Warianty tytułu
Języki publikacji
Abstrakty
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.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
2307--2323
Opis fizyczny
Bibliogr. 90 poz., rys., tab.
Twórcy
autor
- GEOMODELE Laboratory, Faculty of Sciences, University of Sfax, BP 1171, 3000 Sfax, Tunisia
autor
- GEOMODELE Laboratory, Faculty of Sciences, University of Sfax, BP 1171, 3000 Sfax, Tunisia
autor
- Laboratory of Management, Maintenance and Rehabilitation of Facilities and Urban Infrastructure, University Kasdi Merbah Ouargla, Ouargla, Algeria
autor
- Institute of Applied Technology, Thu Dau Mot University, Thu Dau Mot, Binh Duong Province, Vietnam, phambaoquoc@tdmu.edu.vn
autor
- GEOMODELE Laboratory, Faculty of Sciences, University of Sfax, BP 1171, 3000 Sfax, Tunisia
Bibliografia
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-37088e1c-e0a9-4997-89b7-7caa8452f72e