Figure 1 - uploaded by Emmanuel Arinze
Content may be subject to copyright.
Source publication
Abstract: Landslides are present in all continents playing important role in the continual evolution of this type of or similar
geohazard. They constitute a serious hazard in many areas of the world. The landslide event can be single or multiple. This
paper involves the geotechnical analysis of landslide that occurred in Amuzukwu Abia State Nigeria...
Contexts in source publication
Context 1
... is geographically located within the coordinates N05°32′ and N05°41′ Latitude and E07°28′ and E07°32′ Longitude. Figure 1 shows the township map of Amuzukwu and neighbouring communities highlighting settlements and road networks [27]. ...
Similar publications
![Figure 5. X-ray diffraction of undisturbed clay [20] The following...](publication/368659581/figure/fig1/AS:11431281121199376@1676896573553/X-ray-diffraction-of-undisturbed-clay-20-The-following-methodological-process-is-shown_Q320.jpg)
The landslide problem in the city of Constantine (Algeria) is mostly due to clayey soil, which is covering the whole area. Therefore, all the structures and foundations built over such soil are quite vulnerable. The sensitivity of this soil increases during the rainfall season, which might reach an extreme magnitude and cause damage to the structur...
Citations
... The numerical analysis integrates more advanced models of hydraulic properties (Rahimi et al. 2010). Prime examples of such applied models in landslide analysis include GeoStudio (Geo-slope) (Das et al. 2022;Huang and He 2023;Xu et al. 2022;Calvello et al. 2009;Pagano et al. 2010;Wan et al. 2017); MIDAS/GTS (Qiu et al. 2019;Yang et al. 2023); ABAQUS (He et al. 2021); GEOtop 2.0 (Formetta and Capparelli 2019); Rocscience software (RS2) (Purnama et al. 2022); BGSlope (Abolmasov et al. 2015); SLIDE (He et al. 2016;Khan and Wang 2021;Liao et al. 2010); and PLAXIS (Arinze et al. 2021;Oguz et al. 2022). ...
Landslides are frequent hillslope events that may present significant risks to humans and infrastructure. Researchers have made ongoing efforts to assess the potential danger associated with landslides, intending to ascertain the location, frequency, and magnitude of these events in a given area. This study is meant to supplement the previous study (Part I), which explored empirical and physically based causative thresholds. In this paper (Part II), a systematic review is used to conduct an in-depth study of existing research on prediction models. Deterministic physical approaches were investigated for local-scale landslides. Next, national-scale landslide susceptibility models are discussed, including qualitative and quantitative models. Consequently, key findings about rainfall-induced landslides are reviewed. The strategy selection is generally governed by data and input factors from a macroscopic perspective, while the better prediction model is defined by dataset quality and analysis model performance from a microscopic perspective. Physically based causative thresholds can be used with limited geotechnical or hydrological data; otherwise, numerical analysis provides optimal accuracy. Among all statistical models, the hybrid artificial intelligence model achieved the best accuracy. Finally, current challenges have concentrated on integrating AI and physical models to obtain high accuracy with little data, prompting research suggestions. Advanced constitutive models for real-time situations are lacking. Dynamic and spatiotemporal susceptibility maps are also used, although their subjectivity needs further research. This study analyses how to choose the best model and determine its key traits. This research provides valuable insights for scholars and practitioners seeking innovative
approaches to lessen the severity of landslides.
