https://www.iranquaternary.ir/ Quaternary Journal of Iran en daily 1 Wed, 19 Feb 2025 00:00:00 +0330 Wed, 19 Feb 2025 00:00:00 +0330 https://www.iranquaternary.ir/article_723485.html 1-IntroductionThe Lower Khuzestan plain, located in southwestern Iran, forms the southeastern extension of the Lower Mesopotamian plain. It borders to the west one of the most important estuaries of the Middle-east region, i.e. the Shatt-el Arab. Three major rivers (Tigris, Euphrates and Karun) flow into the Shatt-el Arab which debouches into the Persian Gulf nearby Fao (Fig. 1). The study of palaeoenvironmental changes in the Lower Khuzestan plain is challenging, because of its rich archaeological heritage. One of the most ancient civilizations, the Elamite Kingdom (2700–539 BC) was primarily centred in the province of what is now called modern-day Khuzestan. Changes in coastal configuration could have had a profound effect on the population occupying the Khuzestan region from Elamite time to present. In this study, the Holocene sedimentary sequence of the Lower Khuzestan plain is investigated to reconstruct the Holocene evolution of the coastline and plain.The Lower Khuzestan coastline is today being shaped by a semi-diurnial mesotidal regime. The tidal range averages ca. 3–4 m along the coastline, increasing to 5–6 m in the Khawr-e Musa tidal embayment. Because of the gentle offshore slope, wave energy is very low. The tide-dominated coastline is fringed by a large tidal flat with a width up to 15 km, extending landward along the Khawr-e Musa tidal embayment. The vast intertidal area is bordered by supratidal salt marshes and clastic coastal sabkha''''s with saltpans. There is no freshwater inflow into the intertidal area, except in case of extreme river flood events. In the south, the Jarrahi river distributary fan system feeds the Shadegan marshes. The vegetation density (Typha and Phragmites) and extension of these marshes vary greatly, as a function of the seasonal rainfall regime. The Holocene sequence of the Lower Khuzestan plain in southwest Iran has been investigated in the context of coastal evolution and relative sea-level change.2-Materials and methodsFor the stratigraphical investigation, 11 cores were collected manually. The coring was carried out using a gouge auger to obtain undisturbed and continuous cores to a depth of 5–10 m below the surface. A spiral auger was used to penetrate the compact clay layers. Borehole locations were registered using GPS. The surface elevation of the boreholes was inferred from topographic maps and sitespecific measurements obtained at the regional topographic institute. In the field, the cores and outcrops were described on lithology, sedimentary structures and macrofossils and preliminary facies identification was made. Samples were taken for laboratory analyses when significant changes in color, texture or lithology were observed. A further interpretation of the different depositional (sub) environments was carried out on the basis of the integration of lithological and palaeoecological (foraminifera and diatom) analyses and is discussed. In this study, radiocarbon dating 14C-AMS (Accelerator Mass Spectrometry) was performed using organic materials and bulk of 6 samples. The sample age was calibrated by the OxCal software (Bronk Ramesy and Lee 2013) with a 2-Sigma error range and a reliability coefficient of more than 95%.3-Results and discussionThe sedimentary succession in undisturbed hand-operated cores and temporary outcrops is described and facies are identified on the basis of lithology, sedimentary structures and macrofossils. Three main sedimentary environments are interpreted from the Holocene sedimentary record of the plain: tidal flat and coastal sabkha, brackish–freshwater marsh and fluvial plain.  This study shows that during the early and middle Holocene, the Lower Khuzestan plain was a low-energy tidal embayment under estuarine conditions. During the initial sea-level rise of the early Holocene, the coastline rapidly transgressed across the shelf, and drowning of a major valley resulted in the development of extended tidal flats. Deceleration of sea-level rise after approximately 5500 cal BP, together with probably more arid conditions, allowed coastal sabkhas to extend widely and to aggrade while the position of the coastline remained relatively stable. Continued deceleration of sea-level rise initiated the progradation of the coastline from ca. 2500 cal BP. The effect of sediment supply by the rivers became more important than the effect of relative sea-level rise. The Karun megafan developed under a descelerating rate of sea-level rise, controlling the avulsive shifting of the river Jarrahi and their loci of sediment input. The development of the Jarahi River megafan has occurred in the study area with a decrease in the rate of sea level rise and stabilization of the river course in the upstream sections of the river, as well as an increase in sediment input from a depth of about 3 to 5 meters depending on the location of the core.4- ConclusionAs the Jarahi River alluvial fan advances from east to west, environmental changes from coastal and tidal sediments to wetlands and then alluvial sediments appear in the upper part of the cores. The presence of alluvial and wetland sediments in the wetland marginal cores can be affected by changes in the level of the wetland, migration of the Jarahi River channel at the level of the alluvial fan, and human factors and manipulations. https://www.iranquaternary.ir/article_727611.html Introduction:Land subsidence, defined as the downward movement of sediments, is one of the significant geological hazards primarily caused by the decline in groundwater levels and the increase in effective stress in aquifer sediments. This phenomenon leads to considerable damage to surface and subsurface infrastructures, including road networks, urban water and sewage systems, and buildings. However, due to the relatively low immediate human casualties, it has not been considered a serious hazard. Over time, the continued subsidence of land results in irreparable damage to urban infrastructure. In most plains of the country, especially in densely populated provinces, excessive groundwater extraction has led to land subsidence.Alborz Province is no exception