Slope stability modelling in Karongi district, Western Rwanda

Barayagwiza, Sylvain; Meriaux, Catherine A.; Armigliato, Alberto

doi:10.5194/egusphere-2026-3426

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https://doi.org/10.5194/egusphere-2026-3426

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29 Jun 2026

| 29 Jun 2026

Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).

Slope stability modelling in Karongi district, Western Rwanda

Sylvain Barayagwiza, Catherine A. Meriaux, and Alberto Armigliato

Abstract. The Karongi District in Western Rwanda is frequently subject to landslides. To date, however, physics-based slope stability assessments remain pending. In this study, we apply a three-dimensional Limit Equilibrium Method (LEM) using Scoops3D software to compute Factor of Safety (FOS) distributions in Karongi District. The model evaluates the effects of the pore-pressure ratio (ru) and horizontal pseudo-static seismic coefficient (k_eq) on slope stability. Results identify critical thresholds at ru ∼ 0.10 and k_eq = 0.075, beyond which unstable areas expand rapidly. When combined to pore pressure and at low pore pressure ru ≤ 0.10, seismic loading can significantly amplify slope instability. Model validation using historical landslide inventories shows 80 % spatial agreement between simulated unstable areas (FOS < 1) and observed landslides in two scenarios: (1) ru = 0.18 and k_eq = 0.10; and (2) ru = 0.35 and k_eq = 0.03. Although applied to the Karongi district, the methodology presented in this study can be used to assess the relative importance of pore pressure and seismic forcing in slope stability in a seismically active region prone to landslides.

Received: 12 Jun 2026 – Discussion started: 29 Jun 2026

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Sylvain Barayagwiza, Catherine A. Meriaux, and Alberto Armigliato

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'Comment on egusphere-2026-3426', Olivier Dewitte, 06 Aug 2026 reply
Dear Sylvain Barayagwiza and co-authors,
I read your study on slope stability modelling in Rwanda with great interest. To further enrich your analysis, I would like to draw your attention on several points that, I believe, are relevant.
The landslide susceptibility model developed in this study is validated against, among other datasets, a rainfall-triggered landslide event that has occurred on 6 May 2018. Such type of rainfall-triggered landside clusters, often comprising several hundreds of landslides, are common in the region (Deijns et al., 2024; Dewitte et al., 2021). With regard to the triggering mechanism, it is important to emphasize that none of the numerous landslide events documented in the region over the past decades has been associated with seismic activity (Dewitte et al., 2021; Depicker et al., 2024). The role of seismicity as a trigger is clearly to be discarded for the landslide used for the validation. This raises questions about the relevance of the seismicity-related analyses presented in this study. Nevertheless, seismicity may still play a long-term preparatory role by influencing hillslope conditions and modifying their response to subsequent stresses, thereby affecting landslide characteristics such as size (Depicker et al, 2021).

The Discussion states: “In this respect, it is regrettable that the historical data available on landslide inventories (Depicker et al., 2021a) do not systematically provide the dates of the events, which could have revealed certain correlations (temporal and/or spatial) with those of the earthquakes.” While the inventory of Depicker et al. (2021) is indeed a historical inventory, the dates it reports correspond to the time intervals constrained by the availability of Google Earth imagery. However, the occurrence date of the landslide cluster analyzed in this study is well established (Deijns et al., 2022). Furthermore, as noted above, none of the documented landslide events in the region has been linked to seismic activity (Dewitte et al., 2021). Therefore, the discussion of potential earthquake–landslide correlations appears unsupported in the context of the available evidence.

Agricultural terrasses influence hillslope hydrology and, consequently, slope stability. Sibomana et al. (2025) investigated three landslide cluster events in Rwanda in relation to agricultural terracing, including the 2018 event analyzed in this study. Their results indicate that terracing leads to a greater number of landslides, although these tend to be smaller in size. Given the relevance of these findings to the present study, the influence of agricultural terracing should at least be discussed.

The landslides investigated in this study are rainfall-triggered. In addition to the triggering rainfall, antecedent hydrological conditions and seasonal variability are known to play an important role in landslide occurrence. These factors should be more thoroughly addressed and discussed in light of the regional state of the art (Monsieurs et al., 2018a, 2018b, ; 2019; Uwihirwe et al., 2020, 2022a, 2020b).

Several data-driven landslide susceptibility assessments have already been conducted in the study area. Among these, the study by Depicker et al. (2020) provides, to my knowledge, the most comprehensive regional assessment of landslide susceptibility under natural conditions in the Kivu Rift. As the datasets from this study are publicly available, they provide an excellent opportunity to compare and discuss the results presented here with an existing regional benchmark.. https://zenodo.org/records/5524161

I hope you find these references helpful.
Kind regards,
Olivier Dewitte
References

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Deijns, A.A., Michéa, D., Déprez, A., Malet, J.P., Kervyn, F., Thiery, W. and Dewitte, O., 2024. A semi-supervised multi-temporal landslide and flash flood event detection methodology for unexplored regions using massive satellite image time series. ISPRS Journal of Photogrammetry and Remote Sensing, 215, pp.400-418.
Depicker, A., Jacobs, L., Delvaux, D., Havenith, H.B., Mateso, J.C.M., Govers, G. and Dewitte, O., 2020. The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift. Geomorphology, 353, p.106886.
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Dewitte, O., Dille, A., Depicker, A., Kubwimana, D., Maki Mateso, J.C., Mugaruka Bibentyo, T., Uwihirwe, J. and Monsieurs, E., 2021. Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region. Landslides, 18(1), pp.161-177.
Monsieurs, E., Kirschbaum, D.B., Tan, J., Maki Mateso, J.C., Jacobs, L., Plisnier, P.D., Thiery, W., Umutoni, A., Musoni, D., Bibentyo, T.M. and Ganza, G.B., 2018b. Evaluating TMPA rainfall over the sparsely gauged East African Rift. Journal of Hydrometeorology, 19(9), pp.1507-1528.
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Sibomana, P., Vanmaercke, M., Depicker, A., Tychon, B., Hubert, A. and Dewitte, O., 2025. Effects of agricultural terraces on landslide occurrence: Insights from a tropical mountainous region (Rwanda, Africa). Catena, 253, p.108898.
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Uwihirwe, J., Hrachowitz, M., and Bogaard, T., 2022a. Integration of observed and model-derived groundwater levels in landslide threshold models in Rwanda, Nat. Hazards Earth Syst. Sci., 22, 1723–1742, https://doi.org/10.5194/nhess-22-1723-2022.
Uwihirwe, J., Riveros, A., Wanjala, H., Schellekens, J., Sperna Weiland, F., Hrachowitz, M. and Bogaard, T.A., 2022b. Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda. Natural Hazards and Earth System Sciences, 22(11), pp.3641-3661.

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Citation: https://doi.org/10.5194/egusphere-2026-3426-CC1

Sylvain Barayagwiza, Catherine A. Meriaux, and Alberto Armigliato

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Short summary

Located along the East African Rift, the Karongi district in Rwanda combines steep slopes, a humid temperate climate, and seismic activity that results in frequent landslides. A physical and numerical modeling approach was used for the first time to analyze slope stability in this district, weighting the influence of pore pressure and seismic forcing. Results show that slope instability requires either very high soil water content or combined moderate seismic forcing and water content.


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