Document Type : Research Article
Authors
1
Department of Geography Education, Farhangian University,Tehran,Iran
2
Master of Science, Technical and Soil Mechanics Laboratory, Maku, Iran
3
Department of Geology, Faculty of Sciences, Urmia University, Urmia, Iran
Abstract
This study was conducted to analyze the effects of active tectonic processes on geomorphological features and assess the potential for slope instability occurrences within the Shaharchay River Basin of Urmia. To achieve this objective, an integrated approach was employed, utilizing morphotectonic indices (such as hierarchical stream anomaly, anomaly density, and bifurcation ratio), logistic regression statistical modeling,and analysis of remote sensing data and field data. The results from the logistic regression model (with an ROC accuracy of 0.922) indicate that approximately 43.13% of recorded instabilities in areas with semi-resistant to resistant lithology are located within less than 1 km of active faults. Furthermore, 87.25% of these instabilities occurred within less than 3 km of rivers, and 90% occurred within less than 2 km of roads, typically in areas with sparse or inadequate vegetation cover. Analysis of landslide hazard zonation also reveals that the highest hazard is concentrated in elevations between 1268 and 2000 meters and on south-facing slopes. The findings highlight the significant role of active tectonics, slope gradient, and human infrastructure (such as roads) in intensifying slope instability processes. Consequently, adopting an integrated approach to risk management, restoring natural vegetation cover, and implementing land-use restrictions in high-risk areas is deemed essential.
Introduction
Landslide hazards and slope instabilities rank among the most devastating natural geomorphological disasters, inflicting significant human, economic, and environmental damage on a global scale each year. Iran, situated within the tectonically active Alpine-Himalayan belt, is especially prone to these hazards due to its rugged mountainous terrain, seasonal heavy rainfall, and intricate geological framework. This study focuses on the Shahrchay River Basin in Urmia, northwestern Iran, a region characterized by intense tectonic activity and diverse geomorphological features that amplify the risk of slope failures. The historical backdrop reveals that landslides in Iran, particularly in mountainous zones such as the Zagros, Alborz, and Binalud ranges, are driven by a complex interplay of natural factors—including geological composition, topographic steepness, climatic variability, and hydrological dynamics—and human-induced activities such as land-use alterations, road construction, and vegetation clearance. Previous research, including works by Hemmati and Mokhtari (2017) and Baharvand and Sori (2015), has underscored the pivotal role of tectonic processes, notably faulting and the resultant increase in shear stress, in initiating landslides. The Shahrchay Basin, located near active fault systems like the Urmia Lake Fault, North and South Salmas Faults, Ashnoye Fault, and Kuh-e-Shahidan Fault, exemplifies this vulnerability, with notable seismic events such as the 5.7 magnitude Silvaneh earthquake in April 2015, the 7.9 magnitude earthquake in October 1965, and the aftershocks following the 1982 Ahar-Varzeqan earthquake highlighting the region’s seismic susceptibility. The primary objective of this research is to explore the detailed relationship between morphotectonic indices, drainage network patterns, and slope instability risks, tackling the core question of how active tectonic processes reshape drainage structures and predispose the area to landslides. This study addresses a significant knowledge gap, as integrated analyses combining tectonic, geomorphological, and anthropogenic factors in the Shahrchay Basin remain scarce, despite the urgent need for enhanced risk management, hazard zoning, and sustainable development strategies. The research is directed toward environmental scientists, geologists, urban planners, policymakers, and disaster management professionals, employing a multidisciplinary approach that integrates geomorphological assessments with advanced statistical modeling to deliver practical insights for land-use planning and disaster mitigation. The methodological design is grounded in its ability to construct a theoretical framework for understanding tectonic influences on slope stability while providing actionable applications for hazard reduction in comparable mountainous regions. The literature review, drawing on studies by Khazri et al. (2006), Nikjoo et al. (2016), and Rofii et al. (2014), highlights ongoing debates regarding the relative impacts of tectonic versus human factors, leading to the hypothesis that tectonic activity, when compounded by human disturbances, is a primary driver of landslide occurrences in the basin. This framing sets expectations for a comprehensive analysis that bridges theoretical geomorphology with practical policy implications, addressing both the scientific community’s need for deeper understanding and the public’s demand for safety measures.
