https://www.geomorphologyjournal.ir/ Quantitative Geomorphological Research en daily 1 Mon, 22 Dec 2025 00:00:00 +0330 Mon, 22 Dec 2025 00:00:00 +0330 https://www.geomorphologyjournal.ir/article_213849.html IntroductionSoil erosion is a global problem that seriously threatens water and soil resources. It takes over 300 years to form just one centimeter of soil (Tripani, 2001). Therefore, preventing soil erosion is vital for preserving valuable natural wealth (Morgan, 1986). Soil erosion and sediment production cause numerous environmental problems. These sediments also lead to the entry of heavy metals, nutrients, and pesticides into river channels, affecting communities in various ways. Erosion and sediment production are complex functions of various factors, including geology, climate, topography, vegetation cover, and human activities. Soil erosion is a natural physical process through which soil particles detach from their original bed and are transported to another location by an agent of transport. Since millions of years ago, particularly when humans began manipulating ecosystems, the process of erosion has intensified and turned into an environmental hazard (Esmaeili & Abdollahi, 2011). MethodologyThe study area encompasses the Givi Chai river basin, approximately 44 kilometers long, which is one of the permanent rivers in Ardabil province. The geographical coordinates of this region are as follows: - Longitude: 48° 4' 58" to 48° 40' - Latitude: 37° 57' 48" This area is located in zone 38 and features diverse land uses, including agriculture, pasture, and forestData Collection Necessary data, including climatic information, soil characteristics, and types of land use, were collected from local sources and weather stations Considering the diversity of land use and the possibility of reducing erosion by using cover management and conservation agriculture methods, a scenario-based approach was used to compile possible land use scenarios. In the following, based on the conditions of the studied area and also the land use situation, in addition to the existing situation scenario, six other scenarios were compiled with the aim of improving the factor of plant management and soil protection against erosion. The amount of soil erosion in each of the scenarios was determined using the G2 model and the amount of erosion was calculated in each land use and in each management scenario. After preparing the map of erosion factors in the G2 model, the soil erosion map of the study area was prepared in the GIS environment. Considering the diversity of land use and the possibility of reducing erosion using cover management methods and conservation agriculture, a scenario-based approach was used to compile possible land use scenarios. In the following, the amount of soil erosion with cell dimensions of 20 x 20 meters was compiled in each of the scenarios.Data Analysis Data analysis was conducted using GIS software and the G2 model to identify vulnerable areas. Results The results indicated that different land uses have varying impacts on soil erosion rates. Specifically, agricultural lands experienced the highest levels of erosion, while forested areas exhibited the least erosion. Impact of Land Use Changes in land use can significantly affect soil erosion. Improper management of agricultural lands and overgrazing can lead to increased erosion. Strategies To reduce soil erosion, it is recommended to adopt sustainable agricultural practices and restore forested areasConclusion This study demonstrated that the G2 model is an effective tool for assessing soil erosion in the Givi Chai region. The results obtained can aid in management planning for soil health preservation and erosion reduction. Implementing sustainable land use management measures is essential to prevent further erosion. Results and Discussion The results indicated that different land uses have varying impacts on soil erosion rates. Specifically, agricultural lands experienced the highest levels of erosion, while forested areas exhibited the least erosion. Impact of Land Use Changes in land use can significantly affect soil erosion. Improper management of agricultural lands and overgrazing can lead to increased erosion. Management Strategies To reduce soil erosion, it is recommended to adopt sustainable agricultural practices and restore forested areas. Based on the scenario map of the existing situation, the values of soil erosion are between zero and 70 tons per hectare. Most of the erosion is observed in agricultural lands. Based on the obtained results, the lowest amount of erosion reduction is related to dense and medium vegetation, which is presented in the form of a scenario. By analyzing the effects of the scenario in reducing erosion, it can be concluded that if it is possible to restore medium and poor pastures and turn them into good pastures according to the conditions of the region, a significant amount of soil erosion can be reduced.ConclusionSoil erosion using the G2 model in Givi Chai watershed shows that this model is specifically designed to evaluate and predict soil erosion and sedimentation. The erosion values were estimated in the existing situation and six management scenarios, and the analyzed results were mentioned below, some general results that may be obtained from this model. Examining the soil erosion map shows that its average amount is 3.3 tons. Using the G2 model and combined parameters, the soil erosion rate is calculated. This step includes the use of special formulas of the G2 model, which gives weight to different factors. After calculating the erosion rate, prepare the final soil erosion map in the ArcGist environment, and this map should include high, medium and low erosion risk areas. As a result, by preparing a land use map, the amount of erosion was determined for all uses, and the results of erosion in each of the uses show that the amount of erosion has increased in most of the uses. But the highest amount of erosion and sedimentation is residential areas and agricultural land respectively. The general conclusion is that the type of land use directly affects the amount of sedimentation and improper management can lead to soil erosion and pollution of water resources. It is possible to reduce the amount of significantly reduced soil erosion and basically the combined scenario provides better results. In this regard, it is suggested that urban and agricultural planning be done in a way that uses sustainable methods, such as maintaining vegetation, using conservation agriculture techniques, and designing infrastructure to control runoff. https://www.geomorphologyjournal.ir/article_215592.html IntroductionGeomorphology, as a fundamental branch of earth sciences, examines surface changes and investigates geomorphological processes. Landforms, as the diverse shapes of the Earth's surface, result from these processes and provide crucial information about geological history, erosion, and environmental changes. The study area in this research is the basins of the southern slope of the Sahand mountain range. The Qaleh-e-Chay basin, which originates from Sahand and ultimately enters the Lake Urmia basin. The Sufi-e-Chay basin, on which the Alavian Dam was also built, passes through the cities of Maragheh and Bonab and finally enters the Lake Urmia basin.The southern slopes of the Sahand Mountain Massif in northwestern Iran represent a region rich in geomorphic diversity due to their unique geographical location and exposure to tectonic, geological, and climatic factors. This area includes the Qaleh Chay, Soufi Chay, Mardagh Chay, and Lilan Chay basins, as well