the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Nov 2025
Tsunami-Sediment Interactions Amplify Coastal Hazard and Reshape Inundation Dynamics in Tumaco Bay, Colombia
Abstract. Tumaco, situated on the Colombian Pacific coast, is particularly vulnerable due to its location within the Pacific Ring of Fire. Although studies on tsunami risk in the region have been conducted, the interaction between these events and sediment transport has been little explored, despite its impact on flooding dynamics. This study addresses this gap by comparing two scenarios – those with and without sediment transport – and evaluating the morphodynamic effects of tsunami events on proposed mitigation measures for Tumaco. The results show that including sediment transport in the simulations increases wave heights, flooding depth and extent, as well as coastal impacts. In particular, maximum flood depths increase by 24.4 % on Morro Island, 11.57 % on Tumaco Island, and 30.91 % on the mainland. Likewise, flooded areas increase by 4.12 %, 5.15 %, and 13.43 %, respectively, due to increases in flow density and momentum. The mitigation measures reduce the extent of flooding, although they cause local increases in wave heights due to reflection effects. It is noteworthy that in the simulations with mitigation measures, sediment transport does not cause erosion that compromises these coastal defenses. These findings underscore the importance of incorporating sediment transport into tsunami modeling to enhance hazard assessments and refine mitigation strategies, ultimately contributing to the development of more effective coastal resilience plans.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-4986', Anonymous Referee #1, 09 Dec 2025
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AC1: 'Reply on RC1', Erick Mas, 09 Mar 2026
Firstly, we sincerely appreciate the time taken to read our manuscript in detail and the depth of your comments. We consider your observations valuable and contribute significantly to strengthening scientific quality. Below are our responses to the observations made:
Response 1 (physical behaviors of the phenomena analyzed—tsunamis and sediment transport)
We agree with the reviewer that sediment transport implies that a fraction of the flow energy is used to erode, mobilize, and maintain the material in suspension, so there is no increase in the initial energy of the tsunami, whose source remains unchanged. However, several studies (e.g., Xiao et al., 2010; Cao & Roberts, 2014) have shown that the incorporation of sediments simultaneously modifies the effective mass of the flow, its density, depth, and turbulence structure, with direct implications for the timing and dynamics of flooding.
Within this framework, although the total energy of the system is conserved, its spatial and temporal distribution can vary significantly. Sediment acts as a mediator, redistributing the energy of the flow and concentrating it locally through increases in effective depth, while in other sectors it is dissipated through internal friction and processes associated with solid transport.
In particular, a sediment-laden flow can have greater depths and a greater mass per unit area, even when velocities decrease due to increased internal friction and dissipative processes associated with solid transport. Since the momentum of the flow depends on the product of mass and velocity, an increase in effective mass can compensate for, or even exceed, the reduction in velocity, resulting in momentum values comparable to or greater than those observed under clear-water conditions. However, as the reviewer points out, it is also possible that a significant portion of the flow energy is devoted to transporting the sediment, thereby reducing the mechanical energy available for the flow itself.
In the absence of direct evidence to characterize the system's internal behavior during the flood, it was decided to eliminate the interpretation that a possible increase in flow momentum was present. Instead, the analysis focuses on the fact that the variations observed in the threat level are mainly due to morphological changes induced by sediment transport, which have been widely documented and validated in previous studies (Tehranirad et al., 2015; Apotsos et al., 2011; Yamashita et al., 2016; Masaya et al., 2020).
This approach is based on the fact that mobile sediment can induce bathymetric and topographic changes during flooding, thereby modifying the propagation characteristics of the tsunami. Tehranirad et al. (2015) explicitly demonstrated that morphological adjustments induced during flooding can increase run-up and inland flood extent, compared to simulations that assume fixed bathymetry and topography. This study shows that localized erosion in shallow areas and natural barriers can reduce effective dissipation and facilitate greater inland flow transmission.
Consistent results have been reported by Apotsos et al. (2011) and Yamashita et al. (2016), who show that sediment transport induced by breaking waves generates feedback between flow and morphology that affects the propagation and attenuation of energy on a wave-by-wave scale. In this sense, the increase in run-up and inundation observed in our simulations is interpreted as the combined result of: (i) morphological adjustments during inundation, (ii) modifications in the mass and effective depth of the flow, and (iii) changes in the turbulence structure induced by the presence of sediments, rather than as a net increase in the initial energy of the tsunami.
