Structural and Geotechnical Vulnerability of Mosques in Fez, Morocco: An Integrated Analysis

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R. Harroucha
A.A. Chaouni
A.E. Ouardani
M.E. Alaoui

Abstract

The vulnerability assessment of mosques is a crucial topic due to the need to ensure the safety of worshipers and preserve culturally significant religious structures for Muslim communities and their cultural heritage. This study aims to evaluate the safety of 360 existing mosques in Fez, Morocco, and propose preventive measures to minimize the risks they face, taking into account natural risks related to the soil and subsurface, as well as the structural characteristics of the mosques. While previous studies have primarily focused on classifying structures based on seismic zones, this study takes into account five key natural risks (Floods, Landslides, Soil Liquefaction, Groundwater Rise and Soil Swelling) that influence stability. By combining geotechnical vulnerability assessment with structural vulnerability, the Analysis classifies mosques into distinct vulnerability levels, revealing that 47.8% (172 mosques) are highly vulnerable, 16.1% (58 mosques) have medium vulnerability, and 24.2% (87 mosques) exhibit moderate vulnerability. Only 9.4% (34 mosques) fall into the low vulnerability category, while a critical 1.5% (9 mosques) require emergency intervention due to extreme vulnerability. This classification enables decision-makers to prioritize prevention measures, emergency planning, and rehabilitation efforts based on quantified vulnerability levels. The proposed preventive measures, such as drainage systems for flood-prone mosques or slope stabilization for landslide-threatened mosques, are tailored to address each type of risk. The findings provide a replicable model for protecting religious and cultural heritage in other cities facing similar multi-hazard challenges.

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How to Cite
Harroucha, R., Chaouni, A., Ouardani, A., & Alaoui, M. (2025). Structural and Geotechnical Vulnerability of Mosques in Fez, Morocco: An Integrated Analysis. International Journal of Geoinformatics, 21(6), 79–89. https://doi.org/10.52939/ijg.v21i6.4237
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