Spatio-temporal analysis of the role of climate cycles on landslide activity: the case of Majorca (Spain)
- 1Geological and Mining Institute of Spain from the National Research Council (IGME_CSIC), Urb Alcázar del Genil, edf Zulema 4 bajo, 18006 Granada, Spain
- 2Geological and Mining Institute of Spain from the National Research Council (IGME_CSIC), Ríos Rosas 23, 28003 Madrid, Spain
- 1Geological and Mining Institute of Spain from the National Research Council (IGME_CSIC), Urb Alcázar del Genil, edf Zulema 4 bajo, 18006 Granada, Spain
- 2Geological and Mining Institute of Spain from the National Research Council (IGME_CSIC), Ríos Rosas 23, 28003 Madrid, Spain
Abstract. Intense precipitation is one of the main drivers of landslides around the globe. On a global scale, the occurrence of very wet periods is controlled by different, well-known natural cycles: ENSO, NAO, SUNSPOT, etc. In this paper, we present a spatio-temporal analysis of climate cycles on the island of Majorca (Spain) and their correlation with the landslide inventory. Firstly, using spectral analysis techniques, the main climatic cycles that control the rainy periods on the island have been identified. For this purpose, rainfall data from 62 weather stations have been analysed in a comprehensive manner, with time series of more than 30 years. The cycles with the greatest influence on rainfall, from the point of view of statistical confidence, are ENSO (5.6 y and 3.5 y), as well as NAO (7.5 y) and QBO. Then, using geostatistical methods, the distribution of rainfall during dry, average, and wet years was mapped, as was the spatial representation of the statistical significance of the different natural cycles, in order to define the areas of greatest danger from heavy rainfall. The Serra de Tramuntana is not only the rainiest region of the island, but also the area where the highest values of statistical confidence for the set of climatic cycles are concentrated. The 5 largest landslides of the series are very well located in the areas of highest statistical weight, mainly for the NAO (7.5 y), QBO and HALO (22.4 y) cycles, as well as in the wettest sector for the wet type year.
Juan Antonio Luque-Espinar et al.
Status: final response (author comments only)
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RC1: 'Comment on nhess-2022-50', Stefan Hergarten, 09 May 2022
This paper addresses the occurrence of various climate cycles in precipitation data on the island of Mallorca. As a major finding, the effect of these cycles shows a strong spatial variation. From this finding, conclusions about the importance of the climate cycles on landslide frequency are drawn.
First, I have to state that I am not an expert in climate analysis. While I found the part about the climate cycles interesting, the relation to the landslides does not make much sense to me. Landslide occurrence depends on topography as well as on precipitation. So it is not very surprising that a large amount of the documented landslides took place in a few very wet years. The five biggest landslides happened in regions where relief is -- to my knowledge -- very high. However, I did not find any serious analysis of the spatial distribution of the smaller landslides.
So what can we conclude if we find that one of the considered climate cycles has a quite strong effect on precipitation in the region with the highest number of large landslides, which is rather wet and steep anyway? I think we cannot draw any conclusions about the relation between landslides and climate going beyond what we already know. So the paper does not keep the promise made in the title.
Based on the vague relation to landslides, I cannot recommend publication of the present paper. I might have missed the key point, in which case I would have to apologize.
Best regards,
Stefan Hergarten-
AC1: 'Reply on RC1', Juan Antonio Luque Espinar, 11 May 2022
Dear Dr Hergarten
Firstly, thank you very much for taking the time to read the submitted paper, and thank you for your comments. They will certainly help us to improve the article.
We undoubtedly agree that factors such as relief, geology, slope orientation, etc. condition the occurrence of landslides. It is also widely known that heavy rainfall is the main trigger of landslides, and intense rains are often orographically controlled. There is extensive literature on this subject. Likewise, it is also known that certain natural climatic cycles, such as ENSO, NAO or sunspot, have a clear relationship with landslides and flood records, an aspect that has also been analysed in different publications, including the authors of the present paper. However, the really novel aspect of this work, and the main reason for the publication, is the spatial (and not only temporal) behaviour of climate cycles. As we know, they do not have a homogeneous spatial distribution. In this sense, once the rainfall cycles have been analysed and the ones most related to landslides or floods are identified, the mapping of these influences becomes a (powerful?) prevention tool.
In this work, the use of the inventory of rockfalls in the Tramuntana Range is a first step to validate the methodology here shown, as it can be applied in any region, regardless of its location and climatology. What is relevant is the temporal/spatial analysis of the natural cycles. However, it seems appropriate and a relevant advice from you to validate the climatic results with all the rockfall records, taking into account their volume; not only with the five largest ones.
In summary, we would like to stress that what is important in this work is the methodology, by applying statistical tools. The landslide inventory serves only to validate the results. It is not a work on landslides, as the methodology could be applied to any other rhydroclimatic risk.
