https://esrj.sbu.ac.ir/ Researches in Earth Sciences en daily 1 Wed, 21 Jan 2026 00:00:00 +0330 Wed, 21 Jan 2026 00:00:00 +0330 https://esrj.sbu.ac.ir/article_106700.html IntroductionThe Gachsaran Formation, known as the cap rock of the Asmari oil reservoirs, is the first formation of the Fars Group within the Zagros Basin and extends from the Dezful-Lurestan embayment to the Persian Gulf Basin. In the Fars province, the Gachsaran Formation shows significant variations in thickness, lithological characteristics, and fossil content particularly foraminifera compared to other parts of the Zagros. James and Wynd (1965) divided this formation into three members: Chehel, Champeh, and Mol. The Gachsaran Formation was deposited in two separate basins (the main and northern salt basin, and the southern Persian Gulf salt basin), which are not time-equivalent. Previous studies on this formation have primarily focused on geophysical properties, diagenesis, and sediment geochemistry, and relatively limited information is available regarding its sequence stratigraphy. Given the scarcity of such studies, detailed investigation of microfacies, depositional environment, and sequence stratigraphy can contribute to a better understanding of this formation and enhance exploration knowledge in the region. Accordingly, a subsurface stratigraphic section within the Bostaneh anticline, located in the southern salt basin of the Persian Gulf, was selected and studied. The Gachsaran Formation does not crop out in the study area; the subsurface section is situated at the core of the anticline, where the deposits of the Mishan Formation are exposed. Materials and MethodsA total of 446 thin sections from 1288 meters of the Gachsaran Formation, obtained as drill cuttings, were examined in this study. The stratigraphic column of the studied section was constructed by integrating laboratory data with gamma-ray well logs and correlating these with the plotted composite log. Subsequently, microfacies analysis and sequence differentiation were carried out following the methodology of Flugel (2010). Carbonate rock nomenclature was based on the Dunham (1962) classification, while facies belt comparisons were made according to Flugel (2010).Sequence-stratigraphic analysis was performed using the approaches of Hunt and Tucker (1992, 1995) and was correlated with the tectonostratigraphic megasequences proposed by Sharland et al. (2001). Gamma-ray logs were also employed to refine and accurately delineate certain lithological and sequence boundaries.Results and DiscussionStratigraphy: In the Bostaneh Anticline, the Gachsaran Formation, with a total thickness of 1,288 meters, is subdivided into the Chehel (1087 m), Champeh (170 m), and Mol (31 m) members. This formation consists of alternating layers of salt, anhydrite, limestone, argillaceous limestone, and marl, and it conformably overlies the Pabdeh Formation and underlies the Mishan Formation. Paleontological investigations resulted in the identification of 32 genera and 47 species of foraminifera. The presence of key index fossils such as Borelis melo curdica, Austrotrillina howchini, Peneroplis evolutus, Globorotalia praescitula, and Miogypsina sp. confirms an Early Miocene (Aquitanian–Burdigalian) age for this section.Microfacies and Depositional Environment: Microscopic analyses led to the identification of five main microfacies, which belong to two major depositional environments: peritidal (Sabkha) and lagoonal settings.Peritidal MicrofaciesA) Alternating evaporite and mudstone layers:This microfacies contains diverse anhydrite textures including laminated, lath-shaped, dispersed and isolated evaporitic crystals, needle-shaped, and swallowtail structures indicating highly evaporative conditions characteristic of peritidal Sabkha environments. The rhythmic alternation of layers reflects short-term fluctuations in relative water level. This microfacies corresponds to RMF25 of Flugel (2010).B) Mudstone microfacies:The dominant matrix is micrite with a mudstone texture, containing less than 1% carbonate and non-carbonate allochems. The absence of faunal diversity, together with the presence of iron oxide and detrital particles, suggests deposition in a very shallow, restricted environment with limited water circulation, likely a coastal Sabkha. This microfacies resembles RMF19 of Flugel (2010).Lagoonal MicrofaciesC) Miliolid wackestone:The presence of porcelaneous foraminifera (e.g., miliolids) within a micritic matrix indicates deposition in a semi-enclosed, low-energy lagoon. This microfacies corresponds to RMF16 of Flugel (2010).D) Bioclastic peloidal packstone-wackestone:The presence of peloids and hyaline foraminifera within a micritic-sparry matrix suggests deposition in the middle parts of the lagoon. This microfacies is comparable to RMF20 of Flugel (2010).E) Bioclastic wackestone-packstone:An increased abundance of hyaline foraminifera suggests deposition in the outer lagoon, near sand shoals. This microfacies also corresponds to RMF20 of Flugel (2010).Overall, the microfacies in the studied section transition gradually from one to another. This, together with the absence of reefal structures, as well as the lack of cortoids, oncoids, pisoids, and aggregate grains features typically associated with carbonate shelf settings and the absence of slump or gravity-induced deposits, indicates that sedimentation took place on a carbonate ramp comprising peritidal and lagoonal environments.Sequence Stratigraphy: Based on relative sea-level variations and paleoenvironmental interpretations, two depositional sequences and three sequence boundaries (two SB1 and one SB2) were identified.The first sequence, with a thickness of 1013 meters, includes LST, TST, and HST systems tracts and is bounded by SB1 and SB2. It begins with evaporitic and carbonate deposits of the Chehel Member. The upward increase in benthic foraminifera and miliolid abundance particularly within the TST and HST reflects variations in water depth and depositional energy. The transgressive surface (TS) and maximum flooding surface (MFS) occur at approximately 608 m and 538 m, respectively. These surfaces are identifiable on the gamma-ray log through distinct API shifts, with a marked decrease indicating the TS and an increase corresponding to the MFS.The second sequence, with a thickness of 74 meters, contains TST and HST systems tracts and extends from the upper part of the Champeh Member into the deposits of the Mol Member.The results of this study correlate well with the Ap11 tectonostratigraphic megasequence and the Ng10 and Ng20 maximum flooding surfaces proposed by Sharland et al. (2001). Although this research focuses on a single stratigraphic section, it provides a valuable foundation for future investigations and for developing a comprehensive analysis of the sedimentary basin. ConclusionThe Gachsaran Formation in the Bostaneh Anticline section, with a total thickness of 1288 meters, comprises the Chehel, Champeh, and Mol members. In the studied subsurface interval, the formation consists of alternating layers of limestone, argillaceous limestone, marl, anhydrite, and a considerable thickness of salt, and it is stratigraphically positioned between the overlying Mishan Formation and the underlying Pabdeh Formation.Microfacies analysis reveals five major microfacies, including evaporite-mudstone alternations, mudstone, miliolid wackestone, bioclastic-peloidal packstone-wackestone, and bioclastic wackestone-packstone, representing deposition in peritidal to lagoonal environments. The absence of cortoids, oncoids, pisoids, and aggregate grains features typical of carbonate shelf settings supports a carbonate ramp as the depositional model for this formation.Sequence stratigraphic interpretations, integrated with paleontological evidence, demonstrate the presence of two depositional sequences: a lower complete sequence consisting of LST, TST, and HST, and an upper sequence comprising TST and HST. Additionally, three sequence boundaries were identified (two SB1 and one SB2).The stratigraphic succession at this section correlates well with the Ap11 tectonostratigraphic megasequence and the maximum flooding surfaces Ng10 and Ng20 defined by Sharland et al. (2001). Although this investigation focuses on a single section, it provides a robust basis for future regional studies and contributes to a more comprehensive understanding of the sedimentary evolution of the basin. https://esrj.sbu.ac.ir/article_101281.html IntroductionAlborz Mountains range in northern Iran is an arc that extends from the end of Talesh in the west to its intersection with the Kopeh Dagh Mountains in the east (Jackson et al, 2002). (Alavi, 1996) introduced the mountains as a multi-orogen belt that has been influenced by the Cimmerian and Alpine orogenies from Late Triassic to Oligo-Miocene. Detailed structural studies in the mountains indicate it has been suffered inversion tectonics (Zanchi et al, 2006; Yassaghi and Madanipour, 2008; Gholami et al, 2016). Materials and MethodsThe geological map of the study area has been constructed based on the present geological maps of Kiasar (Akbarpour and Saeedi, 1991) and Jam (Alavi and Hamedi, 1997), investigation of Landsat 8 satellite images with 15 meters spatial resolution, and detaile field mapping. Using the constructed geological map in this study, detailed field mapping, and Digital Elevation Model (DEM)1 data, two cross-sections perpendicular to the general trend of the structures have been constructed. For fault kinematic analysis, Riedel shear fractures, fault steps, crescentic fractures, mineral fiber growth on fault surfaces, as well as stereographic analysis have been employed. Results and Discussion- Pop-up structure of Tuyeh Darvar Mountains:The Tuyeh Darvar Mountains are bounded by the Mila Fault in the north and the Giv Fault in the south. These faults with opposite dip directions thrust the Lower Paleozoic and Mesozoic rocks over the younger Tertiary units. The Giv and Mila faults, with opposite dips, have uplifted the Paleozoic rocks and present a geometry similar to one introduced as inlier structure in the Taleghan Mountains (Annels et al, 1975). Structurally this geometry is known as pop-up structure, which is mostly formed by faulting during inversion tectonics (Mcclay, 1995). Since the displacement of backthrust is greater than that of the main fault in the inverted area (Conney et al, 1996), this geometry can be considered a characteristic of faulting related to inversion tectonics in the Tuye Darvar area. As a result of Mila's fault activity, in the eastern part, Upper Paleozoic rock units (Jeirud Formation) were thrust over Cenozoic rock units (Fajan Conglomerate) and in the western part, Mesozoic rock units (Lar Formation) were thrusted over Cenozoic rock units (Eocene marls). From east to west, the strike of the fault changes from east-west to northeast-southwest. In the hanging wall of the Mila fault, the Tuyeh Fault has formed, causing the lower Paleozoic rock units to be thrust over the upper Paleozoic units in the western part, and over the Triassic rock units in the eastern part.The NE-striking Giv Fault with approximately 20 km in length forms the southern border of Tuyeh Darvar Mountains. As a result of the Giv fault activity, the deposits of the Shamshak Formation (Jurassic) and the Cretaceous limestone units have been thrusted over the Eocene units. The dip angle of the Giv fault plane varies between 60 and 75 degrees to the north-west and has a left-lateral reverse mechanism.The Darvar Fault in AA' section, has a dip of 75 degrees in the north-west of the Giv fault and has a left-lateral reverse mechanism. The Darvar Fault, as a hanging-wall branch of Giv fault, has caused Triassic rock units (Elika formation) to thrusted over Jurassic rock units (Shamshak Formation).- Tectonic evolution of Tuyeh Darvar Mountains:  Because of the early Paleozoic extension or Permian-Triassic peripheral bulge and formation of normal faults, the Giv Fault could have been formed during this process.  Following the compressive phase in the Upper Cretaceous, reactivated the pre-existing normal faults and inverted them to reverse faults. The inversion effect of the Giv Fault is associated with the development of the Darvar Fault in its hangingwall. Consequently, the Mila Fault has formed as a backthrust to the Giv Fault and the Tuyeh Fault has also formed in the hangingwall of the Mila Fault. The inversion mechanism has been continued until Upper Eocene by considering the outcrops of the Paleocene and Eocene rocks in the footwall of the Mila and Giv faults. Continuation of convergence, since Miocene, through westward movement of the southern Caspian Block relative to central Iran causes reactivation of the left-lateral strike-slip faults. Therefore, the Giv Fault has been formed during the early Paleozoic extensional phase or as a result of environmental uplift and the formation of normal faults in Eastern Alborz during the Permian-Triassic age. Closure of the Neo-Tethys Ocean (Upper Cretaceous), applied the compressive phase that renewed activity of the pre-existing normal faults and their inversion. Therefore, the Giv Fault could have started to invert from this time. The effect of inversion of the Giv Fault is associated with the development of the Darvar Fault in its outer wall, and with the continuation of this inversion, the Mila Fault is formed as a backthrust of the Giv Fault and the Tuyeh Fault in the outer wall of the Mila Fault. According to the Paleocene (Fajan conglomerate) and Eocene (Karaj Formation) outcrops and their location in the footwall of the Mila and Giv faults, it can be inferred that the inversion mechanism continued until the upper Eocene.It seems that the evolution of Alborz crust at the end of the Cenozoic (Miocene), was more compressive and accompanied by generally strike-slip movement (Allen and et al, 2003).  The westward movement of the South Caspian basement relative to Central Iran has caused left-lateral movement of the faults. Accordingly, the Alborz mountain range is currently under oblique left-lateral shortening, while the faults in its eastern parts has greater amount of left-lateral than its western parts (Jackson et al, 2002). ConclusionTuyeh Darvar Mountains are asymmetric pop-up structure that thrust the older Paleozoic-Mesozoic rock formations over the Tertiary rock units by the Giv and Mila faults, which have opposite dip directions. The Giv Fault as the main thrust and the Mila Fault as its back thrust are southern and northern boundaries of the pop-up structure, respectively. The Giv Fault as initial normal fault has formed during the Early Paleozoic extension phase or during the Permo-Triassic uplift in the eastern Alborz. Compressive phase in Upper Cretaceous, related to Neotethys closure, reactivated the pre-existing, e.g., the Give Fault, normal faults and invert them to reverse faults. Inversion mechanism has been continued until Upper Eocene by considering the outcrop of Paleocene (Fajan conglomerate) and Eocene rocks (Karaj Formation) in the footwall of the Mila and Giv faults. The post-Miocene to Quaternary left-lateral-shear in the eastern Alborz is proposed to be related to the southern Caspian westward movement.  https://esrj.sbu.ac.ir/article_104965.html IntroductionThe northwestern region of Iran is located on the Alpine-Himalayan orogenic belt, in an area between the South Caspian, the South Caucasus Orogeny, the Eastern Anatolia Plateau and the Northern Zagros, and is affected by the movements caused by the convergence of the Arabian and Eurasian Plates. The study area in this research is located in the Northwestern Iran and includes the provinces of East Azerbaijan, West Azerbaijan, Ardabil and Zanjan. One of the most important structures in this area is the North Tabriz fault, Aras, Ardabil-Miyaneh and Astara faults, which have controlled the geology of the region. North Tabriz fault is one of the most important structures in the northwestern region of Iran, which has controlled the geology and tectonics of the region. These faults have played an important role in the seismicity of this region and have caused major earthquakes in the history of this land. It is also very important to identify the origin of named faults and lineaments and their importance in future construction and reinforcement of structures. Therefore, detection of the pattern of distribution and spatial epicenter of earthquakes, and Lineation in GIS, help to relocated the faults and revealed the new faults.TectonicsThere are many faults with different trends in the northwestern region of Iran, and the important and active faults known in this region, include the North Tabriz Fault, Aras Fault, Mishu Fault, Salmas Fault, Urmia Fault, Astara-Ardabil Fault, and Mianeh-Ardabil Fault (Zamani, G. and Masson, 2014; Zamani G., 2017). These faults, which have been identified by various researchers and some of them have been introduced, control the major structure and tectonics of this region and also play an important role in the seismicity of this region and have caused major earthquakes in the history of this land. Some unknown earthquakes have also occurred without any connection to a specific fault, and it is very important to identify their origin and consider their importance in civil construction and structural reinforcement in the future. For example, the North Tabriz fault, with at least 16 historical earthquakes, is considered an active seismic fault in the region. In this regard, the present study has attempted to identify such structures using remote sensing methods. The methods used in this study include using Landsat images, using DEM images, applying geometric and spatial correction to the images, image segmentation, and applying appropriate filtering.Materials and MethodsConsidering that many fault lineation in the North-West of Iran have not been identified and studied so far, or parts of them are hidden, therefore, in this research, an attempt has been made to first prepare a map of the known faults drawn from the different sources. Then by examining them and remote sensing studies, the unknown important and effective fault lineation in the Northwestern Iran should be identified and introduced. The data used for this research include Geological, Tectonic and seismic maps of the of Iran. After preparing information layers from the mentioned maps and referencing them to the ground, first the faults related to different maps were identified and unified, then the location of all the faults due to the non-observance of the grid and the global coordinate system in most of the maps that have been Now they have been published, from the point of view of the location of the faults, the images with a spatial resolution of 15 meters were corrected. In this connection, in this research, the identification of structures has been carried out with the use of Remote Sensing. Remote sensing can be used as a method to reveal geological Lineaments by using different digital processing methods on satellite images, important information can be revealed. The techniques used in this project are: combining color images (RGB), performance filters and using DEM images. By examining the faults in the reference layer using the images and filters used (Gussian, Laplacian and Sobel). In addition to the use of satellite images and the combination of different bands, in order to identify the main location of the faults and their spatial correction, defined filters (Laplacian, Sobel and Gusssian) were used to identify the lineaments or highlight the edges. Extracting lineaments from satellite images can be done in three ways: analog (manual), digital (automatic), and semi-automatic (combination of two methods), each of which has its own advantages and disadvantages. Based on the sensitivity of the project and the knowledge of the study area, the lineaments have been separated by analog (manual) method. After correcting the faults extracted from different sources, the new lineaments were extracted from satellite images. For this purpose, first, all the corrected faults in the area were implemented on satellite images to identify the dominant trend of existing faults, areas with fewer faults, and expected diagonal fractures and areas without such fractures, in order to extract the lineaments from these areas. There is a lot of morphological and structural evidence in the identification and isolation of fault lineaments on the earth's surface, including fault detection signs such as linearities, mountain fronts, abrupt interruption of elevations, subsidence intakes, etc. The existence of above ground and subsurface, elongation of strata, seismicity, bending occurred in the process of the axis of folds or along the alignment and displacement of layers, and sudden changes in sedimentary facies in the region. Considering the aforementioned evidences and remote sensing studies and the processing done on satellite images such as the analysis of shadow-highlight images, filtering, etc. New lineaments were extracted in these areas. It was found that each of the faults extracted from different maps are located in different positions and sometimes it is observed that the faults cross the boundaries. In the other cases in some of the geological maps one could see that faults are on the virtues of the mountains. The integration of information and data related to the improvement of remote sensing images and geological maps, tectonic earthquakes significantly helped in the analysis and processing of the lineaments. In this research a lot of these errors have corrected and renew the design of the fault maps in the North-West of Iran. Results and DiscussionIn order to extract new fault lines, various evidences have been used, among them are shifting of layers, lithology change, stretching of strata, and remote sensing signs.   