runoff and can lead to flooding. If action is taken to reduce runoff, it could be eventually possible to prevent the river flow from increasing too much, so that it does not exit the main channel and overflow the floodplains. There are many solutions to this issue and some examples were given in the text.
Lines 204 - 207
This passage repeats the well-known ideas of reduction of flood losses by coming back to as natural conditions in the catchment as it is possible. From my experience as a flood hazard modeler, it results that such methods may not be very effective. So, this passage expresses some wishes, but these may not be real, in my opinion.
The authors thank the reviewer for this valuable comment, which points to the practical aspect of the problem. However, the shortcomings in implementing the policies and strategies by the decision-makers have always been a major problem, which has been the product of hasty development neglecting the environmental requirements. However, although some policies may be slow to implement in some areas at the moment, we hope that efforts to implement proposed solutions adapted to nature will continue.
Line 213
I cannot agree that the linkage between the growth of GDP and flooding is in deforestation and rapid urbanization. In my opinion, there might be different mechanisms. The river are economically useful for centuries. The increasing GDP could mean that more people are living near the rivers.
Thank you. The text has been revised as “…and increased population density in the adjacent areas of rivers.”
Lines 249 – 250
This sentence fits more the section Conclusions.
Thank you for the hint. We moved the sentence to the end of the Conclusions section.
Section “Conclusions”
This section presents a summary of the research, not the real conclusions. I would expect in this section some comments on the further usage of these results, their impact on other areas of engineering and scientific activity, etc.
Thank you for the comment. We expanded the Conclusions, providing a few more comments on the further use of our results, as well as on open questions to be addressed in the future.
Citation: https://doi.org/10.5194/nhess-2021-357-AC1
-
RC2: 'Comment on nhess-2021-357', Anonymous Referee #2, 21 Jan 2022
I have carefully read the manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” whose main focus is the description of simple analyses of the number of fatal flood events and on the number of flood fatalities per event carried out at nationwide scale. The work is based on the available EM-DAT Emergency Database. The results draw a picture of the global situation of the impact of flood events on the global population even if they limited their analyses to the subset of fatal events with casualties between 10 and 9999. The authors selected this magnitude threshold for the flood fatal events since the research hypothesis is focused only on disastrous floods.
The topic is of extreme importance and the effort made by the authors in trying to compare the various data at a global scale is remarkable, but in my opinion not sufficient to make the manuscript acceptable. A global analysis is certainly very demanding and involves the elaboration of huge amount of data - demographic, economic, social, climatic and physical data - which, really, I did not find in the manuscript. At present, the text is a description of the analyses performed and the true purpose of the work does not emerge at all. Due to the lack of a clear aim, the manuscript has some weak sections including the method and discussion. What is missing is a broader discussion focused on the importance of the results presented in the context of the extensive literature available on these topics in light of the climate change context.
My general comments:
The source of data the authors used is available at global scale, and it is a good point, but it can’t be considered a comprehensive overview of the impact that floods produce to the population for most of the countries. The very frequent but less disastrous fatal flood events occurring every year anywhere in the world were not recorded in EM-DAT since the difficulty in capturing the information does not allow the minor events to be recorded. We do not know how much these minor events cumulatively amount to. Moreover, the EMDAT casualties estimates are not always consistent with those available in other sources and, frequently, these estimates include among the flood fatalities those due for other factors. The authors do not at all discuss the problem of the estimates uncertainty and how it might affect their results
I wonder if it makes sense to compare data on flood fatalities on a global scale when the geographical, demographic, social and economic characteristics of different nations are so profoundly different. Can the GDP as unique parameter explain the relation between the flood fatalities and the effort done to increase knowledge and technologies to mitigate the effects of flood events? Maybe the authors should consider additional socio-economic parameters and assess, for example, the social vulnerability of the single countries. I can support the authors in considering administrative limits as important in calculating true fatality coefficient of floods in order to compare them with each other. But this is true only in relation to the economic and political conditions of each country and how government choices can affect flood risk management. However, the administrative limits have nothing to do with the risk zoning where the people, who are most at risk, live. How did the data were spatialized? I bring this question to the attention of the authors since the distribution of the population within very large countries cannot weigh as much as the distribution of smaller ones, where the average density is approximately equal throughout the national territory. Have they considered this aspect? to strengthen the work, it could be helpful the estimation the real number of the population exposed to risk using, for example, the dasimetric maps.
To compare the human losses caused by floods in the different countries, the authors firstly used the fatality coefficient of floods calculated by dividing the total number of death tolls by the number of flood events for each country. I cannot understand if they calculated this coefficient year by year (for the 70-year period) and then they used the average in the long period, or if they simply divided the total number of fatalities by the total number of fatal event.
This consideration points to my second comment concerning the meaning of disastrous event. How can we define disastrous an event at global scale without considering at least the different country population density? Is It possible to quantitatively define “disastrous” merely with the number of fatalities for event, and is this parameter actually useful for comparing data across countries of different size and population density? To define a disastrous event the authors could make a greater effort and estimate a moving thresholds, weighed both on the number of victims per event and on the population density.
