the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jun 2026
Slope stability modelling in Karongi district, Western Rwanda
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 (keq) on slope stability. Results identify critical thresholds at ru ∼ 0.10 and keq = 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 keq = 0.10; and (2) ru = 0.35 and keq = 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.
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Status: open (until 17 Sep 2026)
- CC1: 'Comment on egusphere-2026-3426', Olivier Dewitte, 06 Aug 2026 reply
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RC1: 'Comment on egusphere-2026-3426', Anonymous Referee #1, 15 Aug 2026
reply
The manuscript presents a useful first physics-based assessment of slope instability in Karongi District using Scoops3D to investigate the individual and combined effects of pore-water pressure and seismic loading, and the attempt to validate the simulations against historical landslide inventories is valuable. However, the current model relies on several strong simplifications—including homogeneous soil properties over the entire district, uniform ru and seismic forcing, a coarse 100-m computational DEM, and failure volumes substantially larger than the predominantly shallow landslides documented in the region—which limit the physical interpretation and generalizability of the reported threshold values. In particular, representing rainfall solely through a prescribed pore-pressure ratio does not reproduce rainfall infiltration, transient suction loss, groundwater evolution, or the unsaturated hydraulic response that is central to rainfall-induced slope instability. The reported 80% agreement with the inventory is encouraging, but validation should be strengthened quantitatively because two very different combinations of ru and keq produce essentially the same agreement, indicating substantial non-uniqueness in model calibration. Therefore, I recommend major revision, with particular attention to hydro-mechanical representation, spatial variability, scale consistency, uncertainty/sensitivity analysis, quantitative validation, and a substantially deeper comparison with recent literature on unsaturated slope behavior, rainfall infiltration, soil hydraulic characterization, and regional-scale slope stability.
1. How can the authors justify representing rainfall-induced slope instability solely through a spatially and temporally uniform pore-pressure ratio ru? The manuscript acknowledges that this approach does not simulate rainfall infiltration or spatial/temporal rainfall variability and cannot account for negative pore-water pressures. Since many tropical residual slopes initially exist under unsaturated conditions, the authors should more thoroughly discuss the role of matric suction, SWCC, permeability functions, and wetting-induced suction loss. The discussion could be substantially strengthened using the practical unsaturated-slope framework developed by Adiguna et al. (2023), which specifically emphasizes the importance of incorporating soil suction into slope-stability assessment. (doi.org/10.3390/app13031811)
2. Can the critical value ru≈0.10−0.15 genuinely be interpreted as a physically meaningful threshold when ru is prescribed rather than derived from rainfall infiltration or groundwater observations? The manuscript identifies an apparent nonlinear transition beyond approximately ru=0.15, but without linking ru to actual rainfall intensity, duration, antecedent moisture, or measured pore-water pressures, its practical significance remains unclear. The authors should consider linking these results to transient infiltration and evapotranspiration processes; Hamdany et al. (2023), for example, numerically examined how infiltration and evapotranspiration alter soil suction and residual-slope stability and would provide highly relevant context. (doi.org/10.3390/su15118653)
3. Why is the entire Karongi District represented by a single homogeneous soil layer with uniform c, ϕ, and unit weight derived from measurements at a nearby site rather than from the district itself? The adopted values are based on measurements from Bigugu Village in Rutsiro District, whereas the model domain covers approximately 993 km². The authors should quantify how uncertainty and spatial variability in these properties affect the calculated FS and the proposed ru and keq thresholds. Regional soil-property databases and spatial parameterization strategies should also be discussed; the recent database approach of Li et al. (2025) demonstrates how spatially variable soil properties, including biologically influenced properties, can be assembled for regional slope-stabilisation analysis. (doi.org/10.1038/s41598-025-85250-5)
4. There appears to be a major scale inconsistency between the observed landslides and the simulated failure volumes. How does this affect the validity of the conclusions? Observed landslides in Karongi are reported to be shallow, approximately 0.5–2 m deep, with estimated volumes from about 25 to 1.36×105 m³, whereas Scoops3D searches for failure volumes of 107−108 m³. This two-to-several-orders-of-magnitude mismatch requires much stronger justification, and preferably additional higher-resolution simulations representative of the actual shallow landslide dimensions.