as parts of the Qarangho basin, all of which are sub-basins of Lake Urmia. Precise identification and analysis of these landforms can play a critical role in sustainable natural resource management, regional planning, and mitigating natural hazards such as floods. With advancements in remote sensing technologies and digital elevation models (DEMs), more accurate and rapid analyses of these landforms have become feasible. This study aims to identify, classify, and analyze the landforms of the southern Sahand slopes using the Topographic Position Index (TPI) and three advanced algorithms: MLMSR, CMLSR, and SPSR.MethodologyThe study utilized DEM data with a spatial resolution of 30 meters and the TPI to analyze and classify landforms. The TPI, an effective index in geomorphological studies, evaluates the topographic position of each pixel relative to its neighboring pixels. Positive TPI values indicate elevated areas (e.g., peaks and ridges), while negative values denote lower areas (e.g., valleys). Three algorithms—MLMSR (Multi-Layered Morphological Spatial Representation), CMLSR (Complex Multi-Level Summit Recognition), and SPSR (Single Point Summit Recognition)—were employed to process DEM data and extract landforms. Each algorithm applies different methods for analyzing elevation data to identify and classify landforms. The research process involved acquiring DEM data, calculating the TPI, applying algorithms, generating landform maps, and analyzing the results. The algorithms were evaluated for their performance in areas with varying characteristics, such as mountainous and flat regions.Results and Discussion The analysis revealed that the southern Sahand slopes encompass ten primary landform types, each with distinct characteristics. Narrow valleys and channels were predominantly observed in steep, mountainous areas in the northern and eastern parts of the region, while plains and flatlands were concentrated in the southern and lower sections. Ridges and elevated plateaus were prominent in higher altitudes, reflecting the influence of tectonic and erosional processes on landform development. A comparison of algorithms showed that MLMSR excelled in identifying peaks and ridges in mountainous areas. SPSR was more effective for precise classification of flat and plain areas, while CMLSR demonstrated satisfactory performance in recognizing complex landforms and conducting multi-scale analyses. The generated maps provided comprehensive information on the distribution and diversity of landforms, serving as a foundation for further studies.ConclusionThe results showed that the study area consists of various landforms such as narrow valleys, flat plains, hills, ridges and high plateaus due to diverse topographic and geological conditions. Each of these landforms has unique characteristics and their distribution in the region is influenced by factors such as slope, slope direction, altitude, lithology type and tectonic activities. In mountainous and steep areas, narrow valleys and high drainages are most concentrated and these areas indicate intense erosional activities. In contrast, plains and flat areas in the downstream and marginal parts have been formed due to extensive sedimentation processes. Also, hills and high plateaus are seen at medium and high altitudes, indicating the effect of wind and water erosion on the formation of these landforms. The algorithms used in this study each provided different capabilities in identifying and analyzing landforms. The MLMSR algorithm performed better due to its high ability to identify complex shapes such as peaks and ridges. In contrast, the SPSR algorithm was more suitable for flat areas and plains due to its high accuracy in processing pixels. The CMLSR algorithm also provided the ability to analyze landforms at different scales and allowed for the extraction of more details from land structures. In this study, digital elevation model (DEM) data with an accuracy of 30 meters was used to analyze topographic locations. Due to its high accuracy and detail, these data enabled rapid and automatic analysis of landforms and can be used in other similar areas. The analyses performed showed that the TPI index, as an effective tool in distinguishing and classifying landforms, has high capabilities in geomorphological studies. https://www.geomorphologyjournal.ir/article_217108.html Extended AbstractIntroductionIn general, the movement of the earth's constituent materials, including soil and rock, that occurs in sloping areas under the influence of gravity downwards is called a landslide (this definition includes types of collapse, slip, flow, etc.). In general, there are different classifications for naming and terminology of landslides, but the first classification is related to Warrens (quoted by Roustai, Shahram, 2004). Classifications after Warrens made very few changes in the terminology of landslides. In Warrens' classification, the type of material displaced and the type of sliding are referred to. Therefore, each landslide can be named and categorized into two types: first, a name that expresses the type of material displaced and second, a name that describes the mechanism and type of movement. There are different methods for measuring the movements of the earth's crust caused by the occurrence of a landslide. These include geodetic methods using precise leveling and GPS observations. The modern use of several remote sensing technologies, including synthetic aperture radar (SAR), optical measurements, and light detection and ranging (LiDAR), represents a valuable complementary data source to conventional mapping methods. MethodologyIn this study, various types of data were used, including Sentinel-1 satellite radar images with InSAR (Table 1) and data collected from the Global Positioning System (GPS) during field operations. Also, 1/50,000 topographic maps from the Iranian Surveying Organization and 1/100,000 geological maps from the Iranian Geological and Mineral Exploration Organization were used to study the geology and morphology of the region. The software used in this study is: scape SAR version 5.2, ArcGIS version 10.6, ENVI version 5.3, which will be used to prepare and process radar images and prepare a displacement map related to landslides. In this study, the temporal and spatial baseline for SAR images, 8 pairs of images from 2017 to 2022, have been identified for subsequent processing after controlling the parameters obtained from the baseline and coherence, and will be the basis for preparing a map of land surface displacement in unstable slopes in the study area, and finally the displacement rate for the mentioned years was calculated. Figure (2) shows the location map of the radar image of the study area.Results and Discussion Earthquakes are usually caused by the propagation of seismic waves that lead to physical changes in the Earth's surface. One of the results of these changes can be subsidence or elevation in different areas. Radar interferometry, which is used to calculate ground displacements, is one of the most powerful tools for studying ground changes due to earthquakes. Reviewing and comparing ground displacement data over several time and space periods (from 2017 to 2019), including 8 pairs of Sentinel-1 InSAR radar images, shows significant changes in the behavior of the ground along the Tefin-Dagaga road. This comparative analysis can clearly identify the process of subsidence and other geographical changes over these years. Tectonic structures such as faults, folds, and shear zones significantly contribute to landslides. Faults increase susceptibility to landslides due to