A worldwide event-based debris flow barrier dam dataset from 1800 to 2023 DOI Creative Commons

Haiguang Cheng,

Kaiheng Hu,

Shuang Liu

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(4), P. 1573 - 1593

Published: April 15, 2025

Abstract. Debris flows, as a special kind of landslide, often block rivers to form barrier dams and trigger series disasters such upstream aggradation outburst floods. The understanding debris flow (DFBDs) is poor, mostly due existing studies focusing on individual events lack summarization multiple DFBD events. global or regional datasets landslide (LDs) contain only few cases DFBDs ignore the differences between other (LDs), rock slides, avalanches, earth slides. To fill this gap, we reviewed 2519 high-quality literature media reports. Focusing identified damming events, rigorous data review validation process was conducted using Google Earth. A systematic approach employed prioritize conflicting information from various sources. Consequently, dataset compiled, encompassing 555 historical 1800 2023. This pioneering includes 6 categories 38 attributes, detailing DFBDs. It captures basic (location, date formation, etc.), dam characteristics (height, length, volume, lake (area, capacity, length), (velocity, discharge, failure (peak loss life, climate (precipitation temperature). Our elucidates that exhibit key features instability, complete blockage, overtopping failure. number has notably increased, especially in China. total 15 % channels showed recurrent resulting make up 35 all Further analysis suggests Ls (AHV) model should be used for priority use, followed by DBI model, stability assessment Compared datasets, our more targeted places greater emphasis raw data, stresses unification terminology concepts (i.e., blockage modes stability), ensuring consistency accuracy data. results work may help deepen distribution, evolution. can accessed through link: https://doi.org/10.5281/zenodo.14766647 (Cheng et al., 2025).

Language: Английский

Multidisciplinary Perspectives in Understanding Himalayan glacial lakes in a Climate Challenged World DOI Creative Commons
Nitesh Khadka, Weiming Liu, Milan Shrestha

et al.

Published: Feb. 1, 2025

Language: Английский

Citations

0

Multi Breach GLOF Hazard and Exposure Analysis of Birendra Lake in the Manaslu Region of Nepal DOI Creative Commons
Utsav Poudel, Manish Raj Gouli,

Kaiheng Hu

et al.

Natural Hazards Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0

Glacial Lake Outburst Floods (GLOFs) Susceptibility in the Northwest Himalayas using AHP-TOPSIS and AHP-COPRAS DOI
Anup Upadhyaya, Abhishek Kumar

Environmental Science and Pollution Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Language: Английский

Citations

0

A worldwide event-based debris flow barrier dam dataset from 1800 to 2023 DOI Creative Commons

Haiguang Cheng,

Kaiheng Hu,

Shuang Liu

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(4), P. 1573 - 1593

Published: April 15, 2025

Abstract. Debris flows, as a special kind of landslide, often block rivers to form barrier dams and trigger series disasters such upstream aggradation outburst floods. The understanding debris flow (DFBDs) is poor, mostly due existing studies focusing on individual events lack summarization multiple DFBD events. global or regional datasets landslide (LDs) contain only few cases DFBDs ignore the differences between other (LDs), rock slides, avalanches, earth slides. To fill this gap, we reviewed 2519 high-quality literature media reports. Focusing identified damming events, rigorous data review validation process was conducted using Google Earth. A systematic approach employed prioritize conflicting information from various sources. Consequently, dataset compiled, encompassing 555 historical 1800 2023. This pioneering includes 6 categories 38 attributes, detailing DFBDs. It captures basic (location, date formation, etc.), dam characteristics (height, length, volume, lake (area, capacity, length), (velocity, discharge, failure (peak loss life, climate (precipitation temperature). Our elucidates that exhibit key features instability, complete blockage, overtopping failure. number has notably increased, especially in China. total 15 % channels showed recurrent resulting make up 35 all Further analysis suggests Ls (AHV) model should be used for priority use, followed by DBI model, stability assessment Compared datasets, our more targeted places greater emphasis raw data, stresses unification terminology concepts (i.e., blockage modes stability), ensuring consistency accuracy data. results work may help deepen distribution, evolution. can accessed through link: https://doi.org/10.5281/zenodo.14766647 (Cheng et al., 2025).

Language: Английский

Citations

0