Engineering Measures for Landslide Disaster Mitigation

Popescu, Maria-Cristina; Sasahara, Katsuo

doi:10.1007/978-3-540-69970-5_32

Cited by 36 publications

(15 citation statements)

References 3 publications

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“…This will enable the incorporation of ERI monitoring into early‐warning systems that can provide reliable alarms to endangered communities and assets [ Lacasse and Nadim , ; Michoud et al ., ], by informing about the historic and present moisture contents and pore pressures in slopes, thus mitigating their risk [ van Westen et al ., ; Berti et al ., ; Bogaard and Greco , ]. This will provide the potential not only to define triggering thresholds but also to study the causes for landsliding and proactively provide information to facilitate the design of early and effective intervention strategies to stabilize slopes [ Crozier and Glade , ; Popescu and Sasahara , ; BSI , ], which are more cost‐effective than reactive remediation of failures.…”

Section: Discussionmentioning

confidence: 99%

Four‐dimensional imaging of moisture dynamics during landslide reactivation

et al. 2017

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Landslides pose significant risks to communities and infrastructure, and mitigating these risks relies on understanding landslide causes and triggering processes. It has been shown that geophysical surveys can significantly contribute to the characterization of unstable slopes. However, hydrological processes can be temporally and spatially heterogeneous, requiring their related properties to be monitored over time. Geoelectrical monitoring can provide temporal and volumetric distributions of electrical resistivity, which are directly related to moisture content. To date, studies demonstrating this capability have been restricted to 2‐D sections, which are insufficient to capture the full degree of spatial heterogeneity. This study is the first to employ 4‐D (i.e., 3‐D time lapse) resistivity imaging on an active landslide, providing long‐term data (3 years) highlighting the evolution of moisture content prior to landslide reactivation and showing its decline post reactivation. Crucially, the time‐lapse inversion methodology employed here incorporates movements of the electrodes on the unstable surface. Although seasonal characteristics dominate the shallow moisture dynamics during the first 2 years with surficial drying in summer and wetting in winter, in the months preceding reactivation, moisture content increased by more than 45% throughout the slope. This is in agreement with independent data showing a significant rise in piezometric heads and shallow soil moisture contents as a result of prolonged and intense rainfall. Based on these results, remediation measures could be designed and early‐warning systems implemented. Thus, resistivity monitoring that can allow for moving electrodes provides a new means for the effective mitigation of landslide risk.

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Section: Discussionmentioning

confidence: 99%

Four‐dimensional imaging of moisture dynamics during landslide reactivation

et al. 2017

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“…Thus, if landslides reoccur in Rwanda, people and their belongings, and natural resources located in moderate and high hazard zones may record greater losses and damages. For such areas, soft engineering, known as biotechnical slope stabilization technique, if applied, can help to stabilize the slope due to its advantage of combining both the use of vegetation and man-made structural elements (Popescu and Sasahara 2009). In addition, residents from high landslides hazard areas (Fig.5) can be transferred to safe hazard zones like eastern province (Table 2) with low values of triggering factors (Fig.6).…”

Section: Discussionmentioning

confidence: 99%

Landslides Hazard Mapping in Rwanda Using Bivariate Statistical Index Method

Nahayo

Mupenzi

Habiyaremye

et al. 2019

Environmental Engineering Science

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Landslides hazard mapping (LHM) is essential in delineating hazard prone areas and optimizing low cost mitigation measures. This study applied the Geographic Information System (GIS) and statistical index (SI) method in landslides hazard mapping in Rwanda. Field surveys identified 336 points which were employed to construct a landslides inventory map. Ten landslides predicting factors: normalized difference vegetation index, elevation, slope, aspects, lithology, soil texture, distance to rivers, distance to roads, rainfall, and land use were analyzed. The factor variables were converted into categorized variables according to the percentile divisions of seed cells. Then values of each factor's class weight were calculated and summed to create landslides hazard map. The estimated hazard map was split into five hazard classes (very low, low, moderate, high and very high). The results indicated that the northern, western and southern provinces are largely exposed to landslides hazard. The major landslides hazard influencing factors are elevation, slope, rainfall and poor land management. Overall, this landslides hazard mapping would help policy makers to recognize each area's hazard extent, key triggering factors and the required hazard mitigation measures. These measures include planting trees to enhance vegetation cover and reduce the runoff, and construction of buildings on low steep slope areas to reduce people's hazard exposure; while agroforestry and bench terraces would reduce sediments which take out the exposed soil (erosion) and pollute water quality.

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“…There is two type of casual factor affecting the landslide: preparatory causal factor, triggering causal factor. As name signify preparatory casual factor responsible for making slope vulnerable to landslide whereas triggering factor initiate the movement [5]. Most of time there are several causal factors responsible for landslide such as ground condition, geomorphic process, physical process, manmade process.…”

Section: Factor Effecting Landslidementioning

confidence: 99%

Landslide Killing Himalayas: Collective Study on Causal Factors and Possible Remedies

Khanduri

Verma

2020

ARASET

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Soil is naturally available material used for construction all over the world. When this material available in form of natural slope can cause landslide. Purpose of this study is to understand behavior of different causal factor of landslide at Himachal Pradesh and then suggest some remedial measure. To fulfill this, aim five-year data of precipitation for every district is collected from metrological department and analyzed. Data of earthquake activities is also collected. Work done by different author in this area is analyzed thoroughly. It is found that the change in climatic conditions such as increase in precipitation over years, earthquakes and anthropogenic interference has increased the landslide susceptibility of area. Remedial measure suggested as use of landslide susceptibility zonation map future land use pattern, use of advance technology like soil nail and gabion wall and use of numerical modeling to analyze slope stability.

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Engineering Measures for Landslide Disaster Mitigation

Cited by 36 publications

References 3 publications

Four‐dimensional imaging of moisture dynamics during landslide reactivation

Four‐dimensional imaging of moisture dynamics during landslide reactivation

Landslides Hazard Mapping in Rwanda Using Bivariate Statistical Index Method

Landslide Killing Himalayas: Collective Study on Causal Factors and Possible Remedies

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