Research Data Leeds Repository

River Augmented Global Landslide Dams (RAGLAD)

Wu, Hang and Trigg, Mark and Murphy, William and Fuentes, Raul (2024) River Augmented Global Landslide Dams (RAGLAD). University of Leeds. [Dataset]

Dataset description

To address the current data and understanding knowledge gap in landslide dam inventories related to geomorphological parameters, a new global-scale landslide dam dataset named River Augmented Global Landslide Dams (RAGLAD) was created. RAGLAD is a collection of landslide dam records from multiple data sources published in various languages and many of these records we have been able to precisely geolocate. In total, 779 landslide dam records were compiled from 34 countries/regions. The spatial distribution, time trend, triggers, and geomorphological characteristic of the landslides and catchments where landslide dams formed are summarized. The relationships between geomorphological characteristics for landslides that form river dams are discussed and compared with those of landslides more generally. Additionally, a potential threshold for landslide dam formation is proposed, based on the relationship of landslide volume to river width. Our findings from our analysis of the value of the use of additional fluvial datasets to augment the database parameters indicate that they can be applied as a reliable supplemental data source, when the landslide dam records were accurately and precisely geolocated, although location precision in smaller river catchment areas can result in some uncertainty at this scale. This newly collected and supplemented dataset will allow the analysis and development of new relationships between landslides located near rivers and their actual propensity to block those particular rivers based on their geomorphology.

Subjects: F000 - Physical sciences > F600 - Geology > F680 - Geohazards
Divisions: Faculty of Engineering and Physical Sciences > School of Civil Engineering
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 07 Feb 2024 09:02




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