Finally, we recognize that sediment properties, particularly grain size and distribution, play a decisive role in the magnitude of these processes by controlling bottom mobility, the fraction of suspended sediment, and the intensity of fluid-solid interactions. Our simulations represent a conservative scenario of highly mobile sediments, corresponding to non-cohesive sediments characterized in the study area as fine sands with a D50 of approximately 140 µm. This type of sediment has a loose, granular structure, with no cohesive forces between particles, which favors rapid response to flow and high efficiency in transport (van Rijn, 1993). Variations in sediment properties, such as cohesiveness, spatial distributions of grain size, or high concentrations of suspended sediment associated with river inputs with different sedimentary characteristics, could modify the system's response (Röbke et al., 2018), without invalidating the underlying physical mechanisms discussed here.
Therefore, and in response to the reviewer's observation, we have revised the manuscript's wording, replacing terms such as "amplifies" or "intensifies" with "modulates" to more accurately reflect the role of sediment transport in tsunami hydrodynamics. In this context, the results are presented emphasizing that sediment transport modulates the hydrodynamic response of the tsunami upon its arrival at the coast and that, in the particular case of Tumaco Bay and Islands, this modulation manifests itself as an increase in the main threat metrics analyzed: tsunami height and flood extent (height and area). These parameters are used in Colombia to assess the tsunami threat and estimate the risk to coastal populations.
On the other hand, regarding the agreement between the results presented in Table 3 and those represented in the tide gauge (Fig. 6), it should be noted that the values recorded in the table correspond to the maximum height reached in the continental sector of each zone, without discounting the topographic elevation of the terrain. In contrast, the tide gauge represents the temporal variation of sea level at specific observation points. In this sense, the maximum differences reported in the table may not be directly reflected in the tide gauges, since the latter are strongly conditioned by the specific location of each gauge, where, for the locations considered, spatial variations are usually smaller.
This is corroborated by Figure 5, which shows the differences between simulations with and without sediment transport. This figure shows that, at the locations of the analyzed points, the differences are less pronounced than those observed in other sectors of the study area.
For this reason, and to avoid possible confusion in interpreting the results, it was decided to omit this parameter from the table and focus the comparative analysis on the changes associated with flood depth. Likewise, to analyze wave height behavior in sectors with more pronounced spatial differences, an additional analysis point was incorporated where such differences are evident.
Regarding constructive interference, various studies on the propagation of tsunamis and long waves have shown that the reflection of the incident wave against the coastline or rigid structures generates reflected waves that, when superimposed on the incoming waves, can produce local amplifications of the free surface. This phenomenon can lead to localized increases in wave height and sea level near the coast (Mei et al., 2005; Rabinovich, 2009). Consistent with this behavior, it was decided to incorporate a complementary animation (as supplementary material) that visualizes the process, showing how the incident wave undergoes amplification when interacting with mitigation works, due to wave superposition.
Response 2: (constant thickness) Is the sediment thickness uniform throughout the domain? If not, how is it distributed? If so, what evidence supports this statement?
Yes, since no direct information is available on the initial sediment thickness in the study area, a uniform thickness was assumed in the simulations. This value was not arbitrary but was determined through a sensitivity analysis, in which the model's response to different initial thicknesses was evaluated, specifically their effect on cumulative sediment deposition (CSD).
The procedure adopted follows a methodological approach similar to that used in previous studies, such as that of Velasco et al. (2024; https://www.nature.com/articles/s43247-024-01643-w), who implemented a comparable analysis to define a representative sediment thickness in the absence of direct measurements, thereby adequately capturing the expected variability in depositional processes. Including this reference in the manuscript allows us to contextualize and support the methodology used.
We also recognize that the assumption of uniform thickness is a limitation of the study, which should be addressed in future research by incorporating more detailed field information, such as sedimentological profiles, surveys, or shallow geophysical data, to more realistically represent the spatial heterogeneity of the sediments.
Response 3: (high tide) The use of high tide can, in fact, change exposure, but from a sediment point of view, shallower flows can have much higher velocities and, therefore, greater sediment transport capacity. Any comments on this?
