Temporal and spatial distributions of landslides in the Qinba Mountains, Shaanxi Province, China

The spatial and temporal distributions of landslides can be used to assess the potential future impacts of landslides over large scales. However, quantitatively characterizing the spatial and temporal distributions of landslides and their causes remains a critical challenge. In this work, a typical...

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Bibliographic Details
Published in:Geomatics, natural hazards and risk natural hazards and risk, 2019-01, Vol.10 (1), p.599-621
Main Authors: Qiu, Haijun, Cui, Yifei, Hu, Sheng, Yang, Dongdong, Pei, Yanqian, Yang, Wenlu
Format: Article
Language:English
Subjects:
Distribution patterns
Earthquakes
Landslides
Landslides & mudslides
Mountains
Power law
Probability theory
Qinba Mountains
Rain
Rainfall
Seismic activity
Spatial distribution
Temporal distribution
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Summary:The spatial and temporal distributions of landslides can be used to assess the potential future impacts of landslides over large scales. However, quantitatively characterizing the spatial and temporal distributions of landslides and their causes remains a critical challenge. In this work, a typical landslide-prone region (the Qinba Mountains) is selected to identify this spatial and temporal trend. Information on 295 landslides spanning ten years from 2005 to 2014 was collected. The results revealed that landslide occurrences were clustered in time and space. Approximately 81% of the total landslides occurred from July to October. Moreover, a power law relationship between the cumulative frequency and number of landslides per day was discovered. Notably, the probability density of the time interval decreased as the time interval between landslide events increased, and this relationship was well described by a negative power-law correlation. Furthermore, the spatial and temporal distribution pattern of most landslides were influenced by rainfall events and earthquakes. There were several clustered centers in the study area, and the mean centers of the landslide distribution varied among years.
ISSN:1947-5705
1947-5713
DOI:10.1080/19475705.2018.1536080