The results obtained from this analysis, the spatial correction of the faults extracted from the maps that reduced from various sources which were located in different positions were drawn at the exact location using satellite images, hidden faults and new lineaments with the help of Landsat 8 images. Also fault detection signs were identified in the studied area and thy help about 38 lineaments have been identified in the entire study area. Mainly these faults have East-West and North-East and South-West trend that was for the first time have identified and introduced. The new lineaments identified in the study area have been extracted based on evidence and external signs of fault detection and using satellite images and existing filters, so calling a lineament as a fault, they require identifying the field signs for fault detection, including fault surfaces, fault slickensides, crash on it, etc., therefore, in this research, the name of the lineation is used for them. Conclusion1-Integration of data related to image enhancement by remote sensing method and geological maps and seismiotectonics has significantly helped in the analysis and processing of lineaments.2-As a result of these studies, 38 lineaments have been revealed as new lineaments in the northwest region of Iran, and the dominant trend of most of the lineaments is northeast-southwest and east-west, while these lineaments were not displayed on the geological maps prepared by the Geological Survey of Iran.3- Detailed studies of new lineaments and fault signs such as layer displacement, displacement of streams, lithological changes in linear growth of plants, elongation of strata, etc. has led to the identification of 21 new faults out of 38 lineaments in the region.4- The intersecting lineaments with the existing faults and the almost west-east trend are in line with the trends mentioned by Nogol Sadat (1978) and show a close trend with the basement faults mentioned by him.5- New lineaments identified in the area based on external evidence and signs of fault detection and using satellite images and existing filters have been extracted, so naming a lineament as a fault requires identifying field signs to identify faults, including fault surfaces, fault mirrors, slips on it, etc. Therefore, in this study, the name of lineament has been used for them.6- The existence of a lineament on the ground is never a definitive indication of the existence of a fault, and also the certainty of the existence of a fault on the ground does not indicate its exact location, because in some cases, despite the sign or effect of the fault on the ground, the fault itself is located at a distance from this effect. Therefore, in the continuation of this study, it is necessary to scrutinize the lineaments identified by field studies in terms of mechanism and also in terms of location and then introduce them as faults. https://esrj.sbu.ac.ir/article_106146.html IntroductionThe Ismailabad copper deposit is located in the 55 km NE of Saveh, Central Iran. It is situated in the middle-northern part of the Urmia-Dakhtar magmatic arc (UDMA) of Iran. The Cenozoic volcanic units in the middle part of the UDMA around Saveh host several Cu-Au-Ag-Fe deposits, (Heidari et al, 2022), Narbaghi (Fazli et al, 2019), Rangerz (Zamanian et al, 2021), Zarandiyeh (Yousefi and Alipour-asll, 2019) and Koh Peng (Rajabpour et al, 2017, 2018). General studies in the middle part of the UDMA show the importance of mantle metasomatism in the formation of intrusive rocks. Based on U-Pb dating, this magmatic complex crystallized in the upper Eocene (Nouri et al, 2018).Although there are many signs of old mining, mineral indices and Cu-Au-Ag deposits that are temporally and spatially related to Eocene magmatism in this area, but compared to other areas such as Arasbaran and Kerman belts, it has received less attention from researchers. It has been tried to understand the factors controlling of the copper mineralization based on the field geology, petrology, structure and texture, mineralogy and paragenesis of ore minerals, geochemistry and microthermometry of fluid inclusions. This research can be used to improve the exploration criteria of this type of deposit in the central part of UDMA and other similar places.Materials and MethodsDifferent rock units from geological sections were used. Petrographic and mineralogical studies were conducted on 23 thin and thin- polished sections. In order to conduct geochemical studies of ore samples, 15 samples were analyzed by the ICP-OES method in the Iran Minerals Research and Processing Center. Also, to determine the characteristics of the ore-forming fluid, petrographic and microthermometric studies were conducted on two calcite mineral samples in the laboratory of Tarbiat Modares University. Results and DiscussionThe host rock for Cu-mineralization in the area is volcanic and volcano-sedimentary units of Eocene age that affect intrusive masses of granitic, monzonite, and gabbro-diorite. These host rocks have been affected by siliceous-carbonate, propylitic-chloritic, sericitic, and intermediate argillic alteration with different intensities. Mineralization occurs in the form of sulfide-oxide veins.Primary minerals include chalcopyrite, pyrite, tennantite, tetrahedrite, ologist, and magnetite, and secondary minerals include chalcocite, coveolite, azurite, malachite, chrysocolla, goethite, and limonite, which were deposited in the endogenous, secondary enrichment, and oxidant stages. The main textures of ore minerals include vein-veinlet, disseminated, open space filling, brecciated, replacement and coloform. The association of copper sulphide minerals such as chalcopyrite, chalcocite, covellite with pyrite and sulfosalts such as tennantite and tetrahedrite is the characteristics of epithermal deposits (Hedenquist, 2015). Microthermometric studies of fluid inclusion indicate that the homogenization temperature of 140.3 to 330℃, which according to Arribas et al. (1995) characterize fluid flow in the deep levels of hydrothermal systems. The salinity is 11.4 to 17.8 %wt. NaCl and the density is 0.78 to 1.05 g/cm3. The depth-pressure diagram (Fournier, 1999) shows that this process probably occurred at a depth of about 100 to 500 meters below the underground water level and hydrostatic pressure of 130 to 20 bar. In subvolcanic environments, meteoric waters, under the influence of physicochemical processes (temperature > 370 °C and lithostatic pressure), form complexes with sulfide anions (SO4-2 and HS-) and, to some extent, chloride, and these complexes have played an active role in transporting copper and accompanying elements (Pirajno, 2009). The processes of boiling, mixing and surface dilution of fluids are one of the important factors of the instability of chloride and sulfide complexes that lead to the simultaneous formation of Fe and Cu ore minreals. Sudden decrease of pressure in the fractures of the area is responsible for the formation of sulfide phases in the final stages of mineralization. There is an obvious overlap between the temperature and salinity range of mineralization in the Ismailabad deposit with the manto-type deposits.ConclusionThe low-sulfidation epithermal Cu mineralization in the area is associated with Oligo-Miocene intrusive bodies and Eocene volcanic rocks, which is controlled by northwest-southeast trending faults. Copper mineralization occurred in the form of vein-veinlet and is associated with hydrothermal alteration including of siliceous-carbonate, argillic, propylitic, and sericitic. The mineralization includes hypogene, supergene and oxidant zones. In the hypogene zone, sulfide phases are mainly pyrite, chalcopyrite, and is associated with ologist, hematite, and magnetite. In the supergene zone, chalcocite and covellite are occured on the margin of primary sulfides. In the oxidan zone, malachite, azurite, chrysocolla and iron hydroxides have been formed. Cu shows highest correlation to the Ag, S, Sb, As, Ca, and Sc respectively. The instability of sulfide and chloride complexes leads to the simultaneous precipitation of Fe and Cu and the formation of sulfide phases in the last stage of mineralization. It has been significantly affected by the phenomenon of boiling, mixing and dilution of basin evaporation brines. Based on the values obtained from homogeneous temperature and salinity, the mixing of magma waters with meteoric waters and basin evaporation brines have played a role in the formation of ore minerals. Geological, mineralogical, alteration, and fluid inclusion data indicate that the occurance of manto-type mineralization. https://esrj.sbu.ac.ir/article_100883.html IntroductionThe Qeysari copper deposit is located on the 1:100,000 scale of Kalateh-e-Resham, 105 km south of Damghan, with geographical coordinates of 54 ˚18´ 00 ˝to 54 ˚19´ 00 ˝east longitude and 35 ˚19´ 00˝ to 35 ˚ 21´ 00 ˝ north latitude. Along the Troud-Chah-Shirin volcanic belt, copper mineralization has occurred in various forms under the influence of younger semi-deep masses (with Oligo-Miocene age). In some places, such as the Chah-Musa and Koh-Zar deposits, mineralization has taken place adjacent to relatively large intrusive masses. In some parts, major intrusive masses are not present, but traces of younger magmatic activity are exposed in the form of dykes composed of diabase and microdiorite, but they are directly related to mineralization. In the Qeysari region, diabase dykes have played a direct role in mineralization. As it occurs, it is limited only to the edge of the dike and sometimes inside the dike itself. Materials and MethodsIn this study, after preparing a 1:2000 geological map of the region and conducting field surveys and sampling of the rocks of the region, 25 microscopic thin sections and 15 polished sections were prepared and examined to identify the mineralogical composition, petrology and textural relationships. For geochemical studies, 8 samples were selected for XRD analysis, 8 samples for XRF analysis and 8 samples for ICP-MS analysis. Results and DiscussionThe Qeysari copper deposit is located in the northern part of the Central Iran structural-sedimentary zone. The volcanic and volcanic-sedimentary rocks host the semi-deep intrusive masses of the region, equivalent to the Karaj Formation of the Eocene period. In this area, andesitic, andesite-basalt, basalt and pyroclastic rocks of Middle Eocene to Oligomiocene age are exposed. The uplift of the Troud-Chah-Shirin mountain range has been formed under the influence of the action of the two main Troud faults in the south and Angelo in the north with left-lateral action. The mechanism of these two faults has caused the creation of smaller faults with two trends of northeast-southwest and northwest-southeast within this mountain range. Faults with these trends are also observed in the Qeysari copper area. The controlling factor of mineralization in this area is the diabase dyke with a northeast-southwest trend, which was probably a function of faults with this trend. Mineralization in the study area is seen as veins of different thicknesses along fractures and fault zones, and most mineralization has occurred in basalts and andesites of the area.Amphibole and plagioclase have generally been transformed into chlorite and sericite, which indicates the effect of atmospheric waters on the rocks of the area. Pyroxenes are also seen in the background composition. In order to investigate the petrogenesis, determine the tectonic setting and chemical nomenclature of the rocks containing the deposit, the results of chemical analysis of 8 samples by ICP-MS method were used. Based on the Na2O+K2O vs. SiO2 variation diagram, the volcanic rocks containing the deposit are in the range of andesite, trachyandesite, and basalt. In order to determine the composition and nature of the rocks in question, diagrams related to trace elements, including Zr, Ti, Nb, and Y, which are HSF and immobile elements, were used. In order to determine the tectonic environment, the ratios of trace elements were used. The ratio of trace elements Th/Ta>2 indicates the location of continental arc formation for the constituent rocks. There are various geochemical diagrams to determine the tectonic location of igneous rocks, and in this study, more diagrams based on immobile elements were used.Conclusion Based on geochemical studies, the lavas belong to the high-potassium alkaline and calc-alkaline magmatic series, which formed in a tectonic regime of volcanic arcs associated with active continental margins. This feature is related to the tectonic environment associated with subduction zones and shows the phenomenon of crustal contamination in the rocks. Among the factors controlling magmatism in subducting oceanic crust magmatic arcs are subducting sediments, which represent the effects of crustal contamination and digestion in the magma forming the rocks of the studied area. https://esrj.sbu.ac.ir/article_106255.html IntroductionTucked away in the eastern reaches of Iran’s Lut Desert, Rig-e Yalan sprawls across roughly 9,800 square kilometers, standing as one of the world’s most arid and vibrant desert landscapes. With annual rainfall barely trickling past 50 millimeters and vegetation so sparse it’s almost a mirage, this region is sculpted by relentless regional winds that etch out a mesmerizing array of aeolian landforms—towering dunes, sweeping wind corridors, and restless sand ridges that seem to shift with every gust. These dunes are like nature’s archives, their shapes, orientations, and intricate patterns telling stories of the winds that have shaped them over countless years. My goal in this study was to dive into these stories, mapping the dominant wind directions and unraveling the geomorphological dance of Rig-e Yalan using a blend of cutting-edge machine learning tools—Random Forest and K-Means clustering. What excites me most about this approach is how it bypasses the need for exhaustive field campaigns, offering a fresh, scalable way to decode desert dynamics that could inspire similar explorations across the globe. Rig-e Yalan’s elongated, oval form, stretching about 150 by 70 kilometers along a northeast–southwest axis, feels like a living canvas, painted by a symphony of regional weather systems—monsoonal winds, local airflows—and the rugged terrain that channels them. The sun blazes down here, with summer temperatures often soaring past 45°C, and the air is so parched it seems to pull the moisture right out of you. These extreme conditions fuel a relentless erosional force, giving rise to a stunning variety of dunes: linear ones that stretch like ribbons across the horizon, crescent-shaped barchans that glide over the sands, and complex star dunes that defy simple description. I drew inspiration from studies in places like China’s Hobq and Kumtag Deserts or Africa’s Namib Desert, where researchers have shown how dune shapes can unlock secrets about past climates and wind patterns. But what’s less common—and what I set out to tackle—is using a fusion of machine learning and clustering to map wind patterns across an entire region. This work bridges that gap, offering a deep dive into how winds and landforms intertwine, with insights that could resonate far beyond Iran’s borders. To pull this off, I turned to advanced remote sensing, pulling data from the Shuttle Radar Topography Mission (SRTM) and high-resolution satellite imagery to extract 15 geomorphometric indices—think of them as the landscape’s vital signs, revealing its structure and behavior. These allowed me to pinpoint wind directions by analyzing dune shapes without ever stepping foot in the desert, a method that feels almost like reading the land from afar. I grouped these directions into eight main categories: north, northeast, east, southeast, south, southwest, west, and northwest. The results don’t just deepen our understanding of Rig-e Yalan’s wind-driven world; they open doors to practical applications—tackling climate change impacts, managing wind erosion, picking prime spots for wind farms, planning military operations, or safeguarding fragile desert ecosystems in places where data is scarce. By leaning on technology rather than costly field treks, this approach is both practical and far-reaching, potentially guiding sustainable resource management in deserts worldwide, from the Sahara to the Gobi.Materials and Methods This study unfolded through a carefully crafted seven-step journey, designed to peel back the layers of Rig-e Yalan’s aeolian landscape: pinpointing the study area, gathering data, cleaning it up, extracting geomorphometric features, analyzing dune shapes, modeling wind patterns with machine learning, and clustering similar regions. I chose Rig-e Yalan for its extreme aridity and diverse landforms—its dunes, from crescent-shaped barchans to sprawling linear ones, are like a natural laboratory for studying wind patterns. The region’s hyper-arid climate, with its sparse vegetation and relentless winds, makes it a perfect canvas for exploring how landscapes evolve under the influence of aeolian forces. The data came from a rich mix of sources: Landsat 8/9 and Sentinel-2 satellite imagery, offering 10–30-meter resolution, SRTM and ALOS PALSAR digital elevation models at 30-meter resolution, and Google Earth for close-up visual checks of dune shapes. Preprocessing was like tuning an instrument before a concert—I used techniques like Dark Object Subtraction (DOS), FLAASH, and 6S to correct for atmospheric noise, ensuring the data was as clear as the desert sky. From the elevation models, I extracted 15 geomorphometric indices: slope (SLP), aspect (ASP), general curvature (CURV), plan curvature (PC), profile curvature (PRC), height variation (HV), topographic position index (TPI), surface roughness (RUG), sediment transport index (STI), terrain ruggedness index (TRI), slope direction gradient (SDIR), windward/leeward index (WI), local elevation difference (ED), local relief (LR), and relative position index (RPI). These metrics were my tools for decoding how dunes move and how winds shape them, each one offering a piece of the puzzle. For modeling wind patterns, I chose Random Forest with 50 decision trees—a method I admire for its reliability and ability to wrestle with complex, non-linear data without tripping over itself. I trained it using wind direction data from 3,948 field stations, sorting directions into those eight main classes. To group similar landscape zones, I turned to K-Means clustering, settling on six clusters after testing with the Elbow and Silhouette Score methods, which helped me find the sweet spot for grouping without forcing unnatural divisions. This clustering approach felt like sorting the desert into distinct neighborhoods, each with its own topographic character. Validation was crucial to ensure the results held up under scrutiny. I used statistical measures like overall accuracy (around 78%), Kappa coefficient (about 0.64), F1-Score, mean absolute error (MAE), and mean squared error (MSE). For a reality check, I compared the model’s predictions to actual dune shapes seen in Google Earth imagery, looking for that moment of alignment between data and desert. The toolkit was a powerhouse: Google Earth Engine for crunching remote sensing data, ArcGIS and SAGA for spatial analysis, Python (with scikit-learn, TensorFlow, and XGBoost) for the machine learning heavy lifting, and R and MATLAB for stats and visualizations. Together, these tools wove a seamless pipeline for dissecting Rig-e Yalan’s geomorphological story, blending precision with creativity. Results and DiscussionThe findings painted a vivid picture of Rig-e Yalan’s wind-driven world: southeast (SE) and south (S) winds dominate, shaping 41.42% and 39.59% of the landscape, respectively, while east (E) and northeast (NE) winds play a quieter role, influencing just 19% of the area. The Random Forest model nailed the wind direction classifications, hitting an accuracy of about 78% and a Kappa of 0.64. It shone brightest for SE, S, and SW directions, with F1-Scores above 0.8, showing it’s got a sharp eye for the main players. The west (W) direction was a tougher nut to crack, with a lower F1-Score of 0.31, likely because its dune shapes blend into neighboring classes or get tangled in local terrain quirks. When I cross-checked the model’s predictions with real-world dune patterns in Google Earth, I found a solid 78% match, especially in areas with crisp barchan and linear dunes in the south and center—moments when the data felt like it was singing in harmony with the landscape. K-Means clustering revealed six distinct morphogenic zones, each with its own topographic personality. Zones 1 and 3, with gentle slopes (5–10 degrees) and smoother surfaces, were hotbeds of dune movement, swept along by the dominant winds. Zones 2 and 4, tucked in leeward areas with rougher terrain (roughness > 0.5), were more stable, acting as sediment traps where the sands settle. I also spotted anomalies—519 pixels, or about 129.75 square kilometers, that didn’t follow the dominant wind patterns, mostly clustered in the central and eastern parts. These outliers likely stem from secondary eastern winds or localized terrain quirks, like sudden ridges or dips that nudge the winds off course. The geomorphometric indices were the heart of this analysis. The average slope (11.54 degrees) suggested a mostly gentle landscape, but steeper slopes (up to 77.4 degrees) in certain spots steered the winds like natural funnels. The aspect, averaging 174.6 degrees, showed slopes mostly facing south-southeast, perfectly aligned with the main wind directions. The sediment transport index (mean 3.97) highlighted intense sediment movement in steep, rough areas—places where the desert is in constant motion. Southern regions with negative curvature were erosion hotspots, where winds scour the land, while central and northern areas with positive curvature were where sediments piled up, forming natural repositories. The Shannon entropy map lit up the central and southern regions as the most complex (entropy > 1.5), signaling high morphodynamic activity and erosion risk—areas where the desert is alive with change. These findings echo studies in deserts like Hobq and Kumtag in China or the Namib in Africa, proving that machine learning can unlock wind patterns without needing boots on the ground. The blend of Random Forest and K-Means clustering let me pinpoint homogeneous zones and spot anomalies with precision, like finding hidden patterns in a vast, sandy tapestry. Statistically, elevation had little to do with dune movement (R² = 0.0299), confirming winds as the main sculptor. Indices like topographic position and sediment transport correlated positively with dune shifts (r > 0.6), while roughness tied negatively to stability in sheltered areas (r < -0.4), painting a clear picture of how the landscape responds to wind. Conclusion By weaving together Random Forest and K-Means clustering, this study offers a fresh lens on Rig-e Yalan’s aeolian landforms and long-term wind patterns. The Random Forest model, with its 78.36% accuracy and 0.64 Kappa, proved a trusty guide for predicting dominant winds, while K-Means clustering mapped out six zones that mirrored the region’s wind and topographic rhythms. This approach, needing minimal field data, delivered a vivid picture of aeolian dynamics, backed up by Google Earth comparisons that felt like a nod from the desert itself. The study isn’t without its challenges—long-term field data is hard to come by, the eight-direction classification might miss finer nuances, and remote sensing resolution has its limits. I’d love to see future work place portable sensors in anomaly-prone areas, like the central and eastern zones, and blend field data with numerical models to sharpen the picture. Extending this method to other Iranian dune fields, like Rig-e Jen or the Central Kavir, could unravel broader regional wind patterns and climatic shifts, adding new chapters to the story. The implications are vast: from grappling with climate change and wind erosion to picking ideal wind farm sites, planning military strategies, or safeguarding desert ecosystems. This framework is a blueprint for data-driven geomorphological studies in arid regions, offering a scalable, cost-effective way to inform sustainable resource management and paleoclimate research globally. It’s a method that feels alive with possibility, ready to explore deserts from the Sahara to the Gobi and beyond. https://esrj.sbu.ac.ir/article_106256.html IntroductionEarth's surface landforms and geomorphological landscapes are constantly evolving. Geomorphic systems are complex, leading to uncertainties in our understanding of their state. Thus, the ability to measure variables is crucial for geomorphologists. Therefore, the main goal of scientific explanation in the science of geomorphology is the ability to measure the processes and environmental factors that affect the evolution of the Earth's landscapes and landforms. As Mansouri et al. (2023) noted, quantitative methods in geomorphology are important because they offer tools to accurately and efficiently quantify interactions between landforms and related processes, enabling more effective description and interpretation. Tectonic geomorphology studies the interplay between tectonic forces and surface processes that sculpt Earth's landscapes, particularly in active deformation zones. Quantitative topographic analysis is valuable for measuring landforms and geomorphological landscapes because tectonic activity significantly shapes the Earth's topography. In earth sciences, including geomorphology, digital elevation models are commonly used to extract and evaluate topographic swath profiles, providing insights into surface conditions and roughness. Geoscientists commonly employ topographic and drainage network analyses in tectonic geomorphology (Pérez-Peña et al, 2009a; 2009b; 2010; Kirby and Whipple, 2012; Giaconia et al, 2012; Royden and Perron, 2013; Willet et al, 2014; Pérez-Peña et al, 2017). Specifically, topographic swath profiles are used to analyze these patterns, revealing landscape elements and tectonic influences (Molin et al, 2004; 2012; Andreani et al, 2014; Scotti et al, 2014; Azañon et al, 2015). Swath profiles analysis is most widely used in tectonic geomorphology. Numerical evaluation of tectonic uplift or subsidence, detection of fault location, explanation of river capture and antecedent valley formation, as well as testing of geophysical models, are among the most common applications. The present-day great availability of high-resolution Digital Elevation Models has improved tectonic geomorphology analysis in its methodological aspects and geological meaning. Today, it has been proven that swath profile analysis has proved to be useful in the study of large orogens to evaluate the effects of vertical surface movements, as well as in the investigation of fluvially or glacially sculpted topography. One of the main applications of topographic swath profiles is morphological and morphotectonic analysis of various landscapes on the Earth's surface to explore the short and long-term landscape response to tectonic activity and climate changes. Most of the morphometric analyses are conducted in GIS software, which has become a standard tool for analyzing drainage network metrics.Materials and MethodsTo investigate the long-term evolution of the landscape within