and is considered one of the high-risk areas in the country. Studies on subsidence in Alborz Province began in 2005, conducted by the GSI. In 2017, the organization's Remote Sensing Group updated these studies to monitor subsidence and its development patterns in Alborz Province. Research Findings Using radar interferometry technology, the maximum rate of subsidence in Nazarabad Plain was calculated for the period 2014–2017, revealing a maximum rate of 22 centimeters.Result:In addition to the rates obtained from remote sensing studies of the GSI, data prepared by the land subsidence portal under the name COMIT-LICS were also used. The subsidence rates obtained from the processing of COMIT data are consistent with the studies conducted by the GSI. The 9-year subsidence rate for the Hashtgerd plain is more than 90 centimeters cumulatively.Additionally, the groundwater level decline model for Hashtgerd Plain, developed using data from the Alborz Regional Water Management, along with geological and sedimentological analyses of the area, was used to assess the causes of subsidence in Nazarabad Plain. In the northern parts of the Hashtgerd Plain, due to the coarse-grained nature of the sediments, the aquifer receives adequate recharge, which helps reduce the subsidence rate. In the central parts of Hashtgerd Plain, limited recharge from the north and south, the fine-grained sediments, and the presence of clay interlayers result in the highest subsidence rates. In the northern parts of the Hashtgerd Plain, there is no evidence of land subsidence due to the significant accumulation of coarse-grained sediments from the Karaj and Kordan rivers. Although the greatest decline related to groundwater withdrawal occurs in this Part of the Plain. In fact, the result of high withdrawals from the groundwater table in the north of the plain has been manifested in the form of subsidence due to the drop in water level in the fine-grained sediments in the southern parts.Discussion: Changes in Hashtgerd groundwater level over 25 years using the Surfer model software. The behavior of the level lines is an expression of the aquifer geometry. Therefore, to interpret and analyze the risk of subsidence, a set of different factors must be evaluated. The complexities of the Hashtgerd plain's groundwater table affect water resource management. The geology and hydrogeology of the plain are such that the spread of subsidence can be prevented by aquifer management and balancing. Currently, the central and southern parts of the Hashtgerd Plain are at risk of subsidence. The depletion of groundwater resources and excessive exploitation in the north, on the one hand, will limit the supply to the aquifer in the central parts of the plain, and on the other hand, will lead to the reversal of the hydraulic gradient and the ineffectiveness of controls and balancing.Conclusion:The total number of wells drilled in the Hashtgerd Plain aquifer is 2,852, with a withdrawal volume of 241 million cubic meters. The share of wells in the subsidence area is 518, of which 211 are abandoned according to the Ministry of Energy statistics. The volume of water that can be withdrawn in this area is 58 million cubic meters, which 24% of the total water withdrawn from the plain. The results of the study of groundwater level changes in the Hashtgerd Plain show that an area of the plain that is at risk of subsidence, based on field evidence, has fewer wells and fewer discharges compared to the entire plain.The specific geological and geomorphological conditions of the Hashtgerd Plain and the presence of the permanent and abundant Kordan River have a positive effect on controlling the subsidence rate. Therefore, to control the subsidence rate, monitor and prevent future damage, it is recommended to: manage the aquifer and create underground dams to increase the water level in the north of the plain, control surface water and implement artificial recharge plans; identify the geometry of the aquifer, and identify the type of aquifer in the Hashtgerd Plain using pumping tests. https://www.iranquaternary.ir/article_728819.html The canyon of Rud-Mojan waterfall in Torbat-e Heydarieh city is one of the significant Quaternary geological features of the Noth eastern zone of central Iran. This canyon was formed on an area of Lower Cretaceous Rudist limestones, containing Orbitolinid (Barremian-Albian) foraminifera, and from the beginning of the Quaternary. A major deformation and severe erosion have occurred in its limestone beds. The source of its waterfall is related to the quaternary karst water reserves of the northern heights of the Mojan River. In this research, using Corbel's equation (1959) and field studies, the erosion rate of the Mojan waterfall canyon has been calculated. Considering the tectonic and faulting conditions of the region, the creation of this canyon can be considered affected by tectonic-faulting factors and at the same time, water erosion. The results of the calculations indicate that the erosion rate of limestone dissolution in the canyon of Rood Mojan waterfall is about 188.14 mm/thousand years, which shows the relative effectiveness of this model.IntroductionDissolution erosion in carbonate rocks and masses depends on several factors. Among these factors are the turbulence or linearity of the system, the flow velocity, the separation of irons from mineral surfaces, the amount of carbonic acid (H2CO3), transport processes, partial pressure of CO2, PH and other factors (Dreybrodt, 1998).One of the most important studies on karst erosion to date was conducted by the French geographer Corbel (1959). He examined the waters drained by rivers in cold regions and compared them with those in tropical regions in terms of the amount of dissolved calcium carbonate, and concluded that the rate of karst erosion in cold regions was greater than in tropical regions, and this can be justified by the amount of carbon dioxide dissolved in cold and warm water (Corbel, 1959). The main goal of this research is to calculate the karst erosion rate of the Rud-Majan Waterfall Canyon using the Corbel equation.Material and Method The canyon (deep valley) of Rud-Majan Waterfall is one of the prominent geological features in the east of the Central Iranian Zone, formed on a Cretaceous (Barremian-Aptian) Rudist limestone area, and especially since the early Quaternary, major deformation and severe erosion have occurred in its limestone bed. Rud-Majan Waterfall is located in Torbat-e Heydarieh province. This waterfall is located in Central Iranian and originates from the Chehel Tan mountain range located 54 km west of Torbat-e Heydarieh city and has an altitude of about 28 meters (Modaresi, 2019). Its geographical coordinates are between latitudes 35°18'50"N to 35°20'55"N and longitudes 58°49'40"E to 58°52'45"E. Among the important tectonic structures, the east-west trending Daruneh fault can be mentioned, and the lithology of the northern part of this fault mainly consists of Paleogene volcanic rocks with inclusions of Nummulitic limestones.Among the limestones that this waterfall has eroded are those of Lower Cretaceous age. These limestones include Rudist and limestones with benthic foraminifers (Orbitolinides) and are of Barremian and Aptian age and equivalent to the Tirgan Formation in the Kopeh-Dagh Basin and are ridge-forming. These deposits include very thick, strong, rock-forming marly limestone, marl, and calcareous shale, rich in Orbitolinides and Miliolids. ResultsBy definition, the incorporation and transport of materials by a fluid agent such as water, ice, and wind are called erosion. Fairbridge (1968) also refers to chemical erosion as opposed to corrosion, and some have considered it to be the same as chemical weathering.Corbel (1959) proposed an equation to estimate the rate of karst erosion :(1) X=4ET/100 (2) X=4ETn/100where X is the erosion rate in millimeters per thousand years (mm/ky) or cubic meters per square kilometer per year, E is the depth of runoff in decimeters (dm), and T is the average concentration of dissolved solids (dissolved calcium carbonate) in water in milligrams per liter (Corbel, 1959) (mg/L). To use the formula, it should be noted that the density of carbonate rocks should be between 1.5 and 2.9, and for dolomites, the water hardness and temperature must be measured to obtain the dissolution rate through precipitation, and to determine sulfate rocks, the calcium ion content and the hardness of carbonate rocks must be measured. Using the available data and the Corbel equation, the karst erosion rate in the study area was obtained as 188.14 mm/thousand years.ConclusionsThe Rud-Majan Waterfall Canyon in Torbat-e Heydarieh County is one of the most significant geological features of the northeastern part of the Central Iranian Zone, formed on Lower Cretaceous limestones containing Orbitolinid foraminifera (Barremian-Albian). Since the early Quaternary, major deformation and severe erosion have occurred in limestone beds. In this study, using the Corbel equation (1959) the erosion rate of this canyon can be estimated to be equal to 188.14 mm/thousand years. Considering the tectonic and fault conditions of the region, the formation of this canyon can be regarded as being affected by tectonic-fault factors and at the same time, water erosion.ReferencesCorbel, J., (1959). Erosion en terrain calcaire (vitesse d’érosion et morphologie). Annales de géographie, 68(366), 97-120. https://doi.org/10.3406/geo.1959.16541Dreybrodt, W., (1998). Limestone dissolution rates in karst environments. Limestone Dissolution Rates in Karst Environments, (16), 167–183.Fairbridge, R., (1968). Corrosion, etching, Springer Link. Retrieved February 21, 2024, from https://link.springer.com/referenceworkentry/10.1007/3-540-31060-6_69 https://www.iranquaternary.ir/article_730061.html IntroductionThe Qazvin Plain, located on the northern margin of Iran’s Central Plateau, is considered one of the most significant prehistoric settlement centers in the region. Over thousands of years, this landscape has been continuously reshaped by complex geomorphological processes such as erosion, sedimentation, and fluvial dynamics. These processes have not only modified the physical environment but have also influenced the preservation and visibility of archaeological sites. Understanding the relationship between sedimentation and site distribution is therefore critical for reconstructing past environments, interpreting patterns of human settlement, and refining predictive models for future archaeological research. Beyond its theoretical implications, this line of inquiry helps shed light on the decision-making logic of prehistoric communities, their perception of environmental stability, and their long-term strategies for sustaining habitation within dynamic landscapes.ObjectivesThis study aims to analyze the relationship between sedimentation intensity and the spatial distribution of prehistoric sites (Neolithic and Chalcolithic) within three sub-basins of the Qazvin Plain—Abharrood, Kharrood, and Hajiarab. The research further seeks to evaluate the relative importance of multiple geomorphological and environmental factors in shaping settlement suitability and to develop an integrated framework that combines machine learning and multi-criteria decision-making techniques for environmental archaeological modeling.Materials and MethodsThe study was conducted in two main phases.Phase 1 – Sediment Yield Modeling:Sediment yield maps were reconstructed using the Fournier Index, expressed in tons per square kilometer, to quantify the spatial variability of sedimentation. These initial outputs were subsequently refined using three machine learning algorithms—Multiple Linear Regression (MLR), Random Forest (RF), and Artificial Neural Networks (ANN). For this section ten environmental predictor variables were incorporated, including elevation, slope, clay content, sand content, Topographic Position Index (TPI), Normalized Difference Vegetation Index (NDVI), channel network distance, profile curvature, plan curvature, and lithology. Model performance was assessed using Root Mean Square Error (RMSE) to identify the most accurate algorithm.Phase 2 – Settlement Suitability Modeling:A settlement suitability model was developed to identify areas with high potential for prehistoric occupation. Seven key environmental and geomorphological criteria were selected: elevation, slope, aspect, flow accumulation, distance to water sources, distance from faults, and NDVI. These criteria were standardized and weighed using a hybrid