the Creative Commons Attribution-NonCommercial 4.0 International License.
the Creative Commons Attribution-NonCommercial 4.0 International License.
A process-based framework for regional landslide debris inundation hazard assessment: application to the West Coast region of New Zealand
Abstract. Regional landslide debris inundation hazard assessments commonly rely on scenario-based formulations that require explicit enumeration of discrete landslide events. While effective for local studies, these approaches are computationally intensive, sensitive to scenario design choices, and difficult to apply consistently at regional scales where landslide catalogues are incomplete and long-term behaviour is poorly constrained. In parallel, geomorphological models provide insight into landslide-driven sediment production over long timescales, but are rarely formulated to generate spatially explicit hazard metrics relevant to runout and inundation.
Here we present the Landslide Source-to-Inundation Process Model (LS-IPM), a reduced-complexity, process-based framework that reframes landslide debris inundation hazard as a flux-based intensity problem. Rather than simulating discrete landslide scenarios, LS-IPM couples spatially distributed landslide sediment production to mass-conservative, topography-controlled debris routing, producing continuous fields of landslide-derived debris flux. Landslide magnitude and frequency are implicitly linked through a constraint on sediment production, allowing hazard to be evaluated everywhere in the landscape without explicit specification of individual failure events.
We apply the LS-IPM to the ~25,000 km² West Coast region of New Zealand at 25 m resolution, generating hazard estimates for present-day conditions, future climate scenarios (RCP6, 2081–2100), and a scenario Alpine Fault Mw 8.0 earthquake. Results show highest debris flux on steep slopes, at the base of high-relief landforms, and along convergent topography, consistent with geomorphological expectations. Approximately 80 % of the region is affected by some degree of landslide debris inundation hazard, with future climate conditions expected to increase mean annual debris flux by ~50 %.
By integrating geomorphological constraints with reduced-complexity runout modelling, the LS-IPM provides a scalable framework for regional landslide debris inundation hazard assessment that is compatible with subsequent probabilistic risk analysis.
Status: open (until 20 Oct 2026)
- RC1: 'Comment on egusphere-2026-4888', Anonymous Referee #1, 20 Sep 2026 reply
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CC1: 'Comment on egusphere-2026-4888', Syed Azeem Inam, 20 Sep 2026
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1. Please demonstrate that the sediment production constraint yields identifiable frequency-magnitude relationships rather than multiple equally plausible event populations with identical debris flux.
2. Please justify the suspended sediment multiplier of 1.5 using a spatially explicit uncertainty model rather than agreement with selected regional denudation estimates.
3. Please propagate uncertainty jointly from erosion rate, bulking factor, density, susceptibility, volume distribution, source geometry, mobility, and movement mode into every reported hazard metric.
4. Please assess whether summing rainfall and earthquake probabilities is valid when triggers are non-independent and when repeated failures alter local susceptibility through time.
5. Please replace the binary kinematic feasibility criterion with a probabilistic formulation that represents uncertainty in source geometry, strength, depth, and spatially variable lithology.
6. Please test whether the assumed log-normal source volume distributions remain valid after inventory incompleteness, mapping resolution, censoring of small failures, and source runout separation are explicitly corrected.
7. Please conduct independent component-wise validation of source probability, mobilized volume, runout extent, deposition, and debris flux rather than validating final outputs using reconstructions based on the same GPP framework.
8. Please calibrate and validate the PCM parameters and the avalanche versus flow weights against geographically independent West Coast observations instead of transferring classifications from Cyclone Gabrielle.
9. Please demonstrate numerical and physical convergence across DEM resolution, routing iterations, volume class discretization, integration interval, smoothing scale, and sink filling settings before presenting regional hazard percentages.
Citation: https://doi.org/10.5194/egusphere-2026-4888-CC1 -
RC2: 'Comment on egusphere-2026-4888', Anonymous Referee #2, 21 Sep 2026
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Review of “A process-based framework for regional landslide debris inundation hazard assessment: application to the West Coast region of New Zealand”
This paper presents the LS-IPM, a reduced-complexity, flux-based framework for regional landslide debris inundation hazard assessment. It couples landslide source susceptibility, long-term sediment production, and downslope debris routing, avoiding the need to enumerate discrete landslide scenarios. The manuscript is well structured and beautifully written. The reviewer has no critical concerns but a few major/minor comments.
