Uatzau basin in northwestern Ethiopia is one of the most landslide-prone regions, which characterized by frequent high landslide occurrences causing damages in farmlands, non-cultivated lands, properties, and loss of life. Preparing a Landslide susceptibility mapping is imperative to manage the landslide hazard and reduce damages of properties and loss of lives. GIS-based frequency ratio, information value, and certainty factor methods were applied. The landslide inventory map was prepared from detailed fieldwork and Google Earth imagery interpretation. Thus, 514 landslides were mapped, and out of which 359 (70%) of landslides were randomly selected keeping their spatial distribution to build landslide susceptibility models, while the remaining 155 (30%) of the landslides were used to model validation. In this study, six factors, including lithology, land use/cover, distance to stream, slope gradient, slope aspect, and slope curvature were evaluated. The effects of the landslide factor of slope instability were determined by comparing with landslide inventory raster using the GIS environment. The landslide susceptibility maps of the Uatzau area were categorized into very low, low, moderate, high and very high susceptibility classes. The landslide susceptibility maps of the three models validated by the ROC curve. The results for the area under the curve (AUC) are 88.83% for the frequency ratio model, 87.03% for certainty factor, and 84.83% of information value models, which are indicating very good accuracy in the identification of landslide susceptibility zones of a region. From these resulted maps, it is possible to recommend, the statistical methods (Frequency Ratio, Information Value, and Certainty Factor Methods) are adequate to landslide susceptibility mapping. The landslide susceptibility maps can be used for regional land use planning and landslide hazard mitigation purposes.

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Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia

Landslides are one of the natural disasters that affect socioeconomic wellbeing. Accordingly, this work aimed to realize a landslide susceptibility map in the coastal district of Mostaganem (Western Algeria). For this purpose, we applied a knowledge-driven approach and the Analytical Hierarchy Process (AHP) in a Geographical Information System (GIS) environment. We combined landslide-controlling parameters, such as lithology, slope, aspect, land use, curvature plan, rainfall, and distance to stream and to fault, using two GIS tools: the Raster calculator and the Weighted Overlay Method (WOM). Locations with elevated landslide susceptibility were close the urban nucleus and to a national road (RN11); in both sites, we registered the presence of strong water streams. The quality of the modeled maps has been verified using the ground truth landslide map and the Area Under Curve (AUC) of the Receiver Operating Characteristic curve (ROC). The study results confirmed the excellent reliability of the produced maps. In this regard, validation based on the ROC indicates an accuracy of 0.686 for the map produced using a knowledge-driven approach. The map produced using the AHP combined with the WOM showed high accuracy (0.753).

https://www.mdpi.com/2071-1050/13/2/630/pdf

GIS-Based Expert Knowledge for Landslide Susceptibility Mapping (LSM): Case of Mostaganem Coast District, West of Algeria

Abstract. On 1 October 2009, a prolonged and intense rainstorm triggered hundreds of landslides (predominantly debris flows) in an area of about 50 km2 in the north-eastern sector of Sicily (Italy). Debris flows swept the highest parts of many villages and passed over the SS114 state highway and the Messina-Catania railway, causing more than 30 fatalities. This region has a high relief, due to recent uplift. The peculiar geological and geomorphological framework represents one of the most common predisposing causes of rainstorm-triggered debris flows. This paper deals with the geological and hydro-geomorphological studies performed as a part of the post-disaster activities operated in collaboration with Civil Protection Authority, with the aim at examining landslides effects and mechanisms. The data were elaborated into a GIS platform, to evaluate the influence of urbanisation on the drainage pattern, and were correlated with the lithological and structural framework of the area. Our study points at the evaluation of the volume involved, the detection of triggering mechanisms and the precise reconstruction of the influence of urbanisation as fundamental tools for understanding the dynamics of catastrophic landslides. This kind of analysis, including all the desirable approaches for the correct management of debris flow should be the starting point for robust urban planning.

https://flore.unifi.it/bitstream/2158/922530/1/Del%20Ventisette%20et%20al%20GRA%20vol%2015%20EGU%202013.pdf

Catastrophic debris-flows: geological hazard and human influence

Karst aquifers supply an important freshwater resource for MENA (Middle East and North Africa) semi-arid regions. Their functioning conditions reveal often several contaminations. The Cheria carbonate aquifer (NE Algeria) has never had management tools to deal with the pollution of this resource. The outlining and protection of the vulnerable areas are essential to ensure the water purity and the consumer health. Based on the EPIK multicriteria analysis method, we aim in our study to assess the karstic aquifers intrinsic-vulnerability to contamination in the Cheria Plateau. This method has been already applied for contamination problems in Northeast Algeria. It uses a conceptual scheme that considers epikarst, protective cover, infiltration, and karst network as parameters. In addition, it also uses the interpolation of the geophysics data to define the conditioning attributes. The resulting vulnerability map categorizes all the basin vulnerable areas and the groundwater protection zones. Nearly 30% of the study area was judged as highly vulnerable to anthropogenic pollution, whereas around 10% is moderately vulnerable. These results confirm that the karst aquifer of the Cheria Plateau is severely polluted by chemical pesticides resulting from farming activity. In addition to the surrounding agricultural lands, the underground of Cheria city was found as extremely vulnerable to pollution (F < 19). Our study delimited boundaries for the karst aquifer protection zones and for an integrated resource management in this region. It recommends applying this method for comparable problems.

The EPIK multi-attribute method for intrinsic vulnerability assessment of karstic aquifer under semi-arid climatic conditions, case of Cheria Plateau, NE Algeria

Modelling of potential groundwater artificial recharge in the transboundary Algero-Tunisian Basin (Tebessa-Gafsa): The application of stable isotopes and hydroinformatics tools*

Effects of clay properties in the landslides genesis in flysch massif: Case study of Aïn Draham, North Western Tunisia

Abstract The Tunisian North-western region, especially Tabarka and Ain-Drahim villages, presents many landslides every year. Therefore, the landslide susceptibility mapping is essential to frame zones with high landslide susceptibility, to avoid loss of lives and properties. In this study, two bivariate statistical models: the evidential belief functions (EBF) and the weight of evidence (WoE), were used to produce landslide susceptibility maps for the study area. For this, a landslide inventory map was mapped using aerial photo, satellite image and extensive field survey. A total of 451 landslides were randomly separated into two datasets: 316 landslides (70%) for modelling and 135 landslides (30%) for validation. Then, 11 landslide conditioning factors: elevation, slope, aspect, lithology, rainfall, normalized difference vegetation index (NDVI), land cover/use, plan curvature, profile curvature, distance to faults and distance to drainage networks, were considered for modelling. The EBF and WoE models were well validated using the Area Under the Receiver Operating Characteristic (AUROC) curve with a success rate of 87.9% and 89.5%, respectively, and a predictive rate of 84.8% and 86.5%, respectively. The landslide susceptibility maps were very similar by the two models, but the WoE model is more efficient and it can be useful in future planning for the current study area.

Zorgati Anis

Papers

Effects of clay properties in the landslides genesis in flysch massif: Case study of Aïn Draham, North Western Tunisia

GIS-based landslide susceptibility mapping using bivariate statistical methods in North-western Tunisia