the Iranian part of the Makran Accretionary Prism, with a particular focus on the interaction between active tectonic processes and the erosional impact of deep river incision, we employed the SwathProfiler plugin.This methodology allowed us to generate topographic swath profiles, providing a detailed representation of the landscape's morphology. A key advantage of this approach, as originally described by Pérez-Peña et al. (2017), lies in its streamlined and automated execution. The entire workflow is designed to be readily implemented using digital elevation models (DEMs) data within the widely used ArcGIS software environment, ensuring efficient data processing and analysis. The ease of use and automation significantly reduce the time and effort required for generating swath profiles, making it a valuable tool for large-scale landscape studies. Furthermore, to complement the topographic analysis, we integrated both topographic and geological datasets. Topographic information was extracted from topographic maps at scales of 1:250,000 and 1:50,000, providing a range of spatial resolutions for detailed and regional analysis. Geological data, crucial for understanding the underlying structural controls on landscape evolution, were derived from geological maps at scales of 1:100,000 and 1:250,000. The integration of these diverse datasets, encompassing topographic and geological information at multiple scales, allowed for a comprehensive assessment of the factors influencing the long-term landscape development of the Makran Accretionary Prism. The combination of the SwathProfiler plugin's efficient processing capabilities with the availability of detailed topographic and geological data enabled a robust and insightful investigation into the complex interplay of tectonic and fluvial processes shaping this dynamic region. The SwathProfiler minimizes the time and the calculation process to extract swath and longitudinal river profiles. They also allow the extraction of key information from profiles that may help in their interpretation and analysis. Swath profiles can be examined statistically to extract maximum, minimum, and mean topographic elevation for each transect. Mean elevation is a good approximation to the general topographic trend of the landscape within the swath profile band, whereas maximum and minimum elevation can inform about landscape variations in the direction perpendicular to the swath profile. Moreover, other parameters as local relief (maximum elevation - minimum elevation) or quartile (Q1 - Q3), can also describe topographic variations along the swath. Generally, stable areas, such as basins or plateaus with low-to-moderate incision, will yield low values of local relief and swath profiles where all lines will merge. Conversely, high local relief and wider variations of swath profiles will be characteristics of mountain ranges or highly dissected landscapes exposed to high incision and/or uplifting (Pérez-Peña et al, 2017). Results and DiscussionIn general, the longitudinal topographic profiles show remarkable features. Generally, the results indicate substantial variations in both longitudinal and transverse profiles, with a significant degree of oscillation observed in their respective values (maximum elevation (0-2200 m), minimum (0-1500), mean (0-1680), Q1 (0-1610), Q3 (0-1850), local relief (0-1550) and THi* (0-0.8)). All longitudinal profiles have recorded a very high percentage of relief, which indicates the presence of a rugged mountainous landscape along the main direction of the Makran belt. Additionally, by carefully examining these profiles, we can observe a type of topographic asymmetry in the path of the profiles, except for the diagram related to the inner Makran, which somehow displays a state of relative topographic symmetry. Overall, a general examination of the longitudinal profiles shows that in the outer and inner Makran subzones the topographic situation is relatively compact; however, in northern and coastal Makran, the level of compression and density of relief is reduced in favor of the expansion of low and low-lying surfaces (corresponding to the unit of wide valleys, plains). However, the northern Makran highlands still have a higher relative density than coastal Makran. On the other hand, the transverse topographic profiles also show very interesting features and differences in the topographic situation of the region. Generally, all profiles perpendicular to Makran are asymmetrical. The main reason for their asymmetry is the effect of the action of the main faults and thrusts in the region (including: Chahkhan, Ghasr-e Ghand, Bashagard, and Bampour thrusts). Therefore, as these profiles show, it is easy to observe the Makran subzones and their boundaries. Overall, the findings show that all longitudinal and transverse profiles recorded high changes in their values. In other words, in most profiles, the local relief curve has high variability and values. Also, the values of the enhanced transverse Hypsometric Integral index (THi*) show high variations. Thus, the highest and lowest THi* values were recorded in the North Makran longitudinal profile (affected by the Minab Thrust) and Outer Makran longitudinal profile, respectively, as well as in transverse profiles 1, 2, and 4. In addition, in significant parts of the longitudinal and transverse profiles, it was observed that the profile of the mean elevation moved away from the minimum and, along with the third quartile curve, approached the maximum. Overall, the findings of this study demonstrated that higher values (close to 1) of the THi* index, along with the mean elevation curve and the third quartile closing the maximum in many areas, indicate the existence of a young landscape and a transient state of adjustment to higher uplift rates. Overall, the results indicate a strong correlation between the first quartile parameter and both the mean and minimum elevation, with a confidence level of 99%. Pearson's correlation coefficient (r) values for the first quartile were 0.997 with mean elevation and 0.993 with minimum elevation. On the other hand, the results also demonstrate a robust correlation between the mean and minimum height parameters (Table 4). Positive values between these parameters indicate a positive and additive effect between them. Furthermore, strong relationships and correlations are evident between the Q3 and the mean, the Q1 and Q3, the Q3 and the maximum elevation, and the Q3 and the minimum elevation, all at a 95% confidence interval (Table 5).ConclusionThe topographic analysis conducted in this study, characterized by its rapid execution, has demonstrated the considerable potential for employing topographic swath profiles. This method proves both useful and practical when examining the relief characteristics of mountainous regions, especially when such analyses are performed over a regional extent. The study highlights the value of topographic swath profiles as a powerful tool for understanding and quantifying the complex surface variations inherent in mountainous landscapes. By employing this approach, researchers and practitioners can gain valuable insights into the geomorphological features and processes that shape these areas. Therefore, the application of topographic swath profiles offers a valuable and efficient means of analyzing the relief of mountainous terrains at a regional scale, highlighting its applicability in various geomorphological studies and environmental assessments. The SwathProfiler extension within the ArcGIS software provides a streamlined approach to conducting sophisticated topographic analyses. This tool is designed to facilitate rapid and efficient processing, making it particularly useful for geomorphological and morphotectonic investigations that cover extensive geographic areas. Specifically, its capabilities are optimized for landscape studies conducted at a regional scale, allowing researchers and analysts to easily perform advanced analyses of topographic data. By employing the SwathProfiler extension, ArcGIS users can readily extract valuable insights from topographic information, leading to a more comprehensive understanding of landscape evolution and tectonic processes across broad regions. The creation and subsequent analysis of topographic swath profiles within the Iranian section of the Makran prism proved valuable in discerning and elucidating regional topographic characteristics. This process, utilizing a digital elevation model as its primary data source, facilitated the consideration of both internal tectonic processes and external erosional influences that collectively shape the landscape. By employing topographic swath profiles, we were able to effectively recognize and interpret the dominant topographic patterns present in the region. The extraction of these profiles specifically allowed for a more detailed examination of the interplay between the forces of tectonic uplift and deformation, which originate from within the Earth, and the surficial processes of erosion, driven by external factors such as climate and weathering. This approach offers a comprehensive understanding of the factors responsible for the observed topographic features in this tectonically active area. https://esrj.sbu.ac.ir/article_106323.html Extent AbstractIntroductionThe significance of rivers has increased due to their role in understanding the water cycle, ecology, and interactions with groundwater across local to global scales. Rivers are now recognized as dynamic environments where significant interactions and changes occur (Chakraborty & Datta, 2013). In river engineering projects, an understanding of fluvial geomorphology principles and channel processes allows researchers to understand the form-process relationship within the landscape. Geomorphic assessment generally comprises data collection, field investigations and channel stability evaluation, establishing a foundation for analysis and design (The Federal Interagency Stream Restoration Working Group, 2001). Therefore, to achieve sustainable and integrated river management, a comprehensive evaluation of river planform and channel morphology must be conducted.In this context, one of the most important aspects involves analyses related to the classification of river planforms and channel patterns.Two primary purposes can be identified for river classification: (1) to advance scientific understanding of fluvial processes and enable channel clustering, and (2) to provide management recommendations for decisions regarding channel restoration or conservation.in this regard, geomorphic criteria may be integrated with those from other Fields (e.g., ecology, water chemistry) (Kandulfo & Pigi, 2003). River classification is one of the fundamental and important subjects in geography, hydrology, and ecology that focuses on understanding their diverse characteristics and functions. Describing hydraulic and hydrological processes requires an understanding of river behavior. Comprehensive identification of river systems and classification of natural rivers are critically important for resolving environmental and ecological challenges and achieving sustainable development. Since the late 19th century, numerous classification systems for rivers have been developed. Most of these classifications have been developed based on tectonic activities (Powell, 1875; Davis, 1895), the stage of river development (Davis, 1899), fluvial planforms (Leopold and Wolman, 1957; Miall, 1977; Rust, 1977; Qian, 1985), river sediment transport (Schumm, 1963; Wang, 1999), fluvial processes and the geomorphic characterization of riverbeds (Montgomery and Buffington, 1997) (Li et al., 2024). Despite these numerous classifications, most of these methods cannot be directly applied in river engineering. This is because, firstly, most of these classifications were developed with an academic and scientific approach and Few of them are practical. Secondly, very few of these classifications can provide a comprehensive perspective of fluvial geomorphology and its hydrological components (Li et al., 2024). Among these, the Rosgen classification provides a practical tool for predicting river behavior based on geomorphological characteristics. This method establishes a direct linkage between fluvial geomorphology and ecological restoration assessment, while contributing to improved integrated river management. Rosgen (1994, 1996) classified rivers based on parameters such as single-thread channels or multiple channels, entrenchment ratio, width/depth ratio and sinuosity, categorizing them into nine major types. He further subdivides these types into 41 subclasses and 94 sub-types based on gradient variability and channel deposits. In this study, The Givi-Chay River channel morphology was evaluated through integrated application of the Rosgen classification system and HEC-RAS hydrodynamic modeling.Materials and methodsIn this study, the main data include 1:2000 scale topographic maps of the Givi-Chay Riverbed (Ardebil Regional Water Authority), 1:50,000 topographic maps (National Geographical Organization), 1:100,000 geological maps of the Khalkhal, Givi, and Hashtchin sheets (Geological Survey & Mineral Explorations of Iran), a digital elevation model (DEM) with a resolution of 12.5 meters from the ALOS-PALSAR satellite, Sentinel2 images (2024) with a resolution of 12 meters, google earth images, and hydrometric data from Istisou and Firozabad stations. Data processing was performed with HEC-RAS, ArcGIS with HEC-GeoRAS and ENVI software. The Rosgen classification system was used for geomorphological analysis and the HEC-RAS hydrodynamic model was used to optimize it. The Rosgen model includes four analytical scales from landform to physical and biological processes (Shroder, 2013) and often emphasizes general geomorphic surfaces and morphological description (levels 1 and 2) (Rosgen, 1994). This system has six key indicators including entrenchment ratio, width-to-depth ratio, sinuosity, channel number, slope, and bed grain size, and divides rivers into eight main classes and 90 types (The Federal Interagency Stream Restoration Working Group, 2001). The entrenchment ratio is defined as the ratio of flood-prone width to bankfull width, which was simulated using HEC-RAS and GIS (Kheirizadeh et al., 2018). The width-to-depth ratio represents the channel width at bankfull discharge divided by the mean depth, calculated for a 2-year return period (Rosgen, 1994). Sinuosity is determined as the ratio of stream length to valley length. Bed material grain size was assessed through Wolman pebble count methodology and volumetric sampling.Result and discussion Evaluating channel morphology is one of the most essential components of river management. In recent years, river classification and morphological assessment have increasingly focused on watershed management and river restoration, with the Rosgen hierarchical classification system now widely recognized as one of the most important and effective approaches. This study evaluates the geomorphological characteristics of Givi-Chay river channel through an integrated approach combining Rosgen’s classification model and HEC-RAS hydrodynamic modeling. Givi-Chay is one of the most important sub basins of the Ghezel Ozan River, playing a significant role in water supply for the counties of Khalkhal and Givi in Ardabil Province. Based on geomorphological characteristics, this river was divided into four reaches in the downstream direction: Khalkhal, Givi Dam, Givi, and Firozabad. The Khalkhal reach has an extensive floodplain with developed meandering patterns. Based on the Rosgen classification system, this reach was categorized into two main types (C and E) and four sub-types (C5b, E6b, E5b, and C4). All river types in this system exhibit high vulnerability to both natural and anthropogenic disturbance. Anthropogenic modifications to channel form and fluvial processes have been extensive near Khalkhal city, resulting in multiple disturbances to the river's natural functioning. In the Givi Dam reach (Reach 2), the river was classified into two main types (B and C) and four sub-types (B4, C5b, B3, and B4) based on the Rosgen classification system. The C5b-type reach, extending approximately 4.4 km near Anaviz village, displays a relatively wide floodplain and well-developed meandering patterns, characterized by high width-to-depth ratios and significant entrenchment. The C5b-type reach, extending approximately 4.4 km near Anaviz village, displays a moderately wide floodplain and well-developed meandering morphology, featuring high width-to-depth ratios and significant entrenchment characteristics. The remaining sections of this reach are classified as primary Type B. Two dominant controls explain this reach's morphology: canyon confinement and non-existent floodplain development. The banks of this river type exhibit stable to moderately stable conditions. The Givi reach contains three primary channel types (E, C, and D) under the Rosgen classification system, with downstream sub-types occurring in the following sequence: E5, C5, D4b, C4, D4, and C4. This reach features an extensive floodplain with quaternary young alluvial deposits. D4b and D4 types are classified as braided rivers, characterized by wide channels, abundant bars, high erodibility, and unstable banks. The extensive floodplain, confluence of multiple high-discharge rivers, and presence of erodible bank materials constitute the primary controlling factors for Type D channel formation in this reach of the Givi-Chay River system. Ultimately, the entire Firozabad reach is classified as Type B, which downstream differentiates into three subtypes: B4, B3a, and B3, formed in response to geological structure controls. In this reach, the river valley is narrow and confined by resistant volcanic rocks.ConclusionIn this study, the Givi-Chay River was analyzed using Rosgen's hierarchical classification system and the HEC-RAS hydraulic model. The river was divided into four reaches: 1) Khalkhal, 2) Givi Dam, 3) Givi, and 4) Firozabad. The Khalkhal reach (Reach 1) is situated within a developed floodplain and exhibits a meandering pattern, though lateral channel mobility has been constrained by anthropogenic modifications. This reach was classified into Rosgen Classes C and E, specifically including types C5b, E6b, E5b, and C4. The C4 and C5 channels exhibit high sensitivity to disturbance but demonstrate adequate recovery potential, with vegetation cover playing a critical role in their stability. In this reach, establishing riparian parks could significantly contribute to channel restoration. The Givi Dam reach (Reach 2) is predominantly mountainous with narrow valleys, and was classified into Rosgen Classes B and C (types B4, B3, and C5b). Type B3 channels exhibit low sensitivity to disturbance and high recovery potential. The Givi reach (Reach 3) features an extensive floodplain and is classified into three primary Rosgen classes (E, C, D), including the following subtypes: E5, C5, D4b, C4, and D4. The presence of braided patterns (types D4 and D4b) in this reach indicates high channel mobility and high sediment supply. This reach exhibits high sensitivity to disturbance and requires riparian zone management. The Firozabad reach (Reach 4) was classified as Rosgen Type B, including subtypes B4, B3a, and B3. In summary, the results demonstrate that the Givi-Chay River system exhibits disturbance-sensitive channel classes with variable recovery potential. The integrated application of the Rosgen classification system and HEC-RAS modeling proves effective for analyzing morphological conditions and developing river conservation/restoration management plans. By understanding how these factors interact and change river morphology, we can predict future river development trends and provide a scientific basis for river management and conservation.Keywords: Fluvial Geomorphology, Rosgen stream classification, Geometric Channel Parameters, The Givi Chay River https://esrj.sbu.ac.ir/article_106701.html Introduction Natural phenomena, due to their inherent nature, while having beneficial effects, can also have destructive consequences. Natural hazards claim the lives of thousands of people every year in different parts of the world, and a high percentage of these casualties are the product of weather hazards. Among the types of weather hazards, we can mention thunderstorms, regional floods, etc. Thunderstorms are local and mesoscale weather systems that form in a limited area of 20 to 50 km and depend on the height of convective clouds, and in addition to lightning and strong winds, they are often accompanied by heavy rainfall. Iran, due to its special geographical location, has always faced fundamental challenges in the field of water resources. The southwest region of Iran, due to its mountainous location, large-scale climatic systems affecting the region, access to moisture sources in the warm southern seas, is prone to the formation of thunderstorms. This region includes the provinces of Khuzestan, Chaharmahal Bakhtiari and Kohgiluyeh and Boyer-Ahmad, which are among the most important commercial, port, industrial and agricultural regions of Iran. Thunderstorms, in addition to the damage that can be caused to the region's infrastructure, agriculture, soil and vegetation in the event of torrential rains, air and sea transportation are also severely affected by phenomena related to thunderstorms, such as the occurrence of severe gusty winds and lightning. The results of previous research show that thunderstorms are influential and variable weather phenomena in different regions of the world and Iran. Due to the dispersion and significant effects of thunderstorms in different regions of Iran, statistical and spatial analysis of these phenomena on a monthly scale, especially in the south of the country, seems necessary. This analysis can help to better understand the temporal and spatial patterns of the occurrence of thunderstorms and be effective in planning natural hazard management and more accurate forecasting of weather conditions.   