Even if the authors attempted to consider the population density and the number of events per unit area (plots in figure 10), it is not clear if they have used the population data by nation and year by year and if the relation they found has changed in time, or if they have counted only the average in the long period. To overcome this weakness, the authors could calculate for the investigated period (1951–2020) the average mortality rates - at nation level - which are given by the number of fatalities recorded every year in a single nation, scaled to the size of the population in the related period of time. The mortality rate is normally used to compare the impact on the population of technological, health and even natural hazards. The authors could rank the nations on the basis of the mortality rates. They should use the annual population data for each country for the 70-year period. If the annual data are not available for the long period, they could reduce the time period.
In the discussion section the authors state that reducing flood will reduce the number of fatalities. This is conceptually wrong. It is possible reducing the impact, the losses and the intensity of a flood events, with structural and non-structural mitigation measures, but not the number of the physical processes, since it is due to the combination of many physical variables, firstly the rainfall intensity.
I would also like to point out the lack of thoroughness description in the way the authors present their results and outputs. The plots they produced are poorly described and not properly discussed and, in some cases, the citations of the figure numbers in the text are wrong.
Comments on the manuscript structure:
The data and method section is too poor and the method they used is not described anywhere, they only described why they selected the subset of data from EM-DAT.
The list of events they include in section 2 should be removed or moved in an appendix section, together with table 1.
Most of the results are in the discussion section. The authors should better define what they consider as results of their analysis and what they want highlight and discuss
The conclusion should be rewritten.
Citation: https://doi.org/10.5194/nhess-2021-357-RC2 -
AC2: 'Reply on RC2', Michael Nones, 26 Jan 2022
Dear Reviewer,
We would like to thank you very much for your comments, which were very helpful to better structure our manuscript, and to drive the key messages. In the revised version we addressed all your comments in detail, trying to combine your feedback with the hints coming from the other reviewer. Our point-by-point answers can be found in the following, where we numbered the reviewer’s comments using the format R2Cn, with n indicating the comment’s number.
R2C1: The source of data the authors used is available at global scale, and it is a good point, but it can’t be considered a comprehensive overview of the impact that floods produce to the population for most of the countries. The very frequent but less disastrous fatal flood events occurring every year anywhere in the world were not recorded in EM-DAT since the difficulty in capturing the information does not allow the minor events to be recorded. We do not know how much these minor events cumulatively amount to. Moreover, the EMDAT casualties estimates are not always consistent with those available in other sources and, frequently, these estimates include among the flood fatalities those due for other factors. The authors do not at all discuss the problem of the estimates uncertainty and how it might affect their results.
Thanks for the comment and suggestions. We have emphasized this at the end of the Conclusions as a limitation of our study. It is stated there that: “It is worth note that the presented conclusions derive from a single database, and are therefore influenced by the data availability and the uncertainty of the collected information. Future studies will concentrate on integrating information coming from multiple databases, aiming to obtain more structured and event-based outcomes. Moreover, a comparison between different datasets will allow for gaining major insights in the data uncertainty (namely, differences between the datasets) and its sources.”
It should also be noted that EM-DAT adopts a recognized ranking method to select sources for flood disaster statistics, combining data from the United Nations, governmental and non-governmental agencies, insurance companies, research institutes and press agencies[1]. We revised the text to better pinpoint this approach.
R2C2: I wonder if it makes sense to compare data on flood fatalities on a global scale when the geographical, demographic, social and economic characteristics of different nations are so profoundly different. Can the GDP as unique parameter explain the relation between the flood fatalities and the effort done to increase knowledge and technologies to mitigate the effects of flood events? Maybe the authors should consider additional socio-economic parameters and assess, for example, the social vulnerability of the single countries. I can support the authors in considering administrative limits as important in calculating true fatality coefficient of floods in order to compare them with each other. But this is true only in relation to the economic and political conditions of each country and how government choices can affect flood risk management. However, the administrative limits have nothing to do with the risk zoning where the people, who are most at risk, live. How did the data were spatialized? I bring this question to the attention of the authors since the distribution of the population within very large countries cannot weigh as much as the distribution of smaller ones, where the average density is approximately equal throughout the national territory. Have they considered this aspect? to strengthen the work, it could be helpful the estimation the real number of the population exposed to risk using, for example, the dasimetric maps.
English translation.
Thank you very much for the comments. We revised the text to further detail the study goals and to avoid misunderstandings, as well as improved significantly the Discussion section to compare our work with past investigations.
While it is true that floods fatalities are functions of several parameters, the individual participation of these unique parameters on floods fatalities is not yet clear. For example, a previous study has shown that mortality varies by region, but the expectation that floods in areas with lower living standards will cause higher mortality cannot be supported [2].
As one of the goals of the current study is to visualize the trend of variations of floods fatalities over a 70-years period, and keeping in mind the fact that there is not much information available for the early floods in the studied period, GDP was selected as an indicator. Obviously, more studies considering additional indicators should be done to provide a comprehensive picture of floods fatalities.
Although the authors agree with the reviewer that the population is not uniformly distributed in different countries, studying changes in population density and its impact on flood damages was not among the objectives of the current study. Even though investigating the effect of population density can increase the accuracy of the indicators presented in the present study, the application of these challenges may be difficult from a managerial point of view.
R2C3: To compare the human losses caused by floods in the different countries, the authors firstly used the fatality coefficient of floods calculated by dividing the total number of death tolls by the number of flood events for each country. I cannot understand if they calculated this coefficient year by year (for the 70-year period) and then they used the average in the long period, or if they simply divided the total number of fatalities by the total number of fatal event.
Only one coefficient was calculated for the entire range of the years studied. We revised the text to clarify this concept.
