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Dr. Ehsan Pegah,
Volume 17, Issue 1 (3-2023)
Abstract
The ratios of elastic shear stiffness anisotropy and fabric anisotropy in granular soils are of very important characteristics in soil mechanics, which can influence directly lots of geotechnical engineering attributes. The shear stiffness anisotropy in a soil mass is directly related to the soil fabric anisotropy, which in turn has a fundamental contribution in variations model of shear stiffness anisotropy ratio. The main objective of this study is to evaluate the variations ranges of shear stiffness and fabric anisotropy ratios in granular soils by developing a novel approach for estimating fabric anisotropy ratio from soil grading and particles shape properties. By presuming cross-anisotropy, the anisotropic shear stiffness values of 1042 conducted tests on 200 distinct sandy and gravelly soil specimens from 43 various soil types of diverse sites throughout the world were acquired from literature. Those were then integrated with their associated void ratios, stress conditions, grading parameters and particles shape specifications to produce a comprehensive database of anisotropic shear moduli with respect to testing conditions. The collected data were analyzed, from which the shear stiffness and fabric anisotropy ratios could be calculated for examined geomaterials. The resulting values for fabric anisotropy ratio were then depicted versus grading and particles shape information to inspect the level of dependences through deriving the respective correlations. The findings of this study may serve as a suitable technique to obtain first-order approximations for fabric and shear stiffness anisotropies from soil grading and particles shape characteristics.
Ehsan Pegah,
Volume 17, Issue 2 (9-2023)
Abstract
The ratios of elastic anisotropy in cohesionless soils are always of substantial importance in respective analyses to the geotechnical and geological engineering projects. These ratios are raising from the available discrepancies in anisotropic elastic parameters ascribed to the different directions and planes of soil mass. The major objective of this study is to recognize the variations range of anisotropy ratios resulting from anisotropic shear and Young’s moduli for a variety of cohesionless soils followed by assessing the potential relations among these two anisotropies. To this end, by assuming the transversely isotropy in cohesionless soils, the anisotropic elastic constants from 266 conducted laboratory tests on 37 various soil specimens relating to 10 different sands were derived from conventional triaxial and seismic waves laboratory tests coupled with the numerical testing results in literature. By sorting the collected data and subsequently their analyses, at the first stage, the values of shear and Young’s moduli anisotropy ratios were calculated for the studied soils. Furthermore, by plotting the anisotropy ratios in several joint panels and performing a series of regression analyses on the resulting values, the possible dependencies were inspected between these two anisotropies. At last, the indicative equations among shear and Young’s moduli anisotropies were developed with insistence on use of which instead of the former similar relations in literature.
Tahereh Azari, Sakineh Dadashi, Fatemeh Kardel,
Volume 17, Issue 2 (9-2023)
Abstract
Qualitative assessment of coastal waters affected by seawater salinity can be done using the parameter of chloride in groundwater. This research proposes a supervised artificial intelligence committee machine (SAICM) method for accurate prediction of chloride concentration in groundwater of Sari plain. SAICM predicts chloride concentration as the output of the model by non-linear combination of artificial intelligence models. In this research, Principal Component Analysis (PCA) method was used to identify effective hydrochemical parameters related to chloride concentration as input components to artificial intelligence models. Based on the results of PCA, parameters (Na, K, EC, TDS, SAR) were selected as input components of artificial intelligence models. Firstly, four artificial intelligence models, Sogno fuzzy logic, Mamdani fuzzy logic, Larsen fuzzy logic and artificial neural network were designed to predict chloride concentration. Based on the modelling results, all the models showed a good fit with the chloride data in Sari Plain. Then, the combined SAICM model was built, which combines the prediction results of 4 separate AI models using the nonlinear ANN combiner and determines the chloride concentration more accurately. The results show that the proposed SAICM can estimate chloride concentration with much higher accuracy than individual methods.