approach that combined Analytic Hierarchy Process (AHP) with Principal Component Analysis (PCA). The integration of AHP and PCA ensured that statistical variance structure contributed to the final weighting scheme, thereby reducing subjective bias and improving model robustness. Raster maps were generated in the Python programming environment and subsequently analyzed in ArcGIS Pro, where overlay operations, reclassification, and weighted linear combination were applied to produce the final settlement suitability map.ResultsThe machine learning comparison revealed that ANN and RF significantly outperformed MLR, achieving lower RMSE values and higher spatial accuracy. ANN demonstrated superior capability in capturing the non-linear and complex relationships between environmental variables and sediment yield, thereby producing more realistic sedimentation maps.The suitability analysis showed that the majority of known archaeological sites are located in areas characterized by lower sedimentation rates. Statistical testing confirmed a significant negative correlation between sedimentation intensity and site presence probability. This finding indicates that regions with high sedimentation are less likely to preserve visible archaeological sites, either because such areas were less frequently chosen for habitation or because existing sites have been buried beneath thick sediment layers.DiscussionThe results suggest that prehistoric communities in the Qazvin Plain tended to occupy geomorphologically stable zones with lower sedimentation rates. This pattern likely reflects an experiential understanding of landscape dynamics, even if not formally articulated scientific knowledge. The preference for stable locations may have been shaped by the need for long-term settlement sustainability, reduced risk of flood damage, and better preservation of arable land. It should be noted that the lower number of identified sites in areas with high sediment production may result from their burial beneath sediments rather than deliberate avoidance. Therefore, site burial should be considered when interpreting spatial distribution and settlement patterns.Furthermore, the use of machine learning techniques, particularly ANN and RF, highlight the potential of artificial intelligence along with Analytic Hierarchy Process to improve environmental reconstruction and predictive modeling in archaeology. These approaches allow researchers to capture complex, non-linear relationships that traditional statistical methods may fail to represent.ConclusionsThis study demonstrates that combining machine learning models with multi-criteria decision-making methods offers a powerful framework for understanding the interplay between environmental processes and human settlement patterns. The integrated approach not only enhances the accuracy of sedimentation modeling but also improves the reliability of archaeological predictive models.From a practical standpoint, the findings can assist archaeologists in identifying high-probability areas for future excavations, prioritizing regions for survey, and allocating resources more efficiently. Moreover, this research underscores the importance of considering geomorphological stability as a key factor in cultural heritage management. By understanding where sites are most likely to be buried or preserved, heritage managers can design more effective conservation strategies and anticipate potential threats posed by ongoing erosion and sedimentation processes.On a broader level, the study bridges the gap between archaeology, geomorphology, and data science, offering a replicable methodological template for other regions and time periods. Ultimately, the synergy between AI-driven modeling, PCA, AHP, GIS-based spatial analysis, and multi-criteria evaluation represents a forward-looking approach to environmental archaeology—one that not only reconstructs the past but also informs sustainable management of cultural landscapes for the future. https://www.iranquaternary.ir/article_730079.html IntroductionThe Lut Desert, located in southeastern Iran, represents one of the most remarkable hyper-arid regions on Earth, characterized by extreme temperatures, minimal precipitation, and diverse geomorphological features such as kaluts, hammadas, and vast sand seas (Rig-e Yalan). Due to its unique geomorphic and climatic conditions, the Lut Desert provides an exceptional natural laboratory for studying sedimentological and geochemical processes in arid environments. The desert’s surface materials are shaped by the interplay between aeolian, fluvial, and playa processes that operate under intense evaporation and limited weathering.Despite extensive geomorphological research in the Lut Desert, relatively few studies have focused on the geochemical composition, provenance, and tectonic setting of its surface sediments. Understanding these parameters is crucial for reconstructing source lithologies, sediment transport pathways, and regional tectonic evolution. The present study aims to investigate the mineralogical and geochemical characteristics of surficial sediments in different geomorphic units of the Lut Desert, including kaluts, intermediate hammadas, and the Rig-e Yalan sand sea, to identify their provenance, weathering intensity, and tectonic setting. 2.Materials and MethodsRepresentative sediment samples were collected from multiple geomorphological units across the Lut Desert, covering the kalut area in the west, the intermediate hammada zone, and the extensive sand sea of Rig-e Yalan in the east. Field observations focused on grain size, sorting, rounding, and sediment color, while laboratory analyses determined the mineralogical and geochemical composition.Mineralogical studies were conducted using optical microscopy and X-ray diffraction (XRD), revealing the dominant minerals present in the sediments. Major and trace element concentrations were measured using X-ray fluorescence (XRF) and Inductively Coupled Plasma (ICP) techniques at certified laboratories. The obtained data were processed statistically and plotted on various geochemical discrimination diagrams to interpret provenance and tectonic environment.Key geochemical ratios such as Al₂O₃/TiO₂, TiO₂-Zr, Na₂O/K₂O, and SiO₂/Al₂O₃ were used to infer source rock composition and weathering intensity. Provenance and tectonic setting discrimination diagrams, including SiO₂/Al₂O₃ vs. Fe₂O₃+MgO, La/Th vs. Hf, and Ti/Zr vs. La/Sc, were applied to evaluate the dominant lithologic sources and the tectonic environment of sediment derivation.  