Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique

Pandey, Kushagra; de Bruijn, Jens A.; de Moel, Hans; Botzen, Wouter; Aerts, Jeroen C. J. H.

doi:https://doi.org/10.5194/egusphere-2024-17

Preprints

https://doi.org/10.5194/egusphere-2024-17

Preprints

17 Jan 2024

| 17 Jan 2024

Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique

Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts

Abstract. Coastal flooding and sea level rise (SLR) will affect farmers in coastal areas, as increasing salinity levels will reduce crop yields, leading to a loss of net annual income for farming communities. In response, farmers can take various actions. In order to assess such a response under SLR, we applied an agent-based model (ABM) to simulate the adaptation and migration decisions of farmers in coastal Mozambique. The ABM is coupled with a salinization module to simulate the relationship between soil salinity and SLR. The decision rules in the model (DYNAMO-M) are based on the economic theory of subjective expected utility. This theory posits that households can maximize their welfare by deciding whether to (a) stay and face losses from salinization and flooding, (b) stay and adapt (switching to salt-tolerant crops and enhancing physical resilience such as elevating houses), or (c) migrate to safer inland areas. The results show that coastal farmers in Mozambique face total losses of up to US$12.5 million per year from salt intrusion and up to US$800 million per year from flooding of buildings (RCP8.5 in the year 2080). Sorghum farmers may experience little damage from salt intrusion, while rice farmers may experience losses of up to US$15,000 per year. We show that medium-sized farmers (1–20 ha) are most at risk. This is because their farm size means that adaptation costs are substantial, while their incomes are too low to cover these costs. The number of households adapting varies between different districts (6 %–50 %), with salt adaptation being the most common, as costs are lowest. Despite adaptation measures, about 13 %–20 % of the total 300,000 farmers in coastal flood zones will migrate to safer areas under different settings of adaptive behaviour and different climatic and socioeconomic scenarios.

Received: 03 Jan 2024 – Discussion started: 17 Jan 2024

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Journal article(s) based on this preprint

06 Dec 2024

Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique

Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, W. J. Wouter Botzen, and Jeroen C. J. H. Aerts

Nat. Hazards Earth Syst. Sci., 24, 4409–4429, https://doi.org/10.5194/nhess-24-4409-2024,https://doi.org/10.5194/nhess-24-4409-2024, 2024

Short summary

Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-17', Anonymous Referee #1, 25 Jan 2024
I have read the abovementioned paper. The analysis is executed well, and I am generally well satisfied with the paper. However, there are some small issues that should be solved before the paper is accepted. I list them in the order I encountered them in the paper.
line 66. Gravity model is a statistical, i.e. empirical model. Therefore, writing "statistical and gravity models are less suitable" is confusing for a reader. Authors should explain what other empirical models apart from gravity models are used and reformulate this part.

I find motivation for the use of ABM very brief and insufficient. Authors could for example refer to Savin et al. (2023) who argued that ABMs help to combine insights from different disciplines (in this case, behavioural economics/psychology, agriculture and climate adaptation) by seriously addresing the role of bounded rationality, social interaction and agent heterogeneity. You could also refer to a recent literature review on the use of ABM to climate issues like by Castro et al., 2020.

Savin I. F. Creutzig, T. Filatova, J. Foramitti, T. Konc, L. Niamir, K. Safarzynska and J. van den Bergh, 2023 Agent-based modeling to integrate elements from different disciplines for ambitious climate policy, WIREs Climate Change 14(2): e811 https://doi.org/10.1002/wcc.811
Castro J., Drews S., Exadaktylos F., Foramitti J., Klein F., Konc T., Savin I. and van den Bergh J., 2020 A Review of Agent-based Modelling of Climate-Energy Policy, WIREs Climate Change 11(4):e647 https://doi.org/10.1002/wcc.647
reference error on p. 6 lie 148

font size in figures like 4 and 5 is too small. Please make sure all figures are readable. Similarly, indices (a,b,c) in figures like 9 and 10 could be improved by putting them outside the plot. Currently they are too small and sometimes overlap with plot content

