Morocco AI Flood Prediction Technology Outperforms Spain

The effectiveness of this system was verified during the major floods that occurred between January and February 2026. Continuous rainfall, river overflow and dam releases caused significant damage and forced the evacuation of thousands of people. Satellite imagery confirmed that the submerged areas corresponded exactly to the sectors previously identified as high-risk by the system, whose Multilayer Perceptron artificial neural network displays 91% accuracy.

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This predictive program was designed by researchers from Abdelmalek Essaadi and Mohamed V universities. The scientists focused their efforts on the Loukkos basin. Their study area targets the agricultural plain located between Ksar el Kebir and Larache, a zone highly vulnerable due to its low altitude, proximity to waterways and frequent winter storms.

To assess vulnerabilities, experts combined images provided by European Sentinel satellites with machine learning algorithms. They used spatial radars capable of detecting water-covered surfaces through cloud cover. The machine analyzes various geographical variables such as altitude, slope, distance from the river, drainage density and potential precipitation accumulation.

This technological advance is being closely followed on the other side of the Mediterranean. The newspaper El Español indicates that this Moroccan initiative gives a real lesson to Spain. The Iberian peninsula, still very reactive to emergencies, recently suffered devastating episodes of cold drop (DANA) resulting in heavy flooding, particularly in the Valencia region.

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Anticipating water rise allows for establishing a genuine prevention strategy. Precisely identifying threatened infrastructure, neighborhoods and fields facilitates the prioritization of public investments. This targeting data also offers the possibility of optimizing evacuation plans and prohibiting future construction in the most exposed perimeters.