Characterization of El Kherba landslide triggered by the August 07, 2020, Mw = 4.9 Mila earthquake (Algeria) based on post-event field observations and ambient noise analysis

Tebbouche, Mohamed Yacine; Benamar, Dalila Ait; Hassan, Hany M.; Singh, A. P.; Bencharif, Raouf; Machane, Djamel; Meziani, Abdelghani Aghiles; Nemer, Z.

doi:10.1007/s12665-022-10172-8

Cited by 14 publications

(10 citation statements)

References 52 publications

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“…MB is for Mitidja Basin; DM is for Djurdjura Massif. Study N° 1 is by [7], 2 and 9 are by [8] and [13], 3 is by [10], 4 is by [11], 5 is by [12], 6 is an unpublished ANRH report, 7 is by [21], 8 is by [15].…”

Section: Study Of the Effects Of Sites Constructed In Algerian Urban ...mentioning

confidence: 99%

Synthesis on the Shear Wave Velocity of Engineering and Seismic Bedrocks in Northern Algeria based on Recent Experimental Investigations

2023

1st International Conference on Modern and Advanced Research Icmar 2023

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In the field of civil engineering, knowledge of good rocky ground resistant to collapse minimizes the level of seismic risk, often known as the "engineering bedrock". In lithology, it overlays a harder rock known as "seismic bedrock". The latter is a transition zone between the earth's crust and the surface layers. It is sometimes impossible to carry out deep drilling and investigation techniques to define the engineering substratum for the foundations; in this case we rely on the seismic regulations. In Algeria, after the 2003 Boumerdès earthquake, seismology studies were expanded in order to better understand the Algerian crust on both the marine and continental sides. Furthermore, studies on seismic risk reduction in urban environments are increasingly focusing on the phenomenon of site effects or local amplification. Several experimental studies conducted in Algeria as part of seismic microzoning programs have defined the existence of these two substrate interfaces by identifying the natural frequencies of the ground. In this work, we describe the findings of numerous key research that reached the seismic bedrock in Algeria. It is classified as having two geological natures: Mesozoic with a shear wave velocity, Vs, less than 3000 m/s, and metamorphosed Paleozoic with Vs greater than 3500 m/s.

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Section: Study Of the Effects Of Sites Constructed In Algerian Urban ...mentioning

confidence: 99%

Synthesis on the Shear Wave Velocity of Engineering and Seismic Bedrocks in Northern Algeria based on Recent Experimental Investigations

2023

1st International Conference on Modern and Advanced Research Icmar 2023

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“…The landslide has been seen as one of the main reasons leading to the failure of the sewer network because of causing road subsidence, and sewer pipes in the landslide areas have a higher probability of deterioration than others [66]. Similarly, sewer pipes under building areas are more vulnerable compared to other areas due to operational pressure because they have suffered from high pressure for a long period [8].…”

Section: ) Environmental Factorsmentioning

confidence: 99%

Comparison of Machine Learning Techniques for Condition Assessment of Sewer Network

2022

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Assessment of the structural condition of sewer pipes is one of the critical steps in asset management and support investment decisions; therefore, structural condition models with high accuracy are important that can help the utility managers and other authorities correctly assess the current condition of the sewage network and effectively initiate maintenance and rehabilitation strategies. The main objective of this research is to assess the potential application of advanced machine learning (ML) for predicting the structural condition of sewer pipes with a case study in Ålesund city, Norway. Nine physical factors (i.e., age, diameter, depth, slope, length, pipe type, material, pipe form, and connection type) and ten environmental factors (i.e., rainfall, geology, landslide area, building area, population, land cover, groundwater level, traffic volume, distance from the road, and soil type) were used to assess the sewer structural condition employing seventeen ML models. After processing the sewer inspections, 1,159 of 1,449 individual pipelines were used to train the structural condition model. The performance of ML models was validated using the 290 remaining inspected sewer pipes. The area under the Receiver Operating Characteristic (AUC-ROC) curve and accuracy (ACC) showed that the Random Forest (AUC-ROC = 77.6% and ACC = 78.3%) is a sensitive model for predicting the condition of sewer pipes in the study area. Based on the RF model, maps of predicted conditions of sewers were generated that may be useful for utilities and water managers to establish future sewer system maintenance strategies.

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“…In northern Algeria, landslides are among the most damaging geohazards that threaten mountainous regions, hilly terrain, agricultural fields, and even urban areas, causing significant economic losses, material damage, and human casualties (Machane et al 2008;Djerbal and Melbouci 2012;Bougdal et al 2013;Hadji et al 2013;Bourenane et al 2014;Bourenane et al 2016;Achour et al 2017;Cheikh Lounis et al 2017;Hallal et al 2017;Hadji et al 2017;Meziani et al 2017;Mahdadi et al 2018;Merghadi et al 2018;Hallal et al 2019;Mezzereg et al 2019;Bourenane et al 2021aBourenane et al et 2021bGoumrasa et al 2021;Tebbouche et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

MOKADEM

Lounis

Machane³

et al. 2023

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Landslide susceptibility assessment and prediction are among the main processing for disaster management and land use planning activities. Therefore, the general purpose of this research was to evaluate GIS-based spatial modeling of landslides in the western Algiers province using five models, namely: frequency ratio (FR), weights of evidence (WoE), evidential belief function (EBF), logistic regression (LR) and analytical hierarchy process (AHP), then, compare their performances. At first, a landslide inventory map was prepared according to Google Earth satellite images, historical records, and extensive field surveys. The recorded landslides were divided into two groups (70% and 30%) to establish the training and validation models. In the next step, GIS techniques and remote sensing data were used, to prepare a spatial database containing thirteen landslide conditioning factors; lithology, distance to lithological boundaries, permeability, slope, exposure, altitude, profile curvature, plan curvature, precipitation, distance to rivers, TWI, NDVI, and distance to roads. Finally, the landslide susceptibility maps were produced using the five models and validated by the areas under the relative operative characteristic curve (AUC). The AUC results showed a significant improvement in susceptibility map accuracy, the FR model has the best performance in the training and prediction process (90%), followed by LR (88%, 89%), WoE (88%, 87%), EBF (86%,86%), and AHP (76%,75%), respectively. The produced maps in the current study could be useful for land use planning and hazard mitigation purposes in western Algiers province.

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Characterization of El Kherba landslide triggered by the August 07, 2020, Mw = 4.9 Mila earthquake (Algeria) based on post-event field observations and ambient noise analysis

Cited by 14 publications

References 52 publications

Synthesis on the Shear Wave Velocity of Engineering and Seismic Bedrocks in Northern Algeria based on Recent Experimental Investigations

Synthesis on the Shear Wave Velocity of Engineering and Seismic Bedrocks in Northern Algeria based on Recent Experimental Investigations

Comparison of Machine Learning Techniques for Condition Assessment of Sewer Network

Integration of multi-criteria decision analysis and statistical models for landslide susceptibility mapping in the western Algiers province (Algeria) using GIS techniques and remote sensing data

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