5. Is reducing the DEM resolution from 10 m to 100 m appropriate for identifying shallow landslide susceptibility in such steep and dissected terrain? Although the appendix indicates broadly similar vulnerable zones, the percentage of unstable area changes from approximately 0.40% to 1.75% depending on resolution/search settings, which is not negligible when quantitative thresholds are being inferred. A formal grid-resolution/convergence assessment should therefore be provided, particularly because slope gradients and small-scale topographic controls are strongly resolution dependent.
6. How robust are the proposed power-law relationships between unstable area and ru or keq? The manuscript fits power laws only over selected intermediate ranges and then notes departures from those relationships at larger values. The authors should report goodness-of-fit statistics, parameter confidence intervals, sensitivity to the fitted interval, and ideally a physical explanation for the exponents rather than treating empirical curve fitting as evidence of a fundamental threshold.
7. The seismic analysis relies on pseudo-static loading, but how representative are the selected keq values of actual site-specific seismic demand? The manuscript combines event-based estimates with a broad keq=0.03−0.35 range and acknowledges that pseudo-static loading neglects dynamic amplification and shaking duration. The authors should conduct a sensitivity assessment and clearly distinguish scenario analysis from actual seismic hazard prediction; ideally, the adopted coefficient range should be linked more rigorously to PGA, return period, local site effects, and uncertainty.
8. Is an “80% match” sufficient to validate the model when there is no corresponding assessment of false positives or correctly predicted stable areas? Two markedly different parameter combinations—ru=0.18, keq=0.10 and ru=0.35, keq=0.03—both yield approximately 80% agreement, demonstrating non-uniqueness. The authors should calculate more rigorous performance measures such as ROC-AUC, precision, recall/sensitivity, specificity, success/prediction rate, or confusion matrices and demonstrate whether the proposed model performs significantly better than a terrain-only baseline.
9. The manuscript should provide a much deeper discussion of unsaturated hydraulic properties and potential approaches for obtaining them rather than simply acknowledging the absence of pore-pressure data. SWCC and hydraulic conductivity functions provide the physical relationship between water content, matric suction, and infiltration response. For this reason, the authors are encouraged to discuss modern methods for establishing these properties, including the high-suction SWCC measurement approach reported by Prakoso et al. (2024/2025), which demonstrates the importance and feasibility of obtaining suction-dependent hydraulic information over an extended range. Such discussion would also clarify how future versions of the Karongi model could replace prescribed ru with physically calculated transient pore-water pressures. (doi.org/10.3390/su17010218)
10. The discussion of mitigation and practical applicability should be expanded beyond identifying unstable zones. What engineering interventions would follow from the modelling results? For rainfall-dominated slopes, surface protection, drainage, vegetation, and modifications to infiltration can substantially change the hydraulic boundary condition rather than merely changing static strength parameters. The authors should therefore discuss relevant rainfall-protection strategies and recent examples such as the recycled-concrete-aggregate capillary-barrier study by Rahayu et al. (2024), which evaluates how slope-cover systems alter pore-water pressure and stability during rainfall. (doi.org/10.1016/j.rineng.2024.103244) Together with the wetting-induced slope framework of Adiguna et al. (2023), transient infiltration–evapotranspiration modelling of Hamdany et al. (2023), regional soil-property database of Li et al. (2025), and SWCC measurement study of Prakoso et al., these references would help the authors place the present simplified ru-based framework within the broader state of the art and identify a credible pathway toward a more physically based model.
Citation: https://doi.org/10.5194/egusphere-2026-3426-RC1
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- 1
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.
I hope you find these references helpful.
Kind regards,
Olivier Dewitte
References
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