the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Jun 2024
Assessment of coastal inundation triggered by multiple drivers in Ca Mau Peninsula, Vietnam
Abstract. The Ca Mau Peninsula plays a critical role in the agricultural and aquacultural productivity of the Vietnam Mekong Delta (VMD), central to regional food security and the population’s economic and social welfare. Unfortunately, this region has also historically been a hotspot for natural disasters, particularly from flooding, which is initiated by seasonal river flux upstream and heightened sea levels downstream, but also exacerbated by global climate change (e.g., increased rainfall and sea-level rise, tropical storm surges) and human activities (e.g. river bed lowering, land subsidence). The potential risks associated with rising inundation levels is important information for the future sustainability of the region and its ability to adapt to both current and forthcoming changes. The research around the influence of such drivers on future flood risk, in the Ca Mau Peninsula, is incomplete, primarily due to the absence of a quantitative coastal inundation map corresponding to future compounded scenarios. In this study, we therefore evaluate flooding dynamics in the Ca Mau peninsula using a fully calibrated 1D model, to represent a range of anthropogenic and climate change compound scenarios. Our findings indicate that factors such as increased high-flows upstream, alterations in the riverbed of the main Mekong channel, and occurrences of storm surges effecting the mainstream Mekong River, are unlikely to significantly affect inundation dynamics in this region. However, land subsidence, rising sea levels, and their combined effects emerge as the primary drivers behind the escalation of inundation events in the Ca Mau peninsula, both in terms of their extent and intensity, in the foreseeable future. These results serve as vital groundwork for strategic development and investment as well as for emergency decision-making and flood management planning, providing essential insights for shaping development policies and devising investment strategies related to infrastructure systems in an area which is rapidly developing.
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CC1: 'Suggested improvements for nhess-2024-107', Philip S.J. Minderhoud, 24 Jul 2024
The paper presents some of the first insights into compound flooding in the Mekong Delta. By providing a range of scenarios, including variations in discharge, storm surge, lowering of the riverbed and integration of (extraction-induced) land subsidence and sea-level rise, the authors aim to attribute modelled inundation to the drivers investigated. They conclude that relative sea-level rise (i.e. land subsidence and absolute sea-level rise) constitutes the most to increase inundation in the delta.
We think this paper addresses a so far huge research gap and can make a significant contribution to the advancement of exposure and risk assessment in the Mekong Delta and the investigation of compound flooding and their local specific characteristics. However, we found some critical aspects that have not been touched by the authors but which are necessary to be at least discussed if they cannot be considered in the processing. We briefly address the major points by listing them as follows and also provide a section-wise feedback:
Details and references to the datasets used are missing. The datasets and their quality also need to be reflected in the discussion section.
- The assessment heavily relies on the use of a local elevation model but the DEM details are not provided – only the source – how is the DEM acquired, is it a DSM or a DTM? What is vertical accuracy? What are the artifacts (e.g. blocks) in the elevation model that are very visible in the results? What is the influence of these uncertainties/error on the final outcomes of this study? How does the DEM relate to other DEMs/ground truth data on elevation in the delta?
- The DEM used was based on data from 2008 – how was this combined with the sea level and the land subsidence data? These should also be computed starting in 2008 – as both processes effectively change the relative elevation of the delta plain.
- Reference for the gauge data is missing and should be provided.
- LULC details / references are not provided and should be briefly summarised or at least provided by adding a reference.
- Details on roughness are missing. Was it a single value? Were the initial roughness value(s) determined based on the land-use land cover map? Please provide some more information.
- The paper uses a quantification of ‘Delta subsidence’ while based from the description this is based on a groundwater model however the paper doesn’t reference the original model source (i.e. Minderhoud et al., 2017), which is required as this holds the assumption and also shortcomings of the modelling approach. It is important to note that the modelling results only provide land subsidence following groundwater extraction and not includes other components of land subsidence – this should be made explicit in the result presentation (e.g. change delta subsidence to extraction-induced subsidence) and discussion on the other components not included in the assessment. For this also other literature specifically on land subsidence in Ca Mau on the other components and local measurements can be used: e.g. Zoccarato et al., 2018 (10.1038/s41598-018-29734-7), Karlsrud et al., 2020 (10.5194/piahs-382-111-2020), de Wit et al., 2021 (10.3390/rs13020189). Also Nguyen et al., 2023 (10.1016/j.ecss.2023.108259) provides a valuable comparison with water level measurements to discussed in this study.