Finally, the text should be spell checked. e.g. on p. 22 "Third, The input" or "from Ton, Marijn, (2023)"
Citation: https://doi.org/10.5194/egusphere-2024-17-RC1
- AC1: 'Reply on RC1', Kushagra Pandey, 02 Apr 2024
  
  RESPONSE to RC1
  
  Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique
  
  Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts
  
  ________________________________________________________________________________
  
  I have read the abovementioned paper. The analysis is executed well, and I am generally well satisfied with the paper. However, there are some small issues that should be solved before the paper is accepted. I list them in the order I encountered them in the paper.
  We would like to thank Referee #1 for the kind words and helpful suggestions to improve the paper. We have assessed each comment, and in our reply below, we explain how we would address the comments in our revised manuscript.
  line 66. Gravity model is a statistical, i.e. empirical model. Therefore, writing "statistical and gravity models are less suitable" is confusing for a reader. Authors should explain what other empirical models apart from gravity models are used and reformulate this part.
  The reviewer is correct. We propose changing the text to: "Gravity models are less suitable for individual adaptation and migration decision-making. This is why we selected an agent-based model to simulate these decisions."
  I find motivation for the use of ABM very brief and insufficient. Authors could for example refer to Savin et al. (2023) who argued that ABMs help to combine insights from different disciplines (in this case, behavioural economics/psychology, agriculture and climate adaptation) by seriously addressing the role of bounded rationality, social interaction and agent heterogeneity. You could also refer to a recent literature review on the use of ABM to climate issues like by Castro et al., 2020
  This is a valuable suggestion. We propose extending the motivation for selecting the agent-based model (ABM) by including the reviewer's suggestion to incorporate Savin et al. (2023) and other relevant literature such as Castro et al. (2020). In the revised paper, we will better highlight the benefits of ABMs for adaptive decision-making by combining insights from different disciplines and addressing aspects like bounded rationality, social interaction, and agent heterogeneity. ABMs are increasingly used for adaptation modeling, as shown by de Ruig et al. (2022) and Haer et al. (2020). Klabunde et al. (2016) have conducted a review study that suggests using different behavior theories within ABMs for migration. This includes the Expected Utility Theory we have included in our model. Thank you for noting this; we will increase the font size accordingly.
  Minor comments:
  reference error on p. 6 lie 148
  Correct, we will change this to Fishburn et al. (1981).
  font size in figures like 4 and 5 is too small. Please make sure all figures are readable. Similarly, indices (a,b,c) in figures like 9 and 10 could be improved by putting them outside the plot. Currently they are too small and sometimes overlap with plot content
  Thank you for noting this, we will increase the font size accordingly.
  Finally, the text should be spell checked. e.g. on p. 22 "Third, The input" or "from Ton, Marijn, (2023)"
  Thank you, this should be Ton et al. (2023). We will take extra care to check the references in the final revised version.
  References
  Castro, J., Stefan Drews, Filippos Exadaktylos, Joël Foramitti, Franziska Klein, Théo Konc, Ivan Savin, Jeroen van den Bergh (2020) A review of agent-based modeling of climate-energy policy. WIRES CC, doi.org/10.1002/wcc.647
  Haer, T., Husby, T., Botzen, W.J., Aerts, J.C.J.H. (2020). The safe development paradox: an agent-based assessment for flood risk in the European Union. Global Environmental Change, doi.org/10.1016/j.gloenvcha.2019.102009
  Klabunde, A., Willekens, F. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges. Eur J Population 32, 73–97 (2016). https://doi.org/10.1007/s10680-015-9362-0
  Ruig, L., Botzen W.J., Haer, T., Brody, S., Czajkowski, de Moel, H., Aerts, J.C.J,.H. (2022) How the U.S. can benefit from risk-based premiums combined with flood protection. Nature Climate Change https://doi.org/10.1038/s41558-022-01501-7 (2022).
  Savin, I., Felix Creutzig, Tatiana Filatova, Joël Foramitti, Théo Konc, Leila Niamir, Karolina Safarzynska, Jeroen van den Bergh (2022) Agent-based modeling to integrate elements from different disciplines for ambitious climate policy. WIRES CC, doi.org/10.1002/wcc.811
  