Materials and Methods This research analyzed thunderstorm data from synoptic reports of the Iran Meteorological Organization over a long-term statistical period from 1986 to 2018. The study period was selected to coincide with three 11-year solar cycles (cycles 22 to 24). This timeframe, in addition to covering long-term and comprehensive climate changes, allows for the investigation of the potential effects of solar cycle variations on the occurrence and intensity of thunderstorms. Solar cycle 22 corresponds to the period from 1986 to 1996, cycle 23 from 1997 to 2007, and cycle 24 from 2008 to 2018. Solar flare data were obtained from the Royal Observatory of Belgium. The number of stations studied varied in each cycle (8 stations in cycle 22, 17 stations in cycle 23, and 26 stations in cycle 24). Thunderstorm data were organized monthly and annually in Excel software, and the frequency trend of this phenomenon was analyzed.Subsequently, in order to analyze and display the temporal-spatial changes of thunderstorms, the inverse distance weighting method was used. This analysis was performed on a monthly average basis and for each solar cycle. The inverse distance weighting method is based on Taylor's law or the first law of geography, which states that closer geographical units have a greater impact on each other. Finally, in order to display and analyze temporal-spatial changes, the inverse distance weighting (IDW) method was used by ArcMap software, which has the ability to estimate the distribution of data at points lacking information with minimal error. Spatial distribution maps were generated based on the monthly average of data in each solar cycle. Results and Discussion Based on the results, the Ahvaz station, with the highest number of occurrences (927 cases), had the most reports of thunderstorms. In general, in the northern areas of the province or towards the highlands and foothills, such as the Dezful and Masjed Soleiman stations, the number of thunderstorm occurrences has been increasing. In this period, 738 and 723 cases of thunderstorm potential were reported for each station, respectively. In contrast, the Abadan station, with 374 cases, had the lowest number of occurrences. In cycle 22, an inverse relationship was observed between the number of sunspots and the occurrence of thunderstorms, such that the most thunderstorms occurred in the final years of the cycle. This trend was repeated in cycle 23, and in 2007, coinciding with the lowest number of sunspots, the most thunderstorms (more than 320 cases) were reported. This pattern continued in cycle 24, with the most thunderstorms occurring at the beginning and end of the cycle. In summary, it can be said that the number of thunderstorms has an inverse relationship with the number of sunspots, and the final years of each cycle experienced the highest number of thunderstorms. The results show that in January, the storms in the second decade (1997-2007) had the highest frequency, and the spatial extent of this phenomenon is evident in the Dezful and Imamzadeh Jafar stations. In February, the most events were recorded in cycle 23, which indicates the possible influence of solar cycles on the temporal distribution of this phenomenon. In March, the peak of the storms was observed in cycle 23, with the Dezful and Yasuj stations recording the highest numbers. In cycle 24, although the distribution pattern is similar to cycle 23, the frequency of events has decreased. This analysis emphasizes that climatic fluctuations and solar cycles affect the spatial and temporal distribution of thunderstorms. In April, despite the decrease in rainfall in the southwest of the country, the dispersion of thunderstorms does not change significantly compared to winter, but their concentration increases in the northwest of the region. In May, the highest activity is seen in northern Khuzestan and Chaharmahal and Bakhtiari, especially in Shahrekord during cycle 22 and in Ahvaz and Dezful during cycles 23 and 24. In June, with the strengthening of the Arabian anticyclone and the reduction of the penetration of rainfall systems, thunderstorms decreased in the west, but increased in the east of the country under the influence of monsoon systems. In July, the most occurrences were recorded in the east of the region, especially Shahrekord (cycle 22), Yasuj (cycle 23), and eastern Chaharmahal and Bakhtiari and Kohgiluyeh and Boyer-Ahmad (cycle 24). This increase is due to the penetration of monsoon systems. In August, the distribution pattern is similar to July, and the main centers are located in Shahrekord (cycle 22), Yasuj and Dogonbadan (cycle 23), and Sisakht (cycle 24). In September, the focus of occurrences remains in the east of the region, especially in Dogonbadan, Sisakht, Kuhrang, and Izeh. In October, thunderstorms, moving to the northwest and west, recorded the highest frequency in the Dezful, Ahvaz, and Kuhrang stations. In November, under the influence of winter systems, the highest occurrences were reported in Ahvaz (more than 48) and Dezful (43), and in cycle 24 the number of occurrences reached 685 cases. In December, thunderstorms were concentrated in Izeh, Ahvaz, and Yasuj, and the highest activity was observed in cycles 23 and 24. Conclusion From a temporal perspective, the analysis of thunderstorm frequency in solar cycles 22 to 24 indicates significant differences in the occurrence of this phenomenon between these cycles. The results show that the frequency of thunderstorms in solar cycle 22 was lower compared to the next two cycles (23 and 24). There is also an inverse relationship between the number of sunspots and the frequency of thunderstorms. So that in all three solar cycles, the lowest number of thunderstorms occurred in the middle of the cycle and the highest number of thunderstorm occurrences occurred in the early or late years of the cycle. In examining the temporal distribution, the highest number of occurrences was reported in the years of solar cycle 23, which indicates the significant impact of solar activity on the occurrence of this phenomenon. In total, in the 33-year statistical period, the highest occurrence was related to the year 2006 and the lowest occurrence of thunderstorms was reported in 1990. In terms of monthly distribution, the highest number of thunderstorms is related to April and November, and the lowest occurrence of thunderstorms is reported from September. The results show that the most thunderstorm activities in southwestern Iran occur in the spring and winter  seasons, while significant activities have also been recorded in the fall and summer seasons. However, thunderstorms can occur throughout the year. In fact, the seasonal distribution shows that in the spring, about 41% of the total reports of thunderstorms have been recorded, which is due to the increased atmospheric instability along with the temperature and humidity potential of the seas. In contrast, the summer season with only 8% of the occurrences shows the least thunderstorm activity, which is due to the edge of the summer pattern and the dynamic stabilities resulting from it. In the fall and winter seasons, 24 and 29 percent of the occurrences have been reported, respectivel  y. Thunderstorms in the southwestern part of Iran due to the thermodynamic characteristics of the incoming systems from the south are an integral phenomenon of these systems. These systems are generally accompanied by destructive phenomena such as thunder, lightning and strong winds. Considering the increasing trend of this phenomenon in the last three solar cycles, the awareness of users and institutions affected by this phenomenon, such as pilots, drivers of land and sea transport fleets, and farmers, of the characteristics, signs, spatial ranges, and timing of this phenomenon is of great importance. This awareness includes knowing the wind speed, the height of the systems, and the ability of the storms to intensify the wind speed, which can be effective in planning flights and preventing possible dangers on road and sea transport and agricultural products and urban structures. https://esrj.sbu.ac.ir/article_106702.html Introduction In recent years, the impacts of climate change on water security have been extensively investigated. Evidence suggests that climate change alters precipitation and temperature patterns, thereby affecting access to water resources (Ahmed and Akter, 2024). These changes influence not only the quantity but also the quality of water (Van Vliet et al, 2023). Particularly in urban areas, variability in monthly precipitation and climatic fluctuations is considered one of the key challenges of the 21st century. In Iran, due to its arid and semi-arid climate, water resource management and precipitation pattern analysis hold special importance (Modarres and Sarhadi, 2009). International studies have shown that water accessibility indicators are most sensitive to precipitation variability (Barbosa et al, 2023). Moreover, changes in evapotranspiration can reduce net primary production, thereby influencing water security (Gao et al, 2023). The resilience of water systems has also gained attention; increasing resource diversity and managing demand can enhance resilience against climate change (Kharrazi et al, 2024; Srinivasan et al, 2024). In terms of scenario analysis, recent studies using machine learning reveal that even minor climate variations can significantly impact water security indices (Chen et al, 2024). In Iran, numerous studies have examined precipitation trends. Talaei and Tabari (2011) analyzed annual and seasonal precipitation at 41 stations between 1966 and 2005, reporting a decreasing trend in about 60% of them. Similarly, Modarres et al. (2009), based on 145 rain gauge stations, identified decreasing annual precipitation in more than half of the stations and increasing 24-hour maximum precipitation in others. These findings indicate early manifestations of climate change in Iran. Theoretically, water security is a multidimensional concept encompassing access, quality, and resilience of water resources, requiring interdisciplinary and integrated analyses. Advanced statistical and computational methods such as hydrological modeling, machine learning, and wavelet transforms provide deeper insights into climate variability and precipitation patterns. However, the application of wavelet transform in climate data analysis in Iran, especially in urban areas, remains limited. The aim of this study is to investigate the variability of monthly precipitation in urban areas of Iran using continuous wavelet transform (CWT). Adopting a multiscale approach, the study analyzes temporal-spatial precipitation trends, identifies hidden patterns, and explores periodic variations across different time scales. The novelty of the research lies in employing wavelet analysis for detailed examination of precipitation data, thereby offering deeper insights into the impacts of climate change on precipitation behavior in Iran. Materials and Methods   This study analyzes the variability of monthly precipitation in Iran with a focus on nine synoptic stations located in Tehran, Mashhad, Isfahan, Tabriz, Karaj, Kermanshah, Arak and Ahvaz. The selection of these stations was based on the availability of long-term and continuous data, appropriate geographical distribution, and representation of the country’s diverse climatic conditions. The study period from 1980 to 2020 was considered in order to cover extreme climatic fluctuations, including both dry and wet years, and to enable the assessment of long-term precipitation trends. The stations represent different climatic regimes: Tehran, Karaj, Kermanshah, and Arak are situated in a semi-arid climate with annual precipitation ranging from 250 to 500 mm, with rainfall occurring mainly in winter and spring. Mashhad and Tabriz, characterized by mountainous and semi-arid climates, experience higher winter precipitation, and precipitation variability in these regions is greater due to elevation and geographical factors. Isfahan has an arid and low-rainfall climate, while Ahvaz, located in a relatively dry and lowland region, further enriches the climatic diversity and allows for examining the influence of different climates on precipitation patterns. Monthly precipitation data were obtained from the Iran Meteorological Organization and underwent preprocessing, including the identification and replacement of missing data, removal of outliers, assessment of inhomogeneities, and normalization. Data validation was performed using statistical tests such as Pettitt, Mann-Kendall, and SNHT to ensure quality and continuity. Data analysis was carried out using Continuous Wavelet Transform (CWT) with the Morlet wavelet to explore simultaneous variations in the time–frequency domain. Wavelet power spectra were generated to identify periods with high precipitation energy, and the Cone of Influence (COI) was used to minimize boundary effects. The wavelet analysis results were validated against independent datasets and previous studies to ensure the reliability of the identified patterns. By applying the wavelet approach, this study provides a detailed temporal–spatial analysis of precipitation trends in urban areas of Iran and offers practical insights for water resources management under climate change conditions. Furthermore, the results can support decision-making in drought and flood risk management across different regions of the country. Identifying precipitation cycles at medium- and long-term scales can also play a crucial role in agricultural planning, dam management, and water resources development projects. Ultimately, the wavelet-based methodology presented here can serve as a model for similar studies in other regions of Iran and countries with comparable climatic conditions.   Results and Discussion Wavelet analysis of precipitation data at the Isfahan, Ahvaz, Arak, Tehran, Mashhad, Karaj, Tabriz and Kermanshah stations showed that seasonal and multi-year precipitation patterns are accompanied by distinct fluctuations. At the Isfahan station, short-term seasonal patterns of about one year exhibited strong fluctuations; the minimum variability occurred in summer, while the maximum seasonal variability was observed in winter and autumn. In the multi-year cycles, the highest fluctuations occurred in the 3–4 year and 8–10 year periods. The intensity of the wavelet coefficients fluctuated across different scales from 1980 to 2005, and from 2008 to 2020 greater intensity and strength were observed at both short (seasonal) and long (multi-year) scales, indicating climate change in recent decades. At the Ahvaz station, the seasonal and multi-year precipitation patterns were irregular, but the amplitude of the fluctuations was smaller compared to high-altitude stations. The temporal analysis over the period 1980–2020 showed that the intensity of the wavelet coefficients increased in the second half of the study period, and fluctuations in seasonal, annual, and multi-year cycles continued, which is not a direct reflection of climate change but is consistent with precipitation patterns at other stations. At the Arak station, seasonal patterns exhibited strong periodicity with frequent short-term fluctuations. Multi-year cycles occurred with high intensity and were influenced by large-scale atmospheric patterns. The analysis of the period from 1980 to the first decade of the 21st century showed that the wavelet coefficients at different scales were significantly associated with precipitation variability, and short-term and multi-year variations became more pronounced under climatic transformations in the second decade of the century. At the Tehran station, one-year seasonal patterns coexisted with multi-year cycles, and the yellow and light green areas on the wavelet spectrum indicated seasonal fluctuations. Multi-year cycles of 2–4 years and 5–10 years were observed with high power, likely associated with large-scale climatic phenomena such as ENSO. Decadal changes from the early 1980s to 2010 reflected stronger or weaker variability in the intensity of the wavelet coefficients, and after 2010 a marked increase in the strength of both short- and long-term scales was observed. At the Mashhad station, seasonal and annual precipitation patterns showed distinct fluctuations during autumn and winter. Multi-year cycles of 2–5 years and 6–10 years also exhibited significant variability. The intensity of the wavelet coefficients increased from 1980 to 2010, reflecting the influence of multiple climatic factors and climate change on precipitation behavior. The Karaj station, with its arid and semi-arid climate, showed minimum  seasonal variability in summer and maximum in autumn and winter. Longer multi-year cycles, especially those of 2–3 years and 5–10 years, occurred with high intensity. From 2010 to 2020, however, the intensity of fluctuations decreased. At the Tabriz station, precipitation was more intense and frequent in winter and autumn, while summer showed weaker variability. Multi-year cycles of 2–4 and 6–10 years displayed considerable fluctuations, and the intensity of the wavelet coefficients increased from 1980 to 2020. The Kermanshah station had strong fluctuations in winter and autumn and weaker ones in summer and spring. Multi-year cycles between 2–5 and 6–10 years were observed, and the intensity of the wavelet coefficients increased after 2010. Comparison with previous studies indicated that this research, by applying wavelet analysis, examined precipitation cycles with greater accuracy and analyzed seasonal and multi-year fluctuations in several major Iranian cities. In addition to ENSO, the NAO and MO climate indices were also investigated. The results are consistent with similar international studies in Europe, China, and the Indian subcontinent, but the focus on Iran’s arid climate and the spatial diversity of large cities provides an innovative perspective. Overall, wavelet analysis showed that short- and long-term precipitation fluctuations with varying intensities are evident in most stations. Stations such as Kermanshah, Tabriz, and Mashhad exhibited high-intensity wavelet coefficients in 2–10 year cycles and were influenced by large-scale climatic indices, while stations such as Ahvaz and Karaj displayed relatively uniform behavior. The increase in wavelet coefficient intensity during 2008–2020 indicates the impact of recent climate changes on precipitation patterns. Furthermore, the results of this study revealed that the intensity and extent of precipitation variability in recent decades have been accompanied by greater fluctuations. Comparative analysis among stations demonstrated that geographical location and elevation play a decisive role in the strength of seasonal and multi-year cycles. In addition, the observed trends can be applied in the management of urban and rural water resources and in the development of climate adaptation strategies. The findings also showed that integrating wavelet analysis with large-scale climate indices increases the accuracy of identifying precipitation cycles. In conclusion, this study provides a comprehensive picture of precipitation behavior in Iran and establishes a valuable foundation for future research on climate change.   Conclusion This study applied continuous wavelet transform (CWT) to analyze temporal variability of monthly precipitation in Iranian metropolitan areas from 1980 to 2020, identifying both seasonal and multi-annual cycles. Results showed precipitation patterns were influenced by annual cycles (~1 year) and multi-annual cycles (3–10 years). Strong oscillations were particularly evident in Tehran, Kermanshah, and Mashhad, coinciding with large-scale climate indices such as ENSO and NAO. In contrast, stations like Ahvaz, characterized by lower altitude and warmer conditions, showed weaker intensities and less regular oscillations, underscoring the importance of geographic factors such as elevation, temperature, and latitude in precipitation variability. The analysis further indicated that after 2010, precipitation variability intensified at both seasonal and multi-annual scales across most stations, serving as evidence of the increasing impacts of climate change. The findings are practically valuable for water resource management, drought and flood preparedness, as well as urban and agricultural planning. Furthermore, linking results to large-scale climate indices enhances the potential for predictive modeling and early warning systems. https://esrj.sbu.ac.ir/article_105906.html IntroductionManganese deposits occur in various tectonic settings from mid-ocean ridges to plagic environments and continental margins. Depending on the difference in the source of manganese supply, these deposits are divided into hydrothermal, hydrogenous and diagenetic (Oksuz, 2011; Polgari et al, 2012; Schmidt et al, 2014). The change in origin causes distinct geochemical differences in these deposits.The studied area in the southwest of Kerman province (Fig. 1) hosts manganese deposits. This area is a part of the South Sanandaj-Sirjan zone, where different rock sequences formed in association with the subduction of the Neotethys oceanic crust beneath the central Iranian micro-plate occur. The aim of this study is to investigate the mineralogical and geochemical properties of the Zaghadareh manganese deposit in order to identify the origin and genesis of this deposit, which has not been studied by researchers so far. Also, the formation of this deposit is compared with some other deposits from the Sanandaj-Sirjan zone to gain a better understanding of the conditions governing the mineralization environment of the Neotethys Ocean during the Mesozoic Era.The study area belongs to the southern part of the Sanandaj-Sirjan zone (Fig 1a). As the other parts of the zone, this area is composed of metamorphic, igneous and sedimentary rocks. The main lithology of the area includes a color mélange with Cretaceous age (Fig. 1b). These rocks cover the southern and southeastern parts of the region and include some parts of the ophiolitic sequence, volcanic rocks, radiolarian cherts and pelagic limestones. In the northern parts, basaltic and andesitic rocks of Mesozoic-Cenozoic age occur.The Zaghdarreh deposit occurs at the boundary between the ophiolitic color mélange and pelagic limestones (Fig. 1b). In this area, radiolarian cherts host the Mn-ore mineralization (Fig. 2). The cherts occur as interlayers with pelagic limestones in the region (Fig. 2a, b and c). The thickness of the Mn-ore layers in different parts of the deposit varies from 1 cm to more than 1 m. The occurrence of iron oxides and hydroxides (hematite and limonite) is visible in some parts of the deposit (Fig. 2d), which is evidence of the presence of Fe along with Mn in this deposit. Faulting has caused crushing and uplift in limestones and radiolarite cherts. Based on field surveys, these faults have a NW-SE trend and a 60º dip to the SW.Materials and MethodsThe samples were analyzed for major elements in the Kansaran Binaloud laboratory, Tehran using a Philips PW 1480 XRF instrument. The trace emelent contents were measured through ICP-MS methos in ACME labratoy, Shivana, Indian. The XRD analyses were carried out in the Zarazma laboratory, Tehran.Results and DiscussionMineralographyThe samples shows a uniform paragenesis in the polished and thin-polished. Pyrolusite is the main manganese-bearing mineral, which is accompanied by braunite. Pyrolusite is generally occur as fine-grained and associated with fine-grained quartz (Fig. 4a). Psilomelane and todorokite were identified in some samples, occurring as thin veins or filling the empty spaces between the other grains. Quartz, hematite and calcite are other minerals in these samples.The main textures in the studied samples include colloform, micronodular, synchronous fine-grained and stockwork veins (Fig. 4). The colloform texture (Fig. 4b), which is abundant in the samples, indicates formation in a deep marine environment where manganese oxides and hydroxides precipitated slowly. The micronodular texture (Fig. 4c, d, and e) consists of spherical or elliptical aggregates of manganese minerals in a matrix of fine-grained silica and is indicative of slow depositional environments. The cores of the nodules are made of braunite, which is covered by a coating of pyrolusite (Fig. 4d, e). The synchronous fine-grained texture (Fig. 4f) indicates the coeval deposition of silica and manganese minerals, which is often associated with early diagenetic conditions. The presence of thin, interconnected stockwork veins filled with manganese and quartz minerals (Fig. 4g) indicates the intrusion of hydrothermal fluids into the host rock. Another characteristic of these samples is the alternation of manganese-bearing and silica layers, which demonstrate variations in depositional conditions and the influence of hydrothermal fluids on the mineralization process (Fig. 4h and i).MineralogyThe results of X-ray diffraction analysis of two samples from the Zaghdarreh deposit are presented in Fig. 4. The analyses show that quartz, calcite, braunite and hematite are the main minerals and fluorapatite, dolomite, clay minerals and amphibole are the minor ones. Pyrolusite is the main mineral in one sample and is considered as a minor mineral in the other sample, indicating that the conditions of formation of the deposit were not uniform in all parts of it.GeochemistryThe results of the whole rock geochemical analyses of the Zaghdarreh deposit samples are represented in Table 1. SiO2 is the most abundant oxide and its amount range from 46 to 63 wt% in the samples. MnO range from 11 to 19 wt%. The other important oxides include CaO (8-14 wt%), FeOt (8 to 11 wt%) and Al2O3 (0.8 to 1.4 wt%). The correlation diagrams between Mn and Fe, Co, Cu, Ni, Zn and V are presented in Fig. 6. The results show that manganese has the highest correlation with Fe (R = 0.62) and the lowest correlation with Ni (R = -0.63). The SiO2 vs. Al2O3 variation diagram (Toth, 1980) (Fig. 6a) shows that the Zaghdarreh deposit formed from hydrothermal fluids. Also correlations between Al2O3, TiO2 and MgO can be attributed to detrital materials from the adjacent island arcs (Zarrasvandi et al, 2023) and submarine volcanic activities.GenesisManganese oxides are formed by a variety of processes and in a variety of geological environments. In general, manganese deposits are divided into three main categories: sedimentary (sedimentary-diagenetic or stratiform), hydrothermal, hydrogenic, and supergene (e.g. Roy, 1992; Kuleshov 2011). Maynard (2010) also has divided manganese deposits into two types: primary (resulting from hydrothermal, diagenetic, and hydrogenic activities) and secondary (resulting from supergene processes). Hydrothermal deposits are formed by the deposition of metal-rich hydrothermal fluids near oceanic ridges, seamounts, arc islands, and around submarine hot springs, and hydrogenic (deposition from seawater) and primary diagenetic (deposition from pore water) processes produce Fe-Mn sedimentary nodules in the seas (e.g. Roy, 1992).Petrographic studies can be useful in determining the origin and genesis of manganese