Evaluation of Moisture Level Using Precipitation Indices as a Landslide Triggering Factor—A Study of Coonoor Hill Station

Round 1

Reviewer 1 Report

The title of the manuscript is “Evaluation of moisture level using precipitation indices as a landslide triggering factor – A Study of Coonoor Hill Station”. However, the landslide problem is only mentioned, even often and regularly, as a natural hazard, which is necessary for risk assessments. Any evidences, quantitative estimates or simulation results confirming statistical relations between rainfalls and surface moisture, on one hand, and landslide characteristics, on the other hand, obtained within the study have not been presented. So far, there are no proofs issued from this research to tell that moisture serves as a landslide triggering factor. Although, there are numerous references to similar studies across the manuscript.
Thus, the suggestion is either necessary to add in the manuscript sections devote to landslide quantitative estimations and their statistical relations with rainfalls and surface moisture, or to change the title by withdrawing “...a landslide triggering factor...”

2. Abstract. In the sentence “All heavy rainfall events do not cause a landslide in the hilly region“, the link “All … do not cause” is not clear and contradictive to the manuscript content.

3. The authors use three types of assessment indices for evaluation of a moisture level. Those indices are based on the Gamma or Pearson distribution. However, numerous researches have shown that, among weather or climate variables, precipitation amount has the strongest evidence for a “heavy tail” distribution. It concerns both, the daily and season time scales. This evidence is not overwhelming when individual sites are analyzed separately, but becomes stronger when either relatively long records are available or when regional analyses are performed (e.g., assuming common shape parameter within the region). For impact variables related to the weather or climate, the evidence of “heavy tails” will be quite a bit stronger in application to the landslide triggering factor depending on extreme rainfalls and surface moisture parameters. In other words, extreme rainfalls are underestimated when the Gamma or Pearson distribution are explored.

 

References to “heavy tail distribution for precipitation”:

G.J.Babu and A.Toreti. A goodness-of-fit test for heavy tailed distributions with unknown parameters and its application to simulated precipitation extremes in the Euro-Mediterranean region. Journal of Statistical Planning and Inference. 2016

N.M.Neykov, P.N.Neytchev, and W.Zucchini.Stochastic daily precipitation model with a heavy-tailed component. Nat.Hazards Earth Syst.Sci., 2014

H.Pavlopoulos, J.Picek, J.Jurečková. HEAVY TAILED DURATIONS OF REGIONAL RAINFALL. APPLICATIONS OF MATHEMATICS. 2008

N.R.Cavanaugh, A.Gershunov, A.Panorska, and T.J.Kozubowski. The probability distribution of intense daily precipitation. Geophysical Research Letters. 2015

S.M.Papalexiou, D.Koutsoyiannis, and C.Makropoulos. How extreme is extreme? An assessment of daily rainfall distribution tails. Hydrol. Earth Syst. Sci., 2013

 

Author Response

The title of the manuscript is “Evaluation of moisture level using precipitation indices as a landslide triggering factor – A Study of Coonoor Hill Station”. However, the landslide problem is only mentioned, even often and regularly, as a natural hazard, which is necessary for risk assessments. Any evidences, quantitative estimates or simulation results confirming statistical relations between rainfalls and surface moisture, on one hand, and landslide characteristics, on the other hand, obtained within the study have not been presented. So far, there are no proofs issued from this research to tell that moisture serves as a landslide triggering factor. Although, there are numerous references to similar studies across the manuscript.
Thus, the suggestion is either necessary to add in the manuscript sections devote to landslide quantitative estimations and their statistical relations with rainfalls and surface moisture, or to change the title by withdrawing “...a landslide triggering factor...”

Reply: We accept the view of the reviewer. But, there is no study that utilizes directly moisture indices (SPI, CZ, Z-score- proposed for assessment of dry and wetness of the region) as a quantitative measure to address as landslide triggering factor. Hence a few selected literature have been considered in the introduction part.

2. Abstract. In the sentence “All heavy rainfall events do not cause a landslide in the hilly region“, the link “All … do not cause” is not clear and contradictive to the manuscript content.

Reply: Accepted. The sentence is modified as follows:

Extreme heavy rainfall events in the hilly region pose a great threat to public safety and cause dangerous landslide in the region.

The authors use three types of assessment indices for evaluation of a moisture level. Those indices are based on the Gamma or Pearson distribution. However, numerous researches have shown that, among weather or climate variables, precipitation amount has the strongest evidence for a “heavy tail” distribution. It concerns both, the daily and season time scales. This evidence is not overwhelming when individual sites are analyzed separately, but becomes stronger when either relatively long records are available or when regional analyses are performed (e.g., assuming common shape parameter within the region). For impact variables related to the weather or climate, the evidence of “heavy tails” will be quite a bit stronger in application to the landslide triggering factor depending on extreme rainfalls and surface moisture parameters. In other words, extreme rainfalls are underestimated when the Gamma or Pearson distribution are explored.

Reply: Authors accept views and observations of the researchers. The present study aimed to utilize SPI, CZ, and Z-score index to assess the moisture conditions and how best these three indices provide a quantitative assessment as a landslide triggering factor. These indices normalize the rainfall data predicted using respective distributions and the impact of the extremeness of rainfall is well taken. Certainly, investigations using other distributions (as suggested by the reviewers and also in the listed references) in the standardization of precipitation will obviously reveal how best these indices estimate the level of moisture.    

Reviewer 2 Report

The study is interesting. I recommend to publish after revision.

some minor comments.

Improve figure 1. What’s the boundary of the map denotes? Produce a good map.

Equation number should be associated with brackets.

How is the missing rate of original data and how the missing data is interpolated? 

double check language and styles.

Author Response

The study is interesting. I recommend to publish after revision.

Reply: Thank you for the recommendation of the manuscript to publish.

some minor comments.

Comment: Improve figure 1. What’s the boundary of the map denotes? Produce a good map.

Reply: Accepted and modified in the revised manuscript.

Comment: Equation number should be associated with brackets.

Reply: Accepted and modified in the revised manuscript.

How is the missing rate of original data and how the missing data is interpolated? 

Reply: There is no missing data problem for the present case study.

Comment: Double check language and styles.

Reply: Proofreading has been done again in light of the above comments.

Reviewer 3 Report

I write in regards to Manuscript entitled "Evaluation of moisture level using precipitation indices as a landslide triggering factor – A Study of Coonoor Hill Station" which you submitted to Climate. I have read this paper that deals with the evaluation of relationship between extreme rainfall and landslide by considering three moisture level assessment indices. In my opinion the paper is well organized and the results shown are valid, and I suggest accepting this manuscript as it is.

Author Response

I write in regards to Manuscript entitled "Evaluation of moisture level using precipitation indices as a landslide triggering factor – A Study of Coonoor Hill Station" which you submitted to Climate. I have read this paper that deals with the evaluation of relationship between extreme rainfall and landslide by considering three moisture level assessment indices. In my opinion the paper is well organized and the results shown are valid, and I suggest accepting this manuscript as it is.

 

Reply: Thank you for the recommendation of the manuscript to publish.

Round 2

Reviewer 1 Report

I have read the revised manuscript and the author's replies. Although, the answers to major comments, which concern the title and the application of standard statistic indices to the precipitation distributions, sound rather formal, I think the manuscript can be accepted for publication. I hope, the reviewer's suggestions will encourage the authors for farther investigations with using other distribution types, as they write in their reply.