Majid Dashti Barmaki, Zahra Yazdani Barmaki, Massoud Morsali,
Volume 17, Issue 4 (12-2023)
Abstract
In order to design and optimize the quality monitoring network in areas with several sub-basins, it is necessary to know the criteria that affect them, so that in each sub-basin the presence or absence of a monitoring station and the required parameters can be determined. In this respect, the use of the surface water pollution index, namely WRASTIC, can be effective. The WRASTIC model is a practical and advanced method for assessing the risk and potential of pollution in sub-basins. Due to its role in the drinking water supply of the city of Bandar Abbas, monitoring the quality of the Shamil-Takht study area is very beneficial. Therefore, to assess the risk of pollution in this plain, the basin was divided into 16 sub-basins using Global Mapper software. The WRASTIC index was presented as different layers of information, and its value was calculated for each sub-basin by rating by expert judgement method, weighting by hierarchical analysis method, and merging layers using weighted overlap. The results showed that three sub-basins have high risk and three sub-basins have low risk. Then, according to the condition of the streams in each sub-basin, the pollution index and its importance, the number of quality monitoring stations and the necessary parameters in this area were determined. Accordingly, five stations were added to the existing ten hydrometric stations at different locations. In the final 15 stations, the measurement of general parameters and major ions was included in the proposed agenda. The measurement of parameters such as phosphate/phosphorus and nitrate/nitrite was also included in six sub-basins, and heavy metals in three sub-basins.
Prof. Mohammad Nakhaei, Dr. Amin Mohebbi Tafreshi, Dr. Tofigh Saadi,
Volume 17, Issue 4 (12-2023)
Abstract
A sharp drop in groundwater level as a result of indiscriminate extraction over a long period of time leads to the drying up of groundwater flows, which is called the phenomenon of groundwater drought. In this regard, this research aims to investigate the process of change and reduction of groundwater level, which is characterised by the phenomenon of groundwater drought. Based on this, the Groundwater Resource Index (GRI) was used to evaluate the drought condition of groundwater and analyse its spatial and temporal patterns based on groundwater level data of 21 observation wells between 1993 and 2019. ArcGIS software was used to create zone maps. The results of the research show that certain areas of the study area have experienced moderate to severe drought since 2001. In addition, the GRI zonation maps show that the southern and south-eastern regions of the aquifer have been more sensitive to drought than other parts of the aquifer during the defined period. The spatio-temporal pattern of groundwater drought in the aquifer shows that after a period of moderate drought from 2001 to 2003, the condition of the aquifer improved slightly, and generally stable conditions were established from 2001 to 2010, but since 2011, the occurrence of drought has intensified and the aquifer has been in severe to very severe drought conditions. These conditions highlight the need for careful attention and implementation of management measures. One of the study's recommendations is to use satellite data on groundwater levels to assess the progress of the drought, and compare it with the findings of this study.
Mohammad Zainali, Dr Mohammad Reza Asef, Dr Ruholah Nadri,
Volume 18, Issue 1 (5-2024)
Abstract
This paper investigates the application of geomechanical and geological engineering methods to determine the optimum working face width for the safe and efficient extraction of manganese ore extraction at the Venarch Mine (Qom Province, Central part of Iran). The underground workings on the west face (240m depth) present significant geotechnical challenges due to the presence of faults, clay seams, and loose rock layers. These features require careful careful stability analysis to ensure the safety and economic viability of the underground mining operation. This study uses three established methods for rock mass classification and stability assessment. The Rock Mass Rating (RMR) classification system, the Q-system (Barton), and the numerical analysis using Plaxis 3D software. A robust and data-driven approach to determining the optimum workshop width was achieved by employing a synergistic combination of these three methods, together with meticulous ground observations and expert engineering judgement. This framework offers a powerful tool for determining the optimal and safe workshop width for this sector of the mine. By capitalizing on the strengths of each methodology, this research aims to establish a data-driven and informed decision-making process to ensure a stable and economically viable approach.