deposits. Deposits close to the source often contain hematite and quartz formed by hydrothermal fluids exhumed from the oceanic crust. Deposits far from the source are associated with jasperite and occur at a distance from mid-ocean ridges (Oksuz, 2011; Brusntinyn and Zhukov, 2012). Hydrothermal deposits usually have coarse-grained crystalline textures with hematite and quartz veins, but hydrogenous deposits have thin-layered textures and ferromanganese crusts (Oksuz, 2011). Also, the presence of stockwork veins and manganese-rich nodules indicates the influence of hydrothermal processes (Maynard, 2010; Oksuz, 2011). The textural and mineralogical characteristics of the studied samples are consistent with hydrothermal deposits.The Fe2O3-SiO2-MnO ternary diagram (Karakuş et al, 2010) also confirms this (Fig. 6b). In addition, the Mn/Fe ratio is also an important factor in investigating the origin of Mn deposits. The Mn/Fe ratio is less than 1 in lacustrine deposits, 1 in hydrogenous deposits, and higher than 10 in hydrothermal deposits (Nicholson et al, 1997). This ratio range 1.17 to 1.9 (Table 1) for the studied samples which is between those of hydrothermal and hydrogenous deposits. Also, TiO2 contents are higher than 1 for hydrogeous Fe-Mn deposits and lower than 1 for the hydrothermal ones (Ahmadi et al, 2019). The TiO2 values ​​of the Zaghdarreh deposit samples (0.03 to 0.06 wt%, Table 1) are consistent with a hydrothermal origin. The values ​​of some minor elements such as Ni, Cu, V, Co, and Zn are also useful in determining the origin of Mn deposits. Hydrothermal manganese deposits have relatively high concentrations of Co, Ni, and Cu compared to hydrothermal deposits located along mid-ocean ridges (Toth, 1980; Usui and Someya, 1997). Co is closely associated with Mn oxides and its abundance decreases on average from hydrogeous to diagenetic and hydrothermal deposits (Sabatino et al, 2011). It should be noted that manganese and cobalt are oxidized together in the same catalytic pathway, and as a result, microbial processes can cause cobalt enrichment in manganese deposits (Moffett and Ho, 1996; Polgári et al, 2012). The Co/Zn ratio is important for separating hydrothermal and hydrogeous deposits. The average ratios are 0.15 and 2.5 in hydrothermal and hydrogeous deposits, respectively (Toth, 1983). The Co/Zn ratio for the Zaghdarreh deposit samples range from 0.02 to 0.5, which is consistent with hydrothermal deposits.Trace element diagrams presented for determining the origin of manganese deposits are shown in Fig. 7. The ternary diagram Fe-Mn-(Ni+Co+Cu)*10 (Fig. 7a) indicates a hydrothermal origin for studied the samples. In the Zn-Co-Ni diagram, the samples are mainly located in the hydrothermal deposits, however some samples lie near the hydrogenous deposits (Fig. 7b).Environment of occurrenceManganese deposits derived from hydrothermal fluids can form in or near mid-ocean ridges and to a lesser extent in arc islands (Roy, 1992). Sedimentary deposits are formed by the slow deposition of Fe-Mn crusts in deep marine waters or by bacterial processes (Toth, 1980; Usui and Someya, 1997; Jach and Dudek, 2005). Deposits close to the mid-ocean ridge have higher iron contents than others and, in turn, lower TiO2 contents (e.g., Murray, 1994; Nicholson et al, 1997; Ahmadi et al, 2019). In the plot of Al2O3/Al2O3+Fe2O3 vs. Fe2O3/TiO2 (Fig. 8), samples from the Zaghdarreh deposit are located near the mid-ocean ridge, where MnO was deposited by the ridge associated hydrothermal fluids. The high Fe contents and presence of hematite in the samples studied (Fig. 4) are consistent with this.Comparison with the other Mn deposits from The Zagros and Sanandaj-sirja zones hosts many Mn-deposits, mainly formed as a result of hydrothermal processes (Zarasvandi et al, 2016b). Comparing the geochemistry of samples from the Zaghdarreh Mn deposit with other deposits can confirm the results and interpretations related to its genesis. In most of the graphs presented in Figs. 7 and 8, geochemistry of the Zaghdarreh deposit are in agreement with the other ones, although there are also some differences. The Fig. 8a shows that, unlike other deposits, diagenetic and bacterial processes did not affect the Zaghdarreh deposit. Also, this deposit, like the Nasirabad deposit (Neyriz area), also exhibits some geochemical characteristics of water-borne deposits, indicating their genesis. Also, the Nasirabad deposit was formed in a pelagic environment and at a distance from the oceanic ridge.ConclusionThe Zaghdarreh Mn deposit occurs in the southern part of the Sanandaj-Sirjan zone and in the color mélange radiolarite cherts of the Neotethys ophiolites. Petrographic studies and X-ray diffraction analyses show that the deposit mineral include pyrolusite, braunite, todorokite, hematite, quartz, and calcite. The main textures are colloform, micronodular, disseminate, and stockwork veins formed by hydrothermal processes. The geochemical properties of samples, such as high of Si, Fe, Zn and low of Ni, Co, and Cu contents is consistent with hydrothermal fluid originated Mn-deposits. Also, the ratios between Al2O3, Fe2O3, and TiO2 indicates that they were formed near a mid-ocean ridge by associated hydrothermal fluids. Submarine volcanic activities and detrital materials from the adjacent island arcs changed the geochemistry of the deposit and elevated Al, Ti and Mg contents. The results obtained for the Zaghdarreh deposit are consistent with other hydrothermal Mn deposits of the Zagros orogeny. Also, differences in position of the adjacent Nasirabad deposit (Neyriz region) and Zaghdarreh deposit indicates that hydrothermal fluids caused both the distal and proximal Mn mineralization in this part of the Neo-Tethys Ocean. https://esrj.sbu.ac.ir/article_106604.html IntroductionThe South Caucasus, which includes Armenia, Azerbaijan, and Georgia, is a region of significant geopolitical and geoeconomic importance. Strategically positioned at the crossroads of Europe, Asia, and the Middle East, it serves as a pivotal area of influence for Iran. The historical, cultural, and geographical ties between Iran and the South Caucasus further emphasize its critical nature in Tehran’s foreign policy considerations. The area's role as an energy corridor, especially through significant pipelines like the Baku-Tbilisi-Ceyhan (BTC), enhances its relevance in discussions surrounding global energy security. However, the region's complex ethnic and political landscape brings about significant challenges related to regional stability.For decades, Iran has encountered difficulties in asserting a proactive stance in the South Caucasus, often resorting to reactive or passive policies. This challenge arises from several geopolitical factors that hinder Iran's ability to effectively implement its foreign policy in the area. Key issues include intra-regional conflicts, such as the protracted Nagorno-Karabakh dispute, the dominant roles played by regional powers like Turkey and Russia, and the increasing involvement of external actors, including the United States, the European Union, and China. Moreover, socio-economic issues, territorial disputes, and geographical barriers exacerbate Iran's struggles in the region. Such dynamics foster a competitive environment wherein Iran's strategic interests—such as energy security, border stability, and regional influence—are frequently compromised by more assertive players. This study aims to identify and assess the geopolitical challenges that shape Iran's foreign policy in the South Caucasus, focusing on the roles of regional and extra-regional powers, the implications of socio-economic and security transformations, and the shortcomings of Iran’s current policy approach. Materials and MethodsTo explore the topic effectively, the study adopted a research method centered around collecting and statistically analyzing the opinions of experts regarding the challenges facing Iran. Given the complexities involved, the Delphi method was deemed most suitable for this research. This subjective forecasting technique is particularly effective for gathering useful data in uncertain contexts, such as the geopolitical landscape of the South Caucasus, and is particularly validated for predicting challenges—one of the core objectives of this study.The Delphi process is an iterative and systematic procedure wherein questions are presented to a panel of experts in successive rounds to achieve a reliable group consensus. In contrast to individual-based forecasting methods like surveys, Delphi focuses on group dynamics, allowing for a richer interaction that leads to more powerful conclusions than the sum of individual perspectives. The selected expert panel consisted of specialists in geopolitics and South Caucasus affairs, who, due to their experience and positions, were expected to provide valuable insights relevant to this study.Participants were contacted, and the response rate was highly satisfactory. Although other groups could have been involved, a selection of 15 experts was made to kickstart this exploratory study; this initial pool can be expanded in future research phases depending on funding and available resources. dropout rate during the process was a mere 7%, which is substantially lower than typical rates in published studies (usually ranging from 20% to 30%), minimizing the risk of distortion in final results.Results and DiscussionThe findings illustrate that Iran's foreign policy in the South Caucasus is significantly constrained by three primary categories of geopolitical challenges: intra-regional dynamics, the influence of regional powers, and interventions from external actors. Intra-regional factors include persistent ethnic and territorial conflicts, particularly the Nagorno-Karabakh conflict between Armenia and Azerbaijan, which has historically destabilized the region and complicated Iran's diplomatic relations. These conflicts contribute to a fragmented geopolitical landscape, where Iran's alignment with one state risks complicating ties with others, thereby limiting its capacity to implement a well-balanced regional strategy.Moreover, the influence of regional powers—particularly Turkey and Russia—constitutes a significant obstacle to Iran's aspirations. Turkey has solidified its position through cultural ties with Azerbaijan, making extensive economic investments and engaging in military cooperation, particularly evident during the 2020 Nagorno-Karabakh conflict. On the other hand, Russia, utilizing its historical dominance and maintaining military bases in the region, retains a formidable grip over security and economic dynamics.Delphi analysis revealed that 78% of experts highlighted the influence of regional powers as the foremost challenge, followed by intra-regional conflicts (65%) and extra-regional interventions (52%). External actors, including the United States, the European Union, and China, have expanded their presence in the South Caucasus through energy projects, security partnerships, and infrastructure investments—most notably, China’s Belt and Road Initiative. Such interventions frequently marginalize Iran, which faces limitations due to international sanctions and domestic political constraints.ConclusionThe results of this research indicate that the upcoming challenges in Iran's relations with the countries of the South Caucasus region have a geopolitical nature and are primarily due to the multiplicity and diversity of issues and influential actors in the region, along with the interactions and interconnections of complex geopolitical matters that play a significant and effective role in the ambiguity and passivity of the foreign policy of the Islamic Republic of Iran in the region. Keywords: Geopolitics, South Caucasus, Iran, Foreign Policy, Regional Powers, IntroductionThe South Caucasus, which includes Armenia, Azerbaijan, and Georgia, is a region of significant geopolitical and geoeconomic importance. Strategically positioned at the crossroads of Europe, Asia, and the Middle East, it serves as a pivotal area of influence for Iran. The historical, cultural, and geographical ties between Iran and the South Caucasus further emphasize its critical nature in Tehran’s foreign policy considerations. The area's role as an energy corridor, especially through significant pipelines like the Baku-Tbilisi-Ceyhan (BTC), enhances its relevance in discussions surrounding global energy security. However, the region's complex ethnic and political landscape brings about significant challenges related to regional stability.For decades, Iran has encountered difficulties in asserting a proactive stance in the South Caucasus, often resorting to reactive or passive policies. This challenge arises from several geopolitical factors that hinder Iran's ability to effectively implement its foreign policy in the area. Key issues include intra-regional conflicts, such as the protracted Nagorno-Karabakh dispute, the dominant roles played by regional powers like Turkey and Russia, and the increasing involvement of external actors, including the United States, the European Union, and China. Moreover, socio-economic issues, territorial disputes, and geographical barriers exacerbate Iran's struggles in the region. Such dynamics foster a competitive environment wherein Iran's strategic interests—such as energy security, border stability, and regional influence—are frequently compromised by more assertive players. This study aims to identify and assess the geopolitical challenges that shape Iran's foreign policy in the South Caucasus, focusing on the roles of regional and extra-regional powers, the implications of socio-economic and security transformations, and the shortcomings of Iran’s current policy approach. Materials and MethodsTo explore the topic effectively, the study adopted a research method centered around collecting and statistically analyzing the opinions of experts regarding the challenges facing Iran. Given the complexities involved, the Delphi method was deemed most suitable for this research. This subjective forecasting technique is particularly effective for gathering useful data in uncertain contexts, such as the geopolitical landscape of the South Caucasus, and is particularly validated for predicting challenges—one of the core objectives of this study.The Delphi process is an iterative and systematic procedure wherein questions are presented to a panel of experts in successive rounds to achieve a reliable group consensus. In contrast to individual-based forecasting methods like surveys, Delphi focuses on group dynamics, allowing for a richer interaction that leads to more powerful conclusions than the sum of individual perspectives. The selected expert panel consisted of specialists in geopolitics and South Caucasus affairs, who, due to their experience and positions, were expected to provide valuable insights relevant to this study.Participants were contacted, and the response rate was highly satisfactory. Although other groups could have been involved, a selection of 15 experts was made to kickstart this exploratory study; this initial pool can be expanded in future research phases depending on funding and available resources. dropout rate during the process was a mere 7%, which is substantially lower than typical rates in published studies (usually ranging from 20% to 30%), minimizing the risk of distortion in final results.Results and DiscussionThe findings illustrate that Iran's foreign policy in the South Caucasus is significantly constrained by three primary categories of geopolitical challenges: intra-regional dynamics, the influence of regional powers, and interventions from external actors. Intra-regional factors include persistent ethnic and territorial conflicts, particularly the Nagorno-Karabakh conflict between Armenia and Azerbaijan, which has historically destabilized the region and complicated Iran's diplomatic relations. These conflicts contribute to a fragmented geopolitical landscape, where Iran's alignment with one state risks complicating ties with others, thereby limiting its capacity to implement a well-balanced regional strategy.Moreover, the influence of regional powers—particularly Turkey and Russia—constitutes a significant obstacle to Iran's aspirations. Turkey has solidified its position through cultural ties with Azerbaijan, making extensive economic investments and engaging in military cooperation, particularly evident during the 2020 Nagorno-Karabakh conflict. On the other hand, Russia, utilizing its historical dominance and maintaining military bases in the region, retains a formidable grip over security and economic dynamics.Delphi analysis revealed that 78% of experts highlighted the influence of regional powers as the foremost challenge, followed by intra-regional conflicts (65%) and extra-regional interventions (52%). External actors, including the United States, the European Union, and China, have expanded their presence in the South Caucasus through energy projects, security partnerships, and infrastructure investments—most notably, China’s Belt and Road Initiative. Such interventions frequently marginalize Iran, which faces limitations due to international sanctions and domestic political constraints.ConclusionThe results of this research indicate that the upcoming challenges in Iran's relations with the countries of the South Caucasus region have a geopolitical nature and are primarily due to the multiplicity and diversity of issues and influential actors in the region, along with the interactions and interconnections of complex geopolitical matters that play a significant and effective role in the ambiguity and passivity of the foreign policy of the Islamic Republic of Iran in the region. Keywords: Geopolitics, South Caucasus, Iran, Foreign Policy, Regional Powers, ی https://esrj.sbu.ac.ir/article_106663.html The occurrence and formation of types of erosion in marls is so widespread that it requires special research on the types of marls with erosive forms.This study investigates the physical and chemical properties, forms of erosion and sedimentation intensity of marl units in Zanjan province. To analyze the physical and chemical properties of marl units, sampling of marl materials of marl units in two depths of 0-10 and 0-30 cm was performed on 120 samples. To provide a map of erosion of marl units by combining maps, marl units, altitude map, slope map, direction map and land use together in GIS environment and by removing duplication and processing units, 366 work units were created. Then, using satellite images, aerial photographs and field study and controls along with completing the BLM method score tables, the type and appearance of erosion in each of the work units was determined. The obtained data were analyzed using SAS and SPSS statistical programs.Erosion forms in Zanjan province include: surface, rill, gully, tunnel, bad land, and mass erosion while sheet, rill and stream erosions are dominant. As the results of T-Test, F-Test and Duncan suggest, organic matter per cent (OC), sodium absorbation ratio (SAR), liquidity limit (LL), plasticity index (PI) in both sheet and rill erosion showed a significant difference; therefore these two forms of erosion can be differentiated using these criteria. Determining the physical, mechanical, and chemical characteristics of marls and investigating the relationship between the type of erosion and these characteristics are very effective and practical in determining and adopting effective strategies to curb erosion and sedimentation of marl fields, but they have received less attention in watershed plans. The result has been the implementation of managements and the implementation of operations that have led to the failure of programs and the desired goals have not been achieved.As the results of T-Test, F-Test and Duncan suggest, organic matter per cent (OC), sodium absorbation ratio (SAR), liquidity limit (LL), plasticity index (PI) in both sheet and rill erosion showed a significant difference; therefore these two forms of erosion can be differentiated using these criteria. Determining the physical, mechanical, and chemical characteristics of marls and investigating the relationship between the type of erosion and these characteristics are very effective and practical in determining and adopting effective strategies to curb erosion and sedimentation of marl fields, but they have received less attention in watershed plans. The result has been the implementation of managements and the implementation of operations that have led to the failure of programs and the desired goals have not been achieved.As the results of T-Test, F-Test and Duncan suggest, organic matter per cent (OC), sodium absorbation ratio (SAR), liquidity limit (LL), plasticity index (PI) in both sheet and rill erosion showed a significant difference; therefore these two forms of erosion can be differentiated using these criteria. Determining the physical, mechanical, and chemical characteristics of marls and investigating the relationship between the type of erosion and these characteristics are very effective and practical in determining and adopting effective strategies to curb erosion and sedimentation of marl fields, but they have received less attention in watershed plans. The result has been the implementation of managements and the implementation of operations that have led to the failure of programs and the desired goals have not been achieved.As the results of T-Test, F-Test and Duncan suggest, organic matter per cent (OC), sodium absorbation ratio (SAR), liquidity limit (LL), plasticity index (PI) in both sheet and rill erosion showed a significant difference; therefore these two forms of erosion can be differentiated using these criteria. Determining the physical, mechanical, and chemical characteristics of marls and investigating the relationship between the type of erosion and these characteristics are very effective and practical in determining and adopting effective strategies to curb erosion and sedimentation of marl fields, but they have received less attention in watershed plans. The result has been the implementation of managements and the implementation of operations that have led to the failure of programs and the desired goals have not been achieved.As the results of T-Test, F-Test and Duncan suggest, organic matter per cent (OC), sodium absorbation ratio (SAR), liquidity limit (LL), plasticity index (PI) in both sheet and rill erosion showed a significant difference; therefore these two forms of erosion can be differentiated using these criteria. https://esrj.sbu.ac.ir/article_107027.html Extended abstractIntroductionThe Natour area is located approximately 33 km south of Kowsar city, Ardabil province, northwestern of Iran. Based on the division of structural zones of Iran (Alavi, 1991), this area is considered a part of the Alborz magmatic arc. The Alborz sedimentary-structural zone includes the northern highlands of the Iranian plate, which continues in a compound anticline with a general east-west trend from Azarbaidjan to Khorasan. Many of the stratigraphic units of Alborz and Central Iran are similar in terms of facies and formation conditions, so that Alborz can be considered as marginal folds of Central Iran, in whose formation the collision of the two Iranian and Turanian plates and its consequences played a fundamental role (Aghanbati, 2004). Alborz is more similar to Central Iran, especially in the southern slope, but there are some differences in the northern slope (Stocklin, 1968). The Alborz magmatic arc encompasses a wide range of tectonic environments, such as normal arc, back-arc, and post-collisional and extensional environments. The Alborz magmatic cycle during the Eocene-Oligocene has resulted in the formation of a wide range of intrusive igneous, subvolcanic, and volcanic-sedimentary rocks. These rocks show calc-alkaline and high-k calc-alkaline and shoshonitic magmatic series. These units include granitic, granodioritic intrusions, basaltic, andesitic, dacite, rhyolite lavas, and their associated tuffs. In the present study, an attempt is made to investigate the geological, petrographic, and geochemical characteristics of volcanic rocks in the Natour area. Also, in this research, based on the results of chemical analyses of major, trace, and rare earth elements, has determined the composition of the volcanic rocks of the area, the parent magma, and their tectonic setting.Materials and methodsIn general, this research was conducted in two parts: field and laboratory. First, in the field part, a visit to the study area was carried out to investigate the condition of volcanic rocks, and in the