Flood susceptibility mapping using qualitative and statistical methods in a semi-arid basin: case of the Manouba–Sijoumi watershed, Northeastern Tunisia

Floods are considered among the gravest natural disasters worldwide and have resulted in enormous human and material damage. The Manouba–Sijoumi basin (Northeast of Tunisia) is often flooded due to urban expansion, population growth and unplanned land use. This study aims to identify and to define t...

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Bibliographic Details
Published in:	Acta geophysica Vol. 71; no. 5; pp. 2307 - 2323
Main Authors:	Khadraoui, Nahed, Dahri, Noura, Bouamrane, Ali, Pham, Quoc Bao, Abida, Habib
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01-10-2023 Springer Nature B.V
Subjects:	Decision analysis Disaster management Earth and Environmental Science Earth Sciences Environmental management Environmental risk Flood mapping Flood risk Floods Geographic information systems Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Land use Modelling Natural disasters Population growth Qualitative analysis Remote sensing Research Article - Hydrology Statistical methods Statistical models Structural Geology Urban areas Urban development Urban environments Urban sprawl Urbanization Tunisia GIS ANP Flood susceptibility Manouba Sijoumi watershed ROC curve FR
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Summary:	Floods are considered among the gravest natural disasters worldwide and have resulted in enormous human and material damage. The Manouba–Sijoumi basin (Northeast of Tunisia) is often flooded due to urban expansion, population growth and unplanned land use. This study aims to identify and to define the flood-prone areas of this basin for the 2003 and 2018 extreme events based on a Geographic Information System, a qualitative method (analytic network process-ANP) and a statistical model (frequency ratio-FR). The flood risk maps obtained by both models were validated using the receiver operating characteristic, the area under the curve (AUC) and inventory map. Areas of high and very high flood sensitivity are located mainly in urban settings, with an increase in risk between 2003 and 2018. The AUC values for both models were of the same significance (98%) for the year 2003 while those for the year 2018 were 94% and 98% for the ANP and FR models, respectively. This would imply that both models yielded reasonable results. However, the FR model showed an ability to reduce the uncertainty associated with expert judgements. The results indicate that the most influential factor on flooding in this area was land use/cover. Indeed, populations were largely settled in unsuitable sites for urbanization and in potentially flood-prone areas located mainly around the Sijoumi Sebkha, especially to the west and south of it. The findings of the study are of great value for policy makers and state authorities to achieve greater awareness and adopt strategies for environmental preparedness and management.
ISSN:	1895-7455 1895-6572 1895-7455
DOI:	10.1007/s11600-022-00966-6