the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Jun 2025
Flood and landslide risk mapping based on a multi-criteria analysis (MCA) in Greater Abidjan (Côte d’Ivoire)
Abstract. This study presents a multi-hazard risk assessment of flood and landslide hazards in the Greater Abidjan metropolitan area of Côte d’Ivoire, aimed at enhancing disaster risk reduction strategies in data-poor contexts. Using a semi-quantitative approach within a multi-criteria decision-making framework, specifically the Analytic Hierarchy Process (AHP), we assess both hazard and vulnerability factors contributing to flood and landslide risks, incorporating climatic, environmental, and social aspects. An innovative validation method is introduced, leveraging a multi-source database of past disaster events in the region, combining information from well-established disaster loss databases and results from field surveys, thereby enhancing the robustness and reliability of the results. The findings identify risk-prone areas within Greater Abidjan and provide actionable insights for improving disaster risk management. This approach, which builds on previous research by incorporating both flood and landslide risks, advances a multi-hazard perspective and contributes to a deeper understanding of hazard dynamics in Greater Abidjan. It also offers a model that can be applied to similar urban settings across sub-Saharan Africa.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2925', Anonymous Referee #1, 05 Nov 2025
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RC2: 'Comment on egusphere-2025-2925', Anonymous Referee #2, 07 Nov 2025
The research by Habal Kassoum Traore and co-authors assesses the risk associated with landslide and flood occurrences in the metropolitan area of Abidjan, Ivory Coast. To achieve this, the authors use a semi-quantitative approach that considers both susceptibility and vulnerability components. The data and information used in the models come from available datasets. The analysis is completed with field surveys. The author highlight that their findings offer insights relevant to disaster risk reduction, especially in data-poor context.
Overall, the research fits well within the scope of NHESS. It is encouraging to see such work carried out in an under-researched type of environment – emphasizing both the societal importance of such a work and also the challenges posed by limited data availability. In this regard, , I fully agree with the authors that using simple, reproducible, and data-efficient approaches represents a relevant and practical strategy.
Nevertheless, there are some important issues in this study that must be stressed.
- The main one to me: the lack of insight into process understanding. What exactly are we studying?
There is too little information with respect to what is being studied/discussed:
What type(s) of flood is considered? Pluvial, fluvial, both? Are we looking at pluvial flooding due to intense (but highlight localised) rainfall events of short duration (like thunderstorm), or are we looking at fluvial flooding associated with few day rainfalls? Different types of floods = different types of drivers and/or weighting in the AHP. What about seasonality? What would be the role of tides in these floods?
In line 311, reference is made about a study on shallow landslides. This is the only part of the manuscript where reference is made about landslide characteristics (although not for this specific study). Overall we clearly miss information about the types of processes that are being studied. Are they recent; old; of natural origin, human induced, triggered by rainfall, favoured by weathering, etc?
Considering the variety of the landscape conditions, and also the climate triggers, it would be normal to have different types of processes, or at least similar processes, but of different ages. In addition to these assumptions that we could have made a few months ago, there is a publication on landslides in Abidjan that has just been released. Although Gnagne et al. (2025)’s work comes with caveats, it still shows some interesting points: different types of landslides (slides,, avalanches, shallow and deep-seated slides), landslides of different ages (different land use/covers than today’s?).
These points with the different types of landslides are that land uses (and dynamics) will not have the same impacts on hazard, whether it is, for example, a shallow or a deep-seated slope failure (Sidle and Bogaard, 2016). Some examples of the role of land use (and land use changes – road construction; deforestation) and urbanization on landslide incidence have been published for similar tropical Africa environments (e.g. Dille et al., 2022; Maki Mateso et al., 2023); these could help to authors to better design their research.
Indeed, beyond the problem of landslide types, the selection of predictor variable, as well as the decisions regarding their categorization and the assignment of weights to these classes; often raises questions. For example, the slope gradient classes do not seems to be based on a geomorphologic consideration (see threshold hillslope concept; e.g. Bennett et al., 2016; Depicker et al., 2021). Roads are known to have an important impact on landsliding (e.g. Tanyas et al., 2022); however this variable, while being considered is the flood analysis, is not considered in the landslide one.
In addition to landslides, as illustrated by Gnagne et al. (2025), gully erosion (large gullies) is also present in the city. These gullies are certainly, in their large majority, induced by urbanisation (Ilombe Mawe et al., 2025). Gullies have influence on landslides and flood (connectivity). Such point would deserve being mentioned (and maybe discussed?)
- The overall modelling approach is questionable.
To study hazard risk, we expect susceptibility and hazard assessment, exposure analysis and vulnerability analysis. In practice we know that all these components of risk are not always easy to assess, especially for one specific region in data-scarce context. In this study, only susceptibility and vulnerability assessments are made. The temporal aspects (hazard) are not considered, nor the exposure one. This is therefore a problematic aspect in the manner the study is being presented and sold.
Another point is that, even for the susceptibility assessments, we do not know what is actually done For example, for landsliding, are the source of landslides being considered or their runout? Depending on those, they may be huge differences in exposure (e.g. Schmitt et al., 2025). In addition, considering the type of speed of the processes (rapid or less rapid landslides, flash floods, etc.), the impacts and hence the overall risk is not the same.