R2C4: This consideration points to my second comment concerning the meaning of disastrous event. How can we define disastrous an event at global scale without considering at least the different country population density? Is It possible to quantitatively define “disastrous” merely with the number of fatalities for event, and is this parameter actually useful for comparing data across countries of different size and population density? To define a disastrous event the authors could make a greater effort and estimate a moving threshold, weighed both on the number of victims per event and on the population density.
As mentioned in the text, “… flood casualties in the category of fewer than 10 people include a small part (less than 0.2%) of the total casualties, and therefore, in the present study, this category of data is not considered in the analysis.” Also, the selection of disastrous flood events with more than a specific number of deaths in flood fatalities analysis is not a new idea and was reported in previous studies, so we based our approach on literature evidence to allow for comparison. For example, Gaume et al. (2016) analyzed disastrous flash flood events with more than 10 deaths to find a general pattern of the spatial and seasonal distribution of flood magnitudes over the Mediterranean region [3]. In 2006, Barredo assessed information on major flood disasters producing more than 70 casualties for the production of the map and catalogue of major flood disasters in Europe [4]. Also, according to Merz et al. (2021), flood events can be considered disastrous when they are included in EM-DAT [5].
We revised the text considering your feedback, and tried to clarify our approach.
R2C5: Even if the authors attempted to consider the population density and the number of events per unit area (plots in figure 10), it is not clear if they have used the population data by nation and year by year and if the relation they found has changed in time, or if they have counted only the average in the long period. To overcome this weakness, the authors could calculate for the investigated period (1951–2020) the average mortality rates - at nation level - which are given by the number of fatalities recorded every year in a single nation, scaled to the size of the population in the related period of time. The mortality rate is normally used to compare the impact on the population of technological, health and even natural hazards. The authors could rank the nations on the basis of the mortality rates. They should use the annual population data for each country for the 70-year period. If the annual data are not available for the long period, they could reduce the time period.
The authors would like to thank the reviewer for pointing out this issue.
Obviously, the population of every country is not constant and changes with time. As we used the cumulative number of fatalities, the population of each country at the end of the study period, as the reference year, was used in both Figure 9 and Figure 10. However, the temporal variations of the number of fatalities and flood events on a global scale are provided in Figure 7.
As the focus of the present study is a global to regional overview of floods fatality, investigating changes in the number of fatalities and the number of flood events in each of the world’ countries individually was outside the objectives of the present study. We revised the text to clarify this, and expanded the Discussion considering your precious feedback.
R2C6: In the discussion section the authors state that reducing flood will reduce the number of fatalities. This is conceptually wrong. It is possible reducing the impact, the losses and the intensity of a flood events, with structural and non-structural mitigation measures, but not the number of the physical processes, since it is due to the combination of many physical variables, firstly the rainfall intensity.
It seems that a misunderstanding happened here. Our purpose was not to reduce rainfall, as we are completely aware that natural phenomena cannot be changed. When rainfall occurs, some of the rainwater flows as runoff and can lead to flooding. If action is taken to reduce runoff, it could be eventually possible to prevent the river flow from increasing too much, so that it does not exit the main channel and overflow the floodplains. There are many solutions to this issue and some examples were given in the text. Following your comments, we revised the text clarifying our idea.
R2C7: I would also like to point out the lack of thoroughness description in the way the authors present their results and outputs. The plots they produced are poorly described and not properly discussed and, in some cases, the citations of the figure numbers in the text are wrong.
We would like to kindly thank you for having pointed out this weakness.
The text has been revised, and more explanations have been added to better describe the plots. Also, the citations of the figures have been double-checked.
R2C7: The data and method section is too poor and the method they used is not described anywhere, they only described why they selected the subset of data from EM-DAT.
Thank you for the comments.
The “Materials and Methods” section has been elaborated to provide more information, which now allow for the study reproducibility.
R2C8: The list of events they include in section 2 should be removed or moved in an appendix section, together with table 1.
Thank you for your suggestion.
We decided to keep the description of the major flooding events (and the related Table 1) in the main text to provide readers with examples of how difficult could be inferring information on flood-related deaths. The text now reads “… the number of events with casualties of more than 10000 people is small (six cases, 1), and the number mentioned in the sources regarding the casualties of these events is mainly mixed with casualties due to incidental events, this category has been investigated on a case-by-case basis…”
R2C9: Most of the results are in the discussion section. The authors should better define what they consider as results of their analysis and what they want highlight and discuss
Following your comments, we revised the text to better clarify our approach: in the Results section, we reported the analysis of the data derived from the EM-DAT database (namely, flood fatalities), while in the Discussion we tried to understand if some patterns of flood fatalities exist, relating them to different drivers, such as population density (physical drivers) or GDP (socio-economic drivers).
We revised the text to stress the differences between the information reported in the Results and the Discussion sections, and we also significantly expanded the latter section by comparing our outcomes with literature evidence.
R2C10: The conclusion should be rewritten.
Thank you for the comment and the opportunity to revise the manuscript.
We revised and expanded the Conclusions, providing more comments on the further use of our results, as well as on open questions to be addressed in the future.
References
- De Groeve, T.; Poljansek, K.; Ehrlich, D. Recording Disaster Losses, Recommendations for a European Research.; Publications Office of the European Union: Luxembourg:, 2013; Vol. 26111;.