  Citation: https://doi.org/10.5194/egusphere-2024-17-AC1
RC2:
'Comment on egusphere-2024-17', Anonymous Referee #2, 02 Feb 2024
The paper presents a comprehensive and well-constructed model addressing a significant issue, showcasing both the quality of writing and the relevance of the problem tackled. However, to ensure its suitability for publication, it's essential to address several major concerns crucial for enhancing the paper's credibility and impact within the scientific community.

Major Comments:

The paper introduces a model focused on adaptation strategies in rural Mozambique but does not convincingly justify its suitability for this specific environment. The application of expected utility theory seems incongruent with the decision-making realities of rural Mozambican farmers, especially considering insights from urban coastal households (Noll et al., 2022). These insights suggest that adaptation behaviors are heavily influenced by non-economic factors, which are presumably more pronounced in rural settings where traditional knowledge and heuristics play a larger role. Furthermore, the use of urban housing values to assess expected annual damages further questions the model's applicability, potentially leading to skewed results. Moreover, the model proposes structural adaptation strategies like elevation that may be impractical and unreflective of the actual measures farmers in rural Mozambique might undertake. This incongruity points to a critical need for the model to integrate a more nuanced understanding of the behavioral patterns and economic realities pertinent to the rural Mozambican context, raising the question of the reliability of the projections presented.

Another significant point that makes me doubt the results presented in this study is the lack of any type of validation. Validation is crucial for establishing the reliability of model outputs, and the absence of any such exercise undermines the strength of the conclusions drawn. Although the challenge of obtaining empirical data for rural Mozambique is acknowledged, the paper would benefit from an attempt to validate the model, perhaps through comparisons with historical trends or alignment with known stylized facts about the region. Without this, the model's predictions remain hypothetical and their relevance to actual scenarios in Mozambique is uncertain.

The sensitivity analysis presented in the study appears to be insufficient. A more robust analysis should consider a wider range of parameter values beyond a few discrete scenarios, which would allow for a better understanding of the model's behavior under different conditions (especially given the points raised before). For instance, the potential impact of soil salinization could be examined over a spectrum of possibilities, such as a 50% increase in salinity levels, to reflect possible variations in climate change outcomes.

The he paper needs to clearly articulate the relationship between income dynamics and environmental factors such as crop salinization. It is important to determine whether farmers' incomes are fixed regardless of the salinization process. The change in crop yield would have a significant impact on farmers’ income, which would play a crucial role in their ability to undertake adaptation action or migrate. This is essential for realistically modeling farmers' capacity to adapt or migrate. Maintaining constant income despite climate changes risks underestimating the economic impact of salinization, potentially restricting farmers' options and leading to misleading results.

Minor Comments:

The justification for the choice of 50 repetitions within the model simulations is unclear. I am not saying it is wrong, but such methodological decisions should be supported by a metric that validates the number's adequacy to capture the variability in results.

The manuscript has omissions in referencing (reference not found), such as missing citations in figure captions and on page 6, line 145.

The consideration of demographic trends, such as the impact of young people's outmigration on fertility rates and population growth, is lacking. I'm not suggesting that the authors should include it explicitly, but they should reflect upon its implications (Hauer et al., 2024).

A reflective discussion on the broader implications of the study's results for the scientific literature and their practical significance would be beneficial. The paper should emphasize how its findings contribute new understanding in the field of climate adaptation.

In summary, the paper presents a valuable model but risks drawing conclusions that may not align with the complexities of the real-world situation in rural Mozambique. More robust and detailed analyses, along with an expanded discussion on the implications of the results, are necessary to ensure the paper's relevance and contribution to the scientific community.