- Coastal erosion and shoreline change are included in discussion while happening in the coastal zone – especially with inundations projected up to 2 meter. Please include this in the discussion (e.g. Anthony et al., 2015)
- In addition to elevation loss following land subsidence and SLR – the accretion of sediment should be discussed – as this may cause a positive elevation change. Especially with high flood/inundation with water - sedimentation dynamics will change and therefore elevation – which in turn changes the inundation depth. The lead author has experience in flood plain sedimentation and adding these dynamics in the discussion would strengthen the changes and future dynamics the paper aims to evaluate.
- The discussion section is very short and in its current version is missing several aspects that require critical reflection. We suggest to insert a subsection where the quality of underlying datasets as well as the limitations are discussed. And include a second subsection to discuss implications of your modelling results for the delta’s future and its development/management. Only a very limited number of mitigation and adaptation measures is discussed (i.e. tidal barriers) and these are hardly suitable to tackle the causes and drivers of compound flooding as well as sustaining mangrove ecosystems. Thus can be improved by restricting the discussion.
Minor comments:
Introduction
- 18: there is no “natural disaster”, please delete “natural”.
- 40-41: “Sand dredging rise” sounds a bit strange. Replace it by “increased sand mining”.
- 70: “Vertical sinking” sounds a bit strange. Remove “vertical”.
- 74: Please cite and acknowledge the required source publications of the NASA SLR projection tool, i.e. Fox-Kemper et al. (2021) and the data works of Garner et al. Please check this throughout the entire manuscript.
- 86-90: Please provide references.
- 93: Vulnerability has not been adequately addressed so far. The previous paragraphs were all about future trends and increasing exposure. Please insert a few lines that underpin your statement of increased vulnerability (i.e., studies focussing on societal aspects) or do not call it vulnerability.
- 99-101: Can you provide a reference who will consider it? MONRE, etc.?
- 111: There is no reference made to figure 1 in the text. Either integrate it into the text (for example if you use it to validate your model) or remove it.
Methods
- 129-130: Similar as reference is provided for monsoon precipitation, please also provide a reference when information on elevation above mean sea level is given.
- 145: Provide a reference for the land-use data used.
- 158-159: Provide year of datum establishment in brackets or provide reference where this information is entailed.
- 159-162: More details on the DEM are needed. How was it acquired? Airborne LiDAR? Is it a DSM or a DTM? This information is very important as it has crucial impacts on your model results.
- 163-164: Provide a reference for the gauge data used.
- 185-186: What are the roughness values used? Were the initial roughness values determined based on LULC data?
Results
- 340: Use singular (“scenario”) and not plural.
- 312-429: Could the observation that extraction-induced land subsidence and SLR result in the max. increase of inundation extent and depth also relate to the fact that the underlying data considered provide projections for the longest time scales? This potential should be discussed in the discussion section.
- 402-405: Why are the 4a and 4b scenarios missing in figure 5? Please add them.
- 406-408: The artefacts of the underlying DEM dataset become clearly visible in figure 6. This should be discussed in the discussion section.
- 419-420: The artefacts of the underlying DEM dataset become visible. Seems like as if there are also interpolation (?) artefacts in the scenarios because they look quite strange (esp. S5_b, S4_a). Please check and at least include a paragraph in the discussion section.
Discussion
- 430-472: The discussion section is too short and in its current version is missing several aspects that require critical reflection. Please insert a subsection where the quality of underlying datasets as well as the limitations are discussed. This relates mainly to the DEM and land subsidence data used but may also go beyond.
- 450-452: When adaptation and mitigation strategies are discussed, not only tidal barriers should be mentioned. What about other solutions such as sedimentation strategies that tackle the cause (i.e. elevation loss due to land subsidence)?
- 453-458: The problem of groundwater overexploitation is not discussed at all but needs to be addressed as it is the main driver of land subsidence in the region. Note that the datasets that were used to simulate scenarios S4a and S4b only consider extraction-induced land subsidence but not the total subsidence.
- 459-466: As the implementation of infrastructure adds new load on the deltaic land surface, land subsidence will increase in that area. Please add this comment when the construction of the North-South Expressway is raised.
- 471-472: The implementation only of the measures mentioned in this discussion does not allow for this conclusion as they rather tackle symptoms than the causes. Measures that tackle subsidence-induced elevation loss need to be discussed.
Conclusions
- 475: It is exposure, not vulnerability as this study does not include any social or socio-economic data.
- 483-485: Consider previous comments on the doubled consideration of land subsidence in the combined scenarios as SLR projections from the NASA SLR projection tool include a VLM component.
- 500-505: Note that the adaptation measures listed here do not address the cause and whether the mangrove ecosystem can be sustained in the future.
Citation: https://doi.org/10.5194/nhess-2024-107-CC1 -
AC1: 'Reply on CC1 Dr. Philip S.J. Minderhoud', N.N. Hung, 07 Aug 2024
Dear Dr. Philip Minderhoud,
Thank you for your kind reading and very helpful feedback, which will considerably improve our manuscript. I will review and edit the manuscript based on your suggestions.
Best Regards
Hung
Citation: https://doi.org/10.5194/nhess-2024-107-AC1 -
AC4: 'Reply on CC1', N.N. Hung, 05 Feb 2025
Dear Dr. Philip,
We would like to sincerely thank you for your time and thoughtful consideration in reviewing our manuscript. We found that your feedback has been extremely helpful in guiding us to finalize and enhance the quality of the paper.
Please find the attached file, where we have provided a point-by-point response to your comments.
Once again, we deeply appreciate your valuable insights and contributions.
Kind regards,
Hung
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RC1: 'Comment on nhess-2024-107', Anonymous Referee #1, 19 Aug 2024
The authors present a well-designed study modeling various flooding scenarios in the Ca Mau Peninsula. They have identified a research gap dealing with regional flooding dynamics, including compound flooding, and through the simulation plan, aim to contribute to filling this gap. Simulations were defined by discharge, storm surge occurrence, lowering of the river bed, land subsidence, and sea level rise, considering SSP5-8.5 scenarios. They conclude that land subsidence, rising sea levels, and their combined effects are the principal drivers behind increased inundation events. Overall I think the manuscript is of high quality with impactful results, my feedback deals mainly with the discussion of the modeling approach and the discussion section in general. I support the suggestions outlined in the community comment (CC1) and there is no need to add repeat suggestions. My review is structured as major points and line-by-line suggestions/feedback.
Major points:
The limitations of 1D hydrodynamic modeling and not considering sediment transport should be discussed or further justified.
What were the roughness values used (lines 182)? Where were they different? And how do they compare to hydraulic manuals in terms of used values vs. guideline values (e.g. Chow, 1959)? If they are different from guideline values this should be explained.
Line 454-458: Potential mitigation measures, if discussed, require a much more thorough assessment with references. I think expanding on this section and connecting it to the natural (nature-based) storm surge buffering effects of mangrove forests would enhance this section while connecting to the importance of the ecological system. How would one establish a freshwater ecological zone within saline environments (lines 449-450)? Additionally, model limitations should be addressed in greater detail in the discussion section.
De Dominicis, M., Wolf, J., van Hespen, R. et al. Mangrove forests can be an effective coastal defence in the Pearl River Delta, China. Commun Earth Environ 4, 13 (2023). https://doi.org/10.1038/s43247-022-00672-7
Line by Line Suggestions:
Line 16: I would remove historically since been implies past tense.
Line 32: Remove comma after area
Line 47: Ward et al., 2018 after Wahl et al., 2018
Line 55: Suggest amplify instead of worsen
Lines 57-58: I would add and before “to facilitate”
Line 66: References in chronological order
Line 66: Suggest: …, which is a major concern… (keep as 1 sentence)
Line 69: Suggest: I would remove penetration since intrusion inland describes the same thing or you could say the extent of the inland tidal intrusion
Line 73: the IPCC report
Line 86: reference prior research
Line 116: Currently
Line 304: DEM of the region
Line 305: ArcGIS model builder?
Line 405: why not put the units with the number in figure 5 (and 6)?
Line 477: delete with after with
Citation: https://doi.org/10.5194/nhess-2024-107-RC1 -
AC3: 'Reply on RC1', N.N. Hung, 05 Feb 2025
Dear Referee #1,
We would like to sincerely thank you for your time and thoughtful consideration in reviewing our manuscript. Your feedback has been extremely helpful in guiding us to finalize and enhance the quality of the paper.
Please find the attached file, where we have provided a point-by-point response to your comments.
Once again, we deeply appreciate your valuable insights and contributions.
Kind regards,
Hung
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AC3: 'Reply on RC1', N.N. Hung, 05 Feb 2025
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RC2: 'Comment on nhess-2024-107', Anonymous Referee #2, 13 Dec 2024
This study aims to investigate multiple drivers of the compound flood risk in Ca Mau Peninsula, Vietnam using a 1D hydrodynamic model under different simulation scenarios. Results indicated that the primary drivers for the escalation of inundation events in the study area are land subsidence, rising sea levels, and their combined effects. Overall, the study is comprehensive, and the findings are meaningful. The community member and the other reviewer have provided constructive comments, upon which I have several additional concerns and suggestions regarding the methodology and results of this study as follows.
Methodology
1) 1D hydrodynamic models have some limitations compared to 2D models especially when we are interested in the flood inundation extents for relatively flat floodplains and urban areas. How did you justify the validity of applying a 1D model to the study area?
2) The definition of risks may be slightly different in literature, either including three primary factors, i.e., hazard, vulnerability, and exposure, or the probability of extreme events and the consequences due to their occurrence. However, this study mainly focused on the possible scenarios of flood inundation depths and extents (or hazards) rather than the consequences due to the floods. I suggest authors keep the terms (e.g., risk and vulnerability) consistent with what is commonly used in relevant literature.
3) What is the time interval used in the model simulation? Hourly and Daily, or adjustable time steps based on the stability of the hydrodynamic model?
4) Previous studies have shown that the roughness parameter is a key factor in 1D flood modeling and roughness coefficients tend to change at different water depths. Even though the model used in this study has been fully calibrated, how did you make sure the calibrated parameters are still applicable under extreme flood events?
5) NSE, deviation, and R2 were employed in the flood model calibration and validation processes. However, the weaknesses of these metrics should be noted, and it is suggested to apply the metrics to the flow periods of interest (high flows in the case) and present the values of metrics with a statistical distribution instead of a fixed number given the sampling uncertainty. The authors can refer to the article below for more information about the limitations of these evaluation metrics.
Reference: “Beyond a fixed number: Investigating uncertainty in popular evaluation metrics of ensemble flood modeling using bootstrapping analysis” (https://doi.org/10.1111/jfr3.12982)
6) In Figure 4, what is the (linear) regression model the R2 is measuring? Also, please note that R^2 may not capture the bias in the model prediction.
7) Line 304: “Areas with a depth < 0.1 m are classified as unflooded.” What is the basis of this assumption? The water depth in Figure 1 (right) may be less than 0.1 m. Flood water with a depth of less than 0.1 m but with a high velocity can be dangerous in urban areas.
Results
8) Figure 4: Why are some data points of water discharge negative?
9) Figure 5: The maps for S4_a and S4_b scenarios are missing?
10) Table 6: The accumulated increase in flooded areas for S1 at the level of 0.1-0.4 m is 43.0%? At least it is not true based on the results in Table 5. Please double-check the results presented in the tables, which will affect your conclusions.
Minor Issues
11) It is suggested to add a north arrow and a scale bar to Figure 2, Figures 5-7, and Figure A1. What are the units of the numbers along the box in Figures 2(a) and A1?
12) Line 273: What do the numbers in “B1.5” and “B2” stand for?
13) Table 4: The caption above S6 should be “Scenarios based on multiple drivers” instead of “individual drivers”.
Citation: https://doi.org/10.5194/nhess-2024-107-RC2 -
AC2: 'Reply on RC2', N.N. Hung, 05 Feb 2025
Dear Referee #2,
We would like to sincerely thank you for your time and thoughtful consideration in reviewing our manuscript. Your feedback has been invaluable in helping us finalize and improve the manuscript paper.
Please find the attached file, where we provide a point-by-point response to your comments.
Once again, we deeply appreciate your insightful contributions.
Kind regards,
Hung
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AC2: 'Reply on RC2', N.N. Hung, 05 Feb 2025
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