| 27 Jan 2026
Integrating multidimensional factors through Bayesian Belief Networks for landslide and debris-flow risk reduction in subtropical zones
Abstract. Current forecasting models for landslides and debris flows mostly look at environmental or socio-economic factors on their own. They rarely combine both into a single probabilistic framework that might give warning in complicated and uncertain situations. This constraint is especially clear in Vietnam, where intense subtropical rain, steep and extensively dissected mountainous terrain, and quick changes in land use and infrastructure are the main causes of landslides and debris flows. This research introduces a novel approach using a Bayesian Belief Network (BBN) to enhance landslide-risk prediction through the integrated analysis of environmental and socioeconomic data. The developed BBN model incorporates inputs from diverse sources, including Geographic Information Systems (GIS), remote sensing, and field survey observations. Structural Equation Modeling was employed to align the BBN with established relationships between landslides and influencing factors. The analysis explored different scenarios by combining rainfall intensity with land-use patterns and assessing the protective role of embankments. Results indicate that precipitation exceeding 130 mm over a period longer than three days markedly increases the likelihood of landslides and debris flows, particularly in agricultural regions. Gabion embankments were found to be highly effective in mitigating risks to both human safety and built environments.
Dear Authors,
I have carefully read your manuscript "Integrating multidimensional factors through Bayesian Belief Networks for landslide and debris-flow risk reduction in subtropical zones". Unfortunately, I have identified several critical issues and shortcomings throughout the manuscript that, in my opinion, make it unsuitable for publication in its current form.
A major concern relates to discrepancies and confusion in the terminology. Based on widely accepted classification schemes, debris flows are a type of landslide. However, the manuscript differentiates two types of phenomena: landslides and debris flows. What do the Authors refer to when using the term landslides? Besides debris flows, what types of landslides does this manuscript address? I think this choice/description should be included in the Introduction or in another section.
A further significant issue is related to the term risk, which appears to be both overused and, in several instances, misapplied. According to Varnes et al. (1984), landslide risk is the expected number of lives lost, persons injured, damage to properties and disruption of economic activity due to a particular phenomenon (in this case, landslides) for a given area and time period. That said, I have found that Authors often use risk as a synonym for the likelihood of landslides. Notably, this probability represents hazard, which is only one component of risk (as correctly illustrated in Figure 4). I strongly suggest the Authors to carefully revise the terminology as they are presenting a research paper.
Another shortcoming lies in how the manuscript describes the novelty and the results. In all fairness, I consider the purpose of boiling down the risk assessment into a single statistical model quite interesting. However, by reading the paper, I had the impression that this objective has not been fully achieved. Specifically, this lack is largely due to terminological inconsistencies and insufficient clarity in both the methodological description and the presentation of results. For instance, if the study aims to produce a landslide risk analysis, why is the well-established risk equation never mentioned in the text? This omission is particularly "strange" as Figure 4 clearly displays risk as the main objective. Furthermore, it remains unclear whether vulnerability and exposure were actually assessed. How were they assessed? The manuscript lacks a description of this part. Both vulnerability and exposure should be analysed differently depending on the type of element at risk.
The outcomes are also not sufficiently supported. As currently presented, the results may appear somewhat predictable. For example (line 373-374): " the higher the perceived rainfall and property risks, the higher the perceived landslide risk" or (line 387) "that weather conditions are an important factor in risk assessment and mitigation". These statements describe relationships that are largely expected. Expanding the supporting analysis would make their contribution clearer.
Ultimately, there is significant confusion regarding the form and scale of the results. Given the landslide context, I would have expected a cartographic translation of the outcomes displaying the spatial distribution of hazard/risk across the study area. CInstead, the results are roughly presented as tables or diagrams. This form limits their interpretability.
For the above reasons, I regret to say that I suggest rejection in its current form. Below, I provide further comments that I hope will help Authors improve the overall quality of their work. Good luck!