Engineering Geology

Engineering Geology

Seismic Risk Assessment and Zoning in Urban Environments Using Spatial Multi-Criteria Analysis: A Case Study of Manjil, Iran

Authors
Manoochehr Mortazavi Chamchali 1
Ghazaleh Mohebbi Tafreshi 2
Amin Mohebbi Tafreshi 3
1 Islamic Azad University
2 Kharazmi University
3 Alborz Regional Water Company
10.22034/JEG.2026.20.1.1020711
Abstract
Manjil City, situated in northern Iran, faces significant seismic risk due to its proximity to active fault systems and its role as a corridor for critical regional infrastructure. Past catastrophic events have underscored the necessity of robust spatial risk assessment to mitigate human, economic, and infrastructural impacts. This study presents a comprehensive seismic risk assessment and spatial zonation for Manjil using an integrated multi-criteria evaluation approach—coupling Geographic Information Systems (GIS), the Analytic Hierarchy Process (AHP), and fuzzy logic. Risk was modeled as a function of the interaction between seismic hazard potential and spatial vulnerability. Vulnerability indicators, including residential density, land-use patterns, and critical urban lifelines, were standardized and weighted through the AHP framework. Our findings indicate that high-density residential areas are the primary contributors to urban vulnerability, whereas critical infrastructure components are disproportionately vital during emergency response scenarios. For the hazard assessment, a range of proxies were analyzed, including proximity to faults, fault density, peak ground acceleration (PGA), active tectonic indices, topographic slope, and lithological characteristics. These parameters reveal heightened hazard levels in zones adjacent to active faults. By applying fuzzy membership functions and a gamma operator (γ=0.9), we generated an integrated earthquake risk map, classified into five vulnerability tiers ranging from ‘very low’ to ‘very high.’ The spatial analysis delineated four distinct high-risk focal zones within the urban footprint, driven by the convergence of elevated seismic hazards and dense concentrations of residential and critical infrastructure. This research demonstrates the efficacy of the GIS–AHP–Fuzzy integration in providing a reliable, data-driven framework for evidence-based urban planning and proactive seismic risk management in seismically prone regions.
Keywords
Earthquake risk
Manjil
GIS
AHP
Fuzzy logic
Fuzzy Gamma
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