- Jonkman, S.N. Global Perspectives on Loss of Human Life Caused by Floods. Nat. Hazards 2005 342 2005, 34, 151–175, doi:10.1007/S11069-004-8891-3.
- Gaume, E.; Borga, M.; Llassat, M.C.; Maouche, S.; Gaume, E.; Borga, M.; Llassat, M.C.; Maouche, S.; Lang, M. Mediterranean extreme floods and flash floods; Coll. Synthèses: Marseille, France, 2016;
- Barredo, J.I. Major flood disasters in Europe: 1950–2005. Nat. Hazards 2006 421 2006, 42, 125–148, doi:10.1007/S11069-006-9065-2.
- Merz, B.; Blöschl, G.; Vorogushyn, S.; Dottori, F.; Aerts, J.C.J.H.; Bates, P.; Bertola, M.; Kemter, M.; Kreibich, H.; Lall, U.; et al. Causes, impacts and patterns of disastrous river floods. Nat. Rev. Earth Environ. 2021 29 2021, 2, 592–609, doi:10.1038/s43017-021-00195-3.
Citation: https://doi.org/10.5194/nhess-2021-357-AC2
-
AC2: 'Reply on RC2', Michael Nones, 26 Jan 2022
Status: closed
-
RC1: 'Comment on nhess-2021-357', Anonymous Referee #1, 04 Jan 2022
General comments
The manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” written by Hamidifar & Nones is a quite interesting approach to the analysis of flood threat on a global scale. The research presented is rather simple – it’s based on the analysis of available data taken from a single source, Emergency Database. However, the information provided and the conclusions drawn may be very useful for many researchers working in different fields of engineering, economy, or social sciences.
The text is written well and the results are presented clearly. In general, the presentation of the findings is understandable. However, there are two drawbacks in my opinion.
- Lack of clearly defined purpose of this analysis. It seems to be obvious for the Authors, but in my opinion, it should be written explicitly in the Introduction.
- The Conclusions should be rewritten. There is an evident lack of broader discussion focused on the importance of the presented findings. A summary of the presented results is not enough for such a paper.
The detailed remarks are presented below.
Detailed remarks
Lines 51 and next
At this part, I would expect a clear definition of the paper's purpose.Lines 71 and next
The presentation of the most severe floods in the World is quite interesting part of the text due to the different reasons, but it's hard to understand the logic behind this detailed discussion of a relatively small category of floods. The paper is not focused only on the phenomena of this kind but tries to discuss the problem broader. Maybe it would be good to present a short overview of different types and discuss the main differences influencing the number of casualties.Line 84
In my opinion, the expression “the great famine that followed” indicates the small weakness of the presented approach. In this study, only the direct fatalities and direct economic losses are taken into account. It's well known that these are not only losses. So this picture of the distribution of the severe flood over the World may be affected by this approach and it may not present the real impacts on the societies, economies, etc.Section “Discussion”
In my opinion, some of the detailed analyses and calculations presented here could be a part of the results. In the discussion, I would like to focus on comparisons of the obtained results with possible causes, explanations, and other results reported in the literature.Lines 194 - 195
In my opinion, the statement “[…] as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase […]” is problematic and basic quotation is not enough in this case. Some additional comments are necessary.Line 202
The conclusion “[…] the number of casualties is directly related to the number of flood events […]” is rather obvious. Maybe it could be better to reformulate this sentence.Line 203
What do the Authors understand as “number of flood events can be reduced”? In my opinion, the losses may be reduced. The number of flood events understood as physical phenomena should not be reduced, because it requires the influence of atmospheric conditions and changes made to the climate. I’m afraid that this is not precise and it should be reformulated.Lines 204 - 207
This passage repeats the well-known ideas of reduction of flood losses by coming back to as natural conditions in the catchment as it is possible. From my experience as a flood hazard modeler, it results that such methods may not be very effective. So, this passage expresses some wishes, but these may not be real, in my opinion.Line 213
I cannot agree that the linkage between the growth of GDP and flooding is in deforestation and rapid urbanization. In my opinion, there might be different mechanisms. The river are economically useful for centuries. The increasing GDP could mean that more people are living near the rivers.Lines 249 – 250
This sentence fits more the section Conclusions.Section “Conclusions”
This section presents a summary of the research, not the real conclusions. I would expect in this section some comments on the further usage of these results, their impact on other areas of engineering and scientific activity, etc.Citation: https://doi.org/10.5194/nhess-2021-357-RC1 -
AC1: 'Reply on RC1', Michael Nones, 06 Jan 2022
Dear Reviewer,
We would like to thank you very much for your comments, which were very helpful to better structure our manuscript, and to drive the key messages.
In the revised version we addressed all your comments in detail, and our point-by-point answers can be found in the following.
General comments
The manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” written by Hamidifar & Nones is a quite interesting approach to the analysis of flood threat on a global scale. The research presented is rather simple – it’s based on the analysis of available data taken from a single source, Emergency Database. However, the information provided and the conclusions drawn may be very useful for many researchers working in different fields of engineering, economy, or social sciences.
Thank you very much for your encouraging words. We are aware that our analysis is intrinsically affected by the reduced data analysed, and we stressed this concept in the manuscript to avoid misunderstandings.
The text is written well and the results are presented clearly. In general, the presentation of the findings is understandable. However, there are two drawbacks in my opinion.
Lack of clearly defined purpose of this analysis. It seems to be obvious for the Authors, but in my opinion, it should be written explicitly in the Introduction.
