首页|Enhancing flood risk assessment in northern Morocco with tuned machine learning and advanced geospatial techniques

Enhancing flood risk assessment in northern Morocco with tuned machine learning and advanced geospatial techniques

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Mapping floods is crucial for effective disaster management.This study focuses on flood assessment in northern Morocco,specifically Tangier,Tetouan,and Larache.Due to the lack of a comprehensive flood inventory map,we used unsupervised learning techniques,such as K-means clustering and fuzzy logic algorithms,to predict flood-prone areas.We identified nine conditioning factors influencing flood risk:elevation,slope,aspect,plan cur-vature,profile curvature,land use,soil type,normalized difference vegetation index(NDVI),and topographic position index(TPI).Using Landsat-8 imagery and a Digital Elevation Model(DEM)within a Geographic Information System(GIS),we analyzed topographic and geo-environmental variables.K-means clustering achieved silhouette scores of 0.66 in Tangier and 0.70 in Tetouan,while the fuzzy logic method in Larache produced a Da-vies-Bouldin Index(DBI)score of 0.35.The maps classified flood risk levels into low,mod-erate,and high categories.This research demonstrates the integration of machine learning and remote sensing for predicting flood-prone areas without existing flood inventory maps.Our findings highlight the main factors contributing to flash floods and assess their impact,enhancing the understanding of flood dynamics and improving flood management strategies in vulnerable regions.

remote sensingconditioning factorsGISflood susceptibilitymachine learningDEM

MOUTAOUAKIL Wassima、HAMIDA Soufiane、SALEH Shawki、LAMRANI Driss、MAHJOUBI Mohamed Amine、CHERRADI Bouchaib、RAIHANI Abdelhadi

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EEIS Laboratory,ENSET of Mohammedia,Hassan Ⅱ University of Casablanca,Mohammedia,Morocco

2IACS Laboratory,ENSET of Mohammedia,Hassan Ⅱ University of Casablanca,Mohammedia,Morocco

GENIUS Laboratory,SupMTI of Rabat,Rabat,Morocco

STIE Team,CRMEF Casablanca-Settat,Provincial Section of El Jadida,El Jadida,Morocco

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2024

10.1007/s11442-024-2301-4

地理学报(英文版)
中国地理学会,中国科学院地理科学与资源研究所

地理学报(英文版)

CSTPCD
影响因子：1.307
ISSN：1009-637X
年,卷(期)：2024.34(12)