next stage, samples of these rocks were taken for laboratory studies. In the laboratory part, a number of thin sections were prepared from the collected samples and then petrographic studies were performed on them. Also, in order to conduct geochemical studies, 12 fresh and less altered samples of these volcanic rocks were selected and analyzed at the Zanjan Zarazma Company. The major elements were analyzed by XRF method and the trace and rare earth elements were analyzed by ICP-MS method.Results and discussionBased on geological location, the Natour area is located on the 1:100000 geological map of the Kivi sheet (Hajalilou and Rezaei, 2001). The most important rock units of the study area are related to the Eocene, Oligocene, and Quaternary. Eocene rock units in the area include Eab, Eclt, Ean, and Etr. The Eab unit is the oldest Eocene rock unit in the area and is often observed in the northeast of the Natour area. This unit consists of gray basaltic andesite. The Eclt unit consists of lithic crystalline tuff in gray to reddish gray color and is mostly spread in the central part of Natour area. In some places, this unit itself has interlayers of pyroclastic units such as tuff, lithic tuff, and lithic tuff andesite. The Ean unit includes porphyry andesite to porphyry basaltic andesite, ranging in color from purple to gray, and is often exposed in the southwest of the Natour area. The youngest Eocene unit in the study area includes Etr with trachytic composition and it is often visible in the area in bright color. The trachyte unit is mainly visible in the southwestern part of the Natour area. The Oligocene rock units in the area consist of the Olrc unit, which contains heterogeneous conglomerate (in red) and is usually seen in the north and northeast of the area and discontinuously overlying Eocene volcanic units. According to petrographic studies, the volcanic rocks of the Natour area mainly show a composition of basaltic andesite, andesite, and trachyte. Basaltic andesite rocks have porphyritic and glomeroporphyritic textures, composed of the main minerals plagioclase and pyroxene in a fine-crystalline matrix. Andesite rocks contain the main minerals plagioclase, amphibole, and biotite and have a porphyritic texture in a fine-crystalline matrix. Trachyte rocks also have a porphyritic texture, consisting of alkali feldspar, plagioclase, and biotite minerals in a fine-crystalline matrix. To determine the composition of volcanic rocks in the Natour area, the total alkali (Na2O+K2O) versus silica (SiO2) diagram (Middlemost, 1994) and the Nb/Yb versus Zr/Ti diagram (Pearce, 1996) were used. In the total alkali versus silica diagram, the samples from the study area are in the range of rocks with a composition of andesite, basaltic andesite, basaltic trachyandesite, trachyandesite, trachyte, and trachydacite. In the Nb/Yb versus Zr/Ti diagram, samples from the Natour area are located in the range of andesite, basaltic andesite, trachyandesite, and alkali basalt rocks. In the Al2O3-K2O-Na2O ternary diagram, samples from the Natour area are located in the metaluminous and peraluminous realms. Also, to determine the alumina saturation index of volcanic rocks in the study area, the diagram presented by Shand (1943) was used. In this diagram, the metaluminous, peraluminous, and peralkaline ranges are distinguished. According to this diagram, samples from the Natour area fall into two ranges: metaluminous and peraluminous. The magmatic series of volcanic rocks in the Natour area was initially determined using the diagram of total alkalis (Na2O+K2O) versus silica (SiO2) (Irvine and Baragar, 1971). In this diagram, two ranges of alkaline and subalkaline are separated. Based on this diagram, all samples in the study area belong to the alkaline range. Then, Th/Yb versus Ta/Yb (Pearce, 1983), Co versus Th (Hastie et al., 2007), and SiO2 versus K2O (Peccerillo and Taylor, 1976) diagrams were used to determine the magmatic series of the igneous rocks of the area. These diagrams are divided into the ranges of tholeiitic, calc-alkaline, high-k calc-alkaline, and shoshonitic magmatic series. Based on the Th/Yb versus Ta/Yb diagram, most of the samples in the study area are located in the calc-alkaline magmatic series. According to the Co versus Th diagram, the samples from the Natour area are within the range of calc-alkaline and high-k calc-alkaline and shoshonitic magmatic series. According to the SiO2 versus K2O diagram, the samples from the study area are mainly located in the range of shoshonitic magmatic series. The trend of changes in trace and rare earth elements in samples of volcanic rocks from the Natour area was determined using spider diagrams. In this regard, samples from the study area were normalized to the primitive mantle (Sun and McDonough, 1989) and chondrite (Nakamura, 1974). The spider diagram of the samples normalized to the primitive mantle shows a positive anomaly in large ion lithophile elements (LILE) such as Cs, K, and Pb, and a negative anomaly in high field strength stability elements (HFSE) such as Nb, Zr, and Ti. Positive anomalies of LILE elements and negative anomalies of HFSE elements are characteristics of arc-related regions, whose formation can be associated with subduction zones and contamination of magma with continental crust (Wilson, 1989; Rollinson, 1993; Thuy et al., 2004; Kuscu and Geneli, 2010; Yu et al., 2017). In the spider diagram of samples normalized to chondrite, enrichment of LREE relative to HREE can be identified. Also, a relatively weak depletion of the Ce element is observed in this diagram. The enrichment of LREE relative to HREE can indicate the formation of volcanic rocks in subduction zones or the contamination of magma by crustal materials (Kuster and Harms, 1998; Ulmer, 2001; Srivastava and Singh, 2004; Peccerillo et al., 2004; Goss and Kay, 2009). The relatively weak depletion of Ce element can most likely be due to the high mobility of this element during the subduction process (Hoyle et al., 1984). Using TiO2-Al2O3 and Y-Zr diagrams (Muller et al., 1992), the tectonic setting of igneous rocks can be interpreted. In these diagrams, the within plate setting and the arc-related setting are separated. Based on these diagrams, all samples of volcanic rocks in the Natour area are placed in the arc-related tectonic setting. To determine the tectonic setting of the volcanic rocks of the Natour area, the Nb/Yb versus Th/Yb diagram (Pearce, 2008) was also used, in which the samples from the study area are located in the tectonic setting associated with volcanic arcs. To distinguish oceanic arc rocks from continental arc and post-collisional arc rocks, the ternary diagram TiO2/100-La-Hf×10 (Muller et al., 1992) can be used. According to this diagram, samples of volcanic rocks from the Natour area are often located in the settings of continental and post-collisional arcs. Also, the Zr×3-Nb×50-Ce/P2O5 ternary diagram (Muller et al., 1992) was used to separate continental arc rocks from post-collisional arc rocks. According to this diagram, the samples related to volcanic rocks of the study area are mainly located in the post-collisional arcs.ConclusionPetrographically, the volcanic rocks of the Natour area represent a composition of basaltic andesite, andesite, and trachyte. These rocks are located in the chemical classification diagrams in the range of andesite, basaltic andesite, trachyandesite, trachyte, trachydacite, and alkali basalt. Volcanic rocks of the Natour area are located in the metaluminous and peraluminous ranges on alumina saturation index determination diagrams. In terms of magmatic series, these rocks represent high-k calc-alkaline and shoshonitic magmatic series. Spider diagrams related to volcanic rocks of the Natour area indicate a positive anomaly in large ion lithophile elements (LILE) and a negative anomaly in high field strength elements (HFSE) and enrichment of LREE relative to HREE, which can indicate the formation of volcanic rocks of the study area in subduction zones or contamination of magma by crustal materials. According to tectonic setting diagrams, the volcanic rocks of the study area were developed in arc-related tectonic settings. Also, in the diagrams of the separation of oceanic arc rocks from continental arc and post-collisional arc rocks, they are placed in the position of post-collisional arcs. https://esrj.sbu.ac.ir/article_107028.html "Stable Isotope (O, C) and Geochemical Constraints of Mineralization in the Qamishlu Lead Deposit, Isfahan, Iran"Extended AbstractIntroductionLead–zinc deposits in Iran are distributed across four major structural zones. These tectonic units include: (1) the Sanandaj–Sirjan Zone (SSZ), hosting deposits such as Irankuh (Ghazban et al., 1994), Tiran (Nejadhadad et al., 2018), Dareh Noghreh (Nejadhadad et al., 2023), and Angouran (Boni et al., 2007); (2) the Yazd–Anarak Metallogenic Belt (YAMB) in central Iran, including the world-class Mehdiabad MVT Zn–Pb deposit (Reichert et al., 2008; Nejadhadad et al., 2025) and Nakhlak lead mine (Jazi et al., 2017); (3) the Tabas–Posht-e Badam area, hosting Pb–Zn–Ba deposits such as Ozbak-Kuh (Ehya et al., 2014); and (4) the Central Alborz Range, containing deposits like Duna and Ellika (Zabihitabar et al., 2015).The Qamishlu lead deposit is part of the Isfahan–Malayir Pb–Zn metallogenic belt within the Sanandaj–Sirjan metamorphic zone. In this deposit, mineralization occurs predominantly in lower Cretaceous massive limestone, localized along fault surfaces, shear zones, and contacts between Cretaceous carbonate and shale units. The average Zn/(Zn+Pb) ratio is less than 0.1, classifying the mineralization as Pb-rich, analogous to the Viburnum Trend in the USA and the Ravanj deposits in Iran (Plumlee et al., 1994; Nejadhadad et al., 2016). Silver concentrations in pure galena samples average 660 ppm, corresponding to the 50th–75th percentile range of Pb–Zn deposits. A strong Sb–Ag correlation (r = 0.93), compared to moderate As–Ag (r = 0.66) and Cu–Ag (r = 0.6) correlations, suggests that Ag enrichment is controlled by both lattice-bound silver in galena and sulfosalt-hosted phases, including jordanite and the tetrahedrite–freibergite group.Alteration at Qamishlu primarily comprises host rock dolomitization, silicification, and late-stage open-space-filling calcite. Systematic stable isotope analyses (δ¹⁸O and δ¹³C) of late-stage calcite, pure dolomite, dolomitized and silicified mineralized host rocks, weakly altered non-mineralized rocks, and distal fresh limestone indicate isotopic mixing between hydrothermal fluids depleted in ¹⁸O but enriched in organic carbon and the carbonate host rocks. The strong spatial association of mineralization with NE–SW-trending faults, combined with isotopic variations in altered zones, suggests that these structures acted as primary fluid conduits. Open spaces in shear zones along normal faults, coupled with interaction between ore fluids and carbonate host rocks, modified the physicochemical conditions of the metal-bearing fluids, ultimately resulting in the deposition of epigenetic mineralization.Materials and Methods Field Investigation and Sampling MethodologyComprehensive fieldwork was systematically carried out across the ore-bearing zone and adjacent areas, including: (1) detailed geological mapping, (2) structural analysis of fault systems and fracture networks, and (3) representative sampling of all lithological units. Special emphasis was placed on collecting specimens with varied textural features (e.g., massive, brecciated, and vein-type mineralization) from both mineralized and unaltered rocks.Laboratory Processing and Analytical TechniquesA total of 30 thin and polished sections were prepared from the collected samples. Additionally, 12 hand-picked galena specimens were carefully purified under a binocular microscope and submitted to LabWest Laboratory, Western Australia, for ICP-MS analysis. Samples of fresh limestone, mineralized limestone, pre-ore calcite, late-stage calcite, mineralization-related dolomite, quartz, and silicified host rocks were similarly purified through manual separation under a standard binocular light microscope and subsequently sent to the Cornell Isotope Laboratory (COIL), Cornell University, USA, for carbon and oxygen isotope analysesResults and DiscussionGeological constraintsThe Qamishlu lead deposit is a carbonate-hosted Pb–Zn deposit situated within the Isfahan–Malayer lead–zinc belt, part of the Sanandaj–Sirjan metamorphic zone in Iran (Fig. 1). This study demonstrates that multiple, interacting factors controlled the localization of mineralization. Ore emplacement is influenced by lithological, stratigraphic, and structural controls, which govern fluid flow at both regional and deposit scales, facilitating fluid focusing and the development of open spaces necessary for ore deposition (Nejadhaddad et al., 2023).The deposit is classified as a vein-type system and formed epigenetically relative to the Cretaceous carbonate host rocks. Limestone, the dominant host lithology, is commonly associated with Mississippi Valley-type (MVT) base-metal sulfide deposits (Leach et al., 2010). In Qamishlu, mineralization occurs within Cretaceous carbonates overlying Jurassic to Cretaceous shale–sandstone sequences (Fig. 2). Shale and carbonate–shale units act as impermeable aquitards within the stratigraphic column, playing a critical role in channeling hydrothermal fluids (Leach et al., 2005).Structural features, including joints and fractures related to fault activity, significantly enhanced fluid flow and created open spaces for ore deposition. Most mineralization is concentrated within NE–SW-trending fault veins and associated fracture networks, indicating that faulting and brecciation of Upper Cretaceous carbonates were key in generating structural conduits for hydrothermal fluids.The mineralogy of the Qamishlu deposit is relatively simple. Primary ore minerals, in order of abundance, include galena, pyrite, sphalerite, tetrahedrite, and chalcopyrite. The dominant gangue phases are calcite, barite, dolomite, and quartz. Secondary supergene minerals comprise cerussite, iron oxides (mainly limonite), smithsonite, covellite, and malachiteGalena geochemistry In the Qamishlu deposit, galena is more abundant than sphalerite, similar to Southeast Missouri lead deposits (Sverjensky, 1986). The deposit is classified as Pb-rich, with a Zn/(Zn+Pb) ratio below 0.1. In addition to Pb and S, silver represents the most economically significant by-product in galena due to its relative abundance and high market value (Zeng et al., 2000). Minor trace elements, including antimony, bismuth, arsenic, zinc, cadmium, selenium, and copper, are also present within galena.The average Ag content in galena samples from Qamishlu is approximately 660 ppm. A strong correlation is observed between Ag and Sb (r = 0.84), while moderate correlations exist with As (r = 0.66) and Cu (r = 0.6) (Table 2). Silver occurs in galena both as a solid solution and as inclusions of sulfosalt minerals such as jordanite and tetrahedrite (Gregory et al., 2014; Lan et al., 2023).Stable Isotopes (O, C)The δ¹⁸O values in altered rocks reflect multiple factors, including the initial δ¹⁸O of the host rock, the isotopic composition of the fluid, the temperature of fluid–rock interaction, and the degree of equilibrium achieved during alteration (Sánchez-España et al., 2003; Bortnikov, 2006; Nejadhadad et al., 2023).In Qamishlu, δ¹⁸O values in altered carbonates (silicified and dolomitized limestones) are lower than in distal, unaltered carbonate rocks. Unmineralized host rocks display δ¹⁸O values averaging ~+22‰, whereas altered and mineralized rocks show values around +20‰. Secondary alteration minerals—calcite, silica, and dolomite—exhibit δ¹⁸O values of approximately +16‰, +18‰, and +18‰, respectively. This trend indicates a ~6‰ decrease in δ¹⁸O during mineralization, reflecting extensive fluid–host rock interaction. The lowest δ¹⁸O values occur in late-stage calcite, consistent with isotopic exchange between hydrothermal fluids and carbonate host rocks. Such depletion likely reflects high temperatures and prolonged interaction, leading to secondary isotopic equilibrium in alteration minerals formed during mineralization (Schindler et al., 2016; Nejadhadad et al., 2023). Isotopic signatures of carbonate phases, spatial patterns of alteration intensity provide further evidence for focused hydrothermal fluid flow along structurally prepared pathways.The progressive transition from fresh limestone in distal zones to weakly altered, silicified, and finally intensely dolomitized rocks toward the fault-controlled ore zones suggests a thermal and chemical gradient decreasing outward from the fluid conduits. Such alteration halos, not only reflect sustained interaction between metal-bearing fluids and carbonate host rocks but also help delineate the geometry and directionality of fluid migration during mineralization. The δ¹³C (PDB) values of fresh and weakly altered host rocks average +1‰, typical of Cretaceous marine carbonates (Gilg et al., 2008; Drake et al., 2009). These values progressively decrease in altered samples, fracture-filling dolomites, and silicified rocks, reaching –2‰, with late-stage calcite recording δ¹³C values as low as –3‰. The depletion in heavy carbon isotopes is likely due to biological activity or the presence of organic matter in the mineralizing fluids. Thermal oxidation of organic matter and hydrocarbons during epigenetic carbonate precipitation can produce isotopically lighter carbonate minerals relative to the original host rock (Gilg et al., 2003; Evans and Battles, 2011; Drake et al., 2009). ConclusionsIn the Qamishlu deposit, barite and galena precipitated together, often in alternating sequences. Geological and textural evidence indicates that ore deposition occurred after lithification of the primary carbonate host rocks and following tectonic deformation, suggesting a post-tectonic mineralization event. This behavior is comparable to other epigenetic sedimentary Pb–Zn deposits, such as Mississippi Valley-Type (MVT) systems.The solubility and precipitation conditions of barite and galena differ significantly. Lead-rich, oxidized fluids under sulfur-deficient reducing conditions can transport substantial amounts of sulfur as dissolved lead–chloride complexes. When sulfur concentration increases, lead is reduced to lead sulfide (galena) and precipitates rapidly (Hanor, 2000).Alteration in the Qamishlu deposit is characterized by dolomitization of the host rock, silicification, and precipitation of late-stage secondary calcite. Stable isotope analyses (δ¹⁸O and δ¹³C) of carbonate samples indicate isotopic exchange between hydrothermal fluids—depleted in δ¹⁸O but enriched in organic carbon—and the δ¹⁸O-rich carbonate host rocks. The strong spatial association of mineralization with NE–SW-trending faults, along with isotopic variations observed in altered zones, suggests that fault planes served as primary fluid conduits.The availability of open space, combined with fluid–rock interactions between ore-bearing fluids and carbonate host rocks, modified the physicochemical conditions of the metal-bearing fluids, ultimately leading to the deposition of epigenetic mineralization.Keywords: geological controls, galena geochemistry, stable isotopes (O, C), Qamishlu lead deposit https://esrj.sbu.ac.ir/article_107029.html .The Indo-Pacific region, with its important and growing role in global equations and competitions, has become one of the most important centers of gravity of the world's strategy. Based on its political, economic, military and security characteristics, this region is the intersection point of the policies of great powers such as the United States of America and China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaThe competition for acquiring and purchasing military weapons is highly intense among key countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and, to some extent, Taiwan. American arms companies hold the highest sales in this region compared to other geopolitical areas. Various reasons drive the arms purchases of these countries, including the economic and military growth of key nations in the region, especially China. Some of these countries, through forming military alliances like AUKUS or striving to outpace one another, aim to reduce their military disparities with other advanced and economically-militarily significant countries in the region.This article aims to analyze the United States' strategy for the arms race among countries in this region, using precise and reliable statistics from global organizations and adopting a comparative approach among the five major countries of the region (the United States, China, Japan, South Korea, and India).The Indo-Pacific region, with its significant and growing role in global equations and competitions, has become one of the most critical strategic centers of gravity in the world. This region, based on its political, economic, military, and security characteristics, serves as a convergence point for the policies of major powers such as the United States and China. In fact, the competitive structure in this region is being shaped by the relationship between these two powers. Additionally, actors like ASEAN, Japan, South Korea, and India exert their unique influences on the region.The competition for acquiring and purchasing military weapons is highly intense among key countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and, to some extent, Taiwan. American arms companies hold the highest sales in this region compared to other geopolitical areas. Various reasons drive the arms purchases of these countries, including the economic and military growth of key nations in the region, especially China. Some of these countries, through forming military alliances like AUKUS or striving to outpace one another, aim to reduce their military disparities with other advanced and economically-militarily significant countries in the region.This article aims to analyze the United States' strategy for the arms race among countries in this region, using precise and reliable statistics from global organizations and adopting a comparative approach among the five major countries of the region (the United States, China, Japan, South Korea, and India).The Indo-Pacific region, with its significant and growing role in global equations and competitions, has become one of the most critical strategic centers of gravity in the world. This region, based on its political, economic, military, and security characteristics, serves as a convergence point for the policies of major powers such as the United States and China. In fact, the competitive structure in this region is being shaped by the relationship between these two powers. Additionally, actors like ASEAN, Japan, South Korea, and India exert their unique influences on the region.The competition for acquiring and purchasing military weapons is highly intense among key countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and, to some extent, Taiwan. American arms companies hold the highest sales in this region compared to other geopolitical areas. Various reasons drive the arms purchases of these countries, including the economic and military growth of key nations in the region, especially China. Some of these countries, through forming military alliances like AUKUS or striving to outpace one another, aim to reduce their military disparities with other advanced and economically-militarily significant countries in the region.This article aims to analyze the United States' strategy for the arms race among countries in this region, using precise and reliable statistics from global organizations and adopting a comparative approach among the five major countries of the region (the United States, China, Japan, South Korea, and India).The Indo-Pacific region, with its significant and growing role in global equations and competitions, has become one of the most critical strategic centers of gravity in the world. This region, based on its political, economic, military, and security characteristics, serves as a convergence point for the policies of major powers such as the United States and China. In fact, the competitive structure in this region is being shaped by the relationship between these two powers. Additionally, actors like ASEAN, Japan, South Korea, and India exert their unique influences on the region.n, with its important and growing role in global equations and competitions, has become one of the most important centers of gravity of the world's strategy. Based on its political, economic, military