References:
Hauer, M. E., Jacobs, S. A., & Kulp, S. A. (2024). Climate migration amplifies demographic change and population aging. Proceedings of the National Academy of Sciences of the United States of America, 121(3), e2206192119. https://doi.org/10.1073/PNAS.2206192119/SUPPL_FILE/PNAS.2206192119.SAPP.PDF
Noll, B., Filatova, T., Need, A., & Taberna, A. (2022). Contextualizing cross-national patterns in household climate change adaptation. Nature Climate Change, 12(1), 30–35. https://doi.org/10.1038/s41558-021-01222-3
Citation: https://doi.org/10.5194/egusphere-2024-17-RC2
- AC2: 'Reply on RC2', Kushagra Pandey, 02 Apr 2024
  
  Dear Referee #2,
  
  We have attached the responses to your comments in the supplementary file; please find the document.
  
  Thanks
  
  Best,
  
  Kushagra Pandey
  
  Citation: https://doi.org/10.5194/egusphere-2024-17-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-17', Anonymous Referee #1, 25 Jan 2024
I have read the abovementioned paper. The analysis is executed well, and I am generally well satisfied with the paper. However, there are some small issues that should be solved before the paper is accepted. I list them in the order I encountered them in the paper.
line 66. Gravity model is a statistical, i.e. empirical model. Therefore, writing "statistical and gravity models are less suitable" is confusing for a reader. Authors should explain what other empirical models apart from gravity models are used and reformulate this part.

I find motivation for the use of ABM very brief and insufficient. Authors could for example refer to Savin et al. (2023) who argued that ABMs help to combine insights from different disciplines (in this case, behavioural economics/psychology, agriculture and climate adaptation) by seriously addresing the role of bounded rationality, social interaction and agent heterogeneity. You could also refer to a recent literature review on the use of ABM to climate issues like by Castro et al., 2020.

Savin I. F. Creutzig, T. Filatova, J. Foramitti, T. Konc, L. Niamir, K. Safarzynska and J. van den Bergh, 2023 Agent-based modeling to integrate elements from different disciplines for ambitious climate policy, WIREs Climate Change 14(2): e811 https://doi.org/10.1002/wcc.811
Castro J., Drews S., Exadaktylos F., Foramitti J., Klein F., Konc T., Savin I. and van den Bergh J., 2020 A Review of Agent-based Modelling of Climate-Energy Policy, WIREs Climate Change 11(4):e647 https://doi.org/10.1002/wcc.647
reference error on p. 6 lie 148

font size in figures like 4 and 5 is too small. Please make sure all figures are readable. Similarly, indices (a,b,c) in figures like 9 and 10 could be improved by putting them outside the plot. Currently they are too small and sometimes overlap with plot content

Finally, the text should be spell checked. e.g. on p. 22 "Third, The input" or "from Ton, Marijn, (2023)"
Citation: https://doi.org/10.5194/egusphere-2024-17-RC1
- AC1: 'Reply on RC1', Kushagra Pandey, 02 Apr 2024
  