Results and DiscussionField observations indicated significant textural variation across geomorphic units. Sediments from the kalut areas contained poorly sorted particles with subangular grains and a mixture of quartz, lithic fragments, and carbonate debris, suggesting limited transport and reworking. In contrast, samples from Rig-e Yalan displayed well-sorted, highly rounded quartz grains, reflecting prolonged aeolian transport and mechanical abrasion. These textural differences illustrate the combined effects of aeolian deflation, fluvial reworking, and episodic playa sedimentation on sediment distribution in the Lut Desert.Mineralogical analysis confirmed that quartz, feldspars, carbonates, and lithic fragments are the dominant detrital components, while heavy minerals such as magnetite, ilmenite, and zircon occur in minor amounts. The abundance of quartz, coupled with depletion in unstable minerals, indicates a high degree of sedimentary maturity, particularly in the aeolian deposits of the Rig-e Yalan. Geochemical analyses revealed that SiO₂, Al₂O₃, Fe₂O₃, and CaO are the major oxides, with SiO₂ content ranging between 62–85 wt%, indicating quartz-rich compositions. Elevated Fe₂O₃ and TiO₂ contents in kalut sediments suggest contributions from volcanic and mafic lithologies. The Al₂O₃/TiO₂ ratios (ranging between 10 and 25) and TiO₂–Zr relationships suggest derivation predominantly from felsic to intermediate igneous rocks such as granites, rhyolites, and volcanic tuffs. The Na₂O/K₂O ratio displays relatively low values, implying advanced chemical weathering and feldspar depletion, consistent with strong mechanical disintegration and limited chemical alteration under hyper-arid conditions. Variations in SiO₂/Al₂O₃ and Fe₂O₃+MgO indicate compositional maturity differences among the three geomorphic zones, with the highest maturity observed in the eastern sand sea.Provenance discrimination diagrams (e.g., Ti/Zr vs. La/Sc and La/Th vs. Hf) suggest that the majority of samples plot within the field of felsic volcanic and plutonic source rocks, with minor influence from recycled sedimentary materials. The spatial geochemical variability implies that the western and central parts of the Lut Desert receive detritus mainly from igneous and metamorphic rocks of the Kerman magmatic arc, whereas the eastern portions are affected by long-distance aeolian transport and recycling of older alluvial and playa sediments. Tectonic discrimination diagrams (e.g., Fe₂O₃+MgO vs. TiO₂ and Th–Sc–Zr/10) place most samples within the fields of Active Continental Margin (ACM) and Continental Arc Settings (CAS), consistent with the geotectonic framework of Central Iran. This correlation reflects sediment derivation from uplifted continental crust and volcanic arc terranes associated with Neogene to Quaternary magmatism and tectonic reactivation along the Lut block margins.  ConclusionThe integrated sedimentological and geochemical data reveal that the surficial deposits of the Lut Desert are products of complex interactions between aeolian, fluvial, and playa processes. The sediments are compositionally immature in the western kalut and hammada regions but become progressively mature toward the eastern Rig-e Yalan due to prolonged aeolian reworking. The dominance of quartz and the depletion of feldspars and mafic minerals indicate advanced mechanical weathering under extreme aridity.Geochemical ratios and element distributions confirm that the sediments were derived mainly from felsic to intermediate igneous sources (granites and volcanic tuffs) with minor sedimentary recycling. Tectonic setting analysis demonstrates that these deposits originated within an Active Continental Margin environment, consistent with the tectono-magmatic evolution of Central Iran.Overall, the findings provide new insights into the provenance, weathering, and tectonic controls on sediment composition in one of the driest and most dynamic desert systems of the world. This study contributes valuable baseline data for future research on geomorphological evolution, sediment transport, and paleoenvironmental reconstruction in arid regions of Iran. https://www.iranquaternary.ir/article_731449.html Introduction:The Central Alborz has sedimentary rocks from Precambrian to Quaternary. This area is part of the Alborz Mountain range, located in the eastern Central Alborz Zone. It lies between longitudes 50°15’ to 50°77’ and latitudes 35°50’ to 36°15’ North. Alborz’s volcanic activity was strong during the Tertiary period, peaking in the late Eocene and Oligocene. After a calm phase, intense activity resumed in the Pliocene. Eocene and Oligocene eruptions across Alborz, including the Qazvin highlands, Takestan, and areas around Tehran, mainly produced andesite, dacite, and rhyolite. These eruptions also created many ignimbritic and tuffaceous deposits, along with pyroclastic fall deposits and pumice lahar flows (Gholami, 2001).Sampling Method: During fieldwork, we used a systematic sampling method, collecting 70 samples. We prepared thin sections from these samples for closer examination. To analyze the major, minor, and trace elements, we selected 18 whole-rock samples. These were analyzed using Inductively Coupled Plasma – Mass Spectrometry (ICP-MS) at Kansaran Binalood and Zar Azma companies in Iran.Discussion: After studying the thin sections, we identified four extrusive igneous rock groups: 1) Foliated Basaltic Trachyandesite, 2) Trachyandesite, 3) Olivine Basalt, and 4) Lamprophyres. Diagrams by Lobas et al. (1986) and Middlemost (1994) show that volcanic rock samples from Polur and the Haraz road fit within Trachybasalt, Basalt, and Trachyandesite categories. Based on the classification by Irvine & Baragar (1971), these rocks fall within the alkaline field and near the subalkaline boundary (Tchameni et al., 2006). In the Verma et al. (2006) diagram, the alkali basaltic samples are in the continental rift basalts and OIB (Ocean Island Basalt) fields. The Xu et al. (2015) diagram places these samples in the