the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A worldwide event-based debris-flow barrier dam dataset from 1800 to 2023
Abstract. Debris flows, as a special kind of landslides, often block rivers to form barrier dams and trigger a series of disasters such as upstream aggradation and outburst floods. The understanding of debris-flow barrier dams (DFBDs) is poor, mostly due to existing researches focusing on individual events and a lack of summarization of multiple DFBD events. The existing global or regional datasets of landslide barrier dams (LDs) contain only a few cases of DFBDs, and ignore the differences between DFBDs and other landslide barrier dams (LDs), such as the dams of rock slide, debris avalanche, or earth slide. To fill this gap, we reviewed 2519 literatures and media reports with high quality. Focusing on identified debris-flow damming events, a rigorous data review and validation process was conducted using Google Earth. A systematic approach was employed to prioritize conflicting information from various data sources. Consequently, a global dataset was compiled, encompassing 555 historical DFBDs from 1800 to 2023.
This pioneering global dataset includes five categories and 36 attributes, detailing DFBDs. It captures basic information (location, the date of formation, etc.), dam characteristics (height, length, volume, etc.), lake characteristics (area, capacity, length), debris flow characteristics (velocity, discharge, volume, etc.), and failure characteristics (peak discharge, loss of life, etc.). Our dataset elucidates that DFBDs exhibit key features of instability, complete blockage, and overtopping failure. The number of such dams has notably increased, especially in China. 15 % of channels showed recurrent debris flows, resulting in DFBDs that make up 35 % of all DFBDs. Further analysis recommends the Ls (AHV) model is recommended for priority use, followed by the DBI model, for the stability assessment of DFBDs. Compared to other barrier dam datasets, our dataset is more targeted, lays a greater emphasis on the review of raw data, and stresses the unification of terminology and concepts (such as blockage modes and stability), ensuring the consistency and accuracy of the data. The dataset and results in this work may help to deepen the understanding of DFBD formation, distribution, and evolution. The DFBD dataset can be accessed through this link: https://doi.org/10.5281/zenodo.13382846 (Cheng et al., 2024).
- Preprint
(1915 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 06 Nov 2024)
-
CC1: 'Comment on essd-2024-382', Thanh-Nhan-Duc Tran, 30 Sep 2024
reply
Publisher’s note: the content of this comment was removed on 2 October 2024 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/essd-2024-382-CC1 -
RC1: 'Comment on essd-2024-382', Thanh-Nhan-Duc Tran, 30 Sep 2024
reply
First and foremost, the proposed idea of constructing a dataset of debris-flow barrier dams (DFBDs) is unique and novel, and I believe it is significantly important to publish. Additionally, I acknowledge the substantial amount of work the authors have done to construct this dataset, which involved carefully reviewing over 2,500 high-quality literature sources and media reports. Regrettably, I must decline the work in its current form, but I would be happy to review it again after substantial revisions have been added. Specifically, there are several major concerns with this dataset that are unacceptable and must be addressed.
- While the dataset is proposed as a worldwide collection, covering data back to the 1800s, which is impressive, only 555 dams were included. This number seems unreasonably low for a 'worldwide' scale. I am generally doubtful of this outcome.
- The data review and validation process was conducted using Google Earth. While this is a traditional and effective approach that I believe many other researchers use when building datasets on dams and reservoirs, it raises the question of how far back the authors were able to retrieve data, especially to validate the geographical coordinates and dates of formation going as far back as 1800. This is a difficult question that I believe the authors need to revisit and carefully consider. Furthermore, the manuscript points out discrepancies between the reported formation dates from data sources (literature) and Google Earth. This raises the question: which source is correct, and how can this be confirmed?
- The dataset is described as worldwide, but the majority of the dams are located in China. While this may be reasonable, given the authors' location, it creates a significant bias when only 39 dams are recorded in Italy, 43 in Japan, 33 in the United States, and 64 in other locations, compared to 333 in China. The authors should carefully reconsider whether they intend to maintain a global scale or refocus the dataset only within China mainland.
- In Figure 7, I understand that the authors aim to highlight some DFBDs using remote sensing imagery; however, I honestly cannot distinguish the DFBDs from the surrounding areas. I recommend using higher-resolution imagery, such as data from Planet, which can provide resolutions as high as 1 to 3 meters.
- When reviewing the dataset provided by the authors at https://doi.org/10.5281/zenodo.13382846, I have the following major concerns:
(1) Many DFBDs (EFBD_ID 1 to 31) are listed in languages other than English. While I understand that translating or converting the names to English can be challenging, the authors are proposing a worldwide dataset. How can others utilize this data if the names are in languages like Taiwanese or Japanese (e.g., 姫川・大所川・赤禿)? After consulting with my Chinese colleague, I believe these names could be converted to English.
(2) Many DFBDs are missing data on important parameters such as debris flow channel slope gradient (%) and debris flow channel length (km). I highly recommend filling in these missing pieces of information before the dataset can be considered for publication.
(3) The dam material information for several entries (EFBD_ID 3-33) is listed in Japanese. Please ensure this information is provided in English.
Citation: https://doi.org/10.5194/essd-2024-382-RC1
Data sets
A worldwide event-based debris-flow barrier dam dataset from 1800 to 2023 Haiguang Cheng et al. https://doi.org/10.5281/zenodo.13382846
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
79 | 14 | 29 | 122 | 2 | 2 |
- HTML: 79
- PDF: 14
- XML: 29
- Total: 122
- BibTeX: 2
- EndNote: 2
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1