  RESPONSE to RC1
  
  Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique
  
  Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts
  
  ________________________________________________________________________________
  
  I have read the abovementioned paper. The analysis is executed well, and I am generally well satisfied with the paper. However, there are some small issues that should be solved before the paper is accepted. I list them in the order I encountered them in the paper.
  We would like to thank Referee #1 for the kind words and helpful suggestions to improve the paper. We have assessed each comment, and in our reply below, we explain how we would address the comments in our revised manuscript.
  line 66. Gravity model is a statistical, i.e. empirical model. Therefore, writing "statistical and gravity models are less suitable" is confusing for a reader. Authors should explain what other empirical models apart from gravity models are used and reformulate this part.
  The reviewer is correct. We propose changing the text to: "Gravity models are less suitable for individual adaptation and migration decision-making. This is why we selected an agent-based model to simulate these decisions."
  I find motivation for the use of ABM very brief and insufficient. Authors could for example refer to Savin et al. (2023) who argued that ABMs help to combine insights from different disciplines (in this case, behavioural economics/psychology, agriculture and climate adaptation) by seriously addressing the role of bounded rationality, social interaction and agent heterogeneity. You could also refer to a recent literature review on the use of ABM to climate issues like by Castro et al., 2020
  This is a valuable suggestion. We propose extending the motivation for selecting the agent-based model (ABM) by including the reviewer's suggestion to incorporate Savin et al. (2023) and other relevant literature such as Castro et al. (2020). In the revised paper, we will better highlight the benefits of ABMs for adaptive decision-making by combining insights from different disciplines and addressing aspects like bounded rationality, social interaction, and agent heterogeneity. ABMs are increasingly used for adaptation modeling, as shown by de Ruig et al. (2022) and Haer et al. (2020). Klabunde et al. (2016) have conducted a review study that suggests using different behavior theories within ABMs for migration. This includes the Expected Utility Theory we have included in our model. Thank you for noting this; we will increase the font size accordingly.
  Minor comments:
  reference error on p. 6 lie 148
  Correct, we will change this to Fishburn et al. (1981).
  font size in figures like 4 and 5 is too small. Please make sure all figures are readable. Similarly, indices (a,b,c) in figures like 9 and 10 could be improved by putting them outside the plot. Currently they are too small and sometimes overlap with plot content
  Thank you for noting this, we will increase the font size accordingly.
  Finally, the text should be spell checked. e.g. on p. 22 "Third, The input" or "from Ton, Marijn, (2023)"
  Thank you, this should be Ton et al. (2023). We will take extra care to check the references in the final revised version.
  References
  Castro, J., Stefan Drews, Filippos Exadaktylos, Joël Foramitti, Franziska Klein, Théo Konc, Ivan Savin, Jeroen van den Bergh (2020) A review of agent-based modeling of climate-energy policy. WIRES CC, doi.org/10.1002/wcc.647
  Haer, T., Husby, T., Botzen, W.J., Aerts, J.C.J.H. (2020). The safe development paradox: an agent-based assessment for flood risk in the European Union. Global Environmental Change, doi.org/10.1016/j.gloenvcha.2019.102009
  Klabunde, A., Willekens, F. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges. Eur J Population 32, 73–97 (2016). https://doi.org/10.1007/s10680-015-9362-0
  Ruig, L., Botzen W.J., Haer, T., Brody, S., Czajkowski, de Moel, H., Aerts, J.C.J,.H. (2022) How the U.S. can benefit from risk-based premiums combined with flood protection. Nature Climate Change https://doi.org/10.1038/s41558-022-01501-7 (2022).
  Savin, I., Felix Creutzig, Tatiana Filatova, Joël Foramitti, Théo Konc, Leila Niamir, Karolina Safarzynska, Jeroen van den Bergh (2022) Agent-based modeling to integrate elements from different disciplines for ambitious climate policy. WIRES CC, doi.org/10.1002/wcc.811
  
  Citation: https://doi.org/10.5194/egusphere-2024-17-AC1
RC2:
'Comment on egusphere-2024-17', Anonymous Referee #2, 02 Feb 2024
The paper presents a comprehensive and well-constructed model addressing a significant issue, showcasing both the quality of writing and the relevance of the problem tackled. However, to ensure its suitability for publication, it's essential to address several major concerns crucial for enhancing the paper's credibility and impact within the scientific community.