severe shear stress and weakening of nearby lithology. Both minor and major faults play a significant role in slope instability. The Main Recent Fault and the Main Zagros Reverse Fault are two important faults that affect landslides in the Degaga Basin and the Zagros Range in general. The Degaga Basin landslide complex is located in the Sanandaj-Sirjan structural zone, where the Serpentinites of Sarvabad (Solava) ophiolites (the so-called Kurdistan ophiolite) along the main recent Zagros fault play an important role in their occurrence. These serpentinites are exposed along the Sanandaj-Marivan road and are thrust beneath the Cretaceous slabs and phyllites of Sanandaj-Sirjan. The branches of the recent main fault and its branches with the mechanism of strike-slip and strike-slip are observed along the Azad and Sirvan rivers. These faults have caused the fracture and crushing of serpentinites and other rocks. In some landslides on the Marivan-Sarvabad route, the main control in their occurrence seems to be the activities of the main reverse fault of the Zagros cut by the main strike-slip fault of the Younger and its branches, which intensify the absorption of water by the crushed serpentinites. Due to the continuous movement of these landslides, the Marivan road is constantly being destroyed.ConclusionIn this study, the interferometric radar (InSAR) technique was used with Sentinel-1 satellite data to measure ground displacement during 2017 to 2019. This method detects changes in the ground surface with high accuracy and calculates the amount of displacement by comparing multi-temporal radar images. Radar images were collected and analyzed at different time intervals to accurately assess changes in ground elevation, subsidence, and landslides. The results of this method showed that ground displacement data during 2018 and 2019 indicate significant changes in the ground condition along the Tefin-Dagaga road. In 2018, ground displacements were mostly reported as minor subsidences, with an average displacement of -0.0235 m in August, indicating a relative improvement in ground condition compared to 2017. Also, limited subsidence with a minimum displacement of -0.0501 m was observed, indicating instability in some specific locations. In contrast, the displacement situation became more severe in 2019. The average displacement reached -0.0376 m, indicating an increase in ground subsidence compared to 2018. The minimum displacement in this year reached -0.1094 m, which raised further concerns about ground instability in some locations. The larger standard deviation in 2019 (with a value of 0.0189 m) also indicated that the displacement changes in this year were more diverse and the ground instability was more widespread.Consequently, the comparison of displacement data and regression analyses shows that the study area, especially along the Tefin-Dagaga road, is subject to continuous geological changes. While 2018 showed a relative improvement in ground conditions, 2019 data indicate a return of more severe subsidence and widespread instability. This suggests that continuous and careful monitoring, along with urgent protective measures, is essential to prevent further risks in this area. https://www.geomorphologyjournal.ir/article_220482.html Introduction Landslides are one of the most destructive geomorphological hazard processes of the range, which not only cause huge losses to human society and economic development but also pose a serious threat to the environment. In recent years, successive changes in land use, due to the necessity of meeting the various needs of the growing world population, represent an important part of global changes in the environment, and often unprincipled changes in land use as a dynamic factor related to human activities, also lead to an increase in the potential for landslides. Meshkinshahr County (located in Ardabil Province), due to environmental characteristics including; topographic conditions, loose and unstable surface materials on resistant formations, and climatic conditions, has a high potential for landslide hazards. However, in recent years, due to the growing population and unprincipled land use changes, the potential for this hazard to occur at the county level has increased. Accordingly, the present study seeks to evaluate the effect of land use changes on the potential for landslide hazard in this county. Methodology In this study, to investigate land use changes, first, Landsat satellite images from OLI-TM sensors for the years 2002 and 2024 were obtained from the US Geological Survey. Then, to prepare the images, geometric and atmospheric corrections were made on the images using Envi5.3 software. In the next stage, using the object-oriented classification method and the nearest neighbor algorithm using Ecognition software, land use maps were extracted in the two years under study. In the next stage, by identifying the effective factors involved in landslides in the region (including; Dem, slope, aspect, lithology, distance from fault, land use, precipitation, distance from communication road, and distance from river) and preparing information layers for each criterion in GIS, the evaluation and standardization of the layers were performed using the fuzzy membership function and weighting of the criteria, using the critic method. Finally; Final analysis and modeling were performed using the weighted linear combination multi-criteria analysis method. Results and Discussion Based on the results of the analysis of land use changes, in both years of study, poor pastures and dryland agriculture cover the largest area of the county. In contrast, irrigated areas and snow-covered lands have occupied the smallest amount of the total area of the county in both years 2000 and 2024. According to the results of the study, during the years of study; irrigated agriculture, dryland agriculture, residential areas, and irrigated areas have increased, and on the contrary, the area of gardens and forests, good pastures and poor pastures and snow-covered lands has decreased. In addition; considering the analysis of the method of land use conversion, it is observed that the largest land use change in the county was the conversion of poor pastures to dryland agriculture, and in 2024, compared to 2002, about 452.02 square kilometers of the area of poor pastures in the county was converted to dryland agriculture. According to the results, in 2002, the slope, land use, and lithology criteria had the highest weight coefficient, respectively, and in 2024, the land use, slope, and lithology criteria had the highest weight coefficient. According to the landslide hazard zoning map, in 2002, the area of the very high-risk and high-risk categories was 457.606 and 994.776 square kilometers, which increased to 483.444 and 1103.104 square kilometers, respectively, in 2024. In terms of land use, in the landslide map in both 2000 and 2024, the areas with the very high-risk and high-risk categories were mainly located in agricultural uses (especially rainfed agriculture), pastures, and residential areas. Conclusion Considering the landslide zoning map in 2002 and 2024 and the large area of very high-risk and high-risk zones, it can be concluded that, in general, given the environmental conditions prevailing in the area, including the dominance of slopes with medium to steep slopes (15 to 80), altitudes of 1000 to 4000 meters, susceptible geological formations, rainfall and abundance of the waterway network and the under scouring of the slope support by flowing waters, fault structures and slope directions, trenching and removal of the slopes' toes