Although shallower flows can reach higher velocities and, consequently, have greater sediment transport capacity, this study focuses on assessing the tsunami threat, quantified mainly in terms of flooding and wave height, in accordance with the warning protocols established by the Colombian Maritime Directorate (DIMAR). This consideration was key to simulating high-tide conditions to represent an extreme or "worst-case" scenario from the flood-threat perspective and to analyze how sediment transport modulates this threat.
Although higher speeds may occur in specific areas during low tide, the tsunami's reach over populated areas, the main focus of this study, is generally less than under high-tide conditions. Additionally, during low tide, greater interaction between the tsunami and bed friction can increase energy dissipation before it reaches the coast.
Under this approach, the aim is to assess the maximum possible exposure of the study area, providing a conservative estimate of the impact of flow and sediment availability, which is relevant for threat assessment and coastal planning.
Response 4: (sensitivity analysis) The authors mention "sensitivity analysis" (section 3.3), but only one simulation per case is shown. How is this sensitivity analysis actually carried out?
In relation to the sensitivity analysis described in Section 3.3, a total of 10 complementary simulations were performed to systematically evaluate the uncertainty associated with the sedimentary parameters.
First, five simulations were developed in which the grain size was varied while keeping the sediment thickness constant. This set of tests enabled analysis of the specific effect of grain-size variability on sediment transport processes and flow propagation, isolating this effect from other variables.
Complementarily, five additional simulations were carried out varying the sediment thickness, while keeping the grain size constant at 140 μm. These simulations allowed the sensitivity of the results to be evaluated with respect to the availability of sediment in the domain and to establish a range of uncertainty associated with this parameter.
The results obtained were integrated using an envelope distribution, such that the simulation presented in the manuscript corresponds to a representative reference case within the defined uncertainty range, with a thickness of 4 m and a grain size of 140 μm.
Answer 5: The Manning friction coefficient is quite low. Why? The usual practice places it at 0.025, which is already a low value.
This was an editing error: the Manning value used in all simulations was 0.025, which, as you mention, corresponds to the usual value reported in the literature (Kotani et al., 1998).
Answer 6: How is the Pearson coefficient calculated?
The Pearson correlation coefficient was calculated in MATLAB using the corrcoef function, which quantifies the linear relationship between two variables.
Answer 7: It is not really a validation, but rather a comparison. More importantly, for sediment transport, velocities are more relevant than flow depths. How do these compare?
Regarding the observation on validation, we agree that what is presented is not strict validation but rather cross-validation between models, given that we do not have in situ records for the 1906 and 1979 tsunamis. For this reason, it was decided to compare with the TUNAMI-N2 model, which has been widely validated in tsunami studies and used in various publications for the same study area.
Answer 8: Where was the LIST measurement taken? Is it representative?
On the other hand, regarding the LIST measurement, data were collected at three points distributed along the bay, and it was observed that all measurements exhibited very similar grain-size distributions. For this reason, it was decided to use a single representative distribution in order to simplify the presentation. It should be noted that detailed sedimentary facies data are not available for the area, so this approximation is considered adequate for the purposes of the study.
Response 9 (Figures)
All figures were reviewed and substantially improved in terms of graphic quality and readability. The resolution, size, and clarity of the axes were optimized. In addition, the scales between comparable figures were standardized, ensuring visual consistency.
We consider the terrain overlap important, as it allows us to identify, visualize, and locate the areas with the highest threat levels within the study area, facilitating the spatial interpretation of the results and their relationship to local terrain conditions.
Likewise, the observation points are already shown in Figure 1 and Table 2.
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AC1: 'Reply on RC1', Erick Mas, 09 Mar 2026
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RC2: 'Comment on egusphere-2025-4986', Anonymous Referee #2, 19 Jan 2026
This study investigated the effect of sediment transport for tsunami modelling using Delft 3D. The reviewer's comments are as follows.
- First, the validation of your sediment transport simulation should be shown by comparing your simulation results and the observed thickness of erosion and sedimentation in your study area. After this, explain how sediment transport affects tsunami propagation and inundation.
-Enhance the quality of all figures. The font and size should be consistent across all figures. In some figures, the font size is too small. Interpreting simulation results is not easy.
-Fig 1: Increase the characters of lat and long.
-Fig 2: Where is this? Add lat and long. Moreover, add the exact location of this figure in Fig. 1. It is better if there is a cross-sectional topography in your study area to show the dune shape and the details of the topography.