Seyyed Mahmoud Fatemi Aghda, Seyyed Sara Mousavi Herati, Mehdi Talkhablo, Amir Maziar Raeis Ghasemi,
Volume 18, Issue 2 (9-2024)
Abstract
The alkali-silica reaction of aggregates is one of the most significant factors in the destruction of concrete structures worldwide. This is due to chemical reactions between alkaline fluids in concrete voids and active silica minerals present in some aggregates. Considering that many physical, chemical and mechanical properties of concrete are related to aggregates, the role of aggregates in concrete is crucial. This research aims to investigate the compatibility of aggregate petrographic studies and accelerated prismatic mortar testing in predicting the reactivity of aggregates and determining the intensity of aggregate reactivity using the DRI index (a semi-quantitative complementary petrographic analysis). The study was carried out on laboratory samples of aggregates from mines around Tehran, using the ASTM C295, ASTM C1260 and ASTM C856-4 tests. The results showed that pyroclastic aggregates, which include sandy tuff, crystalline tuff (dacitic andesite) and glassy tuff, have the potential to cause an alkali-silica reaction due to their glassy background and microcrystalline silica. During the alkaline reaction tests of the aggregates, evidence of gel was found in cracks, holes and cement paste. In addition, the DRI index showed that the fine aggregates of both study areas were in the "slightly damaged" category and the coarse aggregates were in the "severely damaged" category.
Mr. Ehsan Pegah, Mr. Behrang Feiz Aghaei,
Volume 18, Issue 3 (12-2024)
Abstract
Random noise reduction has always been one of the most important issues in seismic data processing. This study investigates one of the most effective random noise reduction methods, the 2D multi-stage median filter. This filter is applied to seismic data by applying a series of 1D median filters in different directions and then selecting the output value corresponding to the center of the 2D window. By applying a 2D multi-stage median filter to both synthetic and real data, it is shown that the filter can effectively attenuate random spike-like noise in both pre-stack and post-stack data. Similarly, based on spectral analysis, it is shown that this filter does a good job of reducing the level of high frequency random noise in both synthetic and real data. In this study, a 2D median filter is applied to synthetic data containing random noise with a density of 10%. Since increasing the filter length can damage useful signals in addition to attenuating random noise, it is important to specify an appropriate filter length. For synthetic data, the error ratio plot shows that a filter length of 9 points is appropriate for the first stage. In the second stage, a 2D median filter with a length of 7 points was applied to the output of the first stage filter. The effect of this filter on random noise suppression can then be observed by spectral analysis. In addition, median filters of 7 points and 5 points were applied to the pre-stack and post-stack real data, respectively. The effect and efficiency of this filter is assessed by examining the resulting difference plots, sections and spectral analysis.
Dr Ali Ghanbari, Fatemeh Mirdar,
Volume 18, Issue 4 (12-2024)
Abstract
Examining the seismic response of the ground surface and its impact on structures due to topographic effects and soil-structure interaction (TSSI) is highly significant. If the site has sloping topography, the importance of this study is further amplified, and the slope effect on soil-structure interaction must be considered. This research uses Loma Prieta (1989) earthquake records to analyze the seismic response of a 5-story concrete building located 5 meters from the crest of the slope for four angles: 15, 30, 45, and zero degrees (SSI), using 3D numerical analysis. Modeling was conducted with MIDAS GTS NX software for both TSSI and SSI systems. An elastic model and an HSS model were used for the building and soil, respectively. The seismic response of the building was evaluated by comparing maximum lateral displacements, base shear forces, inter-story drifts, and horizontal accelerations in TSSI and SSI analyses. As the slope angle increased from zero degrees (SSI) to 15, 30, and 45 degrees (TSSI), the average lateral displacement of the floors increased by 44%, and the average maximum horizontal acceleration increased by 21%. Additionally, with the slope angle increasing from zero degrees (SSI) to 15, 30, and 45 degrees (TSSI), the average ratios of inter-story drift and maximum base shear force increased by 14% and 21%, respectively.
Mr Mohammadreza Harirsaz, Dr Ali Ghanbari, Dr Gholamhosien Tavakoli Mehrjardi,
Volume 18, Issue 5 (English article specials 2024)
Abstract
A series of reduced scale plate load tests was conducted to evaluate the bearing capacity of a strip footing resting on granular slopes. The effect of three factors including geocell burial depth, geocell length and spacing of geocell layers were discussed and evaluated. In this regard, 18 tests were performed to investigate the behavior of one and two layered geocell-reinforced slopes as well as the unreinforced slope and plain conditions. The results suggest that in single-layered geocell-reinforced slope, the optimum burial depth of the first layer of geocell reinforcement is 0.1 times of the strip footing width, whereas at greater depth beneficial effect of the geocell will reduce. In addition, expanding the reinforcement length up to approximately three times the foundation width could effectively increase the bearing capacity, whereas extending the length beyond that does not lead to any significant improvement. Furthermore, it was observed that use of two geocell layers by considering an optimum geocell space of 0.2 times of the foundation width could enhance the bearing capacity up to 226% in comparison with the unreinforced slope, and up to 79% of the plane condition for settlement ratio of 15%. Finally, the results indicate that the efficiency of the geocell reinforcements in lessening the gap between slope and plane conditions increases as the settlement of the footing rises due to better mobilization of dilation characteristics of granular backfill material and better lateral confinement of coarse aggregates in greater strains.