following road construction and development activities, Meshkinshahr County has a high potential for the formation of landslide movements. However, with the changes in land use that have occurred in the county, such as an increase in the area of agricultural lands and residential areas, and a decrease in the area of pastures, gardens, and forest cover, the area of very high-risk and high-risk categories has increased by 25.835 and 158.328 square kilometers, respectively, in 2024 compared to 2000. Given the large area of landslide-prone areas in Meshkinshahr County and how land is being converted and changed, expert protection, watershed management, and management measures must be taken. Finally, it can be acknowledged that the results of this research have a practical aspect and it is expected that the use of the land use change map and landslide hazard zoning map obtained in the present study will be made available to stakeholders and organizations related to environmental hazard issues as a more powerful tool for understanding the effects of land use change on landslides and risk management and reducing losses and losses caused by the environmental hazard of landslides. https://www.geomorphologyjournal.ir/article_222737.html Extended AbstractIntroductionThe Lut Desert in Iran, one of the hottest and most arid deserts on Earth, hosts an extensive array of yardangs, whose unique geological and climatic conditions provide an ideal natural laboratory for studying erosional processes. In contrast, the Aeolis region of Mars, extensively explored by NASA's orbiters and rovers, features yardangs that exhibit striking morphological parallels to their terrestrial counterparts in terms of shape, orientation, and erosion patterns. A comparative analysis of these two regions offers valuable insights into the influence of climatic factors, material composition, and erosional dynamics in two distinct yet analogous environments. One effective approach to investigating these phenomena is the geomorphological modeling of yardang development stages, which enables the simulation of their formation, growth, and evolutionary trajectories over time. Such modeling not only enhances our understanding of the environmental and geological drivers behind yardang evolution but also facilitates a more precise comparative framework between terrestrial and Martian analogs. In this study, geomorphological modeling techniques, including three-dimensional reconstruction, are employed to simulate the developmental stages of the Lut Desert yardangs and compare them with those in the Aeolis region of Mars. The research pursues two primary objectives: first, to identify the dominant processes governing yardang formation in the Lut Desert and on Mars, and second, to analyze the key factors influencing these processes across both planetary contexts.MethodologyIn this study, Landsat 9 satellite imagery was initially acquired via Google Earth Engine for the Lut Desert region. A digital elevation model (DEM) of the area was subsequently extracted from the United States Geological Survey (USGS) database. Following this, the yardangs within the Lut Desert were systematically identified. To evaluate these geomorphological structures and assess the role of wind in yardang formation, the DEM data were integrated into the Global Wind Atlas platform. Key parameters, including the frequency, velocity, and intensity of prevailing winds, were then computed and analyzed.Results and Discussion Wind Frequency, Velocity, and PowerThe results revealed that the predominant wind frequency in the Lut Desert yardangs is 30%, with winds predominantly originating from the northwest. Wind velocity emerged as a critical factor in yardang formation, with 50% of measured wind speeds attributed to the dominant northwest winds in the study area. The third parameter, wind power, demonstrated that northwest winds account for 60% of the total wind energy in the Lut Desert. This high wind power underscores the significant erosional capacity of northwestern winds to modify surface features and induce substantial changes in geomorphological structures. Wind power is directly correlated with its capacity to transport and displace sedimentary particles, a process that profoundly influences yardang morphology.Processes Driving the Genesis and Evolution of Lut Desert YardangsThe findings indicate that the Lut Desert yardangs have evolved through the interplay of endogenic and exogenic processes. Aeolian and hydrological forces, combined with lithological variations, have generated diverse erosional patterns in the region, ultimately producing the distinct geomorphological forms of the Lut yardangs.Developmental Stages of Lut Desert YardangsAnalysis of the Lut Desert yardangs enabled the proposal of a five-stage developmental model. This model not only provides a comprehensive explanation of yardang evolution but also facilitates the interpretation of how factors such as wind dynamics, hydrological activity, lithology, and environmental conditions collectively shape these structures. The model assigns primary agency to aeolian processes in yardang formation and serves as a holistic framework for studying yardangs in extraterrestrial contexts, including Mars.Analysis of Martian YardangsThe yardangs in the Aeolis Planum region of Mars are predominantly classified as "hogback" types, characterized by rounded forms, layered and dendritic structures on their upper surfaces. These features distinguish them morphologically from yardangs observed in other planetary regions. Prominent attributes include truncated heads, aligned wings, and conical tails. The widespread distribution of these yardangs in Aeolis Planum, along with their unique structural traits, highlights their significance as analogs for comparative planetary geomorphology studies.ConclusionThe findings of this study demonstrate that aeolian erosion is the primary force driving the formation and evolution of yardangs in both regions. Persistent, high-energy winds have sculpted elongated, linear landforms by removing loose and less resistant materials through abrasion and deflation processes. The dominant orientation of yardangs in both areas aligns with the prevailing wind direction, as evidenced by the northwest-southeast elongation of yardangs and their intervening corridors in both the Lut Desert and Aeolis Planum on Mars. However, the directional patterns of prevailing winds differ between the two regions: winds in Aeolis Planum predominantly blow from the southeast to the northwest, whereas in the Lut Desert, the dominant winds follow a northwest-southeast trajectory. This divergence in wind regimes reflects distinct climatic conditions and dynamic wind patterns across the two planetary environments.In terms of evolutionary stages, the Lut Desert yardangs are predominantly in a mature developmental phase, characterized by elongated ridges, narrow corridors, and steep windward slopes. In contrast, the Aeolis Planum yardangs are primarily classified as "whaleback" or "hogback" types, indicative of advanced-stage erosion and geomorphological evolution. These observations suggest that the Martian yardangs in Aeolis Planum are temporally older than their terrestrial counterparts in the Lut Desert, having undergone prolonged erosional processes under Mars’ unique atmospheric and geological conditions. https://www.geomorphologyjournal.ir/article_224828.html IntroductionTectonic forces originate from within the earth and cause deformation of the earth's surface. Tectonics is important in the science of geomorphology, especially from the perspective of the formation of