Machine Learning-Based Flood Susceptibility Mapping Using Geoenvironmental Factors in Central Morocco

Key Points

• Flood susceptibility mapping indicates significant risk areas based on geoenvironmental factors.
• The analysis shows a 35% higher prediction accuracy using machine learning techniques compared to traditional methods.
• Mapping employs advanced algorithms to integrate geoenvironmental data for robust flood risk assessment.
• Implications highlight the need for improved flood management practices; further validation in diverse environments is essential.