Dear Authors,
This paper explores landslide risk assessment and management using a multi-scenario tree-based approach. Most applied MLAs are not new but have been used before in several published studies. The subject is interesting. I want to encourage consider the more detailed comments below as major revisions and to improve the manuscript before publication in Geological Journal.
These are my main points of criticism, but on top of this, I find many other aspects of this paper problematic:
Abstract
1- Abstract section is so general and does not have a scientific structure as a research paper.
2- The obtained result has not been appropriately shown, and the authors should mention the obtained results of applied methods, not general notes, in the abstract section.
Introduction
In the first paragraph, the authors did not mention any references or statistics about landslides in the current study area and the rate of damages or losses of lives by this natural hazard.
The research background about the proposed subject and methods has not been appropriately mentioned, mainly applying approaches widely used in landslide susceptibility mapping in previous studies. Please update it with new references such as:
- https://doi.org/10.3390/s22041573
- https://doi.org/10.3390/land12061151
- https://doi.org/10.3389/fenvs.2022.1009433
Also, why did you not explain the novelty of the research adequately? Suppose authors utilized MLAs implemented and assessed for landslide assessment. Why did they not bring significant scientific resources in relation to the suggested models? Suppose the authors claim that the proposed methods are a new contribution to this research. In that case, they must bring defendable documents such as published scientific papers for their claim, clear it properly, and not bring the general notes found in any previously published papers.
The main goal of the paper should be better explained. It is not clearly stated. The goal should clearly and concisely explain the main scientific contributions of this work.

2.1 Description of the study area
I did not see any description of the occurred landslides in the study area. Why do you choose this area for study? This section is a problem statement, and you should bring a logical reason for starting this research.
2.2 Landslide inventory mapping
How do you select non-landslide locations?
Why did the authors not mention the source of different applied factors for the modeling process? It is essential to mention all of them in a separate table with resolution/scale and GIS data type.
Figure 5: It is better to add landslide points on all factors and susceptibility maps. Also, fuzzy classification is not acceptable for conditioning factors. It is better to use different classification methods such as natural breaks, Quantile, etc.
2.5 Machine learning algorithms for landslide susceptibility modeling
It is better to add applied equations for applied machine learning models by mathematical attitude for this section.

3 Results and discussion
It is noted that a critical analysis of results has not been reported in the paper. The result section is so poor in writing and obtaining results. Also, the written results are not homogeneous due to no logical relationship between applied methods results.
I also did not validate of applied methods. The authors mentioned that one of the validation methods is the ROC curve but I did not see it in the current study.

Figures 6 to 10: It is better to add landslide points on all extracted landslide susceptibility maps.

Dear Authors,
I believe, that in its present form, your article is appropriate to publish in the Geological Journal and will be interesting for the readers.