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  • Comprehensive flood control is needed because flooding can be catastrophic for people's lives and ways of living. This management must provide information on the hydrologic, geotechnical, environmental, social, and economic elements of floods. This work created maps for the flood susceptibility of the M'zab Valley using logistic regression (LR) and frequency ratio (FR). The main objective of the research was to strengthen the bivariate probability capabilities of FR and LR. A flood inventory map was created by extracting flood sites from multiple sources. The flood inventory was divided randomly into two parts: 30% was used for validation and the remaining 70% was used to train the models. Independent variable datasets included the distance from the river, rainfall, soil type, land use/land cover (LULC), elevation, drainage density, flow accumulation, and slope. The effect of each variable on flooding was assessed by comparing each independent variable with the dependent flood layer. The flood susceptibility map was assessed using the prediction rate approach on the validation dataset, which was not used for model construction. The accuracy assessment's findings revealed a prediction rate of FR 0.86 and LR 0.881, as well as a success rate of FR 0.924 and LR 0.924.

  • The objective of the present work is to create a geospatial map that assesses the risk of flooding in the Oud M’zab region, by integrating various parameters derived from remote sensing data (soil and land use land cover) and multi-source data (including topography, hydrographic networks, and lithology). Flooding is a significant concern in various sectors, including industrial, urbanization, hydraulic works, and road structures. This study focuses on hydrological modelling approaches to simulate flooding areas in the Oued M’zab region, bases on a peak flow and recorded flood data to obtain a preliminary assessment of potential flooding.In order to validate the hydrological consistency of this work, the HEC-RAS 1D tools were employed. The result of this analysis revealed four flood risk classes, ranging from low to high risk. The risk of flooding is particularly higher in the area where the banks and the river-beds are occupied by the urban population, while it tends to decrease while moving away from Oued and valley.

Dernière mise à jour : 12/06/2026 23:00 (UTC)

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