Geomorphological hazards in a Mediterranean mountain environment - Example of Tétouan, Morocco

Prokos, Hedvig; Baba, Hasnaa; Lóczy, Dénes; Kharim, Younès El

doi:10.15201/hungeobull.65.3.6

Cited by 10 publications

(7 citation statements)

References 11 publications

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“…The predictor variables were chosen according to their expected influence on slope instability and to their control on slope failure mechanisms (e.g., Conoscenti, C. et al 2015;Cama, M. et al 2016;Prokos, H. et al 2016).…”

Section: Predictorsmentioning

confidence: 99%

Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logistic Regression (BLR)

et al. 2018

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In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an inventory of debris flows triggered by the passage of the hurricane IDA and the low-pressure system associated with it 96E, on 7 th and 8 th November 2009, in an area of about 26 km 2 close to the Caldera Ilopango, El Salvador (CA), was employed. Two validation strategies have been applied to both statistical techniques, thus obtaining four models -BLR (I), MARS (I), BLR (II) and MARS (II) -to be compared in pairs. Model performance was assessed in terms of AUC (area under the receiver operating characteristic (ROC) curve), Sensitivity, Specificity, Positive Prediction Value and Negative Prediction Value. Moreover, to evaluate the robustness of the modelling procedure, 50 replicates were created for each model and standard deviation was calculated for each of them. The results show that both techniques allow for obtaining good or excellent performances so that it is not possible to define one of the two techniques as absolutely better. However, the validation procedure reveals slightly better performance of the MARS models, with greater sensitivity and greater discrimination among True Negatives (TNs).

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Section: Predictorsmentioning

confidence: 99%

Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logistic Regression (BLR)

et al. 2018

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“…In the field, there are MM activated by mostly anthropogenic activities (excavations, overweight, disturbance of pipelines) in several urban centers in the various urban municipalities of Tétouan Province. In addition, urban extensions are carried out in areas of stability, precarious and not previously developed by the urban agency (El Kharim 2012;Ait Brahim et al 2002;Fonseca 2014;PATEAU 2014;PROkOS et al 2016;Ait Brahim et al 2018). 1-The susceptibility map of mass movements shows between the cities of Tétouan and Fnidek in the North, the presence mainly of a hazard zone between high and moderate (4 and 3) that encompasses the Tétouan Cluse and along the Mediterranean coast (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…11) on construction, tourist infrastructure, the A6 auto-road and the RN 13 national road in the Gabo Negro, M'diq, Jbel Zem and Fnidek region (Fig. 9) (El Kharim 2012;Fonseca 2014;PATEAU 2014;PROkOS et al 2016;Ait Brahim and Elmoulat 2018). 2-The MMS map also shows, south of Tétouan (on 70% of the province's surface) the presence of the largest hazard zone between very high and high (5 and 4).…”

Section: Discussionmentioning

confidence: 99%

Mass movements susceptibility mapping by using heuristic approach. Case study: province of Tétouan (North of Morocco)

Elmoulat

Brahim

ElMahsani

et al. 2021

Geoenviron Disasters

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This research paper aims to model Mass Movements Susceptibility (MMS) in the province of Tétouan. First, we identified the characteristics and spatial mapping of the different types of MM (collapse, mudflows, and complex landslides) by means of the interpretation of satellite images and from fieldwork. Subsequently, we selected the predictive parameters controlling the occurrence of MM e.g. lithology, land use, fault density, hydrographic network density, slope degrees, slope aspects, and elevation. We used the heuristic method for Modeling Mass Movements Susceptibility (MMMS). The choice of this method compared to other methods (fractal, factorial, and neurons) is justified by the possibilities of intervention and the judgment of the expert who relies on the ground truth to select the parameters, to identify the classes, and to assign the weights to each one; unlike to other methods with steps that are done automatically and randomly. The results of the validation of the susceptibility map correspond to 70% compared to the field data and it includes five susceptibility classes (not susceptible, low, moderate, high, and very high). Indeed, the originality of this paper relies on the fact that the creation of our susceptibility map will eventually indicate the areas of roads, dwellings, the extension of urbanization, and dams, which are located in areas at risk of MM. Our map is also a powerful decision-making tool to conduct management plans and to guide the selection of sites to build new projects; which help mitigate the socio-economic impacts usually encountered when mass movements in Tétouan province are triggered.

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“…In Morocco, the areas subjected to the ground movements are mostly the Rif (El-Fengour 2016; Prokos et al 2016;Benzougagh et al 2017) and to a lesser extent the Middle Atlas, due to the existence of reliefs with much contrasted geological formations (friable clays, flysch units, marl, etc.) and difficult climatic conditions.…”

Section: Introductionmentioning

confidence: 99%

GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco)

Jazouli

Barakat

Khellouk

2019

Geoenviron Disasters

158

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Background: High basin of Oum Er Rbia River, which is located in Middle Atlas Mountain region, is prone to landslide problems due to the geological features combined with the climate change and human activities. The present work including inventory mapping was conducted to establish landslide susceptibility map using GIS-based spatial multicriteria approach. Eight landslide-related factors, including land cover, lithology, distance to road, distance to fault, distance to drainage network, elevation, aspect and slope gradient, were selected for the present assessment. Weight for each factor is assigned using Analytic Hierarchy Process (AHP) depending on its influence on the landslide occurrence. The landslide susceptibility map was derived using weighted overlay method and categorized into five susceptible classes namely, very low (VL), low (L), moderate (M), high (H). Result: The results revealed that 30.16% of the study area is at very low risk, 12.66% at low risk, 25.75% of moderate risk, 22.59% of high risk and 9.11% of very high risk area coverage. The very high landslide vulnerability zones are more common within the river valleys on steep side slopes. Most landslides also involve rocks belonging to the Triassic weathered marl and clay-rich formation. Moreover, human activities namely the construction and the expansion of agricultural lands into forests intervene in inducing landslides through altering the slope stability along the river banks. Lastly, effectiveness of these results was checked by computing the area under ROC curve (AUC) that showed a satisfactory result of 76.7%. Conclusions: The landslide susceptibility map of the Oum Er Rbia high basin provides valuable information about present and future landslides, which makes it viable. Such map may be helpful for planners and decision makers for land-use planning and slope management.

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Geomorphological hazards in a Mediterranean mountain environment - Example of Tétouan, Morocco

Cited by 10 publications

References 11 publications

Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logistic Regression (BLR)

Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logistic Regression (BLR)

Mass movements susceptibility mapping by using heuristic approach. Case study: province of Tétouan (North of Morocco)

GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco)

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