Figures 1 and 2. It would be helpful to label latitude and longitude on the maps, so that readers unfamiliar with the local geography can orient themselves more easily. The authors may consider adding a zoomed-out map of the region for easier reference.
Line 612. Just out of curiosity, will the future land use be considered?
Line 586. Should be kyr-1 not kyr.
The Abstract and Conclusions state that future climate conditions increase mean annual debris flux by ~50%, but Section 4.3 reports a ~50% increase in sediment production, not debris flux. These are not the same quantity: debris flux also depends on routing, deposition, and connectivity, and Section 4.3 explicitly describes the flux response as spatially non-uniform. The Abstract and Conclusions should be corrected to avoid conflating sediment production with debris flux.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC2 -
RC3: 'Comment on egusphere-2026-4888', Anonymous Referee #3, 22 Sep 2026
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This manuscript presents a valuable framework (LS-IPM) for regional hazard assessment based on a flux-driven representation of landslide processes. The conceptual approach is quite interesting and very well motivated, and the West Coast case study demonstrates its potential applicability. However, the manuscript is too lengthy and repetitive in several sections, and the highlight on methodological novelty is not fully matched by the level of validation presented. I suggest a major revision of the manuscript. Comments are presented below.
1. Manuscript structure
- The manuscript could benefit from significant streamlining and reducing redundancy. Several concepts, particularly the distinction between LS-IPM and scenario-based approaches, are repeated throughout Introduction, Discussion, and Conclusions.
- The Introduction is verbose and could be condensed by focusing more clearly on the knowledge gap, limitations of existing approaches, and the objectives of the study.
- Methodology section,especially sub-section 2.3.4, contains extensive mathematical formulation. A conceptual workflow figure presenting the relationships between LSS, LSP, and LSD would greatly improve readability.
2. Performance assessment and model validation
- The manuscript would benefit from a stronger and more explicit validation strategy. Currently, validation relies mainly on qualitative agreement with geomorphic expectations or comparisons with model-derived products, thus, where possible, additional comparisons against independent observations of landslide occurrence, inundation extent, sediment volumes, mapped deposits should be included to better illustrate model performance and predictive capability.
- The distinction between model validation, model evaluation, and plausibility checks should be clarified throughout the manuscript.
3. Assumptions, Uncertainty and Sensitivity
- Several key assumptions supporting the framework require stronger justification, including sediment-production constraint, adopted volume distributions, movement-mode weighting, and the treatment of future climate scenarios.
- The uncertainty related to these assumptions should be discussed more in detail, including how they could affect the resulting hazard estimates.
- A concise sensitivity analysis, or at least a summary of the sensitivity of model outputs to major parameters, would improve the robustness of the framework.
4. Existing literature
- Some statements regarding the novelty of the proposed framework and the limitations of existing approaches appear stronger than necessary. The authors may wish to moderate these claims and more clearly position LS-IPM as a complementary approach within the broader landscape of regional landslide hazard modelling.
- In the discussion, the distinction between methodological elements that are genuinely novel and those adapted from existing modelling frameworks should be made clearer.
5. Results and Interpretation
- The results section would benefit from additional quantitative analysis and synthesis. Currently, much of the discussion remains descriptive.
- More emphasis could be placed on quantifying the relative contributions of different triggers, landslide-volume classes, and topographic connectivity to the final hazard patterns.
- In the discussion section a more detailed consideration of transferability of the framework to other regions could be added, considering different geomorphic, climatic, and tectonic settings.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC3 -
RC4: 'Comment on egusphere-2026-4888', Anonymous Referee #4, 25 Sep 2026
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1. This is the point I keep coming back to. Figure 7 is presented as the main check on the model, but as the authors themselves note in Sect. 4.4, the fluxes reconstructed for the Murchison and Inangahua events are produced with the same GPP routing that generated the predictions. So the comparison says something about the magnitude of the debris budget coming out of the LSS and LSP components, and essentially nothing about whether the LSD routing puts the debris in the right places. For a paper whose central claim is that runout-informed hazard can be mapped continuously at regional scale, the absence of any direct spatial check against mapped inundation is a real gap. The sentence in the Conclusions about modelled flux extending to within one 25 m grid cell of mapped fan margins is exactly the kind of evidence that is needed, but it is reported in passing. I would like a short validation subsection, even for a handful of well-mapped fans or catchments, comparing predicted inundation extent to observed debris extents — hit rates, false-positive rates, something quantified. That would address the "not independent" criticism far more directly than a histogram comparison.
