Multivariate Analysis and Machine Learning Approach for Mapping the Variability and Vulnerability of Urban Flooding: The Case of Tangier City, Morocco

Marc Leblanc,Tarik Bouramtane,Moad Morarech,Maryam Aziz,Ilias Kacimi,Tarik Bahaj,Shiny Abraham,Laurent Barbiero,Vincent Valles,Khalid Omari,Nadia Kassou,Khalil Bouramtane,Suzanne Yameogo,Omar El Beqqali

doi:10.3390/hydrology8040182

Abstract

Urban flooding is a complex natural hazard, driven by the interaction between several parameters related to urban development in a context of climate change, which makes it highly variable in space and time and challenging to predict. In this study, we apply a multivariate analysis method (PCA) and four machine learning algorithms to investigate and map the variability and vulnerability of urban floods in the city of Tangier, northern Morocco. Thirteen parameters that could potentially affect urban flooding were selected and divided into two categories: geo-environmental parameters and socio-economic parameters. PCA processing allowed identifying and classifying six principal components (PCs), totaling 73% of the initial information. The scores of the parameters on the PCs and the spatial distribution of the PCs allow to highlight the interconnection between the topographic properties and urban characteristics (population density and building density) as the main source of variability of flooding, followed by the relationship between the drainage (drainage density and distance to channels) and urban properties. All four machine learning algorithms show excellent performance in predicting urban flood vulnerability (ROC curve > 0.9). The Classifications and Regression Tree and Support Vector Machine models show the best prediction performance (ACC = 91.6%). Urban flood vulnerability maps highlight, on the one hand, low lands with a high drainage density and recent buildings, and on the other, higher, steep-sloping areas with old buildings and a high population density, as areas of high to very-high vulnerability.

Highlights

The year of 2021 was marked by a succession of natural disasters, of which urban flooding was a major event in several parts of the world, such as the February floods inNorth Africa that affected several cities in northern Morocco, the July floods that devastated Western Europe (Germany, France, Switzerland, Belgium, Italy, Netherlands, Romania and United Kingdom) and the flooding caused by Hurricane Ida in New York City in August
These natural disastrous events demonstrate that in the current climate context, in one way or another, all cities are vulnerable to urban flooding, and city dwellers are at high risk, regardless of whether they are in a developed or developing region of the world [1,2,3]
The occurrence of urban flooding is linked to rapid urban development, in developing countries, where uncontrolled growth of urban areas is often accompanied by human encroachment on the active flood channel, changes in drainage networks morphology and low infiltration or storage capacity during heavy rainfall [5,6]

Summary

Introduction

North Africa that affected several cities in northern Morocco, the July floods that devastated Western Europe (Germany, France, Switzerland, Belgium, Italy, Netherlands, Romania and United Kingdom) and the flooding caused by Hurricane Ida in New York City in August These natural disastrous events demonstrate that in the current climate context, in one way or another, all cities are vulnerable to urban flooding, and city dwellers are at high risk, regardless of whether they are in a developed or developing region of the world [1,2,3]. The variability in conditions that influence flood vulnerability in different urban areas has not been comprehensively examined

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