Dr. Ali Misaghi, Dr. Mohammd Raeesi,
Volume 18, Issue 5 (English article specials 2024)
Abstract
In this study, we investigate the spatial distribution of landslides, strong motion data, and seismic intensity patterns associated with the June 20, 1990, earthquake, with a moment magnitude (Mw) of 7.4. Our primary objective is to elucidate the rupture status of the southeastern segment, Zard Geli, of the coseismic rupture by integrating geological and seismological data, Our findings indicate that the southeastern segment experienced only a partial rupture during the 1990 earthquake. This partial rupture is evidenced by the disproportionate distribution and density of landslides along the surface rupture. The incomplete rupture of this segment suggests that it retains a considerable amount of accumulated strain energy that was not fully released during the 1990 event. Consequently, this segment remains a potential source for future seismic activity. These findings have implications for seismic hazard assessment and risk mitigation in the region. This study highlights the need for continued monitoring and detailed geological and seismological investigations to better anticipate and mitigate the effects of future earthquakes.
Tahereh Azari,
Volume 19, Issue 1 (6-2025)
Abstract
Accurately determining hydraulic parameter values is the first step in sustainably developing an aquifer. Since Theis (1935) introduced the type curve matching technique (TCMT), it has been used to estimate aquifer parameters from pumping test data. However, the TCMT is subject to graphical error. To eliminate this error, a multi-layer perceptron (MLP) artificial neural network (ANN) was developed as an alternative to the conventional TCMT. This MLP ANN models the Bourdet-Gringaten well function to determine fractured double porosity aquifer parameters. The MLP model was developed using a four-step protocol and trained using the backpropagation method and the Levenberg-Marquardt optimization algorithm for the well function of double-porosity aquifers. Through a trial-and-error procedure and by applying principal component analysis (PCA) to the training input data, the optimal network structure with the topology [3×6×3] is determined. We evaluated the validity of the developed network with synthetic and real field data. The network receives pumping test data and provides the user with aquifer parameter values. This network provides an automatic, fast procedure for determining double-porosity aquifer parameters, eliminating the graphical errors inherent in the conventional TCMT.
Ehsan Pegah,
Volume 19, Issue 1 (6-2025)
Abstract
Accurately quantifying the anisotropic elastic parameters of in situ soils is essential for many geotechnical and geological engineering studies. This research introduces an innovative geophysical field technique for assessing these parameters in situ by utilizing the directional variations of P-wave and S-wave velocities. Assuming cross-anisotropy in the soil layers at the test location, it was shown that P- and S-wave propagation velocities along different orientations and planes can be effectively measured through a combination of seismic refraction and downhole surveys. The refraction data were analyzed using Seismic Refraction Tomography (SRT), Multichannel Analysis of Surface Rayleigh Waves (MASW), and Multichannel Analysis of Love Waves (MALW) to estimate the horizontal P-wave velocity (VPH), vertical S-wave velocity (VSV), and horizontal S-wave velocity (VSH), respectively.Moreover, the vertical and oblique P-wave velocities (VPV and VPθ) were identified by evaluating the travel times and distances of wave signals obtained from downhole tests. These velocity measurements were then incorporated into advanced equations formulated from elastic wave propagation theory, facilitating the computation of elastic parameters at the site. To evaluate the accuracy and efficiency of the proposed approach, the obtained results were compared with corresponding laboratory measurements, revealing a satisfactory level of agreement between the two datasets. The proposed methodology offers a practical means for in situ assessment of cross-anisotropic elastic properties in near-surface geomaterials using field-based seismic techniques.