2. About the headline figure: "approximately 80 % of the region is affected" appears in the abstract, the introduction and the conclusions, but it is not clear what it means operationally. The flux legend in the maps starts at 0.0000 m³ m⁻² yr⁻¹, and at that threshold essentially any cell that has ever been crossed by debris counts as affected. A percentage computed that way is less a statement about hazard than about topographic connectivity, and it risks being read as "80 % of the West Coast is at risk." Please state the flux threshold behind the 80 % figure, and more usefully show an exceedance curve of affected area against flux threshold, so readers can see what fraction of the region actually falls into the high-flux classes. Without that, the number will be quoted far beyond what the model supports.
3. The results are more sensitive to the movement-mode treatment than the paper suggests, and the inputs behind it are the least constrained. The 66/33 avalanche-to-flow split for rainfall events is transferred from Cyclone Gabrielle on the North Island (Sect. 3.3.3), the 83/17 split for earthquakes is assumed, and the PCM parameters come from Swiss debris-flow work. Figure 7 shows that the movement mode changes the affected area from roughly 72 % to 80 % at the lowest thresholds and reshapes the upper tail — a first-order effect driven by inputs that have no local calibration and no sensitivity analysis behind them. I would like a one-at-a-time sensitivity run over the movement-mode weights, the PCM/fahrböschung parameters, and the production factors (ωL = 1, ηL = 1.3), reporting how the spatial pattern, the 80 % figure and the ~50 % climate change all respond. If the headline conclusions survive that, the paper is considerably stronger; if they do not, we need to know now rather than after publication.
4. One small thing on the literature. In Sect. 1.2 the argument that regional landslide assessments tend to stop at source occurrence or susceptibility, and rarely carry through to debris inundation, is well made but rests almost entirely on the New Zealand context. A couple of recent examples from outside that setting would make the point land harder — for instance work on extreme-rainfall and typhoon-induced landsliding that combines susceptibility mapping with early-warning thresholds (Xiao et al., 2026a, https://doi.org/10.1016/j.envsoft.2026.107034; Xiao et al., 2026b, https://doi.org/10.5194/nhess-26-611-2026), which is precisely the kind of assessment that stops at the source/warning stage.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC4 -
RC5: 'Comment on egusphere-2026-4888', Anonymous Referee #5, 30 Sep 2026
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In this study, the authors propose the Landslide Source-to-Inundation Process Model (LS-IPM), a reduced-complexity, process-based framework that couples spatially distributed landslide-sediment production with a mass-conservative, topography-controlled sediment-routing model, rather than explicitly simulating individual landslide scenarios. The model is applied to the approximately 25,000 km² West Coast region of New Zealand at a spatial resolution of 25 m, and demonstrates a reasonable capability to assess landslide-debris inundation hazard.
However, the model is highly comprehensive and complex, and there are several aspects of the methodology and its underlying assumptions that would benefit from clearer explanation and justification. I therefore provide several major comments below.
#1
What is the scope of the term “debris inundation”? For example, when a landslide occurs and subsequently mobilizes into a debris flow, the transported sediment may be deposited on an alluvial fan as debris-flow lobes. However, in addition to such deposition, sediment-laden flows with very high sediment concentrations may continue downstream, and if the capacity of the downstream river channel is insufficient, overbank inundation of sediment-laden water can also occur there. In this context, which of these phenomena does the term refer to?
For the benefit of readers, it would be preferable either to cite examples of how the term has been used in previous literature or to provide a clear definition of the term.
#2
Among the parameters of the LS-IPM, the long-term landslide sediment-production rate appears to be one of the most influential. Although the manuscript states that this parameter is estimated primarily from observations of river suspended-sediment yield, its validity and underlying assumptions warrant further discussion.