and security characteristics, this region is the intersection point of the policies of great powers such as the United States of America and China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially Chinn, with its important and growing role in global equations and competitions, has become one of the most important centers of gravity of the world's strategy. Based on its political, economic, military and security characteristics, this region is the intersection point of the policies of great powers such as the United States of America and China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially ChinaCompetition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially China.Competition for the acquisition and purchase of military weapons is intense among major countries in the Indo-Pacific region, such as Japan, South Korea, India, Australia, and to some extent Taiwan. American arms companies have the highest sales in the region compared to other geopolitical regions. Among the various reasons for the purchase of weapons by countries in the region, one can mention the economic-military growth of the aforementioned countries, especially Chinn, with its important and growing role in global equations and competitions, has become one of the most important centers of gravity of the world's strategy. Based on its political, economic, military and security characteristics, this region is the intersection point of the policies of great powers such as the United States of America and China.Competition for the acquisition and purchase of military weapons is intense among https://esrj.sbu.ac.ir/article_107030.html IntroductionManto-type (sediment-hosted) copper (Cu–Ag) deposits are of high economic and metallogenic importance due to their relatively high metal grades and significant contribution to copper production, particularly in the Central Andes (Wilson et al., 2003; Oliveros et al., 2008). These deposits are widely distributed along the circum-Pacific and Himalayan–Tibetan belts (Shen et al., 2020). In Chile, manto-type deposits are considered the second most important Cu deposits after porphyries (Wilson and Zentilli, 1999). In Iran, sediment-hosted copper deposits hosted in volcanic-sedimentary rocks, classified as manto-type deposits, are distributed across several structural provinces, including the Sanandaj–Sirjan, Urmieh–Dokhtar, Alborz, Sabzevar, Central Iran, Kopet Dagh, Tabas Block, and Lut Block (Salehi and Rasa, 2016; Maghfouri et al., 2020; Movahednia et al., 2022). The Darreh Takht Cu deposit is located in Lorestan Province within the Sanandaj–Sirjan structural-metasedimentary belt. This study aims to investigate the mineralogical, alteration, and geochemical characteristics of Cu mineralization and to elucidate the formation pattern of this deposit within the framework of manto-type Cu systems.MethodologyTo investigate the Cu mineralization at the Darreh Takht deposit, a large-scale geological map was prepared based on satellite imagery, field surveys, and integration with the 1:100,000 geological maps of Aligudarz (Soheili et al., 1992) and Dorud (Goodarzi, 2002). Systematic sampling of host rocks and ore was conducted according to lithological variations, alteration intensity, and mineralogy. For mineralogical and textural studies, thin sections, polished sections, and thin–polished sections were prepared and examined microscopically. Mineral identification was carried out using X-ray diffraction (XRD), while the chemical composition of ore minerals was determined using electron probe microanalysis (EPMA). Geochemical analyses of least-altered host volcanic rocks were performed for major and trace elements using XRF and for rare earth elements using ICP-MS. These datasets formed the basis for interpreting mineralization characteristics and reconstructing the formation model of the deposit.Results and DiscussionThe Sanandaj–Sirjan zone, with a length of approximately 1,500 km and a width of 150–250 km, extends from southeastern Iran (cities of Sirjan and Esfandqeh) to the northwest (Urmia and Sanandaj) and is considered one of the most important metallogenic regions of the country (Mohajjel and Fergusson, 2014). This zone comprises metamorphosed sedimentary, volcanic–sedimentary, and intrusive igneous rocks, ranging in age from the Paleozoic to the Mesozoic, and forms part of the Sanandaj–Sirjan metamorphic shear zone within the Zagros thrust-fold belt (Sarkarinejad and Azizi, 2008). Its tectonic evolution from the Late Paleozoic to the Middle Triassic involved faulting, carbonate deposition, basaltic lava flows, and coeval sedimentation, reflecting an extensional regime associated with the separation of the Central Iran block from Gondwana and the opening of the Neo-Tethys oceanic basin. The Early Cretaceous volcanic–sedimentary sequences in the southern part of the zone host Manto-type stratabound deposits, including Keshte-Mahki, Kal-Rizeh, Northeast and East Hassanabad, Khvorjan, and Simkan (Movahednia et al., 2020).The Darreh Takht Cu deposit is situated in the northern part of the Sanandaj–Sirjan metamorphic belt, adjacent to the Zangros thrust sub-belt, and is hosted in a Middle to Late Triassic volcanic–sedimentary sequence. The main lithologies include andesitic to andesite–basaltic flows, pyroclastic units such as crystal tuff and lithic tuff, and Permian carbonate sedimentary rocks, all generally aligned with the regional structural trend and partially metamorphosed to green schist facies. Three main rock units were distinguished: volcanic units (andesite to andesite–basalt), pyroclastic units (crystal tuff, lithic tuff, and agglomerate), and sedimentary units (limestone, dolomitic limestone, and green schist). Volcanic and pyroclastic units predominantly host Cu mineralization, and all units are aligned NW–SE along the Sanandaj–Sirjan belt. This lithological sequence reflects a volcanic–sedimentary environment with low- to medium-grade metamorphism.Mineralization at Darreh Takht occurs primarily in pyroclastic units (andesite to andesite–basalt) with sedimentary and metamorphic rocks located in the upper levels. Cu mineralization is mainly vein- and stringer-type and fills fractures, faults, and voids. The copper mineralization is predominantly vein-type, stockwork, and cavity-filling, and is structurally controlled by faults, fractures, and joints. The main factors influencing the mineralization process include: (1) suitable lithology of the host rocks, (2) effective structural features such as faults, fractures, joints, and related porosity and permeability characteristics, (3) the circulation of hydrothermal fluids through chemically favorable rocks leading to copper enrichment, and (4) the presence of granitoid intrusions in the area that provided a thermal source. Alteration types include chloritic, epidotic, sericitic, silicic, carbonatitic, and Fe-oxide/hydroxide zones. Chloritic and epidotic alterations are the most widespread and correspond to early hydrothermal activity, while sericitic and silicic alterations are restricted and associated with late hydrothermal phases.Mineralogical studies (microscopy, XRD, and EPMA) reveal five main mineral groups: sulfide Cu–Fe minerals (chalcocite, covellite, bornite, pyrite, chalcopyrite, tetrahedrite), Cu-carbonates (malachite and azurite), Cu oxides and native Cu (cuprite and native copper), Fe oxides/hydroxides (goethite and limonite), and gangue minerals (quartz, calcite, and gypsum). The dominant textures are vein, stringer, disseminated, void-filling, and replacement, reflecting the synoptic progression of sulfide, carbonate, and oxide mineralization.Geochemical studies of host rocks indicate andesitic to andesite–basaltic and trachyandesitic compositions, belonging to the calc-alkaline series. The Zr/Y versus Zr (Pearce, 1979) and Th–Co (Hastie et al., 2007) diagrams classify the rocks as continental arc-related, consistent with subduction of the Neo-Tethyan oceanic lithosphere beneath the Central Iranian continental block during the Late Triassic–Early Jurassic. Spider diagrams normalized to chondrite show enrichment in light rare earth elements (LREE) relative to heavy rare earth elements (HREE) with positive Sr and Eu anomalies, indicating plagioclase fractionation, high oxidation states, and crustal contamination of arc magmas. Negative Nb anomalies coupled with Sr enrichment are characteristic of subduction zone magmas and crustal assimilation.Among base metals, Cu and Ag show a very high correlation (r = 0.97), indicating a common source and geochemical linkage, likely due to their occurrence in sulfosalts (tetrahedrite, pyrargyrite, and prostite) and covellite.Formation Conditions and Genetic StagesBased on field, petrographic, and geochemical studies, the mineralization and deposit formation can be divided into three genetic stages:1. Early diagenesis (primary volcanic–sedimentary stage): Extensive volcanic activity formed pyroclastic units and lava flows, producing andesitic and pyroxene-andesitic host rocks. Early diagenesis also led to thin hematite layers from the breakdown of Fe-bearing minerals (pyroxene and amphibole).2. Secondary diagenesis (primary sulfide mineralization): Basin-derived Cu released from Fe–Mg minerals and altered feldspars migrated and precipitated as primary sulfide minerals (pyrite, chalcopyrite, and chalcocite) in voids and as disseminated grains. The main source of Cu is the volcanic–sedimentary host rocks.3. Uplift and hydrothermal activity (secondary oxide–carbonate stage): Regional uplift and faulting focused sulfide and oxide–carbonate mineralization along fractures and voids in pyroclastic units. Hydrothermal fluids of meteoric–magmatic origin formed oxide and carbonate Cu minerals (malachite, azurite) and Fe oxides/hydroxides in veins and stringers.ConclusionCu mineralization at Darreh Takht occurs along the northern margin of the Sanandaj–Sirjan belt within andesitic to andesite–basaltic volcanic–pyroclastic sequences. Host rocks are calc-alkaline and related to a continental arc setting. Mineralization is vein- and stringer-dominated, controlled by tectonic structures, and post-dates host rock formation (epigenetic and stratabound). The positive Cu–Ag correlation indicates co-enrichment through metal-bearing hydrothermal fluids. The formation model comprises a multi-stage evolution from primary volcanic activity, diagenetic sulfide precipitation, to secondary hydrothermal concentration, demonstrating that Darreh Takht is a typical manto-type Cu deposit.ReferencesGoodarzi A., 2002. Geological Map of Dorud, scale 1:100,000", National Oil Company.Hastie, A.R., Kerr, A.C., Pearce, J.A. and Mitchell, S.F., 2007. Classification of altered volcanic island arc rocks using immobile trace elements: development of the Th–Co discrimination diagram. Journal of petrology, 48(12), pp.2341-2357.Maghfouri, S., Rastad, E., Borg, G., Hosseinzadeh, M.R., Movahednia, M., Mahdavi, A. and Mousivand, F., 2020. Metallogeny and temporal–spatial distribution of sediment-hosted stratabound copper (SSC-type) deposits in Iran; implications for future exploration. Ore Geology Reviews, 127, p.103834.Mohajjel, M. and Fergusson, C.L., 2014. Jurassic to Cenozoic tectonics of the Zagros Orogen in northwestern Iran. International Geology Review, 56(3), pp.263-287.Movahednia, M., Maghfouri, S., Fazli, N., Rastad, E., Ghaderi, M. and Gonzalez, F.J., 2022. Metallogeny of Manto-type stratabound Cu-(Ag) mineralization in Iran: Relationship with NeoTethyan evolution and implications for future exploration. Ore Geology Reviews, 149, p.105064.Oliveros, V., Féraud, G., Aguirre, L., Ramírez, L., Fornari, M., Palacios, C. and Parada, M., 2008. Detailed 40Ar/39Ar dating of geologic events associated with the Mantos Blancos copper deposit, northern Chile. Mineralium Deposita, 43(3), pp.281-293.Pearce, J.A. and Norry, M.J., 1979. Petrogenetic implications of Ti, Zr, Y, and Nb variations in volcanic rocks. Contributions to mineralogy and petrology, 69(1), pp.33-47.Salehi, L., and Rasa, I., 2016. Sulfur Isotopic Characteristics of the Chalcocite in Madan Bozorg Cu Deposits, Abbas Abad, NE Iran", 34th National and the 2nd International Geosciences Congress, Tehran, Iran, 34.Sarkarinejad, K. and Azizi, A., 2008. Slip partitioning and inclined dextral transpression along the Zagros Thrust System, Iran. Journal of Structural Geology, 30(1), pp.116-136.Shen, P., Pan, H., Li, Z., Sun, J., Shen, Y., Li, C., Feng, H. and Cao, C., 2020. A Manto-type Cu deposit in the central Asian Orogenic belt: The Hongguleleng example (Xinjiang, China). Ore Geology Reviews, 124, p.103656.Soheili M., Jafarian M. and Abdollahi M., 1992.Geological Map of Aligudarz, scale 1:100,000", Geological Survey of Iran.Wilson, N.S., Zentilli, M. and Spiro, B., 2003. A sulfur, carbon, oxygen, and strontium isotope study of the volcanic-hosted El Soldado manto-type copper deposit, Chile: the essential role of bacteria and petroleum. Economic Geology, 98(1), pp.163-174.Wilson, N.S.F., Zentilli, M., 1999. The role of organic matter in the genesis of the El Soldado volcanic-hosted manto-type Cu deposit, Chile. Econ. Geol. 94, 1115–1136. https://esrj.sbu.ac.ir/article_107031.html Extended AbstractIntroductionThe increase in greenhouse gas concentrations in recent decades, alongside the intensification of global warming, has led to more frequent, more intense, and longer-lasting extreme atmospheric events—especially heatwaves. Rising mean air temperatures and a shift in the temperature distribution toward higher values have caused warm-season thermal thresholds to be exceeded more quickly and for longer periods. As a result, episodes of extreme heat not only occur more often but also last longer and are associated with higher peak temperatures, placing greater stress on human health and infrastructure. The Middle East is considered one of the most vulnerable regions to heat stress due to the dominance of arid and semi-arid climates, limited water resources, and the high sensitivity of natural systems. At the same time, population growth, rapid urbanization, and the expansion of the urban heat island effect can further exacerbate heatwave impacts in many cities across the region. Therefore, monitoring and projecting changes in heatwaves is essential for risk management, adaptation planning, and reducing socio-economic consequences in the Middle East.Materials and MethodsIn this study, the Middle East was selected as the target region and, to capture spatial heterogeneity, was subdivided into three sub-regions (northern, central, and southern) based on geographic–climatic characteristics and temperature gradients. To characterize past climate conditions and project future heatwave changes, daily maximum temperature from ERA5 for the reference period 1985–2014 was combined with 0.25° downscaled CMIP6 projections from the NEX-GDDP dataset. Simulations from three selected CMIP6 models were analyzed for the future period 2026–2055 under three emissions pathways_SSP1-2.6 (low), SSP2-4.5 (intermediate), and SSP5-8.5 (high)_to span a range of plausible futures. Before index calculation, all datasets underwent preprocessing, including quality control, handling of missing values, and calendar harmonization (removal of leap days) to ensure consistency across products. Model skill for the reference period was assessed by benchmarking model outputs against ERA5 using the root-mean-square error (RMSE), mean bias, and the Pearson correlation coefficient (R), providing a basis for uncertainty assessment and confidence in future projections.Heatwave intensity was quantified following Russo et al. (2014), where a heatwave is defined as at least three consecutive days with daily maximum temperature exceeding a day-specific 90th-percentile threshold computed from the 1985–2014 baseline using a centered 31-day moving window; the annual heatwave intensity index was then derived as the maximum intensity among all events in each year.Results and DiscussionThe findings indicate that the performance of climate models in reproducing maximum temperature over the Middle East is significantly season-dependent. In summer, the models achieve the lowest systematic and random errors alongside the highest correlation with reanalysis data, demonstrating strong skill in representing both absolute temperatures and their variability during the hottest season. In contrast, winter exhibits the weakest performance: higher bias and overall error combined with reduced correlation point to limitations in capturing wintertime temperature variability. Spring shows an improvement relative to winter, although correlations remain only moderate, whereas autumn—characterized by very high correlation and comparatively moderate overall error—provides robust reliability for temperature-based analyses. Overall, these results confirm that model outputs are more dependable for temperature applications in summer and autumn, while winter requires greater emphasis on seasonal bias correction and targeted calibration. The annual spatial evaluation further shows that model performance is acceptable and relatively stable across much of the Middle East, with errors increasing mainly in areas of complex topography and along land–sea transition zones. This is physically plausible, as simulations in such regions are more sensitive to local processes and land–atmosphere interactions and depend more strongly on parameterization quality. Although the bias pattern is relatively coherent at the regional scale, it appears amenable to correction: a tendency toward underestimation is evident in parts of the Arabian Peninsula, while overestimation occurs in portions of the northwest. Taken together, these results suggest that the selected models are sufficiently capable for regional analyses and future-change assessments, provided that spatial and seasonal biases are explicitly considered in interpretation. For future projections, the overall signal points to a pronounced increase in summertime heat stress during the projected period relative to the reference climate. Heatwave frequency and the number of very hot days rise across most of the domain, with the strongest amplification over interior and desert regions—particularly the Arabian Peninsula, Iraq, and large parts of Iran. A key implication is that, even under optimistic emissions pathways, a substantial intensification of summer heatwaves is largely unavoidable and may have serious consequences for public health, energy demand, and water resources. Under the intermediate pathway, increases in both the frequency and spatial extent of heatwave occurrence become more persistent across many mid- and higher-latitude parts of the region, revealing clearer spatial contrasts. This indicates that regional responses to future warming are not uniform and are strongly shaped by local climate conditions and geographic setting. One of the most important findings is the emergence of nonlinear behavior in heatwave metrics under the high-emissions pathway. While a monotonic increase in heatwave frequency might be expected with stronger warming, the results show that in some areas—particularly toward the end of the projection period—frequency can decline relative to the intermediate pathway, even though overall heat stress remains above the baseline. This suggests that, under intense warming, the dominant change mechanism may shift from “more events” toward event merging and longer-lasting heatwaves. In other words, rather than producing a greater number of discrete episodes, a hotter climate may favor more persistent, multi-week heatwave conditions—reducing the count of events while increasing their duration and intensity. The spatiotemporal analyses further indicate that heatwave changes vary with time and scenario in both latitude and longitude, and do not organize into a single, uniform gradient across the study domain. Under the optimistic pathway, interannual variability and episodic spikes are evident, but a consistent, region-wide upward trend is not dominant. Under the intermediate pathway, increases become more coherent and sustained, with larger portions of the region—especially mid- and higher-latitude areas—remaining at elevated heatwave-day levels for longer periods. Under the high-emissions pathway, the pattern becomes more unstable and distinctly nonlinear: intervals of sharp increases alternate with periods of relative decline or large variability, and hotspots of thermal stress may emerge in different longitudes at different times. This behavior highlights the importance of accounting for interannual variability and regional processes in heatwave risk assessment. At the decadal scale, heatwave intensity generally increases across all scenarios, with scenario divergence becoming more evident from the middle decades onward. In some cases, the intermediate pathway exhibits a larger upward shift in the median and spread of intensity, whereas the high-emissions pathway displays nonlinear responses. Nevertheless, heatwave duration intensifies most strongly under the high-emissions pathway and can accelerate toward the end of the period. This is particularly important for risk management, as prolonged heatwaves—even if fewer in number—can impose greater cumulative stress on public health, labor productivity, electricity demand, and water-system reliability. Sub-regional analyses reveal clear contrasts among the northern, central, and southern sectors. The northern and central sectors are more sensitive in terms of intensity increases, with stronger intensification under higher-emissions pathways. The southern sector, despite being warmer in absolute terms, shows smaller relative increases in intensity—potentially reflecting proximity to already-high thermal thresholds and physical–statistical constraints on relative growth. In terms of duration or heatwave days, all three sectors experience substantial increases, but the central sector exhibits the largest jump; under the high-emissions pathway, heatwaves may shift from multi-day events to multi-week phenomena. The convergence of scenarios early in the period and their divergence later further indicate that the influence of emissions pathways grows over time, and that mitigation and adaptation choices can meaningfully shape future risk. Overall, the Middle East is projected to face a significant rise in summertime heat stress during 2026–2055. Importantly, this increase is not limited to a higher number of events; under warmer scenarios, it may involve a transformation toward longer and more intense heatwaves. Accordingly, adaptation planning should simultaneously address the three core dimensions of heatwave risk—frequency, duration, and intensity—while explicitly considering spatial differences across sub-regions. Given the weaker model performance in winter and the heightened sensitivity of complex terrain and land–sea interface areas, seasonal bias correction and uncertainty assessment should be treated as integral components of both scientific analysis and policy-relevant applications.ConclusionThis study shows that CMIP6 model performance in estimating temperature is seasonally dependent: simulations are more reliable in summer and autumn, whereas winter exhibits the largest bias and RMSE, underscoring the need for seasonal bias correction and targeted calibration—particularly for winter conditions. Spatially, errors are concentrated mainly over mountainous terrain and along land–sea transition zones, while model performance is more stable across interior regions. The results also indicate that future warming is not confined to higher daytime maxima; the widespread rise in minimum temperatures (especially at night) emerges as a key climate-change signal across the region. Heatwave metrics further reveal that thermal risk increases under all emissions scenarios, but the magnitude and spatial pattern of change are scenario- and location-dependent and can be nonlinear. Heatwave intensity increases most strongly in the northern and central sub-regions, while persistence/number of heatwave days shows an even more pronounced rise—particularly in the central sector, where events may extend to near multi-week durations. Overall, the Middle East is likely to experience a shift in the heatwave regime toward more intense and longer-lasting events; consequently, adaptation strategies should address both “intensity” and “persistence” simultaneously and explicitly incorporate sub-regional differences in planning for health, energy, water, and critical infrastructure. https://esrj.sbu.ac.ir/article_107032.html Introduction Land subsidence is one of the geological hazards that leads to the collapse or lowering of