-Line74-75: Explain the details of the altimetric and bathymetric information provided by the Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (CCCP). What is the resolution of this dataset, and how is this data measured?
-Line 97: Add the unit of Manning Coefficient.
-Did the authors include density stratification for the modelling? This will have a significant impact on the final distribution of erosion and sedimentation.
-What is the measured grain size in your study area? Based on this value, determine the settings for your simulation. This should be explained in the Study area section.
-Fig. 6. Characters are too small. It is not easy to interpret these results.
-Fig. 9, 10, 11. Characters are too small……
Citation: https://doi.org/10.5194/egusphere-2025-4986-RC2 -
AC2: 'Reply on RC2', Erick Mas, 09 Mar 2026
- First, the validation of your sediment transport simulation should be shown by comparing your simulation results and the observed thickness of erosion and sedimentation in your study area. After this, explain how sediment transport affects tsunami propagation and inundation.
Response
The scenario analyzed in this study corresponds to a worst-case event used by the Colombian EWS for hazard assessment, not to reproducing a specific historical tsunami. Consequently, there are no observational data on erosion and sedimentation thicknesses in the study area to directly validate the sediment transport model.
The scenario considered was developed following methodologies widely used in tsunami hazard studies, which prioritize the representation of conservative conditions to assess maximum potential impacts. In this context, the validation of the sediment transport component is based on the physical consistency of the model, its hydrodynamic-morphodynamic formulation and morphodynamic formulation, and its ability to reproduce mechanisms documented in the literature, such as erosion in shallow areas, sediment redistribution during flooding, and its effect on tsunami propagation and extension (e.g., Apotsos et al., 2011; Tehranirad et al., 2015; Sugawara et al., 2014).
Under this approach, the analysis focuses on evaluating how sediment transport modulates tsunami propagation and inundation, rather than on reproducing observed patterns exactly. The results show that morphological changes induced during flooding can locally alter the effective depth and energy dissipation, resulting in variations in tsunami height and flood extent, without implying an increase in the event's initial energy.
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-Enhance the quality of all figures. The font and size should be consistent across all figures. In some figures, the font size is too small. Interpreting simulation results is not easy.
Response
All figures were modified in accordance with the recommendation.
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-Fig 1: Increase the characters of lat and long.
Response
The figure was modified according to the recommendation.
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-Fig 2: Where is this? Add lat and long. Moreover, add the exact location of this figure in Fig. 1. It is better if there is a cross-sectional topography in your study area to show the dune shape and the details of the topography.
Response
Figure 2 was incorporated into Figure 1, where its location is now indicated by latitude and longitude coordinates. Specifically, this information is presented in Figure 1c.
Likewise, Figure 1c shows the topography and bathymetry of the study area, including the terrain relief and the works associated with the implemented mitigation measures. This update enables spatial contextualization of the analyzed area and more detailed visualization of the relevant topographic characteristics.
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-Line74-75: Explain the details of the altimetric and bathymetric information provided by the Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (CCCP). What is the resolution of this dataset, and how is this data measured?
Response
The description of the resolution and measurement method for the topographic and bathymetric information was incorporated into the document. This is presented in section 3.2.
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-Line 97: Add the unit of Manning Coefficient.
Response
The unit has been added to the document.
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-Did the authors include density stratification for the modeling? This will have a significant impact on the final distribution of erosion and sedimentation.
Response
No. A uniform sediment thickness was assumed in the modeling because no direct information is available on the initial sediment thickness in the study area. Consequently, a uniform thickness was used in all simulations.
This value was not arbitrary, but was determined from a sensitivity analysis described in Section 3.3.
We recognize that the assumption of uniform thickness is a limitation of the study, particularly in the spatial representation of erosion and sedimentation processes. This limitation should be addressed in future research by incorporating more detailed field information.
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-What is the measured grain size in your study area? Based on this value, determine the settings for your simulation. This should be explained in the Study area section.
Response
The grain size was determined from measurements made with the LIST by acquiring data at three points distributed along the bay, considering the vertical column. The results showed that all measurements had very similar grain size distributions, so it was decided to use a single representative distribution, which is presented in Figure 5a.
Based on the measured grain sizes, a sensitivity analysis (described in Section 3.3) was carried out in which five simulations with different grain sizes were evaluated in order to select the most representative value to be used in the model, which was 140 μm, and to estimate the level of uncertainty associated with this parameterization.