In particular, sediment export from a catchment may not be adequately represented by integrating average annual sediment loads alone. In some mountain catchments, a substantial proportion of the long-term sediment budget can be generated and transported during infrequent extreme events, such as large storms or major earthquakes occurring only once every several decades. It would therefore be helpful for the authors to discuss to what extent suspended-sediment-based erosion estimates can represent long-term landslide-derived sediment production in such systems, and what implications this may have for the model results.
Furthermore, because the long-term sediment-production rate appears likely to exert a strong control on the final hazard estimates, a sensitivity analysis of this parameter would be highly valuable. Such an analysis would help quantify the robustness of the model outputs and provide readers with a better understanding of the uncertainty associated with this key assumption.
#3
The rationale for adopting a bulking factor of 1.3 is not sufficiently explained in the manuscript. Given that the bulking factor directly influences the estimated landslide sediment-production rate and, consequently, the predicted debris-flux values, it would be helpful for the authors to provide a clearer justification for this value.
In particular, is the adopted value based on a specific field study, regional dataset, or previously published research? If so, the relevant references should be explicitly cited. If the value is intended as a representative regional assumption, the associated uncertainty and its potential influence on model outputs should also be discussed.
Because the bulking factor may vary substantially depending on material type, degree of weathering, landslide mechanism, and sediment composition, a brief discussion of the applicability of a uniform value across the study area would strengthen the methodology.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC5 -
RC6: 'Comment on egusphere-2026-4888', Anonymous Referee #6, 30 Sep 2026
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The manuscript examines the "anatomy" of gravitational phenomena and environmental impacts—including the risks posed to human life—to propose a new approach to landslide risk assessment. Specifically, the authors propose a process-based methodology for assessing landslide inundation risk at a regional scale, applied to the West Coast region of New Zealand. The analysis incorporates landslide probability in relation to triggers such as rainfall or earthquakes, integrating various types of susceptibility. Given the technical-scientific nature of the topics addressed, the paper aligns with the mission of NHESS. The proposed methodology is the LS-IPM (Landslide Source-to-Inundation Process Model), a sediment-flow-based model for assessing risk across the West Coast region. Thanks to its methodology, the study could be applied in the future to other areas prone to gravitational phenomena, drawing on the diverse scientific literature cited—which covers unique scenarios from around the world. Unlike scenario-based models—which simulate discrete events and rely on scenario selection—LS-IPM imposes a constraint on the sediment production rate, thereby ensuring consistency between magnitude and frequency. The title clearly reflects the document's content. The abstract is comprehensive and provides a coherent overview of the study, which is suitable for a broad audience—not just specialists—particularly given the implications for civil protection. The overall presentation is well-structured, clear, and accessible, especially to technical experts and scientists in the field. The paper's length is appropriate and well-balanced for an international scientific context. The technical language is precise and accessible to other researchers, thanks to the use of high-quality English that is fluent, simple, and easy to read and understand—even for a broad and diverse audience. The document does not include supplementary material. Given the soundness of the arguments, the paper could be accepted without modification; however, should the authors wish to do so, they could enrich the manuscript by:
• proposing simulations of specific events and complex dynamics, such as entrainment or impact waves;
• including a paragraph highlighting the relationship between available sediment and the size and frequency of potential landslides;
• integrating a brief paragraph on the geological nature of the seismic scenarios associated with the earthquakes analyzed between 1929 and 1968;
• making the conclusions more concise, rather than argumentative in nature.Citation: https://doi.org/10.5194/egusphere-2026-4888-RC6 -
RC7: 'Comment on egusphere-2026-4888', Anonymous Referee #7, 04 Oct 2026
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The manuscript presents a process-based framework, the Landslide Source-to-Inundation Process Model (LS-IPM), for regional landslide debris inundation hazard assessment, with an application to the West Coast region of New Zealand. By coupling landslide sediment production with mass-conservative downslope debris routing, this study provides a meaningful discussion on large-scale hazard assessment. However, there are notable deficiencies in the structural organization of the manuscript and the articulation of its innovation relative to previous research. Therefore, I recommend a major revision. My specific comments are detailed below:
- Currently, the introduction is quite lengthy and is divided into five separate subsections (1.1 through 1.5), covering various sub-topics such as landslide runout modeling, regional risk assessment, and landscape evolution models. This fragmented structure disrupts the coherence of the academic background, making it difficult for the reader to quickly focus on the core scientific problem being addressed.The authors should remove the subsection headings within the Introduction and significantly condense the content. Please integrate the discussion of different modeling approaches and background concepts into a unified, continuous narrative. Using a more compact structure to directly introduce the motivation behind the LS-IPM will greatly enhance the manuscript's readability and coherence.