the earth's surface. The deformations on the earth's surface are mostly in the vertical direction and displacement may also be observed in the horizontal direction. Subsidence can be affected by human activities such as tunneling, mineral production, groundwater extraction and fault activity, which cause abundant morphological outcrops on the earth's surface (Sharifikia, 2012). In some cases, land subsidence is caused by the extraction of underground reserves and valuable mineral materials. One of the methods used to produce useful minerals is mineral solutions. If the mineral is solid and soluble in water, the mineral is dissolved in water by injecting water through wells containing the mineral layer, and then pumping and extracting the mineral solution through the extraction wells is carried out. In the extraction cycle, water injection operations are carried out on the one hand and the production of water-soluble materials is carried out in a controlled manner. The United States, Kazakhstan, China, and Uzbekistan use this method to extract potash ore. The Belle Plaine Potash Mine, located in Canada, is the world's first and largest solution mine (Mark et al, 2010). In the case of deep mineral brines that contain valuable elements such as iodine and bromine, the mineral solution extraction method can be used. In this case, due to the nature of the mineral, which is in the form of a mineral solution, the minerals are exploited by drilling deep wells. In order to reduce the effects of subsidence in such conditions, the wastewater from the extraction should be injected into deep layers after processing and separating the mineral. Currently, the mineral solution extraction method is used in our country and in the northwest of Golestan Province. In the northwest of Golestan Province and near the city of Aq Qala, the exploitation of iodized brines at depths of more than 1000 meters is underway, and the exploitation of iodine minerals by extracting deep brines by the private sector has begun since 2008. The purpose of this research is to investigate the numerical values and zoning of land subsidence due to the extraction of iodized brines in the study area. Although subsidence has a relatively high frequency and sequence, it is often difficult to detect and measure accurately due to the very slow and shallow motion of the Earth. Also, the amount of subsidence is usually very small and occurs in an area of one to several kilometers. Such a large area with very little subsidence cannot be analyzed by methods such as geophysical surveys, seismic waves, electromagnetic waves, soil resistivity, and other methods. One promising technology is high-frequency radar. Remote sensing with high-frequency radar can provide the penetration depth and resolution required for accurate detection and identification of such facilities (Klar A, et al. 2009). Materials and Methods In the present study, the issue of subsidence in the north of Aq Qala city in the northwest of Golestan province has been investigated using remote sensing tools. The study area is located 27 kilometers from Aq Qala city and in the northwest of Golestan province. In this area, withdrawal from surface and deep aquifers has caused subsidence on the ground surface. An examination of the drilled wells shows that the wells drilled by the Ministry of Energy did not extend to the bedrock and in two cases did not even reach the water surface, but the exploration wells of iodine mines and the oil company continued to the bedrock. A general look at the columns prepared in the exploration wells, in other words, the well logging carried out in the area, shows that from the south to the north of the study area, the depth of the bedrock decreases and the water table becomes higher, and also from the south to the north in the direction of drilling the exploration wells, the thickness of the layers decreases significantly. This area is geologically located on the border between three tectonic zones of the southern Caspian Basin, the southwestern part of the Kopeh Dagh folded belt, and the northern ridge of the eastern Alborz. The conditions of the study area are influenced by the tectonic history and stratigraphy of these three tectonic zones, and due to the alluvial covers and insignificant outcrops of formations in the study area, information from the exploration wells of the Oil Company and the iodine exploration wells was used. In this study, the methods of subsidence analysis include radar interferometry and numerical modeling. Radar interferometry is a method for combining Sentinel 51 images taken from radar sensors mounted on aircraft in order to prepare elevation maps, displacements, and changes in the ground surface, as well as determine the speed of target movement. Two Sentinel 1 images are taken before and after the displacement of the ground surface. Any displacement in the ground surface causes a change in the sensor distance (Dong et al. 2018). Sentinel-1 imagery was developed by the European Space Agency and began imaging on 14 April 2013 and is expected to last 7 years. The satellite is a 693 km orbital satellite and images in the C-band at a wavelength of 5.55 mm and with a temporal resolution of 12 days. The most important product of Sentinel-1 is single-view data with a spatial resolution of 20 x 5 m (Rucci et al. 2012). In this study, in addition to monitoring the subsidence phenomenon using radar interferometry, a numerical simulation method using Plaxis 3D software was used to better understand the subsidence problem and the mechanism of related deformations. Plaxis 3D is a 3D finite element program that was specifically designed to investigate and calculate the settlement of offshore foundations, but in version 1.6, with the addition of consolidation settlement, it gained the ability to investigate settlements resulting from water withdrawal and groundwater level reduction. This program takes simple inputs from the user, combines simple graphics, and automatically creates complex finite element models with advanced output and high flexibility. Discussion and Results For modeling the settlement behavior, the Mohr-Coulomb MC behavioral model has been used according to the geological conditions of the rock layers and the results of rock mechanics tests. The Mohr-Coulomb elasto-plastic model requires five input parameters, namely E Young's modulus, ν Poisson's ratio for soil elasticity, ϕ internal shear angle, C cohesion for soil ductility, and ψ as the expansion angle. The Mohr-Coulomb model represents an approximate first-order equation of soil or rock behavior. It is recommended to use this model for initial analysis of soil behavior and compare it with other models. For each layer, an average stiffness estimate is constant, and given this constant stiffness, an initial estimate of deformation is obtained with relatively fast calculations. In addition to the model parameters mentioned above, initial soil conditions, such as preconsolidation, play an important role in many soil deformation problems. This method is the simplest method for calculating soil consolidation settlement with the most basic available data, which has acceptable accuracy (Khosh Akhlagh, 2015). In the present study, the amount of land subsidence due to the extraction of deep brines for the production of iodine in the northeast of Aq Qala city - northern Golestan province was investigated by combining methods, radar interferometry and numerical modeling. Numerical simulation was performed using Plaxis 3D software and the possible subsidence values were predicted if extraction from deep brines continued in the study area. Then, subsidence zoning maps were prepared for the study area using radar images and the actual subsidence values were calculated. Comparing the results of the simulation with the radar zoning maps was able to clearly show the conceptual relationship between subsidence and the exploitation of brines quantitatively in the study area. Using geological data of the region and numerical simulation of Mohr-Coulomb, the range of subsidence changes in the study area is between 0 and 9 centimeters. The above numbers show acceptable agreement with the settlement value obtained by radar images. After creating the shown geometric model, the mechanical and behavioral characteristics of the formations were defined based on the Mohr-Coulomb model and based on the daily pumping values from the well and the groundwater level, other requirements of the model were also considered and finally the maximum possible amount of subsidence due to extraction in a one-year period is predicted to be 9 centimeters. Based on the radar interferometry technique, the subsidence values in the study area have been calculated and the maximum subsidence value in the exploitation area has been calculated to be 0.135 meters, equivalent to 13.5 centimeters. Conclusion Periodic subsidence monitoring in the study area shows that geological and lithological factors of the formations play a decisive role in the rate of subsidence and surface deformations, and accurate assessment of subsidence is highly sensitive to the geomechanical parameters of the formations. The calculated values for subsidence based on numerical modeling and remote sensing maps are relatively close to each other, indicating that the mechanical parameters and behavioral model of the formations are close to reality. Given the continued exploitation in this area and the expansion of exploitation in other areas of the plain and the irrenewability of the deep aquifer, the trend of piezometric level decline in these areas will continue and intensify with increased exploitation. https://esrj.sbu.ac.ir/article_107033.html Extended Abstract Introduction Landslide is one of the most frequent natural hazards, capable of threatening human lives and negatively impacting the natural ecosystem on a larger scale (Tien Bui et al. 2012; Balamurugan et al. 2016; Dey et al., 2024). In terms of severity, landslides rank as the seventh most catastrophic event among the various geohazards occurring on the Earth's crust (Nadim et al., 2006). Landslides, as common natural geological processes in mountainous areas, present serious threats to human safety, transportation infrastructure, economic growth, and ecological environments. Currently, landslides are increasing worldwide, and countries around the globe are experiencing the threat of landslide disasters. In general, landslide susceptibility evaluation can offer a basic foundation for landslide prevention and control, enabling comprehensive management with targeted emphasis (He et al., 2025). Since the 1960s, numerous methods have been developed by researchers worldwide. These methods are generally classified into two main categories: knowledge-driven models, such as expert scoring, analytic hierarchy process (AHP), fuzzy logic, and fuzzy comprehensive evaluation; and data-driven models, which include traditional approaches like information value, frequency ratio (FR), and logistic regression, as well as machine learning techniques such as artificial neural networks (ANN), support vector machines (SVM), random forests (RF), and decision tree models (He et al., 2025, Zhao et al., 2024). The Goujebel pass in East Azerbaijan Province is prone to numerous and large-scale landslides due to its specific topographic, geological, and climatic conditions. The frequent occurrence of landslides has not only caused the destruction of natural resources but has also become a serious threat to human settlements, infrastructure, and particularly the key Tabriz–Ahar transportation corridor. Therefore, accurately identifying high-risk areas and producing reliable landslide susceptibility maps can play a crucial role in reducing human and economic losses and improving the safety of transportation routes in this region. The objective of this research is to assess and map landslide susceptibility in the area from the Goujebel Pass to Ahar City using the Support Vector Machine (SVM) model and to analyze the role of influencing factors. Material and methods The study area is located in northwestern Iran, within East Azerbaijan Province. Geographically, it lies between 38°21' and 38°29' north latitude and 46°50' to 47°02' east longitude. Covering an area of approximately 193 square kilometers, it encompasses sections of the mountains surrounding the Goujebel Pass and extends to the western of the city of Ahar. The primary data used in this study include 1:50,000 topographic maps, 1:100,000 geological maps, a digital elevation model (DEM) with a resolution of 12.5 meters from the ALOS-PALSAR satellite, as well as Sentinel-2 satellite imagery and Google Earth images. For spatial analyses and data processing, ArcGIS, ENVI, and SPSS Modeler software were used. The main method for landslide modeling in this study is the use of the Support Vector Machine (SVM) model. This method was developed in the 1990s and, due to its high efficacy in various algorithms, is recognized as one of the most widely used approaches (Riaz et al., 2024). This model learns the complex relationship between effective factors and landslide occurrence by being trained on a dataset consisting of historical landslide locations and contributing factor layers. The learned relationship is then extrapolated to the entire study region to create a susceptibility map (Kavzoglu et al., 2014). A landslide inventory is recognized for providing a comprehensive record of historical landslide events currently present in the study area. The landslide inventory map (LIM) can be developed using high-resolution satellite imagery, aerial photographs, previous literature documenting landslides, and extensive field surveys (Ali et al., 2022). In this method, a historical landslide distribution map of the study area was first prepared and then divided into two datasets: 70% for training and 30% for testing, while non-landslide points were also randomly selected. Subsequently, the landslide conditioning factors including variables such as elevation, slope, aspect, lithology, distance to faults and drainage networks, the Topographic Wetness Index (TWI), land use, and vegetation cover were prepared in raster format. In the next step, the values of these layers at the locations of the training points were extracted in the ArcGIS environment to construct the data matrix. The SVM model was trained using this matrix with the application of the radial basis function (RBF) kernel, and its parameters were optimized. The performance of the final model was evaluated using the testing data and metrics such as overall accuracy and the ROC curve. Finally, the model was applied to the entire study area, and the final landslide hazard zonation map was produced in five classes: very low, low, moderate, high, and very high. Result and discussion This study aimed to produce a landslide susceptibility map of the Goujebel pass using a Support Vector Machine (SVM) model. Analysis of geomorphological indices showed that more than 98% of the landslides occurred at elevations between 1,450 and 1,750 m, with 42% of them specifically concentrated in the 1,640–1,740 m elevation class. Approximately 88% of the landslides occurred on slopes of less than 30%, and the north aspect, accounting for 63%, was the most significant slope direction for landslide occurrence. The study of geological indicators showed the determining role of lithology, such that the PLQ-c unit (discontinuous conglomerate with marly interlayers) covers only 44% of the area but hosts 95% of the landslides. From a hydrological perspective, a significant overlap was observed between high values of the Topographic Wetness Index (TWI) and the spatial distribution of landslides, with 66% of the landslides occurring within 100 m of drainage networks. Regarding land cover, approximately 70% of the landslides occurred in rangeland areas; however, the NDVI did not exhibit a clear pattern. Evaluation of the Support Vector Machine (SVM) model with a radial basis function (RBF) kernel demonstrated very good performance, with an AUC value of 0.933 for the testing dataset. Based on the results of this model, lithology, with an importance coefficient of 0.268, was identified as the most influential factor, followed by elevation (0.141) and slope (0.138) as the next most significant factors controlling landslide occurrence in the study area. The final hazard zonation map showed that the majority of the area (approximately 54%) is classified as very low and low hazard, about 21.3% of the area is classified as moderate hazard, and 24.4% falls within the high hazard class. High-hazard zones are primarily located on the sensitive PLQ-c formation on moderate slopes (10–30%), which represent the main centers of large and active landslides in the area. Therefore, it can be concluded that a strong and significant relationship exists between the spatial distribution of the PLQ-c formation and the occurrence of major landslides in the region. Water infiltration into conglomerate layers with marl and silt interbeds leads to an increase in pore water pressure, a reduction in internal friction, and ultimately weakens the cohesion of the layers. Under such conditions, the slope gradient plays a significant role as a facilitating factor. For example, some of the large and prominent landslides in the study area, including the one located east of Pireh-Yousefian village, have occurred precisely in areas where the PLQ-c Formation has a significant outcrop and where favorable hydrological conditions have prevailed. Notably, landslides within this formation are not only more frequent but also larger in area and volume. In general, zones with high and very high landslide susceptibility can be identified as the primary centers of instability within the study area. The accurate identification of these hazard zones can serve as a basis for restricting construction development, monitoring slopes, and implementing preventive measures to reduce future landslide damage. Conclusion The present study employed the SVM model with an RBF kernel to perform landslide hazard zonation in the Goujebel area, demonstrating high performance (training AUC = 0.943 and testing AUC = 0.933). Lithology, with a coefficient of 0.268, was the most important factor, and the PLQ-c formation accounted for over 95% of the landslides. Next, elevation and slope were influential factors, with coefficients of 0.141 and 0.138, respectively. Landslides mainly occurred at mid-elevations (1450–1750 m) and on moderate slopes (10–30%). Land cover and land use factors played a lesser role. The landslide hazard zonation of the Goujebel area indicates that structural and lithological controls have a dominant influence on slope instability. The zonation map of the area showed five hazard classes, with approximately 54% of the area classified as low and very low hazard, and 24% as high hazard. High hazard areas are primarily located on the PLQ-c formation and on moderate slopes, requiring continuous monitoring and management. The results demonstrated that combining SVM with spatial data is an effective tool for producing landslide susceptibility maps and supporting disaster management, environmental planning, and infrastructure design. Special attention to susceptible formations (particularly the PLQ-c formation), control of hydrological factors, and monitoring of areas with moderate slopes are among the key strategies for reducing landslide risk in this region. The findings of this research can serve as a basis for environmental planning, disaster risk management, infrastructure design, and land-use planning in the study area. Although the study demonstrates strong performance, future research is encouraged to explore alternative models to further enhance landslide susceptibility predictions. Keywords: Slope Hazard, Landslide, Support Vector Machine (SVM) model, Goujebel Pass https://esrj.sbu.ac.ir/article_107071.html Geopolitical analysis of chaos spaces on Iran's national security (case study of South Caucasus)AbstractDeep transformations in the geopolitics of the South Caucasus after the collapse of the Soviet Union have caused extensive changes in the political structure of the region. In the meantime, Iran has expanded its political-economic cooperation with these countries due to the close historical, cultural and geographical ties. Due to its geopolitical importance and its transit route, energy resources, and the emergence of new security threats, this region has received the strategic attention of regional countries, including Iran, and trans-regional powers. Today, mastering this area has become an important measure of power. On the other hand, the atmosphere of chaos and complexity has become the basis for direct and indirect intervention of powers and has become a factor for competition between actors. In terms of security, the South Caucasus is a barrier between Iran and regional and global powers. Therefore, any threat and chaos causes a threat to Iran's national security. Due to its proximity to the South Caucasus and preventing the spread of crises and conflicts in this region to its borders, Iran pursues a region-oriented foreign policy, based on partnership strategies and without the involvement of major powers. Our goal in this research is to investigate the developments in the South Caucasus on Iran's national security and foreign policy. It seems that considering the role of regional and extra-regional powers in the developments of the South Caucasus, i.e. competition, conflict of interests, different goals, cooperation and alliance are different axes that affect Iran's national security and cause the formation of Iran's foreign policy frameworks in have become South Caucasus. The findings of the research indicate that the most important reason for the crisis in the South Caucasus is the intervention and role-playing of regional and extra-regional powers by means of financial aid, information and support of weapons of their own spectrum. This factor has caused competition, different positions, and ultimately the formation of an atmosphere of chaos in the South Caucasus.Key words: SECURITY, IRAN, GEOPOLITIC, SPACE CHAOS, SOUTH CAUCASUS.Geopolitical analysis of chaos spaces on Iran's national security (case study of South Caucasus)AbstractDeep transformations in the geopolitics of the South Caucasus after the collapse of the Soviet Union have caused extensive changes in the political structure of the region. In the meantime, Iran has expanded its political-economic cooperation with these countries due to the close historical, cultural and geographical ties. Due to its geopolitical importance and its transit route, energy resources, and the emergence of new security threats, this region has received the strategic attention of regional countries, including Iran, and trans-regional powers. Today, mastering this area has become an important measure of power. On the other hand, the atmosphere of chaos and complexity has become the basis for direct and indirect intervention of powers and has become a factor for competition between actors. In terms of security, the South Caucasus is a barrier between Iran and regional and global powers. Therefore, any threat and chaos causes a threat to Iran's national security. Due to its proximity to the South Caucasus and preventing the spread of crises and conflicts in this region to its borders, Iran pursues a region-oriented foreign policy, based on partnership strategies and without the involvement of major powers. Our goal in this research is to investigate the developments in the South Caucasus on Iran's national security and foreign policy. It seems that considering the role of regional and extra-regional powers in the developments of the South Caucasus, i.e. competition, conflict of interests, different goals, cooperation and alliance are different axes that affect Iran's national security and cause the formation of Iran's foreign policy frameworks in have become South Caucasus. The findings of the research indicate that the most important reason for the crisis in the South Caucasus is the intervention and role-playing of regional and extra-regional powers by means of financial aid, information and support of weapons of their own spectrum. This factor has caused competition, different positions, and ultimately the formation of an atmosphere of chaos in the South Caucasus.Key words: SECURITY, IRAN, GEOPOLITIC, SPACE CHAOS, SOUTH CAUCASUS.alliance are different axes that affect Iran's national security and cause the formation of Iran's foreign policy frameworks in have become South Caucasus. The findings of the research indicate that the most im