Physically based and distributed rainfall intensity and duration thresholds for shallow landslides

Marin, Roberto

doi:10.1007/s10346-020-01481-9

Cited by 33 publications

(14 citation statements)

References 51 publications

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“…To predict the possibility of shallow landslides occurring, dynamic pressure fluctuations due to rainfall and downward incursion are included in the TRIGRS method. The S software enables the combination of infinite slope stability calculations with a one-dimensional empirical method for pore-pressure filtration in a limited depth topsoil in response to time-varying precipitation [41][42][43]. While transitory models may improve the quality of susceptibility results by accounting for the transient impacts of changing rainfall on slope stability conditions, they often need a significant quantity of data [44].…”

Section: Physically Based Modelsmentioning

confidence: 99%

A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides

Zou

Zheng

2022

Applied Sciences

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The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.

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Section: Physically Based Modelsmentioning

confidence: 99%

A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides

Zou

Zheng

2022

Applied Sciences

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“…Physically-based models have been used in the last few decades to assess landslide susceptibility and hazard in many regions worldwide (Baum et al, 2005;Lin et al, 2021;Michel et al, 2014;Montrasio et al, 2011). There are developing methodologies such as probabilistic applications (Marin and Mattos, 2020;Raia et al, 2014), or rainfall threshold definition (Alvioli et al, 2018;Marin, 2020;Marin et al, , 2021cMarin et al, , 2021dPapa et al, 2013). Even though the spatial and temporal prediction of landslides is considered a very difficult (almost impossible in many cases) task due to the high variability and that many factors (with great uncertainty) intervene in their occurrence, landslide early warning systems in different regions worldwide have adopted different methods trying to forecast landslide occurrence (Guzzetti et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Understanding the sensitivity to the soil properties and rainfall conditions of two physically-based slope stability models

Marin¹,

Mattos²,

Fernández-Escobar

2022

Boletín de Geología

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Physically-based models have been used to assess landslide susceptibility, hazard, and risk in many regions worldwide. They have also been regarded as valuable tools for landslide prediction and the development or improvement of landslide early warning systems. They are usually validated to demonstrate their predictive capacity, but they are not deeply studied regularly to understand the sensitivity of the input variables and the behavior of the models under many different rainfall scenarios. In this research paper, we studied two distributed physically-based models for shallow landslides: SLIP and Iverson. For this, the first-order second-moment (FOSM) method was used to calculate the contribution of random input variables (soil strength, unit weight, and permeability parameters) to the variance of the factor of safety. Different intensity and duration rainfall events were simulated to assess the response of the models to those rainfall conditions in terms of the factor of safety and failure probability. The results showed that the shear strength (cohesion and friction angle, in order of significance) parameters have the largest contribution to the variance in both models, but they vary depending on geological, geotechnical, and topographic conditions. The Iverson and SLIP models respond in different ways to the variation of rainfall conditions: for shorter durations (e.g. ≤ 8 h), increasing the intensity caused more unstable areas in the SLIP model, while for longer durations the unstable areas were considerably higher for the Iverson model. Understanding those behaviors can be useful for practical and appropriate implementation of the models in landslide assessment projects.

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“…The results show that rainfall is the direct triggering factor of this kind of landslide and debris ow. Rain is mainly re ected in rainfall intensity and rainfall duration (Li et al 2019;Marin 2020;Zhang et al 2019), and terrain topography, geotechnical property, slope structure, and other factors affect the development characteristics and spatial distribution of hazards (Bhardwaj et al 2019;Huang et al 2019;Netto et al 2013;Wei et al 2020Wei et al ,2019. Under favorable topographical conditions, landslides caused by rain become the source of debris ow, and the disaster chain of landslide and debris ow is formed, resulting in more signi cant loss of life and property Fang et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Group-occurring landslides and debris flows caused by the continuous heavy rainfall in June 2019 in Mibei Village, Longchuan County, Guangdong Province, China

Bai

Feng

et al. 2021

Nat Hazards

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From June 10th to 13th, 2019, a continuous heavy rainfall occurred in Longchuan County, Guangdong Province, causing many landslide hazards. Among Longchuan County districts, Mibei village is one of the hardest-hit areas and suffered severe losses. In this paper, eld investigation, remote sensing image interpretation , and UAV aerial photography were used to investigate and analyze hazard characteristics.Combined with rainfall monitoring data, laboratory and eld tests data, and existing research results, the characteristics and failure mechanism of group-occurring landslides in Mibei village were studied.Because of the continuous heavy rainfall, 327 landslides occurred in the study area, mainly distributed in the north of the Mibei river and along the X158 road. The terrain slope of landslide hazards ranged from 35° to 45°, and the slope structure can be divided into two types. Granite residual soil was the main part of landslide mass, and sliding surface developed along with the interface between bedrock and covering layer. The continuous heavy rainfall from June 10th to 13th was the main triggering factor of the disaster.The total precipitation was 281.3 mm, and the rainfall on June 10th was 153.5 mm. The rain led to the continuous increase of volume water content in granite residual soil and completely weathered granite.The shear strength and parameters of the two materials changed differently, and slope stability continued to decrease, and then landslides occurred under terrain conditions and engineering excavation space. Untimely support and unreasonable support measures for the excavation slope exacerbated the disaster.The development degree of debris ows in the study area was very low, and debris ows were shown as the secondary disaster of landslides. The branch gully terrain is the key to transforming the landslide into the debris ow, and a large amount of loose deposits in the main gully will become the potential source of debris ow in the future.

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Physically based and distributed rainfall intensity and duration thresholds for shallow landslides

Cited by 33 publications

References 51 publications

A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides

A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides

Understanding the sensitivity to the soil properties and rainfall conditions of two physically-based slope stability models

Group-occurring landslides and debris flows caused by the continuous heavy rainfall in June 2019 in Mibei Village, Longchuan County, Guangdong Province, China

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