- Upon review, it is apparent that the majority of the core figures presented in this manuscript (including Figures 1, 2, 3, 4, 5, and 6) are cited as being reproduced from the authors' previous publication (Leith et al., 2025b). Relying so heavily on previously published figures significantly weakens the perceived originality of this manuscript as an independent study. The authors must explicitly and thoroughly clarify the differences and connections between this manuscript and the prior work (Leith et al., 2025b) in the text. Please specify what new scientific insights, dynamic mechanisms, or substantive methodological advancements the current LS-IPM framework offers. If this paper serves primarily as an application or extension of the previous method, highlight the novel geomorphological patterns discovered or the specific modeling optimizations introduced in this study.
- In Sections 4.4 and 5.4, the manuscript compares the modeled debris fluxes for the Alpine Fault scenario against reconstructed fluxes from the Murchison and Inangahua earthquakes. However, the authors explicitly acknowledge that this is not a fully independent validation, as the historical fluxes were estimated using the identical Gravitational Process Path (GPP) routing framework. To strengthen the study, the authors should provide a more robust quantitative validation of the debris runout against actual field observations or mapping data, rather than relying on a potentially circular comparison.
- The framework relies heavily on rigid deterministic assumptions, such as applying a uniform cohesive strength of 50 kPa across the region and assigning fixed probabilities for movement modes (e.g., assuming 66% avalanche and 33% flow for rainfall-induced landslides). The manuscript currently lacks a comprehensive sensitivity analysis for these inputs. The authors should evaluate how these assumptions impact the final flux maps. Furthermore, incorporating machine learning algorithms (such as Random Forest or XGBoost) to objectively calibrate these complex routing parameters and movement-mode probabilities based on regional inventories could greatly reduce the framework's reliance on subjective weighting.
- When simulating the future climate scenario (RCP6), the model adopts a highly simplified assumption that increased rainfall susceptibility is naturally sustained by a proportional increase in sediment availability, which results in a ~50% regional increase in sediment production. This linear assumption overlooks the non-linear hydrological controls that govern sediment mobilization. Integrating a physical hydrological model, such as HEC-HMS, to simulate runoff variations and transient pore-water pressure changes under future rainfall regimes would significantly enhance the physical credibility of the sediment production constraints.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC7 -
RC8: 'Comment on egusphere-2026-4888', Anonymous Referee #8, 19 Oct 2026
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Review of “A process-based framework for regional landslide debris inundation hazard assessment: application to the West Coast region of New Zealand” by Leith, Massey, Lukovic, and Wichman
Summary
In a two-part paper series Leith and coauthor(s) present a framework for landslide sediment flux-based hazard assessment. Part 1 (this manuscript) focuses on landslide source identification, landslide sediment volume calculations, and landslide sediment distribution (the hazard). Part 2 decomposes the sediment flux, enabling the calculation of risk, conducts some sensitivity studies, and compares the results with related, prior work. I reviewed both this and the companion manuscript together. The authors present the framework and then describe an application to the Weste Coast of the South Island of New Zealand. The authors are tackling an important problem that is in scope at NHESS. I appreciate that the two-part approach papers split the hazard and risk components of this problem. However, I had a number of major concerns regarding the method and its presentation. I therefore recommend that the editors return the manuscript to the authors for major revisions before considering the contribution further.