Material and Methods
This investigation adopts a multi-stage, integrated methodology to evaluate the contributions of geomorphological and tectonic factors to slope instabilities in the Shahrchay River Basin. The approach encompasses data collection, spatial processing using Geographic Information Systems (GIS), extraction of geomorphic indices, statistical modeling, and thorough validation of findings. Data were compiled from diverse sources: satellite imagery from Landsat-9 (2023, 30-meter resolution) and Sentinel-2 (10-meter resolution) supplied land cover and Digital Elevation Model (DEM) data, obtained from the USGS, while geological maps (1:100,000 scale) and topographic maps (1:50,000 scale) were sourced from the Geological Survey of Iran and the National Cartographic Center, respectively. Field surveys augmented these datasets with detailed records of landslide locations, types, and characteristics, ensuring a robust empirical base. In the GIS environment, topographic layers-such as slope, aspect, and elevation classes—were generated from the DEM, and landslide distribution was mapped using Band 6 of Landsat-9 imagery, correlated with nine critical variables: elevation, slope, aspect, distance from faults, rivers, roads, lithology, vegetation cover, and land use. Each variable was assigned a sensitivity score ranging from 1 to 5, with 5 indicating the highest risk, following established geohazard assessment protocols. Key geomorphic indices, including hierarchical anomaly (Δa), anomaly density (ga), bifurcation ratio (Rb), asymmetry factor (AF), and basin shape ratio, were calculated using standardized formulas within GIS, building on methodologies outlined by Nikjoo et al. (2016) and Burbank and Anderson (2011). The logistic regression model was applied to predict landslide probability, utilizing a nonlinear S-shaped curve to link independent variables (e.g., distance from faults) with a binary dependent variable (landslide occurrence or non-occurrence). Calibration involved assigning 1 to unstable areas and 0 to stable ones, with data processed in IDRISI software. Validation was performed by comparing zoning maps with field observations, employing Chi-Square tests (95% confidence level), Receiver Operating Characteristic (ROC) curves (target value >0.7), and Pseudo R² (>0.2) to assess model accuracy, fit, and predictive power. This methodology ensures replicability and complies with ethical standards by relying on secondary data and non-invasive field techniques, with no direct involvement of human or animal subjects, thus negating the need for specific consent procedures. The approach’s descriptive and interpretive nature aligns with the study’s objectives of elucidating tectonic impacts and informing practical interventions.
Results and Discussion
analysis reveals a multifaceted interaction between tectonic processes and geomorphological dynamics in driving slope instabilities throughout the Shahrchay Basin. The hierarchical anomaly index (Δa) of 1.34 indicates a lower-than-expected ratio of total to first-order streams, suggesting potential tectonic disruption or geomorphic adjustments, a pattern supported by regional studies from Khazri et al. (2006). The anomaly density (ga) of 1.33 anomalies per square kilometer reflects significant tectonic activity, while the bifurcation ratio (Rb) of 1.75, below the global average of 3-5, may suggest lithological or climatic modulation rather than dominant tectonic control, consistent with insights from Burbank and Anderson (2011). The asymmetry factor (AF) of 54.39 indicates a leftward stream shift, likely attributable to lateral fault movements, and a basin shape ratio of 5.62 suggests tectonic elongation aligned with fault orientations. Spatial analysis of landslide distribution, derived from 2023 Landsat imagery, identified 42.4 square kilometers (0.61% of the basin) as unstable, with a pronounced concentration in lower elevations (1268-2000 meters) where human activities such as agriculture, road construction, and urbanization are prevalent, resulting in reduced vegetation cover and diminished soil cohesion. Slope analysis indicated peak instability at 5-20% gradients, linked to human disturbances and unstable lithologies like marls, shales, and loose alluvial deposits, while southern and southeastern aspects exhibited higher risks due to increased solar exposure and soil desiccation.
This study employed a logistic regression model (ROC = 0.922) to analyze the key factors influencing slope instability. The results indicated that elevation, slope, distance to faults and rivers, and vegetation cover type exerted the most significant influence, respectively. The findings revealed that 87.25% of instability events occurred within 3 km of rivers, 90% occurred within 2 km of roads in areas of sparse vegetation, and 43.13% occurred in moderate to resistant lithological units within 1 km of active faults. Spatial analyses further showed that hazard hotspots were predominantly concentrated at elevations of 1268–2000 meters, on gentle to moderate slopes (5–20%), and on southern and southeastern aspects. Moreover, over 87% of instability events occurred within 3000 meters of watercourses. The results underscore the determining tripartite influence of active tectonics (faults), topography (elevation/slope), and anthropogenic activities (road construction/vegetation reduction) in exacerbating geohazards.
Conclusions
This research illuminates the dominant role of tectonic activities, particularly active faulting, in shaping slope instability hazards within the Shahrchay Basin, with morphotectonic indices providing crucial insights into drainage network disruptions and landslide triggers. The findings reaffirm the importance of the research problem, as landslides in tectonically active regions like Iran continue to endanger human lives, infrastructure, and ecosystems, a concern echoed by Hemmati and Mokhtari (2017), Ngarash et al. (2013), and Baharvand and Sori (2015). Theoretically, the study enriches geomorphological models by integrating tectonic and anthropogenic influences, offering a foundation for future research into hazard dynamics and landscape evolution. Practically, the results provide critical guidance for land-use policies, advocating for restricted development in high-risk zones, prioritized reforestation to enhance slope stability, and improved water management to mitigate erosion. The high ROC value (0.9223) and field validation indicate that the logistic regression model accurately predicts landslide susceptibility, potentially explaining real-world phenomena such as seasonal landslide reactivation during heavy rains, as observed by Baharvand and Sori (2015), and offering a basis for modeling similar geohazards elsewhere. Applications are justified, particularly in zoning for controlled construction, implementing watershed management projects, and developing early warning systems, yet unresolved challenges persist, including accounting for long-term climatic variability, adapting to urban expansion pressures, and refining models with advanced technologies like LiDAR and real-time monitoring. The study’s contribution justifies attention from both specialists and policymakers, providing a replicable framework for hazard management that could be extended to other tectonically active basins in Iran, addressing broader environmental resilience, disaster preparedness, and sustainable development issues. Future research could focus on longitudinal studies to track tectonic and climatic interactions, enhancing predictive models and supporting adaptive management strategies in the face of evolving environmental conditions.
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