Many thanks and kind regards
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AC1: 'Reply on RC1', Juan Antonio Luque Espinar, 11 May 2022
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RC2: 'Comment on nhess-2022-50', Omar F. Althuwaynee, 10 May 2022
The article entitled “Spatio-temporal analysis of the role of climate cycles on landslide activity: the case of Majorca (Spain)” discusses the possibility of using spatio-temporal analysis of climate cycles climate cycle and its role as landslide occurrence possible reference phenomenon. And concluded that the 5 largest landslides of the series are very well located in the areas of highest statistical weight.
1- However, the problem statement that need to be solved here is well know hypothesis. Also, the research carried in this article dint come up with interesting facts. More or less the outcome was highly expected.
2- I wish to see a clear sentence that stress on the validity of using the applied method, or compare to current methods that might need to be improved using the presented approach.
3- Some prosaic sentences were mentioned: “the island suffered persistent and abnormal precipitations”, “In this work, ordinary kriging (OK) has been chosen as it is better adapted to the problem under study.”
4- fig. 4 with table 1. you mentioned the wet years, like 2003 but the amount of landslide compare to following years (average to wet) clearly saying different story “dry to wet”
5- fig. 5 However, when there are a significant number of stations where the cycle has not been detected, a dichotomous transformation has been chosen, i.e. observed (1), not observed (0), as in the case of ENSO (6.4y) and Sunspot (11.2y)..!!!!!!
6- What about the false negative and false positive of landslide occurrence within the climate cycle??
I prefer to stop here, as i tried to get along with article searching for significant findings. But, I think due to the poor structure of the manuscript and presented figures, the idea behind it was difficult to follow.
Unfortunately, my decision is against the publication and I recommend to reject the article. In meantime, I ask the authors to have more time to develop the current approach by consider more robust problem statement and methodology.
All the best,
Omar AlThuwaynee
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RC3: 'Comment on nhess-2022-50', Matthias Schlögl, 10 May 2022
The manuscript presents a spatio-temporal analysis of climate cycles on the island of Majorca and seeks to explore correlations with evidence of historic landslides, i.e. a landslide inventory featuring 423 events.
Albeit the general idea (especially the topic of identifying main climatic cycles) is interesting, I am afraid that there are several major issues with this manuscript in its present form:
- I am missing a clear red thread throughout the article, thus rendering it slightly difficult to read. It is not ultimately clear to me why these particular methods were chosen to tackle the problem under consideration and what the main findings are that the authors want to convey.
- Moreover, findings are not put into context, and a discussion section is missing completely.
- Sections are not clearly separated. Some parts of section 3.4 on rainfall series data seem more like results than "Materials and Methods" to me.
- The joint consideration of different process categories, which are simply summarized as "landslides", would need better justification. After all, these different processes are most likely characterized by different trigger conditions (e.g. rockfall - earth slides - debris flows). The authors could explore results per process category (at least for those categories where enough events are available).
- Some sections are not written in a balanced way. Especially section 3 does not really present the methods applied in a stringent and reproducible manner. For instance, Section 3.3 provides a rather general introduction of geostatistics, but ends quite abruptly with the last paragraph somehow falling short of actually explaining what is done here and why. Why was OK chosen specifically? I assume that there is a trend due to the topography? Also, it is quite common to perform cross-validation on kriging results, but it is unclear at this point if any validation was performed and if yes, how?
- I am under the impression that some important details were omitted or are at least hidden in the manuscript. For instance, satistical confidence values estimated at each rainfall station have been reclassified from 0 (not detected) to 4 (more than 99% statistical confidence). How were these thresholds chosen, and where are they listed? I assume this information is hidden in l. 136?
- I think that the connex between the climate cycles and landslide events should be motivated in a better way. Currently, I fail to see this connection. Maybe a more detailed exploratory analysis of the landslide inventory against the identified climate cycles might provide interesting insights?
- On a more general note, all recorded landslides seem to have occurred in the north-western part, i.e. in the Serra de Tramuntana. This is statet in l.68, and indicated by the white dots in the maps (Figs. 5, 7). I do not really understand why a geostatistical estimation of the whole island does relate to landslides that only occurred in a quite specific sub-region near to a mountain range?
- Only some large landslides are prominently mentioned. Consequently, the main connection seems to be event magnitude, not event frequency. An exploratory analysis of event frequency could provide interesting insights as well.
Overall, I do not think that the manuscript is suitable for publication in its current form due to these limitations. However, I do encourage the authors to work out the proposed connection between climate cycles and landslides in a more elaborate manner.
Best regards,
Matthias Schlögl
Juan Antonio Luque-Espinar et al.
Juan Antonio Luque-Espinar et al.
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