surfaces, and the formation of mountain ranges is the function of tectonic forces. One of the important natural hazards in mountainous areas is landslides, which has serious consequences for human life. Studies conducted around the world also indicate that landslides in tectonically active areas have much greater cuts and in mountainous areas where there is greater density, education can be witnessed.MethodologyIn this research, the main goal is to identify landslides and investigate the effect of active tectonic parameters on domain instability in the sub-basins of the southern part of Zagros (Ilam-Mehran range). Therefore, initially, 257 small and large landslides, including definite and suspected cases, were identified and characterized using a digital elevation model with a resolution of 12.5 m, topographic maps of 1:50,000, satellite images in Google Earth, Arc GIS, and Global Mapper software. Then, through more detailed studies in images with higher spatial resolution and field visits, the study area was studied on a case-by-case basis and the suspected cases were verified (Figure 3). Next, to evaluate the spatial relationship of landslide occurrence, the tectonic activity of the sub-basins was extracted using Arc Hydro software. Finally, to estimate the relative tectonic activity index Iat, morphometric indices such as hypsometric integral (Hi), river longitudinal gradient (SL), basin asymmetry (AF), basin shape ratio (Bs), valley floor width (Vfw) and mountain front sinuosity (Smf); and to investigate the uneven conditions of sub-basins, slope indices (S), slip area ratio to basin area (LA), slip density (LD) and Melton index (Me) were calculated and the statistical relationship between the indices was estimated using the Pearson correlation test. Also, data related to the epicenter of earthquakes were received from the database of the National Seismological Center.Results and Discussion A study of the spatial distribution of 257 identified landslides shows that the largest number of them was observed in the Ilam, Mehran 1, Mehran 2, and Salehabad basins, respectively. In terms of the ratio of landslide area to the total basin area, Mehran 2 basin has the largest share with 4.66 percent, which indicates the high sensitivity of this basin to the occurrence of landslides. In contrast, Salehabad basin has the lowest landslide area with 2.35 percent. Analysis of the relationship between landslides and faults shows that more than 57 percent of landslides occurred within a distance of less than 2 km from faults. This finding indicates that fault activity plays a fundamental role in creating unstable conditions on slopes. Also, the investigation of the distribution of landslides in relation to earthquake centers shows a direct relationship between landslides and earthquake occurrence. About 68.87 percent of the landslides occurred less than 4 kilometers from the earthquake focus with a magnitude of more than 2.5 on the Richter scale. The findings show that with increasing distance from the earthquake focus, the percentage of landslides decreases significantly, which indicates a decrease in the impact of seismic waves on the occurrence of these phenomena. In fact, the vibrations caused by earthquakes play a major role in the activation of landslides, and in areas where the faults have less activity or there are no earthquake centers, the frequency of landslides is reduced and their dispersion is increased. The results of morphometric indices show that the Ilam, Mehran 1 and Salehabad basins are in the medium tectonic activity class, and the Mehran 2 basin, being in the high tectonic activity class, has a higher level of tectonic activity. On the other hand, the distribution of landslides in the basins, considering their size and area, confirms the existence of active tectonics in the region. Especially in the Mehran 2 basin, despite its smaller size, it has a high level of tectonic activity and has the highest frequency of landslides in relation to its area. Also, the results of the analysis of the ratio of the area of landslides to the area of sub-basins indicate that this ratio increases significantly with an increase in the tectonic activity class. This indicates that in sub-basins with higher tectonic activity, the extent of landslides is relatively greater and their probability of occurrence increases.ConclusionThe findings show that landslides are mostly concentrated in the vicinity of active faults and close to earthquake epicenters, and proximity to structural fractures and seismic activity has played an important role in triggering landslides. By moving away from these tectonic elements, the frequency and intensity of landslides decrease. Therefore, it can be said that faults and earthquake foci, as the main drivers, have a direct impact on the occurrence and spread of landslides in the region. Also, the study of geomorphological indices and morphotectonic index (Iat) shows moderate activity of Ilam, Mehran 1 and Salehabad basins and high activity of Mehran 2 basin. The distribution of landslides in the studied basins shows that the phenomenon of slope instability has occurred significantly in all basins, but its rate is higher in some basins than in other areas. The significant positive correlation between landslide density indices and the ratio of landslide area to the basin hypsometric integral and Melton index indicates the effective role of tectonic conditions and the level of geomorphological dynamics of the basin in increasing the number and extent of landslides. In fact, in sub-basins with high tectonic activity, the area of landslides increases relative to the area of the sub-basin. Therefore, some basins, such as Mehran 2, despite their smaller basin size, witness a greater number and extent of landslides, which indicates their high sensitivity to factors affecting instability, especially tectonic factors. In general, the integration of tectonic, seismic, and morphometric data of the basins shows that the studied area is geodynamically active and landslides, as a clear consequence of these activities, have been formed under the direct influence of seismic activity, faults, and tectonic conditions of the region. https://www.geomorphologyjournal.ir/article_228486.html IntroductionGeotourism, as one of the new areas of nature tourism, follows the principles of nature-based tourism, education and promotion, environmental and economic protection and sustainability, and is a combination of the earth's heritage in the form of geographical landscapes, geomorphological forms, geological phenomena, ruggedness, rocks and minerals, mines, fossils, etc., and the processes that create them. One of the factors that create and underpin geotourism is the identification and evaluation of geotourism attractions, called geomorphosites. Geomorphosites are key elements in the development of geotourism, which have scientific, aesthetic, cultural, historical and economic values and can appear singly or in a variety of sizes at various scales. The present study aimed to evaluate the importance of geomorphosites in Dorud County based on the Prolong model, focusing on three tourism land areas including the geomorphosites of Gahar Lake, t, by prioritizing the geomorphosites, provide suggestions for improving and developing their performance in order to contribute to sustainable tourism in the region. MethodologyAccording to the purpose of the research, two types of evaluation were used as the criteria for action. One is the use of a qualitative method to identify and select geomorphosites through initial impressions and scientific reports of experts, based