The Conclusions should be rewritten. There is an evident lack of broader discussion focused on the importance of the presented findings. A summary of the presented results is not enough for such a paper.
The detailed remarks are presented below.
We revised the manuscript following your comments, improving both the Introduction and the Discussion to better pinpoint the current state-of-art and the novelty of our work. The Conclusions were expanded to provide readers with more insights on the findings, rather than just presenting them.
Detailed remarks
Lines 51 and next
At this part, I would expect a clear definition of the paper's purpose.
Thank you for your comments. We have added a few new sentences to emphasize the aims of the study.
Lines 71 and next
The presentation of the most severe floods in the World is quite interesting part of the text due to the different reasons, but it's hard to understand the logic behind this detailed discussion of a relatively small category of floods. The paper is not focused only on the phenomena of this kind but tries to discuss the problem broader. Maybe it would be good to present a short overview of different types and discuss the main differences influencing the number of casualties.
To provide readers with more details on the study rationale, the following sentence has been added to the text according to the reviewer’s comment. “While coastal and flash floods are the most catastrophic disasters that cause the most deaths worldwide, river flood has the highest frequency among all types of floods and therefore has the greatest impact on human society in terms of loss of life and economic.”
As discussed in the manuscript, in the long term, most casualties are caused by relatively “small” events, which were quite frequent during the study period. On the other part, very extreme events can cause significant losses, but are very rare. To corroborate the information provided in Figure 1, we analysed in detail these six events, pointing out their major characteristics.
Line 84
In my opinion, the expression “the great famine that followed” indicates the small weakness of the presented approach. In this study, only the direct fatalities and direct economic losses are taken into account. It's well known that these are not only losses. So this picture of the distribution of the severe flood over the World may be affected by this approach and it may not present the real impacts on the societies, economies, etc.
Thank you very much for the comments. As you also pointed out, in the present study, the focus is on direct losses that occurred immediately after the flood and due to flood flow or flooding surrounding the rivers. Clearly, the number of indirect deaths from flooding may increase over time. For example, years after the flood, people may die due to psychological problems caused by the loss of life and property caused to themselves or their relatives, which cannot be closely examined. In this work, only quantitative and direct data were analyzed and indirect losses were not the subject of the present study. We improved the text to clarify our aims, and to acknowledge that indirect and cascading effects of floods were not considered in the present study.
Section “Discussion”
In my opinion, some of the detailed analyses and calculations presented here could be a part of the results. In the discussion, I would like to focus on comparisons of the obtained results with possible causes, explanations, and other results reported in the literature.
The Discussion section has been revised and some new explanations have been added to the text, aiming to better compare our study with literature evidence and similar works.
We also revised the Results section, to highlight that this section was focused on presenting the outcomes in terms of death tolls and fatality coefficient as derived from the EM-DAT database, while possible drivers (e.g., precipitation anomalies) and co-causes (e.g., population density) were analysed in the Discussion.
Lines 194 - 195
In my opinion, the statement “[…] as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase […]” is problematic and basic quotation is not enough in this case. Some additional comments are necessary.
The text has been revised as follow: “For example, Tellman et al. (2021) used satellite imagery to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018, and concluded that as population density increases in areas at high risk of flooding, the number of flood casualties is expected to increase”.
Line 202
The conclusion “[…] the number of casualties is directly related to the number of flood events […]” is rather obvious. Maybe it could be better to reformulate this sentence.
We revised this sentence, which now reads “…the number of casualties increases with the number of flood events…”.
Line 203
What do the Authors understand as “number of flood events can be reduced”? In my opinion, the losses may be reduced. The number of flood events understood as physical phenomena should not be reduced, because it requires the influence of atmospheric conditions and changes made to the climate. I’m afraid that this is not precise and it should be reformulated.
It seems that a misunderstanding happened here. Our purpose was not to reduce rainfall, as we are completely aware that natural phenomena cannot be changed. When rainfall occurs, some of the rainwater flows as runoff and can lead to flooding. If action is taken to reduce runoff, it could be eventually possible to prevent the river flow from increasing too much, so that it does not exit the main channel and overflow the floodplains. There are many solutions to this issue and some examples were given in the text.
Lines 204 - 207
This passage repeats the well-known ideas of reduction of flood losses by coming back to as natural conditions in the catchment as it is possible. From my experience as a flood hazard modeler, it results that such methods may not be very effective. So, this passage expresses some wishes, but these may not be real, in my opinion.
The authors thank the reviewer for this valuable comment, which points to the practical aspect of the problem. However, the shortcomings in implementing the policies and strategies by the decision-makers have always been a major problem, which has been the product of hasty development neglecting the environmental requirements. However, although some policies may be slow to implement in some areas at the moment, we hope that efforts to implement proposed solutions adapted to nature will continue.
Line 213
I cannot agree that the linkage between the growth of GDP and flooding is in deforestation and rapid urbanization. In my opinion, there might be different mechanisms. The river are economically useful for centuries. The increasing GDP could mean that more people are living near the rivers.
Thank you. The text has been revised as “…and increased population density in the adjacent areas of rivers.”
Lines 249 – 250
This sentence fits more the section Conclusions.
Thank you for the hint. We moved the sentence to the end of the Conclusions section.
Section “Conclusions”
This section presents a summary of the research, not the real conclusions. I would expect in this section some comments on the further usage of these results, their impact on other areas of engineering and scientific activity, etc.
