Flood Susceptibility Assessment through Statistical Models and HEC-RAS Analysis for Sustainable Management in Essaouira Province, Morocco

Abstract

Floods are natural disasters that often impact communities living in low-lying areas in the northern and central parts of Morocco. In this study, our aim was to create a flood susceptibility map using three methods; the hierarchy process (AHP) frequency ratio model (FR) and the weights of evidence (WoE) model. We extensively examined the area identified by these approaches using a hydraulic analysis software called HEC-RAS (version 6.3.1). Our analysis focused on the Essaouira watersheds in Morocco, where we identified around 197 flood locations. Out of these, we randomly selected 70% for modeling purposes while the remaining 30% were used for validation. Ten factors that influence floods were considered, such as slope, elevation, proximity to rivers, drainage density, stream order, land use patterns, rainfall data, lithology (permeability level) index (TWI), and curvature. We obtained these factors from data sources. Finally, we generated a flood susceptibility map and evaluated its accuracy by calculating the area under the curve (AUC). The validation results confirmed that all three models were robust and effective with an AUC of 90. Moreover, the research uncovered a trend of vulnerability with the most susceptible area being in close proximity to the city of Essaouira along the Oued Ksob. A detailed analysis using HEC-RAS was conducted at this identified location, pinpointing the village of Diabat as highly exposed. These findings hold significance for flood management, empowering decision makers, scholars, and urban planners to make informed choices and implement strategies that can minimize the impact of floods in susceptible regions while minimizing potential damages.