Mohammad Reza Haddad Tehrani, Mehdi Talkhablou, Mohammad Reza Asef, Mehdi Ostad Hasan,
Volume 19, Issue 2 (10-2025)
Abstract
Complex carbonate reservoirs, such as the Asmari Formation, present challenges to the accurate determination of geomechanical parameters and effective stresses due to high lithological and structural heterogeneity. The objective of this study is to develop a comprehensive three-dimensional model of geomechanical parameters and effective stresses in the Kupal oil field. Well log, core, and seismic data were used, and three-dimensional modeling was performed using the Sequential Gaussian Simulation (SGS) method based on variogram analysis. The prevailing stress regime was validated using FMI logs and wellbore breakout analysis. Additionally, a one-at-a-time sensitivity analysis was conducted on key parameters, including static Young’s modulus, Poisson’s ratio, cohesion, internal friction angle, and pore pressure. Results indicate that the maximum vertical effective stress (σv) is 87 MPa and the maximum horizontal effective stress (σHmax) is 127 MPa. Analysis of wellbore imaging data confirms a normal faulting stress regime (σv>σHmax>σhmin) in the field. Stress concentration around minor faults was also identified. The model was validated against one-dimensional models achieving 88% agreement. The findings of this study can be applied to well design, gas injection, and reservoir stability assessment in the Kupal field.
Younes Mousavi, Mohammad Nakhaei, Gholamhossein Karami,
Volume 19, Issue 4 (12-2025)
Abstract
Planning the management and optimized consumption of groundwater resources is a critical infrastructural necessity, as these resources supply a significant portion of the country's drinking water. A key component of this planning is accurately calculating the water balance, which requires determining the aquifer's hydrodynamic parameters, including transmissivity (T) and hydraulic conductivity (K). This study calculated these parameters using step-drawdown pumping test data from a single-well system across various locations in the 411-square-kilometer Hashtgerd Plain aquifer (an unconfined aquifer) with AquiferWin32 software. The results indicate that transmissivity is distributed unevenly across the plain. The lowest transmissivity values were observed in the southern (Kourosh Town) and southwestern (Najmabad) sectors, while the highest values were associated with the Kordan alluvial fan and its downstream lands. Based on these findings, maximum transmissivity was estimated at 3,682 square meters per day, with an average of 440 square meters per day. Hydraulic conductivity was determined by integrating saturated thickness data from geoelectrical studies with the previously calculated transmissivity values. The final results showed that hydraulic conductivity ranges from a minimum of 0.2 meters per day in the southern regions to a maximum of 9.7 meters per day in the central aquifer.
Prof Seyyed Mahmoud Fatemi Aghda, Dr Asieh Hamidi, Ms Fatemeh Amiri,
Volume 19, Issue 5 (English articles 2025)
Abstract
The evaluation of mechanical strength, particularly the uniaxial compressive strength (UCS) of rocks, plays a critical role in the design and performance prediction of surface and underground structures, significantly impacting project costs and safety in engineering applications. Traditional laboratory testing methods for UCS assessment are destructive, time-consuming, and expensive, while indirect methods often lack reliability due to rock heterogeneity. This study addresses these limitations by developing advanced machine learning frameworks that integrate petrographic features with conventional rock properties to predict UCS and quantify associated uncertainties. The research utilized a comprehensive dataset from sedimentary rocks collected along Iran's southern coastlines (Persian Gulf and Gulf of Oman), encompassing mechanical properties (UCS, Brazilian tensile strength, point load index, porosity, ultrasonic pulse velocity), durability indices (Los Angeles abrasion, slake durability, aggregate impact value), and detailed petrographic characteristics derived from thin-section analysis. Three complementary approaches were implemented: (1) hybrid Neural Network-Gradient Boosting regression (ANN-GBR), (2) AutoML-optimized Random Forest, and (3) Monte Carlo simulation-based uncertainty quantification. Key petrographic features including immature and mature clastic textures, the mineral composition (quartz, chert) were used as input parameters alongside alongside laboratory testing to improve the prediction of UCS.The influence of these petrographic features on the rock’s microstructure and microcrack propagation contributes to reducing model uncertainty and enhances the reliability of predictions in complex and heterogeneous rock conditions. The AutoML-optimized Random Forest model demonstrated exceptional predictive performance with R² = 0.9884, RMSE = 0.5732 MPa, and MAPE = 3.6%, significantly outperforming traditional empirical methods. The ANN-GBR hybrid approach achieved R² = 0.9412 with RMSE = 1.385 MPa, while Monte Carlo simulations provided robust probabilistic assessments through 95% confidence intervals and systematic bias identification. Feature importance analysis revealed that soundness parameters and mineralogical composition are the most influentialpredictors, emphasizing the critical role of micro-scale petrographic properties in determining macroscopic mechanical behavior.