Major Comments:

The paper introduces a model focused on adaptation strategies in rural Mozambique but does not convincingly justify its suitability for this specific environment. The application of expected utility theory seems incongruent with the decision-making realities of rural Mozambican farmers, especially considering insights from urban coastal households (Noll et al., 2022). These insights suggest that adaptation behaviors are heavily influenced by non-economic factors, which are presumably more pronounced in rural settings where traditional knowledge and heuristics play a larger role. Furthermore, the use of urban housing values to assess expected annual damages further questions the model's applicability, potentially leading to skewed results. Moreover, the model proposes structural adaptation strategies like elevation that may be impractical and unreflective of the actual measures farmers in rural Mozambique might undertake. This incongruity points to a critical need for the model to integrate a more nuanced understanding of the behavioral patterns and economic realities pertinent to the rural Mozambican context, raising the question of the reliability of the projections presented.

Another significant point that makes me doubt the results presented in this study is the lack of any type of validation. Validation is crucial for establishing the reliability of model outputs, and the absence of any such exercise undermines the strength of the conclusions drawn. Although the challenge of obtaining empirical data for rural Mozambique is acknowledged, the paper would benefit from an attempt to validate the model, perhaps through comparisons with historical trends or alignment with known stylized facts about the region. Without this, the model's predictions remain hypothetical and their relevance to actual scenarios in Mozambique is uncertain.

The sensitivity analysis presented in the study appears to be insufficient. A more robust analysis should consider a wider range of parameter values beyond a few discrete scenarios, which would allow for a better understanding of the model's behavior under different conditions (especially given the points raised before). For instance, the potential impact of soil salinization could be examined over a spectrum of possibilities, such as a 50% increase in salinity levels, to reflect possible variations in climate change outcomes.

The he paper needs to clearly articulate the relationship between income dynamics and environmental factors such as crop salinization. It is important to determine whether farmers' incomes are fixed regardless of the salinization process. The change in crop yield would have a significant impact on farmers’ income, which would play a crucial role in their ability to undertake adaptation action or migrate. This is essential for realistically modeling farmers' capacity to adapt or migrate. Maintaining constant income despite climate changes risks underestimating the economic impact of salinization, potentially restricting farmers' options and leading to misleading results.

Minor Comments:

The justification for the choice of 50 repetitions within the model simulations is unclear. I am not saying it is wrong, but such methodological decisions should be supported by a metric that validates the number's adequacy to capture the variability in results.

The manuscript has omissions in referencing (reference not found), such as missing citations in figure captions and on page 6, line 145.

The consideration of demographic trends, such as the impact of young people's outmigration on fertility rates and population growth, is lacking. I'm not suggesting that the authors should include it explicitly, but they should reflect upon its implications (Hauer et al., 2024).

A reflective discussion on the broader implications of the study's results for the scientific literature and their practical significance would be beneficial. The paper should emphasize how its findings contribute new understanding in the field of climate adaptation.

In summary, the paper presents a valuable model but risks drawing conclusions that may not align with the complexities of the real-world situation in rural Mozambique. More robust and detailed analyses, along with an expanded discussion on the implications of the results, are necessary to ensure the paper's relevance and contribution to the scientific community.

References:
Hauer, M. E., Jacobs, S. A., & Kulp, S. A. (2024). Climate migration amplifies demographic change and population aging. Proceedings of the National Academy of Sciences of the United States of America, 121(3), e2206192119. https://doi.org/10.1073/PNAS.2206192119/SUPPL_FILE/PNAS.2206192119.SAPP.PDF
Noll, B., Filatova, T., Need, A., & Taberna, A. (2022). Contextualizing cross-national patterns in household climate change adaptation. Nature Climate Change, 12(1), 30–35. https://doi.org/10.1038/s41558-021-01222-3
Citation: https://doi.org/10.5194/egusphere-2024-17-RC2
- AC2: 'Reply on RC2', Kushagra Pandey, 02 Apr 2024
  
  Dear Referee #2,
  
  We have attached the responses to your comments in the supplementary file; please find the document.
  
  Thanks
  
  Best,
  
  Kushagra Pandey
  
  Citation: https://doi.org/10.5194/egusphere-2024-17-AC2

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) (18 Apr 2024) by Andrea Ficchì

Dear authors,

Thank you for the careful consideration of the constructive comments raised by the two reviewers and your satisfactory response.