Thank you for the comment. We expanded the Conclusions, providing a few more comments on the further use of our results, as well as on open questions to be addressed in the future.
Citation: https://doi.org/10.5194/nhess-2021-357-AC1
-
RC2: 'Comment on nhess-2021-357', Anonymous Referee #2, 21 Jan 2022
I have carefully read the manuscript entitled “Global to regional overview of floods fatality: the 1951–2020 period” whose main focus is the description of simple analyses of the number of fatal flood events and on the number of flood fatalities per event carried out at nationwide scale. The work is based on the available EM-DAT Emergency Database. The results draw a picture of the global situation of the impact of flood events on the global population even if they limited their analyses to the subset of fatal events with casualties between 10 and 9999. The authors selected this magnitude threshold for the flood fatal events since the research hypothesis is focused only on disastrous floods.
The topic is of extreme importance and the effort made by the authors in trying to compare the various data at a global scale is remarkable, but in my opinion not sufficient to make the manuscript acceptable. A global analysis is certainly very demanding and involves the elaboration of huge amount of data - demographic, economic, social, climatic and physical data - which, really, I did not find in the manuscript. At present, the text is a description of the analyses performed and the true purpose of the work does not emerge at all. Due to the lack of a clear aim, the manuscript has some weak sections including the method and discussion. What is missing is a broader discussion focused on the importance of the results presented in the context of the extensive literature available on these topics in light of the climate change context.
My general comments:
The source of data the authors used is available at global scale, and it is a good point, but it can’t be considered a comprehensive overview of the impact that floods produce to the population for most of the countries. The very frequent but less disastrous fatal flood events occurring every year anywhere in the world were not recorded in EM-DAT since the difficulty in capturing the information does not allow the minor events to be recorded. We do not know how much these minor events cumulatively amount to. Moreover, the EMDAT casualties estimates are not always consistent with those available in other sources and, frequently, these estimates include among the flood fatalities those due for other factors. The authors do not at all discuss the problem of the estimates uncertainty and how it might affect their results
I wonder if it makes sense to compare data on flood fatalities on a global scale when the geographical, demographic, social and economic characteristics of different nations are so profoundly different. Can the GDP as unique parameter explain the relation between the flood fatalities and the effort done to increase knowledge and technologies to mitigate the effects of flood events? Maybe the authors should consider additional socio-economic parameters and assess, for example, the social vulnerability of the single countries. I can support the authors in considering administrative limits as important in calculating true fatality coefficient of floods in order to compare them with each other. But this is true only in relation to the economic and political conditions of each country and how government choices can affect flood risk management. However, the administrative limits have nothing to do with the risk zoning where the people, who are most at risk, live. How did the data were spatialized? I bring this question to the attention of the authors since the distribution of the population within very large countries cannot weigh as much as the distribution of smaller ones, where the average density is approximately equal throughout the national territory. Have they considered this aspect? to strengthen the work, it could be helpful the estimation the real number of the population exposed to risk using, for example, the dasimetric maps.
To compare the human losses caused by floods in the different countries, the authors firstly used the fatality coefficient of floods calculated by dividing the total number of death tolls by the number of flood events for each country. I cannot understand if they calculated this coefficient year by year (for the 70-year period) and then they used the average in the long period, or if they simply divided the total number of fatalities by the total number of fatal event.
This consideration points to my second comment concerning the meaning of disastrous event. How can we define disastrous an event at global scale without considering at least the different country population density? Is It possible to quantitatively define “disastrous” merely with the number of fatalities for event, and is this parameter actually useful for comparing data across countries of different size and population density? To define a disastrous event the authors could make a greater effort and estimate a moving thresholds, weighed both on the number of victims per event and on the population density.
Even if the authors attempted to consider the population density and the number of events per unit area (plots in figure 10), it is not clear if they have used the population data by nation and year by year and if the relation they found has changed in time, or if they have counted only the average in the long period. To overcome this weakness, the authors could calculate for the investigated period (1951–2020) the average mortality rates - at nation level - which are given by the number of fatalities recorded every year in a single nation, scaled to the size of the population in the related period of time. The mortality rate is normally used to compare the impact on the population of technological, health and even natural hazards. The authors could rank the nations on the basis of the mortality rates. They should use the annual population data for each country for the 70-year period. If the annual data are not available for the long period, they could reduce the time period.
In the discussion section the authors state that reducing flood will reduce the number of fatalities. This is conceptually wrong. It is possible reducing the impact, the losses and the intensity of a flood events, with structural and non-structural mitigation measures, but not the number of the physical processes, since it is due to the combination of many physical variables, firstly the rainfall intensity.
I would also like to point out the lack of thoroughness description in the way the authors present their results and outputs. The plots they produced are poorly described and not properly discussed and, in some cases, the citations of the figure numbers in the text are wrong.
Comments on the manuscript structure:
The data and method section is too poor and the method they used is not described anywhere, they only described why they selected the subset of data from EM-DAT.
The list of events they include in section 2 should be removed or moved in an appendix section, together with table 1.
Most of the results are in the discussion section. The authors should better define what they consider as results of their analysis and what they want highlight and discuss
The conclusion should be rewritten.