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-Fig. 6. Characters are too small. It is not easy to interpret these results.
Response
The figure was modified according to the recommendation.
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-Fig. 9, 10, 11. Characters are too small……
Response
The figures were modified in accordance with the recommendation.
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References for Reviewer#1 and Reviewer#2 responses
Apotsos, A., Gelfenbaum, G., & Jaffe, B. (2011). Process-based modeling of tsunami inundation and sediment transport. Journal of Geophysical Research: Earth Surface, 116(F1). https://doi.org/10.1029/2010JF001797
Cao, M., & Roberts, A. J. (2014). Modelling suspended sediment in environmental turbulent fluids. Environmental Fluid Mechanics, 14, 213–235. https://doi.org/10.1007/s10652-013-9312-2
Masaya, R., Suppasri, A., Yamashita, K., Imamura, F., Gouramanis, C., & Leelawat, N. (2020). Investigating beach erosion related with tsunami sediment transport at Phra Thong Island, Thailand, caused by the 2004 Indian Ocean tsunami. Natural Hazards and Earth System Sciences, 20, 2823–2841. https://doi.org/10.5194/nhess-20-2823-2020
Mei, C. C., Stiassnie, M., & Yue, D. K. P. (2005). Theory and applications of ocean surface waves: Part 1—Linear aspects. World Scientific.
Rabinovich, A. B. (2009). Seiches and harbor oscillations. In E. N. Pelinovsky & A. A. Kurkin (Eds.), Handbook of coastal and ocean engineering (pp. 193–236). World Scientific.
Röbke, B. R., Vafeidis, A. T., Hinkel, J., & Pelling, M. (2018). Future flood hazards in coastal zones: A global assessment. Natural Hazards and Earth System Sciences, 18, 271–285. https://doi.org/10.5194/nhess-18-271-2018
Sugawara, D., Goto, K., & Jaffe, B. E. (2014). Numerical models of tsunami sediment transport: Current understanding and future directions. Marine Geology, 352, 295–320. https://doi.org/10.1016/j.margeo.2014.02.002
Tehranirad, B., Kirby, J. T., Grilli, S. T., & Shi, F. (2015). Does morphological adjustment during tsunami inundation increase levels of hazards? In Proceedings of the Coastal Structures and Solutions to Coastal Disasters Joint Conference 2015: Tsunamis (pp. 145–153). American Society of Civil Engineers. https://doi.org/10.1061/9780784480311.015
van Rijn, L. C. (1993). Principles of sediment transport in rivers, estuaries and coastal seas. Aqua Publications.
Velasco-Reyes, E. R., Sugawara, D., & Adriano, B. (2024). Tracing the sources of paleotsunamis using Bayesian frameworks. Communications Earth & Environment, 5, 478. https://doi.org/10.1038/s43247-024-01643-w
Xiao, H., Young, Y. L., & Prévost, J.-H. (2010). Hydro- and morpho-dynamic modeling of breaking solitary waves over a fine sand beach. Part II: Numerical simulation. Marine Geology, 269(3–4), 149–165. https://doi.org/10.1016/j.margeo.2009.12.008
Yamashita, K., Sugawara, D., Takahashi, T., & Imamura, F. (2016). Numerical simulations of large-scale sediment transport caused by the 2011 Tohoku earthquake tsunami in Hirota Bay, southern Sanriku coast. Coastal Engineering Journal, 58(4), 1640015. https://doi.org/10.1142/S0578563416400155
Citation: https://doi.org/10.5194/egusphere-2025-4986-AC2
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AC2: 'Reply on RC2', Erick Mas, 09 Mar 2026
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Ronald E. Sanchez Escobar
Juan Jose Ferrer
Erick R. Velasco-Reyes
This study shows how tsunamis interacting with coastal sediments intensify flooding risks in Tumaco Bay, Colombia. Using computer simulations, we found that including sediment transport raises water levels, flood depths, and affected areas, while proposed defenses reduce flooding but also reflect waves. These insights underscore the importance of incorporating sediment into tsunami models to design more robust protection and enhance coastal resilience.
This study shows how tsunamis interacting with coastal sediments intensify flooding risks in...
In the reviewed article, Sanchez-Escobar and collaborators present a numerical exercise aimed to assess the possible effect on tsunami intensity metrics, as a result of a)including sediment transport on the modeling, b) by assessing the impact of proposed mitigation strategies. I note these can be treated as independent goals, yet there are somewhat mixed in the article.
