Application and verification of a multivariate real-time early warning method for rainfall-induced landslides: implication for evolution of landslide-generated debris flows Article Swipe
Zongji Yang
,
Liyong Wang
,
Jianping Qiao
,
Taro Uchimura
,
Lin Wang
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s10346-020-01402-w
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s10346-020-01402-w
Rainfall-induced landslides are a frequent and often catastrophic geological disaster, and the development of accurate early warning systems for such events is a primary challenge in the field of risk reduction. Understanding of the physical mechanisms of rainfall-induced landslides is key for early warning and prediction. In this study, a real-time multivariate early warning method based on hydro-mechanical analysis and a long-term sequence of real-time monitoring data was proposed and verified by applying the method to predict successive debris flow events that occurred in 2017 and 2018 in Yindongzi Gully, which is in Wenchuan earthquake region, China. Specifically, long-term sequence slope stability analysis of the in situ datasets for the landslide deposit as a benchmark was conducted, and a multivariate indicator early warning method that included the rainfall intensity-probability ( I-P ), saturation ( S i ), and inclination ( I r ) was then proposed. The measurements and analysis in the two early warning scenarios not only verified the reliability and practicality of the multivariate early warning method but also revealed the evolution processes and mechanism of the landslide-generated debris flow in response to rainfall. Thus, these findings provide a new strategy and guideline for accurately producing early warnings of rainfall-induced landslides.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10346-020-01402-w
- https://link.springer.com/content/pdf/10.1007/s10346-020-01402-w.pdf
- OA Status
- hybrid
- Cited By
- 44
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3014504822
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3014504822Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s10346-020-01402-wDigital Object Identifier
- Title
-
Application and verification of a multivariate real-time early warning method for rainfall-induced landslides: implication for evolution of landslide-generated debris flowsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-04-03Full publication date if available
- Authors
-
Zongji Yang, Liyong Wang, Jianping Qiao, Taro Uchimura, Lin WangList of authors in order
- Landing page
-
https://doi.org/10.1007/s10346-020-01402-wPublisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s10346-020-01402-w.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s10346-020-01402-w.pdfDirect OA link when available
- Concepts
-
Landslide, Warning system, Debris flow, Multivariate statistics, Debris, Natural hazard, Early warning system, Geology, Environmental science, Hydrology (agriculture), Computer science, Seismology, Geotechnical engineering, Machine learning, Telecommunications, OceanographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
44Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 8, 2024: 10, 2023: 13, 2022: 5, 2021: 8Per-year citation counts (last 5 years)
- References (count)
-
39Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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