Applied Machine Learning for Flood Susceptibility Mapping in the Loukkos Basin (Northern Morocco): Validation Using the February 2026 Ksar El Kebir Flood Event

Abstract. Flooding is a recurrent hazard in northern Morocco, where low-lying alluvial plains, strong river–floodplain connectivity, and winter storm sequences combine to produce damaging floods. This study develops an event-informed flood susceptibility assessment for the Loukkos Basin (Ksar El Kebir–Larache floodplain) by integrating satellite-derived flood evidence with geomorphometric and hydro-climatic predictors in a machine-learning framework. A binary flood inventory was derived from Sentinel-1 SAR change detection by contrasting pre-flood (October–November 2022) and flood-phase acquisitions (December 2022), and was validated using Sentinel-2 optical observations and field checks. Nine conditioning factors (elevation, slope, aspect, curvature, distance to rivers, drainage density, TWI, TPI, and CHIRPS-based rainfall) were compiled and standardized on a 10 m grid. Model training used a balanced sample of 220 points (110 flooded/110 non flooded) and was evaluated with a repeated hold-out strategy (10 iterations; 80 % training/20 % testing) using accuracy, precision, recall, and F1-score. Both Random Forest (RF) and Multilayer Perceptron (MLP) produced coherent susceptibility patterns, with the highest classes concentrated along the Loukkos river corridor and downstream floodplains. Mean test performance indicates strong generalization, with MLP outperforming RF (accuracy ≈ 0.909 vs. 0.864; F1 ≈ 0.909 vs. 0.870). Jackknife sensitivity analysis identifies elevation as the leading control for both models, while RF emphasizes terrain metrics (slope, drainage density) and MLP assigns a more balanced importance to topography and hydrological drivers (TPI, rainfall, distance to channel). Notably, flooded areas observed during the January–February 2026 flood episode (Sentinel imagery dated 14 February 2026) largely coincide with zones mapped as high susceptibility, providing an independent, qualitative post-study consistency check. The resulting maps offer a practical inspection tool to support land-use planning and prioritization of mitigation actions across the most flood-prone sectors of the Loukkos Basin.