The vulnerability seems to be assumed to be the same for landslide and flood hazards. This cannot be the case considering the different impacts and also the frequency of the processes.
The data used as predictor variables in both flood and landside assessments, as well as for the vulnerability, are not questioned much about their reliability.
EM-DAT data are being used for validation of the models. However, these data come with significant caveats as they are highly biased towards impactful events and also towards regions provided with better communication means and greater wealth. The same hazard with the same intensity and magnitude is likely to receive less attention if it occurs in a remote location or a low-income neighbourhood. Further discussion of these reporting biases and dataset limitations can be found in Stein et al. (2024) and Delforge et al. (2025).
Fiefd survey is not clearly explained.
Hazard zonation; the meaning of the classes?
Landslide assessment provides results for flat areas.
- Muti-hazard analysis
Line 49: “...and lay the groundwork for effective multi-hazard disaster risk management and mitigation strategies.” Here, and in other places in the text, the authors put a focus on multi-hazard assessment. If I look at the definition of UNDRR (https://www.undrr.org/terminology/hazard) about multi-hazard: “Multi-hazard means (1) the selection of multiple major hazards that the country faces, and (2) the specific contexts where hazardous events may occur simultaneously, cascadingly or cumulatively over time, and taking into account the potential interrelated effects”. In this work, I do not see the real contribution with respect to the point (2). The focus of the study must be better defined with respect to what it contributes to the multi-hazard literature.
- State of the art and lack of discussion with respect to that
The state of the art is rather limited in many aspects, including urban contexts of landslide and flood risk, land transformation, population exposure, and multi-hazard interactions. For instance, when considering landslides and floods jointly, only a few studies have addressed this dual perspective. I recommend that the authors consult works such as Ferrer et al. (2024) and Idukunda et al. (2025), and discuss how the context and findings of these studies relate to the dual nature of both exposure types.
Other comments
- Introduction: The focus is strongly put in the case study of Abidjan, while the state of the art about mulit-hazard and risk assessment is not that much developed. One of the main justifications for the work is its aim to complement existing hazard studies conducted in the city. Although this is a valid rationale—particularly given the importance of improving knowledge in such a context—the study lacks a clear anchor point for a broader, international audience. In other words, why should readers unfamiliar with the study area find this work relevant or compelling?
- Line40: “frequency and severity of flooding and landslides in the region have escalated in recent years, highlighting an urgent need to develop more effective multi-hazard risk management strategies”. We would welcome the inclusion of references to support these statements. Studies capable of disentangling such trends are relatively rare, particularly in data-scarce environments. If such studies exist, they should be cited. Moreover, their comprehensive datasets would be highly valuable for both the design and validation of the present research.
- Line 90: “our study offers a more realistic andpolicy-relevant understanding of hazard exposure and vulnerability across the metropolitan continuum of Abidjan”. As stressed here in the introduction, the relevance of the work in DRR policy is emphasized. beyond the production of maps within a basic zonation framework, there appears to be limited consideration of how the results directly contribute to DRR applications. In this sense, the connection to the DRR context seems somewhat overstated.
- Line 95: “To overcome this gap, our approach introduces an innovative validation component: a geo-referenced database of observed past events, compiled from multiple sources including national reports, humanitarian data platforms, and remote sensing-based event detection”. In fact, many studies are based on similar inventories (for instance, in another data-scarce African context—see Nasabimana et al., 2023). From a methodological perspective, there is no real innovation here. Regarding model validation, comparing model outputs with real-world data is almost a compulsory step.
- Too general in many sections (for example section 2.2), bringing not relevant and accurate information for the study
In conclusion, while the topic holds significant potential, the study does not yet appear sufficiently mature. I hope that my comments will assist the authors in further developing and strengthening their work.
References:
Bennett, G.L., Miller, S.R., Roering, J.J. and Schmidt, D.A., 2016. Landslides, threshold slopes, and the survival of relict terrain in the wake of the Mendocino Triple Junction. Geology, 44(5), pp.363-366.
Delforge, D., Wathelet, V., Below, R., Sofia, C.L., Tonnelier, M., van Loenhout, J.A. and Speybroeck, N., 2025. EM-DAT: the emergency events database. International Journal of Disaster Risk Reduction, p.105509.
Depicker, A., Govers, G., Jacobs, L., Campforts, B., Uwihirwe, J. and Dewitte, O., 2021. Interactions between deforestation, landscape rejuvenation, and shallow landslides in the North Tanganyika–Kivu rift region, Africa. Earth Surface Dynamics, 9(3), pp.445-462.
Dille, A., Dewitte, O., Handwerger, A.L., d’Oreye, N., Derauw, D., Ganza Bamulezi, G., Ilombe Mawe, G., Michellier, C., Moeyersons, J., Monsieurs, E. and Mugaruka Bibentyo, T., 2022. Acceleration of a large deep-seated tropical landslide due to urbanization feedbacks. Nature Geoscience, 15(12), pp.1048-1055.
