Effect of Air Compression and Counterflow on Shallow Landslides Under Intense Rainfall

2018 ◽  
pp. 1479-1482
Author(s):  
Tongchun Han ◽  
Shiguo Ma ◽  
Riqing Xu
Keyword(s):  
Shallow Landslides ◽  
Intense Rainfall ◽  
Air Compression

scholarly journals Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy

2013 ◽  
Vol 13 (3) ◽  
pp. 559-573 ◽  
Author(s):  
D. Zizioli ◽  
C. Meisina ◽  
R. Valentino ◽  
L. Montrasio
Keyword(s):  
Shallow Landslide ◽  
Northern Italy ◽  
Shallow Landslides ◽  
Rainfall Event ◽  
Aerial Photographs ◽  
Intense Rainfall ◽  
Field Surveys ◽  
Ex Post ◽  
Physically Based ◽  
Physically Based Models

Abstract. On the 27 and 28 April 2009, the area of Oltrepo Pavese in northern Italy was affected by a very intense rainfall event that caused a great number of shallow landslides. These instabilities occurred on slopes covered by vineyards or recently formed woodlands and caused damage to many roads and one human loss. Based on aerial photographs taken immediately after the event and field surveys, more than 1600 landslides were detected. After acquiring topographical data, geotechnical properties of the soils and land use, susceptibility analysis on a territorial scale was carried out. In particular, different physically based models were applied to two contiguous sites with the same geological context but different typologies and sizes of shallow landslides. This paper presents the comparison between the ex-post results obtained from the different approaches. On the basis of the observed landslide localizations, the accuracy of the different models was evaluated, and the significant results are highlighted.

scholarly journals Analysis of rainfall-induced shallow landslides in Jamne and Jaszcze stream valleys (Polish Carpathians) – preliminary results

2016 ◽  
Vol 48 (1) ◽  
pp. 27-40
Author(s):  
Tymoteusz Zydroń ◽  
Anna Bucała ◽  
Piotr Demczuk
Keyword(s):  
Slope Stability ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Landslide Susceptibility Mapping ◽  
Intense Rainfall ◽  
Stability Calculation ◽  
Preliminary Results ◽  
Calculation Results ◽  
Polish Carpathians ◽  
Using Data

Abstract Analysis of rainfall-induced shallow landslides in Jamne and Jaszcze stream valleys (Polish Carpathians) - preliminary results. Preliminary shallow landslide susceptibility mapping of the Jamne and Jaszcze stream valleys, located in the Polish Flysch Carpathians, is presented in the paper. For the purpose of mapping, there were used SINMAP and Iverson’s models integrating infiltration and slope stability calculations. The calibration of the used models parameters, obtained from limited field and laboratory tests, was performed using data from 8-9 July 1997, when as a consequence of a very intense rainfall, 94 shallow landslides were observed on meadows and arable lands. A comparison of the slope stability calculation results and the localisation of the noticed shallow landslides showed satisfactory agreement between localisation of the observed and computed unstable areas. However, it was concluded that better simulation results were obtained using Iverson’s model.

A new shallow landslides inventory for Southern Lunigiana (Tuscany, Italy) and analysis of predisposing factors

2018 ◽  
Vol 46 ◽  
pp. 149-154
Author(s):  
Enrico D'Addario ◽  
Emanuele Trefolini ◽  
Elisa Mammoliti ◽  
Michele Papasidero ◽  
Vincenzo Vacca ◽  
...  
Keyword(s):  
Shallow Landslides ◽  
Predisposing Factors

scholarly journals Erratum: Dieu, T.B. et al. A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides. Remote Sens. 2018, 10, 1538

2018 ◽  
Vol 11 (1) ◽  
pp. 57 ◽  
Author(s):  
Dieu Tien Bui ◽  
Himan Shahabi ◽  
Ataollah Shirzadi ◽  
Kamran Kamran Chapi ◽  
Nhat-Duc Hoang ◽  
...  
Keyword(s):  
Spatial Modeling ◽  
Imperialist Competitive Algorithm ◽  
Integrated Approach ◽  
Relevance Vector Machine ◽  
Shallow Landslides ◽  
Competitive Algorithm

The authors wish to make the following corrections to this paper [...]

scholarly journals Wind control of storm-triggered shallow landslides

2007 ◽  
Vol 34 (3) ◽  
Author(s):  
M. C. Rulli ◽  
F. Meneguzzo ◽  
R. Rosso
Keyword(s):  
Shallow Landslides

scholarly journals Regional Analyses of Rainfall-Induced Landslide Initiation in Upper Gudbrandsdalen (South-Eastern Norway) Using TRIGRS Model

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Luca Schilirò ◽  
José Cepeda ◽  
Graziella Devoli ◽  
Luca Piciullo
Keyword(s):  
Numerical Simulations ◽  
Regional Scale ◽  
Shallow Landslides ◽  
South Eastern ◽  
Physically Based ◽  
Triggering Conditions ◽  
Cover Thickness ◽  
Regional Analyses ◽  
Factor Maps ◽  
Eastern Norway

In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.

scholarly journals A Data-Driven Method for the Temporal Estimation of Soil Water Potential and Its Application for Shallow Landslides Prediction

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1208
Author(s):  
Massimiliano Bordoni ◽  
Fabrizio Inzaghi ◽  
Valerio Vivaldi ◽  
Roberto Valentino ◽  
Marco Bittelli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Potential ◽  
Soil Water ◽  
Temporal Trends ◽  
Soil Water Potential ◽  
Shallow Landslides ◽  
Water Dynamics ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Physically Based

Soil water potential is a key factor to study water dynamics in soil and for estimating the occurrence of natural hazards, as landslides. This parameter can be measured in field or estimated through physically-based models, limited by the availability of effective input soil properties and preliminary calibrations. Data-driven models, based on machine learning techniques, could overcome these gaps. The aim of this paper is then to develop an innovative machine learning methodology to assess soil water potential trends and to implement them in models to predict shallow landslides. Monitoring data since 2012 from test-sites slopes in Oltrepò Pavese (northern Italy) were used to build the models. Within the tested techniques, Random Forest models allowed an outstanding reconstruction of measured soil water potential temporal trends. Each model is sensitive to meteorological and hydrological characteristics according to soil depths and features. Reliability of the proposed models was confirmed by correct estimation of days when shallow landslides were triggered in the study areas in December 2020, after implementing the modeled trends on a slope stability model, and by the correct choice of physically-based rainfall thresholds. These results confirm the potential application of the developed methodology to estimate hydrological scenarios that could be used for decision-making purposes.

Sign in / Sign up

Export Citation Format

Share Document