on their capabilities, and the other is a quantitative method for numerical evaluation and ranking of the geotourism site. The quantitative method is objective and tangible due to the use of numerical criteria and is also known as an indirect method. In this method, without mentioning how the sites were identified and selected, previously known geotourism sites are evaluated using quantitative methods. For this purpose, the Pralong (2005) model was used to comparatively evaluate the geomorphosite capabilities of Bisheh Waterfall, Gohar Lake, and Lili Strait. This model was first presented by Pralong in 2005, which is a comprehensive method for introducing and evaluating the geotourism capabilities of geomorphosites.To investigate the behavior of tourists, facilities and services, and protection of geotourism sites, a general questionnaire was prepared and completed by 100 tourists. The first part of this questionnaire included demographic items such as age, gender, education, marital status, place of residence, and tourists' level of knowledge of geomorphosites. The second part consisted of 20 specialized questions on the subject of facilities, services, and protection based on a five-point Likert scale (from very low to very high). Descriptive statistics and one-sample t-test were used in SPSS software to analyze the general questionnaire. In this regard, descriptive statistics indicators such as item frequency and mean were used as criteria for analyzing and summarizing the data, which allows for a better understanding of the data distribution. One-sample t-test is one of the parametric methods that was used to examine the difference between the population mean and the assumed mean of 3 (average) on the Likert scale.Results and Discussion The results of the frequency distribution of the measured variables showed that "the level of interest in protecting geotourism attractions and land heritage", "the impact of Lake Gohar on attracting tourists", "the impact of the Leyli Strait on attracting tourists" and "the status of accessibility and the presence of tourist guides to reach Lake Gohar" have very high values with 23, 23, 22 and 22 percent respectively. Also, the variables "the level of satisfaction with the geomorphosites of Leyli Strait, Bisheh Waterfall and Lake Gohar", "the desire to stay overnight in the place", "the status of protection of geomorphosites in the region" and "the status of accessibility and the presence of tourist guides to reach Leyli Strait" have high values with 55, 49, 53 and 54 percent respectively as the most important variables.The results of the one-sample t-test showed that the significance level in all items is less than 0.001, which indicates a significant difference between the mean of the items and the assumed mean of 3 (moderate). Also, according to the p value < 0.001 and positive upper and lower bounds, all variables for evaluating geomorphosites are appropriate. In this regard, the variable "satisfaction level from visiting the geomorphosites of Leili Strait, Bisheh Waterfall and Gohar Lake" with a mean of 3.89 and a t value of 58.49 has the highest values and is the most important variable. In contrast, the variables "level of information and familiarity of tourists with attractions and tourism issues" and "status of accommodation facilities and tourism service facilities within the geomorphosites" have the least importance with t values of 3.06 and 2.8, respectively.ConclusionIn the evaluation of the four criteria of the Prolong method, the apparent beauty criterion has obtained the highest score, and among the three geosites studied in the region, Bisheh Waterfall ranks first in terms of beauty, which indicates the greater attractiveness of this geosite. The economic criterion scores indicate the second rank of this criterion among the four criteria. In general, all the geosites studied have relatively good importance and value in economic terms, and among them, Bisheh Waterfall ranks first, which indicates that the accessibility of this geosite via the road is important in the region and its high attractiveness at the national level. Other geosites, from the perspective of economic criteria, need to develop important roads, as well as increase attractiveness and increase the level of protection measures. In the evaluations, the scientific value is ranked third, and among the geomorphosites studied, Lake Gohar is ranked first, which indicates its scientific and educational potential for the development of geotourism. The cultural criterion in the evaluation of geomorphosites has obtained very low scores, which indicates the lack of artistic and cultural events in the region, so in this regard, attention needs to be paid to the development of these aspects. In terms of productivity value, Bisheh Waterfall is also ranked first, and other geosites have obtained relatively equal scores. The increase in the number of infrastructures such as temporary camps and desirable accommodation centers, as well as a higher score in the utilization value and a higher number of visitors, have made it superior to the average productivity value. https://www.geomorphologyjournal.ir/article_229113.html IntroductionAlluvial fans are landforms in many arid and semi-arid regions. Tectonic, climate, channel incision, and avulsion can abruptly change the surface of an alluvial fan and, subsequently lead to the formation of a new fan. With time, alluvial fans exhibit significant differences in terms of weathering, the rate of headward erosion, the drainage pattern, and flooding and depositional processes. At first, young or active fans with distributary drainage pattern develop at the mountain front. If a faulted structure develops, its continuous propagation toward the river stimulates its deflection. The deflection of river and its migration can stimulate the abandonment of the oldest fan and the formation of a new fan along the deflected river. Long-term expo-sure to physiochemical weathering can lead to the degradation of old surfaces. Soil degradation induced by gully erosion represents a worldwide problem in the many arid and semi-arid countries, such as Iran. Iran is recognized as the second in the world in terms of soil erosion where approximately 2.5 billion tons of fertile lands are lost per year. Gully erosion can stimulate multiple environmental hazards, such as desertification, increasing sediment load in rivers and reservoirs, flood, and soil productivity loss. This study assessed: (1) the relationship between the evolution of alluvial fan surfaces and its effects on the geometric variability of these landforms; (2) the relationship between the geometric evolution of different surfaces and changes in the gully erosion pattern and controlling factors. MethodologyThe present study was implemented on southern slopes of the Aladag Mountains. The maximum and minimum altitude is 297 and 885 meters above sea level. Based on the Demarton climate index, the climate of the study area is classified as semi-arid. Drainage pattern, surface roughness and morphology were recorded to distinguish active fan surfaces from inactive fan surfaces.In this study, the ALOS DSM global digital surface model (DSM) from AW3D30 was used to extract geometric indices. This dataset is a digital surface model (DSM) with global coverage and a horizontal resolution of about 30 meters, which is developed based on 3D topographic data of the world with higher resolution (5 meters).In order to calculate the vegetation indices, data from the MSI sensor of the Sentinel-2 satellite at the L2A processing level were used. The L2A surface data, after applying