Your article provides a significant novel contribution investigating the adaptation strategies in response to coastal flood risk and salinization in Mozambique, under scenarios of sea level rise and salt intrusion. With the changes and additions proposed, the quality of the paper will be enhanced, making it suitable for publication in NHESS.

I would like to emphasize the importance of the following changes and add a few minor points that you should please carefully consider when revising the manuscript:
- It is essential to extend the justification for the choice of the agent-based model (ABM), as suggested by Reviewer #1, and to expand the discussion on the local relevance of the chosen adaptation strategies and behavioural patterns considered in the model, as suggested by Reviewer #2.
- As recognized in your response, to enhance the credibility and impact of the paper, a validation of the model for the local Mozambican context should be added based on the recent survey data mentioned in your response. The survey results on the drivers of migration and adaptation should also help to back up the selection of the adaptation strategies considered and other assumptions of the study. I would suggest to include the new paragraph on the survey results in the main body of the revised paper (and not as Supplementary Material), given the high relevance and central role in supporting the validation of the model and discussion of the results.
- Following the comments of Reviewer #2, a discussion on the limitations of the applied expected utility theory should be included, acknowledging that further studies should consider additional behavioural factors.
- In addition to providing further justification for the chosen adaptation strategies, please also consider adding a brief acknowledgement of a larger set of possible adaptation options, based on the results of your survey and on previous literature on climate adaptation of farmers that may suggest the possible uptake of more adaptation measures (e.g., agricultural insurance, diversification of activities with aquaculture, etc.).
- I agree that extending the discussion on the sensitivity analysis to consider the uncertainty in prediction of the hazard is a good idea. In addition, I would suggest to consider also extending the discussion on the uncertainty due to other chosen arbitrary parameters that are key for modelling adaptation decisions; for example, the fixed migration cost for Mozambique may influence significantly the results as other non-economic factors could be important to define it (e.g., the friction to move from rural areas to urban slums); similarly the sensitivity of the results to the fixed flood protection standard (with a return period of 10 years) could be discussed.

On behalf of the the Special Issue editorial team, thank you for your valuable contribution and your careful response to the reviewers. We look forward to receiving your revised manuscript.

Yours sincerely,
Andrea Ficchì

Hide

AR by Kushagra Pandey on behalf of the Authors (22 May 2024) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (25 May 2024) by Andrea Ficchì

RR by Anonymous Referee #1 (25 May 2024)

ED: Publish subject to minor revisions (review by editor) (12 Aug 2024) by Andrea Ficchì

Dear authors,

Thank you for your careful revisions and thorough response to the constructive comments raised by the two reviewers. The quality of the revised manuscript has been significantly enhanced, making it well-suited for publication in NHESS, pending a few final minor revisions.

I apologize for the delay in this review process, which was primarily due to challenges in securing a new second reviewer. While I have received positive feedback from the first reviewer, who is satisfied with the revisions, it was also necessary to ensure that your major revisions addressed the concerns raised by the second reviewer, who was unfortunately unavailable at this time (as were several other invited referees).

I have reviewed the revised paper and I found that the revisions have made the study more robust and convincing, particularly through the added calibration and validation of the model using empirical data from a survey conducted in Mozambique. This enhancement has significantly increased the credibility and value of the results, providing an enhanced contribution to the understanding of the combined effects of sea level rise and salt intrusion on adaptation and migration in Mozambique.

The main remaining issue is to clarify the presentation of some parts of the methods, primarily on the Discounted Expected Utility (DEU) formulation, and include a more critical discussion of the equations, assumptions and parameters chosen for modelling adaptation and migration decisions in Mozambique (Section 3.1; see detailed comments below and in the supplement). I attach a supplement report file with a list of other required minor and technical corrections.

I look forward to the revised version of the paper and your response to the minor comments raised. I anticipate that the revised paper will not require an additional round of reviews and will be quickly accepted upon editorial check after minor corrections.

