Flood susceptibiliy mapping by using remote sensing and multi-criteria decision analysis: A case of M'goun geopark (Central High Atlas, Morocco)

Abstract

Floods are common natural hazards causing deaths, economic losses, and destruction of property. In Morocco, floods have become a structural phenomenon. In recent years, exceptional rainfall events have occurred in several regions of the country.With the climate change and weather variability, it may not be possible to prevent flooding. However, flood prevention and mitigation can be enhanced by flood susceptibility mapping.The present study aimed to identify flood susceptible areas in M'goun geopark (central High Atlas, Morocco) using the Analytic Hierarchy Process (AHP) method, which is an interactive decision-making approach under multi-criteria decision analysis.The historic flood data were collected from multi-source satellite images from 1995 to 2016. In this study, the flood inventory was prepared based on the floods that occurred in 1995, 2010, 2014, and 2015. The flood data were randomly classified as training data for mapping and testing data for model validation.The geomorphologic disposition to flooding is influenced by morphometric factors such as the lowest local height level, slope degrees below 10 °, no curvature of the terrain or high flow accumulation that can be derived from digital elevation models (Aster GDEM, SRTM-DEM, ALOS PALSAR-DEM) using GIS software. Further conditioning factor data were acquired from satellite images, topographic maps, geological maps and field work.The factors used to perform flood susceptibility mapping were elevation, slope, aspect, curvature, topographic wetness index, stream power index, rainfall, distance to rivers, stream density, lithology and land use. Digital image processing methods were used to derive the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) based on Landsat data, thus, gaining information of surface water bodies and soil moisture conditions.The relative importance of physical factors has been compared in a pairwise matrix to gain the weight values during the process of AHP model. The flood susceptibility zones have been mapped according to their weights.The validation of the model using the area under the curve revealed that the success rate is 85%, while the prediction rate is 88.5%, indicating this AHP method’s reliability.The results from this study can be useful for local authorities in the study area for flood mitigation. It will be also used for communicating flood risks to the communities around the floods prone areas of the central High Atlas with high touristic vocation.