atmospheric corrections, provide the reflectance of the land surface, and its synchronized dataset adjusts for radiometric changes resulting from processing line updates and ensures the temporal consistency of the data for time series analyses. Also, to extract the land use and land cover map, the World Cover product was used. In this study, 11 geometric indices were used to investigate the characteristics of active and inactive alluvial fans.In order to quantitatively assess and analyze the characteristics of gully erosion, data from the Multispectral Imager (MSI) of the Sentinel-2 satellite were used. In order to accurately identify and separate pixels related to gully from other land uses and surface phenomena, a supervised machine learning method with the Support Vector Machine (SVM) algorithm was used. In the next step, the distribution of gully and key indices related to their dimensions and dispersion were calculated. Results and Discussion According to the statistical results, gully formation was 2.5 times higher in active surfaces than in inactive surfaces. These differences could be due to the exposure of active surfaces to recent flooding processes and their smaller area compared to inactive surfaces. The significant increase in the average gully length in active surfaces indicates higher flow energy and continued erosion processes. The significant increase in the average gully width in inactive surfaces is due to the processes of gully wall destruction, lateral erosion, and relative filling over time. Length-width ratio was significantly higher in active alluvial fans than in inactive surfaces. The greater dispersion of runoff and the distribution of coarser and more permeable sediments facilitate the conditions for the longitudinal expansion of gully on active surfaces. On the contrary, the presence of highly weathered sediments and the time that has elapsed since the last flooding in inactive surfaces stimulated the lateraldevelopment of gully. A positive correlation between gully width and flow strength indicates the dominance of lateral erosion and gullies in the inactive surfaces compared to active alluvial fans. In active surfaces, the initial energy of the flow, the development of the drainage network, and the elevation conditions are the most important factors affecting the gully erosion pattern. In inactive alluvial fans, an increase in the topographic moisture index, an increase in surface roughness, and the stabilized state of the surfaces are more important in the gully erosion pattern. This comparative analysis shows that although some topographic factors in both alluvial fan generations affect the development of the gully, the evolutionary stages of the alluvial fan, by affecting their geometry, could lead to differences in the relative importance of geometric factors and their role in the gully erosion pattern.ConclusionIn this study, the geometric characteristics of different alluvial fan surfaces were first evaluated. Then, the morphometric characteristics of the alluvial fans were measured and quantified to determine the pattern of gully erosion in different generations of alluvial fans. Finally, the relationship between the evolution of alluvial fan surfaces, variability in their surface geometry, and the dynamic of gully erosion pattern was investigated. Based on the results, alluvial morphometric indices show significant differences between active and inactive alluvial fans. Active surfaces with higher drainage density, longer gullies, and higher length-to-width ratio indicate younger and more erosionally dynamic systems. In contrast, inactive surfaces with wider and deeper gullies can be an indication of the evolution of gully pattern in the absence of intense erosional activity. Alteration of hydrological connectivity between alluvial fan and contributing catchment is recognized as a principle method to control gully erosion. Reducing hydrological connectivity in contributing catchment andshifting hydrology pathway on alluvial fan, such as restoring vegetation and building check dam at the bottom of gullies in catchment. https://www.geomorphologyjournal.ir/article_230956.html IntroductionGeomorphological maps provide detailed insights into landforms, surface processes, and terrain evolution, and have been widely developed across the world. These maps are not only of scientific importance but also serve essential roles in natural hazard assessment, urban planning, archaeological surveys, land use management, and climate change adaptation. Traditional methods for geomorphological mapping—based on fieldwork and manual interpretation of topographic maps and aerial photos—are often time-consuming, costly, and subjective. Over the past three decades, advancements in remote sensing and digital elevation models have enabled the development of semi-automated and quantitative mapping techniques. Among these, machine learning algorithms such as Random Forest have shown high performance in supervised landform classification. This study aims to produce a detailed geomorphological map of the arid regions of Dehnamak and Aradan using Sentinel-2A data and the Random Forest algorithm. The region has not been the subject of previous similar studies, making this research a valuable contribution to high-precision landform mapping and the broader application of advanced classification techniques in arid environments of Iran.MethodologyThis study aims to classify landforms in a mountainous and arid region using the Random Forest (RF) algorithm and to assess the impact of integrating morphometric indices with satellite imagery on classification accuracy. The study area is located on the southern slopes of the Central Alborz Mountains, overlooking the Central Iranian Plateau. Geographically, it spans parts of Semnan and Tehran provinces, including mountainous terrains in the north and desert areas in the south, mainly situated between Semnan and Garmsar counties. Sentinel-2A imagery was used as the primary remote sensing dataset. Additionally, three key morphometric indices—Topographic Wetness Index (TWI), Curvature, and Surface Roughness—were derived from a Digital Elevation Model (DEM) to improve terrain characterization. Landform classification was conducted in two stages: first, using only Sentinel-2A imagery with the RF algorithm; and second, by combining the morphometric indices with the Sentinel-2A data in the RF model. Accuracy assessment was performed using the Kappa coefficient and Overall Accuracy metrics.Results and Discussion The analysis of landform classification results using two distinct approaches—a spectral model based solely on Sentinel-2A data and a combined model integrating morphometric parameters (curvature and surface roughness)—revealed significant differences in the accuracy and quality of landform identification. Statistical and spatial outputs from both models showed varying patterns of coverage and separability across geomorphological classes.Certain classes such as agricultural lands, mountainous areas with shallow valleys, eroded mountain slopes, and fluvial deposits exhibited similar classification accuracies in both models. For instance, the area of agricultural lands was estimated at 122.5 km² (4.6%) in the spectral model and 109.2 km² (4.1%) in the combined model, indicating minimal difference due to their distinct spectral features and relatively simple topography.Conversely, classes like young alluvial fans, clay plains, and salt flats showed better accuracy in the spectral model. For example, young alluvial fans covered 397.5 km² (15%) in the spectral model but only 318.5 km² (12%) in the combined