Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding

Round 1

Reviewer 1 Report

The paper presents a way to improve the antecedent rainfall-susceptibility (AR-S) threshold approach for landslide hazard assessment through the case study of a Western branch of the East African Rift in tropical Africa.

Overall, I believe that the paper is well presented and well detailed, thus suitable for publication after minor revisions. My major suggestion is to revise the Introduction by editing the English style and adding other references, especially regarding the statistical threshold methods.

For specific comments please refer to the revised text.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The paper aims to improve an antecedent rainfall-susceptibility threshold model able to identify the rainfall triggering conditions at regional scale in an African setting. The thresholds represented an improvement of previously defined model, taking into account for a bigger and more precise input dataset, the use of satellite rainfall data, the assessment of the effects on modeling related to adopted statistical methodology of sampling of the input dataset.

Even if the paper is an improvement o fan already defined model, the research was carried on well to improve the original model and to possible application of this methodology to other study case.

Suggested reviews follow:

2 line 95: why did the authors of this research choose an antecedent period of 42 days? The Authors have to describe more in details the types of landslides present in the study area and the main predisposing factors and the triggering mechanisms of these phenomena. Moreover, it is required a better description of geomorphological attributes, geological features and soil types. What are the main sources used to create the landslides database? Which are the used satellite images? How did you perform the field surveys? Please, describe more in details. 5 lines 156-158: why did you choose a period of 36 h? Why not another one (e.g. 40, 44, 48 h)? Is there a physical reason? Please clarify this apsect Satellite-measured rainfall data could be affected by significant errors respect to the field measure carried on with traditional method, as rain gauges. I know that field data could not be easy to be obtaines, but I think it is necessary that the Authors insert a comparison between a time series of daily rainfalls measured in ground and ones measured by satellite, measuring the correspondence and the mean errors. What is the Digital Elevation Model used to create geomorphological predisposing attributes of the two susceptibility models? What are the sources of lithological and peak ground acceleration data? Within the predictors of the regional susceptibility model, there is also the parameter “two-day 15 mm rainfall accumulation threshold exceedance”. Why? It seems as a triggering factor. Clarify this aspect, also explaining why you choose different predictors between regional and continental models and the reasons why you choose these predictors. Authors stated that the weak performances of the original threshold model was related to a series of innaccuracies on the treatment of the data. Could the reason of this weak predictive capability be related to the original susceptibility model or to the antecedent rainfall parameter used? Please, discuss about it. Another source of possible innacuracy on the defined thresholds is related to the fact the landslides database is composed by different types of phenomena, whose triggering conditions are different. Please, discuss about this aspect.

Author Response

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Author Response File: Author Response.pdf