crustal contamination field, showing magma mixing with crustal components during ascent.Some sources note that a high Ce/Pb ratio is a feature of mantle-derived ocean island basalts (OIB) (Lustrino, 2005). In the Ce/Pb diagram against Ce for the region's alkaline basalts and primary magma, samples fall within the mantle MORB/OIB range. However, some samples show continental crust characteristics due to crustal contamination and increased lead levels. In the Th/Yb diagram against Ta/Yb, the basaltic samples fit within the OIB range, indicating an asthenospheric origin with some enrichment.Eskandari's (2016) geodynamic model for Damavand magmatism suggests that the lower crust, lithospheric mantle, and asthenospheric mantle all contribute in different amounts to forming primary magma. To determine the tectonic setting of the studied rocks, we used several diagrams. The samples indicate that these rocks have alkaline traits and formed in an intra-continental rift environment. Unlike the simple fractionation process, LREEs and some LILEs come from alkaline basalts to trachyandesites. Multi-element diagrams show that these elements and P are less in trachyandesites than in basalts. Rare element patterns in these diagrams don’t clearly show a tectonic environment. They show traits of both subduction and OIB environments. A look at some crustal contamination indicators, like elemental ratios, reveals that trachyandesites have more contamination than alkaline olivine basalts. High ratios of Ce/Pb, Nb/U, Ba/Nb, and Th/La, along with low ratios of Sm/La in alkaline olivine basalts, indicate these lavas are influenced more by crustal materials.ConclusionAlong the Haraz road and near Polur, we find volcanic rocks ranging from alkali olivine basalt to trachyandesite. Instead of a simple differentiation trend, we observe a depletion of LREE (Light Rare Earth Elements) and some LIL (Large Ion Lithophile) elements from alkali basalts to trachyandesites. Multi-element diagrams also show a decrease in these elements and Phosphorus (P) in trachyandesites compared to basalts. The trace element patterns in these diagrams reflect characteristics typical of an OIB environment. Comparisons of crustal contamination indices suggest that trachyandesites have undergone more crustal contamination than alkali olivine basalts. Overall, these rocks show alkaline features and were formed in an intra-continental rift setting.  https://www.iranquaternary.ir/article_731474.html IntroductionMass movements include all movements that occur under the influence of mass weight. The landslide occurred in the last days of 2018 and early 2019 after floods in many provinces of the country, including North Khorasan, Golestan, Semnan, Mazandaran, Gilan, Hamedan, Lorestan, Kurdistan, Kermanshah, East and West Azerbaijan, and Zanjan. Due to the large number of landslides in rural areas of the country, the perspective of moving to another location and escaping from landslides has changed and the approach of stabilizing the landslides that have occurred and building in situ has been replaced. Therefore, the stabilization and stabilization of a large number of landslides that occurred in late 2018 and early 2019, including the landslides in Hossein Abad Kalpoosh village in Miami County, Semnan Province, was placed on the agenda of the responsible executive agencies.Materials and methodsHossein Abad Kalpoosh village is located in Kalpoosh district of Miami city in Semnan province, at coordinates 37/2003445 and 55/736813. This village is located in Sudaghlan rural district (Razvan) and according to the census of the Statistical Center of Iran in 2016, its number of households was 1013 and its population was 3514. Upstream of this village, a Kalpoosh reservoir dam has been constructed close to the village, which has been impounded in recent years. The research method in this study is based on library surveys and studies and field observations. In this regard, information related to the geological, tectonic and landslide conditions that have occurred in the village area is examined in a library manner, and then the method of landslide management and stabilization is examined. After completing the geological information, faults, landslides that have occurred, and their location, the data will be analyzed and the methods and technical measures taken to stabilize and stabilize landslides will be examined in order to prevent the displacement of the village and the migration of villagers, and to continue the settlement of villagers in the current location of the village, and to determine the direction of village development and their efficiency.Results and discussionA large number of landslides also occurred in the village of Hossein Abad Kalpoosh in Miami County, Semnan Province. The landslides that occurred in the village were categorized into 5 different zones, including 1- the landslide zone downstream of Kalpoosh Dam, 2- the landslide zone above the neighborhood and the southern slopes of the Ghoshe-Dagarman River, 3- the landslide zone above the Saadat Abad neighborhood, 4- the Besat Abad landslide zone, and 5- the landslide zone of Hassan Abad neighborhood and its upstream slopes. The largest landslide area is located downstream of the Kalposh Dam, which has destroyed many homes. This landslide, with an area of about one and a half hectares and an average depth of 11 square meters, occurred in the heart of a large old landslide area. This landslide, with an area of about one and a half hectares and an average depth of 11 square meters, occurred in the heart of a large old landslide zone. It seems that this old landslide in the downstream section of Kalpoosh Dam had a great depth of more than 30 meters and occurred at the border of wind-blown and weak marl deposits with strong underlying limestone bedrock, and in some places it also contains fragments of the underlying bedrock. The recent landslide occurred on March 11, 2018, with a combined rotational-transitional movement, after heavy snowfall in February and heavy rainfall in March. Although the existence of an old landslide and the heavy rainfall mentioned above played an important role in the occurrence of this landslide, the available evidence indicates that the more effective role was played by the rising water level