Best wishes,
Andrea

-----------------------------

Detailed comments

Section 3.1 ‘Adaptation and migration decisions in the 1/100 flood zone’: Please clarify the presentation of the application of the DEU theory by providing more details on the choice and definition of certain functions and parameters, along with a more critical discussion of the methodology chosen for modeling adaptation and migration decisions, following the suggestions below.

- Redistribution of information presented in the supplementary Section S1.1: the supplementary information is important to understand the model and should be moved to the main paper (Section 3.1), as it would help clarify how the utility function U and the risk perception parameter are defined; these are critical elements that should be included in Section 3.1, to ensure that the characterization of the risk aversion and perception is more clear.
- Formulation of the Discounted Expected Utility (DEU) equations: the chosen formulation of DEU (Eq. 1-3) raises some questions regarding the use of the sum of all discounted economic terms over time as argument of the utility function, rather than summing the discounted utilities (U values) themselves over time, as I think it is often done in the literature (e.g., Coble and Lusk, 2010); I believe that some compensations of economic terms (income and costs) occurring at different times are possible in the current formulation. While the chosen formulation may align with the DEU theory, it is worth considering and discussing whether it properly captures the agents' preferences related to the temporal distribution of wealth, income, damages, and costs over time (within T). It would be beneficial to check and discuss this choice (and its possible advantages or limitations) in greater detail in the text, to enhance the clarity of the DEU formulation and assumptions (regarding the agents' time and risk preferences) and to strengthen the rationale of the approach regarding the disentanglement of time preferences.
- Discount factor choice and suitability for rural Mozambique: it would be good to clarify how the value (r=3.2%) has been chosen and discuss how it can reflect the time preferences of households in the case study of Mozambique, as the citation reported (Evans and Sezer, 2005) should refer to the European Union context.
- Definition of all parameters and constants used in all equations: the definition of a few parameters is missing, and should be included more clearly and explicitly within the paper for the sake of clarity (not referring to possible references only); in the current version, the values and meaning of a few parameters are not reported, i.e., pi, p1 and T in Eq. 1-3 (at the moment, one can understand or guess their meaning or value, e.g. T should be 15 years, see L. 167); the terms c, d and sigma in Eq. S1-S2 are not defined.

References:
- Coble, K.H.; Lusk, J.L (2010). At the nexus of risk and time preferences: An experimental investigation. J. Risk Uncertain, 41, 67–79. https://doi.org/10.1007/s11166-010-9096-7
- Evans, D. J., & Sezer, H. (2005). Social discount rates for member countries of the European Union. Journal of Economic Studies, 32(1), 47–59. https://doi.org/10.1108/01443580510574832

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AR by Kushagra Pandey on behalf of the Authors (15 Aug 2024) Author's response Author's tracked changes Manuscript

ED: Publish as is (16 Aug 2024) by Andrea Ficchì

ED: Publish as is (10 Sep 2024) by Philip Ward (Executive editor)

AR by Kushagra Pandey on behalf of the Authors (13 Sep 2024) Manuscript

Journal article(s) based on this preprint

06 Dec 2024

Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique

Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, W. J. Wouter Botzen, and Jeroen C. J. H. Aerts

Nat. Hazards Earth Syst. Sci., 24, 4409–4429, https://doi.org/10.5194/nhess-24-4409-2024,https://doi.org/10.5194/nhess-24-4409-2024, 2024

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Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts

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https://doi.org/10.5194/egusphere-2024-17-supplement

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DYNAMO-M salt intrusion Kushagra Pandey https://doi.org/10.5281/zenodo.10455705

Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, Wouter Botzen, and Jeroen C. J. H. Aerts

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SLR will lead to more frequent flooding, and salt intrusion in coastal areas will be a major concern for farming households that are highly dependent on the soil quality for their livelihoods. In this study, we simulated the risk of SLR and flooding to coastal farmers by assessing salt intrusion risk and flood damage to buildings.


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