Dr Seyed Mahmoud Fatemi Aghda, Dr Mehdi Talkhablou, Habibolah Heidari,
Volume 19, Issue 5 (English articles 2025)
Abstract
Reliable assessment methods are required for designing initial support for tunnels in complex geological conditions. This study provides a thorough comparison of the Rock Mass Rating (RMR) and Rock Engineering System (RES) frameworks, examining a substantial dataset comprising 38 tunnels situated in various lithological and tectonic zones across Iran. While the RMR framework offers empirical simplicity, the RES framework provides a systems-based approach that quantifies parameter interdependencies. Analysis of field data, including shotcrete thickness and bolt density, revealed that the RES framework captures hydro-mechanical coupling more effectively, particularly in intermediate rock masses. To reconcile discrepancies between the two systems, we explored an integrated statistical formulation combining normalized RMR ratings with RES stability indices. This approach demonstrated a significantly higher correlation with field performance (R² ≈ 0.99) than the individual methods. The results emphasise the importance of integrating empirical and systems-based approaches to improve the reliability of predictions in tunnel support design and provide a solid foundation for engineering decisions in heterogeneous rock masses.
Dr Ali Ghanbari, Dr Mohammad Nakhaee, Dr Saeed Kalani, Dr Hamidreza Azizi,
Volume 20, Issue 1 (6-2026)
Abstract
Land subsidence is a complex geotechnical hazard with profound impacts on environmental stability, infrastructure resilience, and socio-economic security. This research presents a systematic field-based assessment of subsidence manifestations across the Hashtgerd, Eshtehard, and Karaj plains in Alborz Province, based on extensive surveys conducted in spring and summer of 2025. Diagnostic indicators, including extensional and compressional ground fissures, localized structural deformations, wellhead displacements, large-scale surface cracks, and variations in groundwater levels, were systematically documented. The Hashtgerd plain, particularly the Saeidabad, Sepehr, and Najmabad areas, exhibited the highest density of subsidence evidence, including progressive surface settlement, widespread fissuring, and instability of near-surface strata. In the Eshtehard plain, structural cracking in school buildings, ground ruptures adjacent to transmission towers, and retaining wall failures were frequently observed. Deep surface fissures were also identified in the Fathabad region, which is located between Eshtehard and Buin Zahra. In contrast, despite significant groundwater withdrawal, field surveys in parts of the Karaj plain revealed no pronounced subsidence indicators. The findings highlight a strong spatial correlation between the severity of subsidence and geological heterogeneity and unregulated groundwater exploitation.The absence of smart metering systems in wells also contributed to this issue. This study underscores the urgent need for integrated monitoring frameworks, adaptive management strategies, and the application of advanced remote sensing technologies to mitigate and control the expansion of land subsidence in Alborz Province.
Dr. Manoochehr Mortazavi Chamchali, Dr. Ghazaleh Mohebbi Tafreshi, Dr. Amin Mohebbi Tafreshi,
Volume 20, Issue 1 (6-2026)
Abstract
Situated in northern Iran, Manjil City 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 emphasised the need for robust spatial risk assessment to mitigate the impact on people, the economy and infrastructure. This study presents a comprehensive seismic risk assessment and spatial zonation for Manjil, employing an integrated multi-criteria evaluation approach that couples Geographic Information Systems (GIS), the Analytic Hierarchy Process (AHP) and fuzzy logic. Risk was modelled as a function of the interaction between seismic hazard potential and spatial vulnerability. Vulnerability indicators, including residential density, land use patterns and critical urban infrastructure, were standardized and weighted using the AHP framework. Our findings suggest that high-density residential areas primarily contribute to urban vulnerability, whereas critical infrastructure components play a disproportionately vital role in emergency response scenarios.. In 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’ Spatial analysis revealed 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 areas.