in the Kalpoosh Dam reservoir, the seepage of water through the crushed rocks of the reservoir wall, and the saturation of the soil mass from the lower part. This is evidenced by the occurrence of numerous springs and seepages in this range, which continued for many months after the landslide occurred, and only with the lowering of the water level in the reservoir, these seepages have begun to decrease. The recent landslide occurred on March 11, 2018, with a combined rotational-transitional movement, after heavy snowfall in February and heavy rainfall in March. Although the existence of an old landslide and the heavy rainfall mentioned above played an important role in the occurrence of this landslide, the available evidence indicates that the more effective role was played by the rising water level in the Kalpoosh Dam reservoir, the seepage of water through the crushed rocks of the reservoir wall, and the saturation of the soil mass from the lower part.This is evidenced by the occurrence of numerous springs and seeps in this range, which continued for many months after the landslide occurred, and only decreased as the water level in the reservoir decreased. The landslides damaged a large number of rural homes, facilities and infrastructure. In order to stabilize and stabilize the landslides that occurred in the village, 8 machine boreholes and 6 geoelectric profiles with a dipole-dipole array, three S and P wave boundary rupture seismic profiles, single station and microseismic array surveys (microtremor) including one in-situ array survey and 17 single station surveys have been conducted. Subsequently, stability analyses and landslide stabilization options were conducted, and finally, plans and implementation plans were presented to stabilize the village's landslides and make rural homes safe, and the aforementioned plans have been implemented.ConclusionBy stabilizing, stabilizing, and securing the village of Hossein Abad Kalpoosh, the migration and relocation of approximately 1,000 households with a population of over 3,500 people was prevented, and the harmful consequences of unsuccessful relocations were prevented. According to available information, 881 villages have been displaced across the country by 2015, most of which were displaced due to risks arising from various natural disasters, with the most important risks causing displacement including floods, earthquakes, and landslides, so that more than 74 percent of displacements in the country are due to the above factors (Gerkani et al., 2018). Sabouri and Garkani (1403) conducted a field study of 9 new sites of relocated villages, all of which were unsuccessful in their relocation and the village was not formed in the new site. Therefore, by adopting recommendations and conducting studies and implementing sustainability plans in the village of Hossein Abad Kalpoosh, the repetition of unsuccessful and costly experiences of rural relocation has been prevented. https://www.iranquaternary.ir/article_733177.html IntroductionThe Eastern Anatolia–South Caucasus–NW Iran sector of the Alpine–Himalayan belt hosts numerous Quaternary volcanic centers amid intense seismicity. This paper quantitatively evaluates how transtensional strike-slip structures control the location and timing of volcanism—an issue that, despite abundant Holocene and historical eruptions, has rarely been tested. The central hypothesis posits that releasing step-overs and pull-apart basins exert first-order control on Quaternary volcanism. Representative cases (Ararat, Tskhou–Karkar, Porak, Sabalan) provide archaeological and ^14C evidence for extension-guided eruptions. Methods(1) Remote sensing & vent inventory: Visual interpretation of QuickBird (0.6 m; 2002–2006), Corona KH-4B (2.7 m; 1967–1972), and Landsat-7 ETM+ (30 m; 1999–2003) identified macroscopic volcanic units (cones, maars, shields); clusters <1 km were treated as single centers. Positional uncertainty is ~±100 m; field/Google Earth Pro validation at 45 sites yielded ≥92% accuracy. A total of 820 centers were mapped. (2) Seismic catalog: Historical sources plus ISC (1900–2020) and NEIC (1964–2020) were merged, duplicates removed, and magnitudes homogenized to Mw. Completeness (Mc) was determined by maximum curvature; a and b parameters were estimated via Aki–Richards (uncertainties ~±0.1 for Mc and ±0.05 for b). (3) Random baseline & statistics: 10,000 random points (excluding lakes/glaciated highlands) provided the null model for vent–fault distances. We applied 10,000-trial permutation tests at p<0.001, two-sample K-S tests for distributions, and t-tests for means. All computations used Python/SciPy v1.10. Results(1) Proximity to active faults: The mean vent–fault distance is 6.3 km, significantly smaller than the random expectation 9.5 ± 0.7 km (p = 1.0×10⁻⁴), implying ~34% reduction relative to a random field. (2) Structural focusing: Vent densities peak within releasing step-overs and pull-apart basins. Three standout clusters are: Ararat–Sevan–Syunik corridor, Van–Erciş–Patnos (Nemrut–Süphan–Tendürek), and the Tabriz–Sahand–Sabalan system. Density lobes align with NW–SE strike-slip traces, whereas compressional bends show depleted vent densities. (3) Within-cluster statistics: Inside KDE90, vents average 2.94 km from the nearest fault (n=23), versus 6.64 km outside (n=207); the 3.69 km difference is significant (p = 0.00120). Spearman’s ρ between the KDE score and fault distance is negative (r ≈ −0.234). (4) Temporal coupling: Holocene/historical eruptions broadly coincide with Mw≥5 earthquake clusters; the A.D. 1840 Ararat event (~Mw7.4) with explosive activity on the northern flank is emblematic. Catalog parameters Mc ≈ 3.0 and b ≈ 0.95 are consistent with active strike-slip belts. (5) Case studies: Ararat’s aligned vents/young flows, Holocene lava generations at Tskhou–Karkar, ^14C-dated historical activity at Porak (~1100 BCE), and geochemical/hydrothermal indicators at Sabalan collectively substantiate an extension-guided magma ascent. ConclusionStrike-slip systems with an extensional component act as a gate valve regulating magma ascent and eruption timing. The statistically significant spatial focusing of vents near active faults and temporal synchronization with regional seismic clusters reveal a coherent tectono-volcanic pattern. 