Major concerns
- Overstated significance: The authors emphasize that this approach improves over others by not needing to prescribe a set of landslide scenarios and integrate across them (e.g., L811). However, it is not clear how the approach they have selected is all that different. Rather than choose a set of landslide scenarios, they choose a magnitude frequency relation and consider landslides within each bin (bins not stated in this paper). How is that different? The relative probability of different triggers, different volume classes, and different movement modes (L448) must still be known. The contribution is certainly valuable in that it lays out how to integrate across these relative probabilities. But I think the difference between this style of approach and scenario-based ones is not as different as is claimed. I entirely agree that the contribution is valuable in that the landslide scenarios are selected in such a way that their relative probability is known. This is an important and valuable advance. But the full extent of it is not entirely justified.
A noted omission is that in many cases, the full distribution of all priors is not know (e.g., what is the prior distribution of material properties). If you don’t know the distribution of the priors, you either have to use scenario-based methods, OR you have to guess the priors. There may be cases in which carefully chosen scenario-based hazard assessments are more informative for the relevant decisions. Importantly, if one wants to fully integrate risk (as is done in part 2), then the full probability space must be quantified. The authors might frame their paper more clearly in terms of the circumstances in which fully characterizing probability is required.
- What is meant by ‘scalable’? The authors use this term extensively and it could mean many things (possible to apply over large areas, computation requirements scale with the size of the domain). Ensure use is consistent and accurate. If the authors mean computational requirements, this must be demonstrated (e.g., by describing compute times and memory used).
- As noted by other reviewers, the authors do not simulate debris-flow inundation but rather debris-flow sediment flux. The entire manuscript must be revised to refer accurately to the hazard metric used.
- What are the probabilistic volume-area scaling relationships for each volume class range and what are the volume class ranges. Nowhere in either manuscript could I find this input. This is a big problem because it reflects a key input distribution. This must be shown and justified.
- Similarly, I could not determine what the characteristic flux for each landslide volume flux was (L203) or the characteristic depth (L294). This must be stated and justified.
- In neither this paper nor the companion is the full relation between the two clearly articulated. It is briefly mentioned in each, but little more. The authors have clearly thought about why each part is separate and drawn the line between the two papers as the end of hazard and the start of risk. In the introduction the relation should be made apparent.
- The manuscript discusses content that is shown but takes substantial digging from the reader. For example, L727 describes how rainfall-induced source activity and earthquake-induced activity are spatially distinct. Yes, this is show in Figure 2, but why not make the reader’s life easier and label the different columns? I strongly recommend that the authors improve the annotation on all figures to aid the reader in understanding the methods, results and implications of this contribution rather than reproducing figures from an existing report.
- All figures lack sufficient context information (latitude longitude at a minimum). Additionally, I found it frustrating that results were only at very large (most of the South Island) or very small (vicinity of Kokiraki). Intermediate scales would be highly informative. Additionally, the perspective views have no scale bar. I know it varies in space but give some context to aid the reader. Finally, many figures have symbology that is not defined in A legend (e.g., roads in the maps). Ensure all figure elements are defined or clearly labeled in all figures
- I am concerned about how the authors link volume to runout across multiple volume classes. Integrating what is presented in the sections introducing the LSP and LSD I understand that the spatially variable rate of landslide debris production (volume per time) is decomposed into components related to each trigger, return interval and volume class (Equation 17). I was then unable to understand whether the GPP simulations were conducted on a grid cell by grid cell basis, on a volume class basis, or something else. Given the role of landslide volume in influencing runout area (e.g., Griswold and Iverson, 2014), I am concerned about grid-cell based approaches because it seems like there would be a resolution-dependence based on the combination of grid cell size and volume interval bins. Why not use a set of representative volumes at each grid cell and then decompose? This point is the most relevant to my concerns about the second part of the paired contributions. I suggest that revisions based on this comment be done consistently with part 2.
- I would expect a paper like this that introduces such a framework to illustrate some of the most important sensitivities rather than just diving into a very large application (as is done in Section 3). I understand that the motivation for the method generation (Section 2) is the application in Section 3, but some additional smaller spatial scale illustration of the method and identification of sensitivities would be appropriate between these two sections. For example, what is the sensitivity to the movement-mode weighting of Section 3.3.3? Some aspect of this is highlighted at L708 and in Figure 7, but in such an application specific way that it is very hard to understand the implications of the results.