Citation: https://doi.org/10.5194/nhess-2021-357-RC2 -
AC2: 'Reply on RC2', Michael Nones, 26 Jan 2022
Dear Reviewer,
We would like to thank you very much for your comments, which were very helpful to better structure our manuscript, and to drive the key messages. In the revised version we addressed all your comments in detail, trying to combine your feedback with the hints coming from the other reviewer. Our point-by-point answers can be found in the following, where we numbered the reviewer’s comments using the format R2Cn, with n indicating the comment’s number.
R2C1: The source of data the authors used is available at global scale, and it is a good point, but it can’t be considered a comprehensive overview of the impact that floods produce to the population for most of the countries. The very frequent but less disastrous fatal flood events occurring every year anywhere in the world were not recorded in EM-DAT since the difficulty in capturing the information does not allow the minor events to be recorded. We do not know how much these minor events cumulatively amount to. Moreover, the EMDAT casualties estimates are not always consistent with those available in other sources and, frequently, these estimates include among the flood fatalities those due for other factors. The authors do not at all discuss the problem of the estimates uncertainty and how it might affect their results.
Thanks for the comment and suggestions. We have emphasized this at the end of the Conclusions as a limitation of our study. It is stated there that: “It is worth note that the presented conclusions derive from a single database, and are therefore influenced by the data availability and the uncertainty of the collected information. Future studies will concentrate on integrating information coming from multiple databases, aiming to obtain more structured and event-based outcomes. Moreover, a comparison between different datasets will allow for gaining major insights in the data uncertainty (namely, differences between the datasets) and its sources.”
It should also be noted that EM-DAT adopts a recognized ranking method to select sources for flood disaster statistics, combining data from the United Nations, governmental and non-governmental agencies, insurance companies, research institutes and press agencies[1]. We revised the text to better pinpoint this approach.
R2C2: I wonder if it makes sense to compare data on flood fatalities on a global scale when the geographical, demographic, social and economic characteristics of different nations are so profoundly different. Can the GDP as unique parameter explain the relation between the flood fatalities and the effort done to increase knowledge and technologies to mitigate the effects of flood events? Maybe the authors should consider additional socio-economic parameters and assess, for example, the social vulnerability of the single countries. I can support the authors in considering administrative limits as important in calculating true fatality coefficient of floods in order to compare them with each other. But this is true only in relation to the economic and political conditions of each country and how government choices can affect flood risk management. However, the administrative limits have nothing to do with the risk zoning where the people, who are most at risk, live. How did the data were spatialized? I bring this question to the attention of the authors since the distribution of the population within very large countries cannot weigh as much as the distribution of smaller ones, where the average density is approximately equal throughout the national territory. Have they considered this aspect? to strengthen the work, it could be helpful the estimation the real number of the population exposed to risk using, for example, the dasimetric maps.
English translation.
Thank you very much for the comments. We revised the text to further detail the study goals and to avoid misunderstandings, as well as improved significantly the Discussion section to compare our work with past investigations.
While it is true that floods fatalities are functions of several parameters, the individual participation of these unique parameters on floods fatalities is not yet clear. For example, a previous study has shown that mortality varies by region, but the expectation that floods in areas with lower living standards will cause higher mortality cannot be supported [2].
As one of the goals of the current study is to visualize the trend of variations of floods fatalities over a 70-years period, and keeping in mind the fact that there is not much information available for the early floods in the studied period, GDP was selected as an indicator. Obviously, more studies considering additional indicators should be done to provide a comprehensive picture of floods fatalities.
Although the authors agree with the reviewer that the population is not uniformly distributed in different countries, studying changes in population density and its impact on flood damages was not among the objectives of the current study. Even though investigating the effect of population density can increase the accuracy of the indicators presented in the present study, the application of these challenges may be difficult from a managerial point of view.
R2C3: To compare the human losses caused by floods in the different countries, the authors firstly used the fatality coefficient of floods calculated by dividing the total number of death tolls by the number of flood events for each country. I cannot understand if they calculated this coefficient year by year (for the 70-year period) and then they used the average in the long period, or if they simply divided the total number of fatalities by the total number of fatal event.
Only one coefficient was calculated for the entire range of the years studied. We revised the text to clarify this concept.
R2C4: This consideration points to my second comment concerning the meaning of disastrous event. How can we define disastrous an event at global scale without considering at least the different country population density? Is It possible to quantitatively define “disastrous” merely with the number of fatalities for event, and is this parameter actually useful for comparing data across countries of different size and population density? To define a disastrous event the authors could make a greater effort and estimate a moving threshold, weighed both on the number of victims per event and on the population density.
As mentioned in the text, “… flood casualties in the category of fewer than 10 people include a small part (less than 0.2%) of the total casualties, and therefore, in the present study, this category of data is not considered in the analysis.” Also, the selection of disastrous flood events with more than a specific number of deaths in flood fatalities analysis is not a new idea and was reported in previous studies, so we based our approach on literature evidence to allow for comparison. For example, Gaume et al. (2016) analyzed disastrous flash flood events with more than 10 deaths to find a general pattern of the spatial and seasonal distribution of flood magnitudes over the Mediterranean region [3]. In 2006, Barredo assessed information on major flood disasters producing more than 70 casualties for the production of the map and catalogue of major flood disasters in Europe [4]. Also, according to Merz et al. (2021), flood events can be considered disastrous when they are included in EM-DAT [5].
We revised the text considering your feedback, and tried to clarify our approach.
R2C5: Even if the authors attempted to consider the population density and the number of events per unit area (plots in figure 10), it is not clear if they have used the population data by nation and year by year and if the relation they found has changed in time, or if they have counted only the average in the long period. To overcome this weakness, the authors could calculate for the investigated period (1951–2020) the average mortality rates - at nation level - which are given by the number of fatalities recorded every year in a single nation, scaled to the size of the population in the related period of time. The mortality rate is normally used to compare the impact on the population of technological, health and even natural hazards. The authors could rank the nations on the basis of the mortality rates. They should use the annual population data for each country for the 70-year period. If the annual data are not available for the long period, they could reduce the time period.
The authors would like to thank the reviewer for pointing out this issue.
Obviously, the population of every country is not constant and changes with time. As we used the cumulative number of fatalities, the population of each country at the end of the study period, as the reference year, was used in both Figure 9 and Figure 10. However, the temporal variations of the number of fatalities and flood events on a global scale are provided in Figure 7.
As the focus of the present study is a global to regional overview of floods fatality, investigating changes in the number of fatalities and the number of flood events in each of the world’ countries individually was outside the objectives of the present study. We revised the text to clarify this, and expanded the Discussion considering your precious feedback.
R2C6: In the discussion section the authors state that reducing flood will reduce the number of fatalities. This is conceptually wrong. It is possible reducing the impact, the losses and the intensity of a flood events, with structural and non-structural mitigation measures, but not the number of the physical processes, since it is due to the combination of many physical variables, firstly the rainfall intensity.
It seems that a misunderstanding happened here. Our purpose was not to reduce rainfall, as we are completely aware that natural phenomena cannot be changed. When rainfall occurs, some of the rainwater flows as runoff and can lead to flooding. If action is taken to reduce runoff, it could be eventually possible to prevent the river flow from increasing too much, so that it does not exit the main channel and overflow the floodplains. There are many solutions to this issue and some examples were given in the text. Following your comments, we revised the text clarifying our idea.
R2C7: I would also like to point out the lack of thoroughness description in the way the authors present their results and outputs. The plots they produced are poorly described and not properly discussed and, in some cases, the citations of the figure numbers in the text are wrong.
We would like to kindly thank you for having pointed out this weakness.
The text has been revised, and more explanations have been added to better describe the plots. Also, the citations of the figures have been double-checked.
R2C7: The data and method section is too poor and the method they used is not described anywhere, they only described why they selected the subset of data from EM-DAT.
Thank you for the comments.
The “Materials and Methods” section has been elaborated to provide more information, which now allow for the study reproducibility.
R2C8: The list of events they include in section 2 should be removed or moved in an appendix section, together with table 1.
Thank you for your suggestion.
We decided to keep the description of the major flooding events (and the related Table 1) in the main text to provide readers with examples of how difficult could be inferring information on flood-related deaths. The text now reads “… the number of events with casualties of more than 10000 people is small (six cases, 1), and the number mentioned in the sources regarding the casualties of these events is mainly mixed with casualties due to incidental events, this category has been investigated on a case-by-case basis…”
R2C9: Most of the results are in the discussion section. The authors should better define what they consider as results of their analysis and what they want highlight and discuss
Following your comments, we revised the text to better clarify our approach: in the Results section, we reported the analysis of the data derived from the EM-DAT database (namely, flood fatalities), while in the Discussion we tried to understand if some patterns of flood fatalities exist, relating them to different drivers, such as population density (physical drivers) or GDP (socio-economic drivers).
We revised the text to stress the differences between the information reported in the Results and the Discussion sections, and we also significantly expanded the latter section by comparing our outcomes with literature evidence.
R2C10: The conclusion should be rewritten.
Thank you for the comment and the opportunity to revise the manuscript.
We revised and expanded the Conclusions, providing more comments on the further use of our results, as well as on open questions to be addressed in the future.
References
- De Groeve, T.; Poljansek, K.; Ehrlich, D. Recording Disaster Losses, Recommendations for a European Research.; Publications Office of the European Union: Luxembourg:, 2013; Vol. 26111;.
- Jonkman, S.N. Global Perspectives on Loss of Human Life Caused by Floods. Nat. Hazards 2005 342 2005, 34, 151–175, doi:10.1007/S11069-004-8891-3.
- Gaume, E.; Borga, M.; Llassat, M.C.; Maouche, S.; Gaume, E.; Borga, M.; Llassat, M.C.; Maouche, S.; Lang, M. Mediterranean extreme floods and flash floods; Coll. Synthèses: Marseille, France, 2016;
- Barredo, J.I. Major flood disasters in Europe: 1950–2005. Nat. Hazards 2006 421 2006, 42, 125–148, doi:10.1007/S11069-006-9065-2.
- Merz, B.; Blöschl, G.; Vorogushyn, S.; Dottori, F.; Aerts, J.C.J.H.; Bates, P.; Bertola, M.; Kemter, M.; Kreibich, H.; Lall, U.; et al. Causes, impacts and patterns of disastrous river floods. Nat. Rev. Earth Environ. 2021 29 2021, 2, 592–609, doi:10.1038/s43017-021-00195-3.
Citation: https://doi.org/10.5194/nhess-2021-357-AC2
-
AC2: 'Reply on RC2', Michael Nones, 26 Jan 2022
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,319 | 734 | 58 | 2,111 | 56 | 50 |
- HTML: 1,319
- PDF: 734
- XML: 58
- Total: 2,111
- BibTeX: 56
- EndNote: 50
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