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Journal of Volcanology and geothermal Research, 112(1-4): 189-220. https://www.iranquaternary.ir/article_733179.html Introduction Urban green spaces, particularly public parks, play a vital role in enhancing environmental quality and improving public health in rapidly expanding cities. However, these areas are increasingly exposed to contamination from anthropogenic sources, with heavy metal pollution being one of the most concerning threats. Urban soils, especially in parks, can accumulate potentially toxic elements (PTEs) due to vehicular emissions, industrial activities, atmospheric deposition, and inappropriate use of fertilizers and pesticides. Monitoring heavy metal concentrations in park soils is therefore essential to evaluate potential environmental risks and inform urban environmental management strategies. This study focuses on the spatial assessment of heavy metal contamination in soils of selected urban parks using pollution indices and Geographic Information Systems (GIS). Heavy metals such as lead (Pb), cadmium (Cd), arsenic (As), chromium (Cr), copper (Cu), zinc (Zn), and nickel (Ni) are selected based on their toxicity, persistence in the environment, and potential health impacts on urban populations. Sampling and Analytical Methods Soil samples were systematically collected from different locations within each urban park to capture spatial variability. The topsoil layer (0–20 cm) was targeted, as it is most susceptible to anthropogenic contamination. Samples were air-dried, sieved, and subjected to acid digestion based on USEPA standard protocols. Heavy metal concentrations were then measured using atomic absorption spectrometry (AAS) or inductively coupled plasma mass spectrometry (ICP-MS), depending on the element and required detection limits. Application of Pollution Indices To assess contamination levels, multiple pollution indices were employed: 1. Geoaccumulation Index (Igeo) – developed by Müller, this index compares current concentrations with background values to determine pollution levels. Values are classified into seven categories, ranging from unpolluted to extremely polluted. 2. Contamination Factor (CF) – this index is the ratio of metal concentration in soil to the background concentration, indicating the degree of contamination. 3. Enrichment Factor (EF) – used to differentiate between anthropogenic and natural sources, calculated using a reference element such as Fe or Al. 4. Pollution Load Index (PLI) – provides a cumulative indication of overall pollution status across multiple metals. 5. Ecological Risk Index (RI) – developed by Hakanson, this index combines toxic response factors with contamination levels to quantify ecological risk posed by each heavy metal. These indices offer a comprehensive view of the contamination status and help prioritize elements of greatest concern. GIS-Based Spatial Analysis GIS tools were applied to interpolate the spatial distribution of heavy metals across the park areas using kriging or inverse distance weighting (IDW) methods. This spatial analysis helps identify pollution hotspots and understand the influence of surrounding urban land use on soil contamination. In addition, land use maps, traffic density data, and proximity to pollution sources (e.g., highways, industrial zones) were integrated to explore potential sources of contamination. Layered visualization through GIS enhances interpretation and supports urban planning decisions. Results and Interpretation The results revealed considerable variations in heavy metal concentrations across different parks, with some areas exceeding international soil quality guidelines, particularly for Pb, Cd, and As. The Igeo values indicated moderate to high pollution levels in parks adjacent to high-traffic roads and industrial areas. CF and EF values confirmed anthropogenic contributions, with significant enrichment for Cu, Zn, and Pb. The ecological risk assessment highlighted Cd as the primary element posing considerable risk, followed by As and Pb. Some park locations fell into the "considerable risk" category according to the RI values, underscoring the need for targeted mitigation measures. Spatial distribution maps generated by GIS clearly identified pollution hotspots and indicated a correlation between metal accumulation and nearby anthropogenic activities. Parks located in city centers or near transportation corridors showed higher contamination levels, emphasizing the importance of buffer zones and soil remediation interventions. Environmental and Public Health Implications Heavy metal accumulation in urban park soils not only degrades soil quality and ecological health but also poses direct and indirect risks to human health. Children are particularly vulnerable due to frequent contact with park soils through play. Chronic exposure to heavy metals can lead to neurological disorders, kidney damage, and developmental delays.   Therefore, understanding spatial patterns and ecological risks associated with heavy metal contamination in urban parks is critical for environmental risk management. The application of pollution indices and GIS supports evidence-based decision-making and enhances public awareness. Recommendations 1. Regular Monitoring: Establish long-term monitoring programs in urban parks, especially in high-risk zones. 2. Remediation Strategies: Use phytoremediation or soil amendments to reduce bioavailability of heavy metals. 3. Urban Planning: Design green spaces with buffer zones and low-exposure zones for children. 4. Public Education: Raise awareness about contamination risks and promote safe park usage practices. 5. Policy Development: Implement regulations to limit urban emissions and manage land use near green spaces. Conclusion This study underscores the significance of combining pollution indices and GIS tools to assess heavy metal contamination in urban park soils. The findings reveal spatially heterogeneous contamination patterns and identify ecological and health risks, particularly in parks located in densely populated or industrialized zones. An integrated approach to monitoring, remediation, and urban design is essential for safeguarding environmental quality and ensuring the safe use of urban green spaces.