- Given that the core contribution of this manuscript is the method, it is frustrating for a reader that there are no figures that illustrate the high-level workflow in a schematic way. Either a workflow diagram illustrating how key inputs combine to the major outputs of each of LSS, LSP, and LSD, or something similar would greatly aid in the comprehensibility of this linked framework.
- I share the concerns raised by other reviewers about the independent nature of the validation portion of the study.
Minor concerns
Ensure all acronyms are defined upon first use (e.g., APLR, L18; OOM L21).
I suggest a figure illustrating how section 2.3.2 works. Some sort of schematic illustrating the geometry and how cases in which landslides are larger or smaller than a single grid cell would be valuable.
Line-level concerns
L41. A relevant reference for this paragraph is not considered is Keeble et al., (2024).
L50. What is meant by ‘process-consistent hazard metric’?
L103. This is the incorrect reference for Landlab. The correct references are Hobley et al. (2017) and Barnhart et al. (2020)
L205. I don’t understand the characteristic event flux. Should it not be distance to source dependent?
L241. When you decompose the flux in paper part 2, how do you know the distance from the source?
L325. Where are the volume classes stated and justified. Are results sensitive to class bin breaks and widths?
L363. I would recommend an idealized figure showing how the sediment flux is partitioned into equation 17.
L532. What is the justification for a 25 m grid cell? How sensitive are the results to different grid cell sizes? Given that this grid cell size may contain many small landslides and only a portion of a large landslide, it seems to me that documenting the sensitivity and interaction between grid cell sizes and volume classes is a critical step to justify the generality of the method.
L573. I suggest a figure documenting key inputs to the West Coast application. I think illustrating the difference in the susceptibility statistical model (Section 3.1) and the landslide-volume distribution (Section 3.2.2) between the two trigger types would be highly useful to explain the difference in the results between these two trigger types .
L592. This paragraph is an example of a place where the manuscript lacks sufficient detail and illustration. What are the H/L values used for each class? For that matter, what are the volume class bins? I would expect these values easily visible in a table or figure.
L791. A discussion section on transferability would be much stronger if the authors discussed which of the required inputs must be from the application area (e.g., DEM, seismic hazard analysis) and which are potentially available anywhere (e.g., RCP projections). An analysis comparing the region-specific distributions with one that used global distributions could demonstrate the sensitivity of the method to the specificity of the input data. Such an analysis is clearly out of scope for this type of study; however, I think the discussion would be stronger with a description of how generality and transferability might be demonstrated.
References
Barnhart, K. R., Hutton, E. W. H., Tucker, G. E., Gasparini, N. M., Istanbulluoglu, E., Hobley, D. E. J., Lyons, N. J., Mouchene, M., Nudurupati, S. S., Adams, J. M., and Bandaragoda, C.: Short communication: Landlab v2.0: A software package for Earth surface dynamics, Earth Surf. Dyn., 8, 379–397, https://doi.org/10.5194/esurf-2020-12, 2020.
Griswold, J. P. and Iverson, R. M.: Mobility statistics and automated hazard mapping for debris flows and rock avalanches (ver. 1.1), US Geol. Surv. Sci. Investig. Rep., https://doi.org/10.3133/sir20075276, 2014.
Hobley, D. E. J., Adams, J. M., Nudurupati, S. S., Hutton, E. W. H., Gasparini, N. M., Istanbulluoglu, E., and Tucker, G. E.: Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics, Earth Surf. Dyn., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, 2017.
Keeble, T., Lyell, C. S., Lane, P., Nyman, P., Noske, P. J., and Sheridan, G.: A landscape scale model to predict post-fire debris flow impact zones, Geomorphology, 455, 109175, https://doi.org/10.1016/j.geomorph.2024.109175, 2024.
Citation: https://doi.org/10.5194/egusphere-2026-4888-RC8
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- 1
The topic of this manuscript falls within the core scope of NHESS, namely natural hazard processes, regional-scale hazard assessment, and landslide/debris-flow hazards under climate change and earthquake scenarios. However, the current version is closer to a “methodological framework description + preliminary application” and is not yet sufficient as an independently reproducible, validated, and critically evaluable NHESS paper. I recommend a “very major revision” before re-evaluation. My main comments are as follows: