the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jan 2026
Regional modeling of the impacts of tidal flooding in the context of mean sea level rise on low-lying in the Global South
Abstract. This study assessed the risks and impacts of rising average sea levels on Brazil's semi-arid coastline in a low-lying coastal area with limited response potential, using freely available data and based on the central hypothesis that, even in conservative scenarios, there will be risks with significant impacts. The methodology integrated DEM calibration, geodetic validation of tide gauge data, flood modeling, and overlay with real estate grids to quantify damage. The results showed relative stability of astronomical tides, with projected extremes of up to 2.975 m and 3.454 m, respectively, for a 20-year return period. Meteorological tides showed low values (≈ 0.11 m), although with episodic variability. The modeling indicated that up to 14 % of the total area (about 730 km²) could be affected in extreme scenarios, with progressive flooding of solar salt pans and low-lying urban areas. Cities such as Areia Branca, Macau, and Porto do Mangue are at the highest risk, with a 60–80 % probability of flooded days in severe scenarios. Economic losses were estimated at approximately R$ 36 million in residences (≈ US$ 6.7 million) and R$ 158 million in land (≈US$ 29 million), with Areia Branca being the most impacted municipality. Towns such as Barra, Cristóvão, and Baixa Grande also experienced significant risks and damage. The findings reinforce the usefulness of open data for regional risk analysis, even recognizing limitations in spatial resolution and vertical uncertainties. The methodology proved promising, replicable, and useful for supporting adaptive policies in regions with low institutional technical capacity.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4929', Anonymous Referee #1, 31 Jan 2026
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RC2: 'Comment on egusphere-2025-4929', Anonymous Referee #2, 12 Feb 2026
This study evaluates the risk of tidal flooding in the low-lying coastal areas in Brazil in the context of sea-level rise using open-source data. The evaluation framework can be helpful in areas with limited technical methods. However, the method used for flooding risk analysis in this study is not explained clearly, and there are several errors in the manuscript. My suggestions and questions are as follows.
- The title indicates that this study evaluates the low-lying areas in the Global South, yet its study area is limited to Brazil. Why was Brazil chosen? Are the low-lying areas in Brazil the only representative cases for this study in the whole Global South? Should the title be “in Brazil” rather than “in the Global South”?
- Equation 1 and section 3.6: Details should be explained on the “hazard” and “vulnerability”. What is the total flood modeling that derives “hazard”? How is “vulnerability” calculated? What factors are considered in deriving “vulnerability”?
- The section about materials and methods is very confusing to read. The methods are not explained in detail. Necessary equations and modeling methods are not explained. The connections between the collected data and methods are not clear. It is recommended to add a flow chart for the risk evaluation processes for clarity.
- There are a lot of acronyms in the manuscript. Some of them seem unnecessary since they are only used once (e.g., BSC, FT, GEV), and some are not given (e.g., SMC-Brazil). It is recommended to check all acronyms and compile a list of them for clear reference.
- Section 3.1: The description of the collected data is very confusing. A table including the information on all the datasets is recommended.
- Section 3.1.1: Elevation data should be demonstrated in a figure.
- Section 3.1.5: Please explain the reason for using MSLR projections on three scales, and how they are “systematized”.
- Section 3.1.6 and 3.1.7: Please add figures for land use data and urban data. What exactly is the urban data, images taken by UAVs, or something more?
- In all figure captions, it is unnecessary to declare that the figures are prepared by the authors unless figures from other sources are used. These statements should be removed.
- The numbering of sections 3.2 to 3.6 is incorrect. Section 3.3 is missing.
- Table 2: Why is the header of the first column “Dates”? What is the meaning of “Initially, differences can be noted between the different processes in the region” in the caption?
- Figure 4: Please add the location and whether it is the astronomical or meteorological tide in each sub-figure.
- Figure 7: It is inappropriate to cite an online news report using a figure. It should be properly cited in words, and a formal reference item should be included in the References section with the title, the news reporter, the publication time, the URL to the news article, the access date, etc.
- Figure 4, 5, 6, 11, and 12: Please label the sub-figures with alphabetical identifiers.
- Please check all the tables and add units to numbers.
Citation: https://doi.org/10.5194/egusphere-2025-4929-RC2
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- 1
The study evaluated the risks and impacts of rising mean sea levels on Brazil’s semi-arid, low-lying coastline using freely available datasets. The authors proposed a framework that integrates calibrated digital elevation models (DEM), validated tide-gauge data, flood modeling, and spatial overlays with real estate grids to estimate the impacts of tidal flooding. Overall, this study is meaningful for more informed coastal flood risk management, especially for areas with limited institutional and technical capacity. However, I still have several concerns and suggestions as follows.
1) Lines 90-94: As the authors mentioned, quite a few studies have been conducted to investigate the flooding risk analysis for low-lying coastal areas. Then what makes this study different from the literature?
2) It is suggested to add a list of acronyms mentioned in the manuscript. The full term of the acronym is only presented the first time it appears, e.g., SGB, however, does not make sense since it is short for "Brazilian Geodetic System". Should it be "BGS"?
3) Equation (1): Exposure is also an important factor in determining the degree of risk. Is it possible to incorporate the effect of exposure in your risk analysis? How would that affect the findings in this study?
4) In the caption of some figures, it is suggested to remove the unnecessary statement like "Map prepared by the authors (2025)".
5) Section 3.1: It is suggested to add a table to present the information of different datasets used in this study and make the corresponding text more concise.
6) Figure 3, Equations (3) and (4), Table 3, Table 4, etc.: To avoid confusion, please change the comma "," to decimal point "." in the elevation numbers.
7) Lines 245-248: The bathtub technique does not account for hydrodynamics and it is very likely that it will lead to overestimates in flood inundation extents. The applicability of the bathtub technique should be justified in more detail. Moreover, it should be noted that various uncertainty sources in the physics-based flood modeling process should not be ignored (Please refer to the paper below). Also, too many references are cited here. It is suggested to remove some old ones.
Reference:
"Uncertainty analysis and quantification in flood insurance rate maps using Bayesian model averaging and hierarchical BMA" (https://doi.org/10.1061/JHYEFF.HEENG-58)
8) Lines 264-266: 0 to 5 is actually six classes. According to Table 1, the hazard class value is from 1 to 5.
9) Table 2 and Table 3: Please add units to the numbers. Also in Table 2, the Kendall’s Tau is a normalized S. Why is S positive, while the Kendall’s Tau is negative?
10) Figure 4: Please add the area name to each sub-figure. For the bottom panel, how would you explain the observed data points of the tidal level are much lower than the fitted values?
11) Figure 6: To make the flooding probability clearer, it would be better to remove the ocean area from the figures.
12) Figure 9: It is suggested to add a scale bar to each sub-figure.
13) Should Figure 13 be Table 6?
14) Line 540: What does “addressing climate change” mean?