The results are a bit counterintuitive, especially for the sediment transport results, where noticeable changes are reported in the text. I note that following the text is extremely difficult, because in general the quality of the figures is very, very poor (more on this regard below), hence the reader can not follow the argumentation. For example, a change of the maximum wave height from 5.0 m to 6.6 is reported (a 30% increase!) but the reader does not know whether this is colocated. In contrast, Fig. 7 shows minimal changes, of less than 5%. How are these two reconciled?
The main problem with the article, is that the justification for this results is very superficial. The authors resort to arguments by Apotsos et al., 2011, and Yamashita et al., 2016. However, I still find these results counterintuitive because even though the argument of the flow carrying more mass and momentum due to the sediment (in suspension??) might be true, but one can think of this process as the flow doing work to transport the sediment. Hence, less mechanical energy is available for the flow itself. The initial energy of the flow remains the same, as the source is unchanged, hence I find the argumentation somewhat unsubstantiated. Is it possible that that movable sediment causes bathymetric changes (eg, fig 12) which in turn change propagation characteristics (something that Yamashita et al. suggest when they analyze the effects of sediment transport on a wave by wave fashion) ? I think the presentation is too light to learn more from this.
Similarly for the goal of assessing the effect of the mitigation projects. One has to take to face value the argumentation that the flow is reoriented in such a way that reflection and constructive interference are the main drivers of the change. The figures do not provide compelling evidence on this regard.
As it stands, I do not think that this is going beyond a case study, but it has certainly picked my curiosity.
Some questions I think would need to be answered in the text:
- is sediment conserved (e.g. Fig 12 adds up to zero) ? Does not look like it but then the colorscale is hard to read.
-is the sediment thickness uniform over the domain? if not, how is it distributed? If yes, what kind of evidence does support this claim?
-using high tide indeed may change exposure, but from the sediment standpoint, shallower flows can have much larger velocities hence more sediment transport capacity. Comments?
-the authors mention “sensitivity analyses” (section 3.3) but only a single simulation is shownper case. How is this sensitivity carried on?
-the Manning friction coefficient is rather low. Why? Usual practice has it at 0.025, which is also a low value.
Figures:
All figures are very poor and very hard to read.
Axes are usually intelligible.
Colorscales change across figures. For example Fig 1 outer figure and inset, with Fig 2.
Many figures are overlain the terrain, with makes them very hard to read. I suggest removing it completely as it adds no value.
Colorscales for difference are non symmetrical and eventhough are divergent, the zero is set to a yellowish color that makes it confusing. Use Python's “seismic” or similar colorscale for differences.
Locations mentioned in the text are not clearly described in the Figures. Places such as Bajito, Morro or others are not included in the Figures, except in the last one! (and here is hard to know where they are, exactly.)
The only Figure with some naming in it early in the text, is Fig 2, which has no axis. Trying to place the Evaluation points of Table 2 is not possible.
Figures are usually presented on a 3 column by 1 row format, with a lot of space to the sides. This makes it very hard to read (Figs 6,8,9, 11, etc). In contrast, Figures with time series are gigantic in comparison.
Points of interest of Table 4 have no correlation with figures.
Fig 1, Does not show clearly the coastline awhile also having a large portion of land that is absolutely irrelevant. The inset is very small.
Fig 1 and 2 can be merged.
Fig 3 and 4 can be merged. By the way, where was the LIST measurement taken? Is it representative?
Figure 3 and 7. I have no idea where are these gages located in the map. It says “near” Morro and Tumaco Islands...that can be anywhere!
Other technical comments:
+”Validation” against TUNAMI.:
--Not really a validation, but a comparison. However, more important than flow depths are velocities, especially for sediment transport. How do they compare?
--How is the Pearson coefficient computed?
--Lesser and Van Rijn references are more pertinent to gravity waves as source of transport. How do the model equations compare with those of , say, Yamashita et al. (op.cit.)
+ I would suggest to use flow depth, coastal amplitudes (peak) and more standardized terms for the Tsunami Intensity Metrics. As a community we have been very lax in terminology and we should be more cautious.
In summary, an interesting numerical experiment with flavor of just a case study, that needs stronger support for some of its claims. At the minimum, improving figures and text, but I would also recommend more physics!