Ferrer, J.V., Samprogna Mohor, G., Dewitte, O., Pánek, T., Reyes‐Carmona, C., Handwerger, A.L., Hürlimann, M., Köhler, L., Teshebaeva, K., Thieken, A.H. and Tsou, C.Y., 2024. Human settlement pressure drives slow‐moving landslide exposure. Earth's Future, 12(9), p.e2024EF004830.
Gnagne, F.L., Schmitz, S., Kouadio, H.B., Hubert-Ferrari, A., Biémi, J. and Demoulin, A., 2025. Predicting Landslide Susceptibility Using Cost Function in Low-Relief Areas: A Case Study of the Urban Municipality of Attecoube (Abidjan, Ivory Coast). Earth, 6(3), p.84.
Idukunda, C., Michellier, C., De Longueville, F., Twarabamenye, E. and Henry, S., 2025. Assessing community vulnerability to landslide and flood in northwestern Rwanda. International Journal of Disaster Risk Reduction, 123, p.105329.
Mawe, G.I., Landu, E.L., Dujardin, E., Imwangana, F.M., Bielders, C., Hubert, A., Michellier, C., Nzolang, C., Poesen, J., Dewitte, O. and Vanmaercke, M., 2025. Mapping urban gullies in the Democratic Republic of the Congo. Nature, 644(8078), pp.952-959.
Nsabimana, J., Henry, S., Ndayisenga, A., Kubwimana, D., Dewitte, O., Kervyn, F. and Michellier, C., 2023. Geo-hydrological hazard impacts, vulnerability and perception in Bujumbura (Burundi): a high-resolution field-based assessment in a sprawling city. Land, 12(10), p.1876.
Ozturk, U., Bozzolan, E., Holcombe, E.A., Shukla, R., Pianosi, F. and Wagener, T., 2022. How climate change and unplanned urban sprawl bring more landslides. Nature, 608(7922), pp.262-265.
Schmitt, R.J.P., Bhandari, S., Vogl, A. and Marc, O., 2025. Leveraging hillslope connectivity for improved large-scale assessments of landslide risk. EGUsphere, 2025, pp.1-34.
Sidle, R.C. and Bogaard, T.A., 2016. Dynamic earth system and ecological controls of rainfall-initiated landslides. Earth-science reviews, 159, pp.275-291.
Stein, L., Mukkavilli, S.K., Pfitzmann, B.M., Staar, P.W., Ozturk, U., Berrospi, C., Brunschwiler, T. and Wagener, T., 2024. Wealth over Woe: Global biases in hydro‐hazard research. Earth's Future, 12(10), p.e2024EF004590.
Tanyaş, H., Görüm, T., Kirschbaum, D. and Lombardo, L., 2022. Could road constructions be more hazardous than an earthquake in terms of mass movement?. Natural hazards, 112(1), pp.639-663.
Citation: https://doi.org/10.5194/egusphere-2025-2925-RC2
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- 1
The authors present a significant study on multi-hazard risk assessment for the Greater Abidjan area, which is highly relevant for regional disaster planning. By using the Analytic Hierarchy Process (AHP) within a Multi-Criteria Analysis framework, the manuscript aims to integrate diverse factors (climatic, environmental, and social) to produce valuable risk maps. The conceptual framework is sound, but the manuscript currently needs to strengthen the Methdology and Results section for clarity and transparency as detailed below.
Line 110: The paper structure is clearly outlined, though the "Sections" should be labelled according to standard scientific paper structure (e.g., Introduction, Methodology, Results, Discussion)
Line 165: There is a mismatch between the locations (4 municipalities listed) and the densities (5 values provided). Please correct this discrepancy.
Tables 1, 3, 5: It is unclear on which grounds the classification bins are established. Please add explanation of how thresholds were determined (e.g., natural breaks, quantile, literature-based).
Lines 175-180: The AHP weight determination process needs more detail. Please include: expert selection criteria, number of experts consulted, and the consensus-building process.
Lines 235 & 258-259: The CR values appear identical (1.3%) for both flood and landslide hazards. Please double-check these calculations and explain if they are indeed identical.
Line 339: Add a paragraph acknowledging missing vulnerability indicators (income, housing quality, infrastructure, health access).
Lines 452-510: The results section severely lacks quantitative visualization. Maps alone are insufficient for comprehensive risk communication. Please add: (1) statistical plots showing risk distributions and population exposure, (2) municipal comparison charts, (3) quantitative summary table showing area (km²) and population at each risk level for both hazards.
Line 482: "landslides (illustrated by red dots)" - the red dots are not visible in Figure 8. Please make them clearly visible or remove this reference.
Lines 515-520: Validation discussion is too brief. Please add ROC curves and confusion matrices to discuss agreement between data and model.
Lines 524-566: Please group the limitations by themes (data limitations, methodological constraints, scope restrictions) and prioritize by impact on results.
Lines 544-546: Expand discussion on how the identified limitations specifically affect your results and their reliability.
All Figures: The figures' quality, size, and font need to be updated for better readability. Ensure minimum 300 DPI resolution and legible text (≥10pt font).