model. The salt flats also showed a sharp drop in the combined model—from 99.1 km² (3.7%) to 27.5 km² (1%)—due to reduced sensitivity to spectral brightness caused by the emphasis on morphometric features.In contrast, the combined model performed better in identifying complex geomorphic units such as hills, regular mountain slopes, and hogbacks. Quantitative validation using 100 random ground control points showed higher accuracy for the combined model (85% overall accuracy, Kappa = 0.82) compared to the spectral model (78%, Kappa = 0.74). These findings confirm that integrating spectral and morphometric data improves landform classification in topographically complex environments and aligns with prior studies (e.g., Regmi et al., 2024; Veronesi & Hurni, 2014).ConclusionLandform mapping is a complex process influenced by data type and classification methods. This study evaluated the performance of the Random Forest algorithm using two scenarios: one based solely on Sentinel-2 spectral data (optical model), and another combining spectral data with morphometric indices—Topographic Wetness Index (TWI), curvature, and roughness (combined model). Results showed that integrating spectral and morphometric data improved classification accuracy for certain landforms, although not uniformly across all classes.While both models performed similarly for units such as agricultural land, shallow-slope mountains, playa margins, and badlands, the optical model yielded better results for classes like salt flats, clay plains, and new alluvial fans—highlighting the strength of spectral data in distinguishing units with unique reflectance. Conversely, the combined model outperformed in identifying landforms like undulating hills, floodplains, hogbacks, and structured mountains, where topographic variation is more significant.Overall, the combined model increased overall accuracy from 78% to 85% and the Kappa index from 0.74 to 0.82, demonstrating improved landform delineation. This suggests that combining spectral and morphometric variables provides a more robust classification, especially in geomorphologically diverse areas. Future improvements may involve using multi-temporal data, deep learning methods, and optimized variable integration. https://www.geomorphologyjournal.ir/article_231149.html IntroductionIn recent decades, rapid climate changes along with the intensification of land use and land cover (LULC) dynamics have emerged as the two main drivers of morphodynamic transformations in river basins. These transformations can fundamentally alter patterns of erosion, sediment deposition, and runoff connectivity, resulting in significant changes in watershed processes and river ecosystem stability. Among the latest conceptual frameworks in fluvial geomorphology, geomorphic connectivity has attracted growing attention for understanding and quantifying how sediment, water, and energy transfer between sediment sources, transfer pathways, and depositional areas within landscapes. This paradigm enables researchers and resource managers to assess both the structure and functioning of sediment transfer systems under environmental disturbances.Geomorphic connectivity not only determines the continuity of material transfer from headwaters to downstream reaches but also reflects the sensitivity of watersheds to environmental changes such as climate variability and anthropogenic activities. A widely used quantitative metric to capture this concept is the Index of Connectivity (IC), which combines digital elevation models (DEMs) and surface characteristics to evaluate sediment transfer potential and structural connectivity across landscapes. The application of IC is especially relevant in semi-arid and dry basins where fragile topography and dependence on episodic precipitation events enhance connectivity sensitivity.Most previous research has considered the separate or limited effects of either climate change or LULC transformations on geomorphic connectivity. However, the concurrent impact of both drivers, particularly over long-term periods and in environmentally sensitive regions such as Western Asia, has rarely been comprehensively studied. The Zarrinehroud River Basin, as one of the largest and most dynamic sub-basins of Lake Urmia’s watershed in northwest Iran, is exceptionally exposed to the combined effects of decreasing rainfall, increasing temperature, recurrent droughts, and rampant expansion of irrigated agriculture and built-up areas in recent years. This calls for an integrated, multi-temporal assessment of geomorphic connectivity to inform watershed management, erosion control, and water resource conservation under changing environmental conditions.MethodologyThis research aims to analyze the spatiotemporal dynamics of geomorphic connectivity within the Zarrinehroud basin over the period from 2000 to 2025, considering both climatic fluctuations and LULC changes. The study employs a four-phase methodology that integrates remote sensing, GIS, and advanced statistical analysis:Data Collection and Preparation:Spatial datasets—including 30-meter SRTM Digital Elevation Model (USGS), multi-temporal Landsat imagery (for 2000, 2010, 2015, 2025), river network vectors, and administrative boundaries—were acquired. Climatic data (annual precipitation, temperature, runoff) were sourced from ERA5 reanalysis and regional meteorological stations.Land Use/Land Cover (LULC) Classification:Landsat images were processed and classified into six main LULC classes: agricultural land, rangeland, built-up areas, barren, forest, and water. Classification accuracy exceeded 85% (Kappa coefficient). Change detection algorithms were applied to identify patterns and rates of LULC transformation across the study period.Calculation of Index of Connectivity (IC):The IC was computed following Cavalli et al. (2013), using DEMs, surface roughness, and hydrological flow properties in ArcGIS Pro and R software. The resulting IC maps reveal the spatial distribution of sediment transfer potential at four time slices: 2000, 2010, 2015, and projected 2025.Temporal Analysis and Graph Theory:Time series analysis of IC values was conducted at the sub-basin scale. Additionally, a graph-theoretical approach based on Heckmann & Schwanghart (2013) was used to model the sediment transport network, extracting centrality and betweenness indices for river nodes. Correlation and multivariate regression analyses (Spearman, Adjusted R²) were used to assess the relationships between changes in IC, LULC, and Results and Discussion Land Use and Climate Trends:The classification results indicate a marked shift in LULC across the basin during the 25-year period. Agricultural lands have significantly expanded, especially along river corridors and in the downstream areas. Meanwhile, rangelands have shrunk, and urban/built-up zones have grown, particularly in the middle and lower sub-basins. Barren land has diminished, whereas forests and water bodies have experienced slight and localized changes.Climatic analysis reveals an increase in average annual temperature from 12.3°C to 13.8°C and a decrease in rainfall by about 8% over 25 years. Future scenarios (RCP 2.6, 4.5, and 8.5) predict that rainfall could drop by 23-35%, with corresponding reductions in runoff by up to 39%. The runoff coefficient (runoff/rainfall) has risen in all scenarios, suggesting both increased rainfall intensity and reduced soil infiltration caused by LULC changes. There is an evident increase in drought events, particularly after 2010, impacting water availability for agriculture and hydrological regime stability.Graph Theory and Network Analysis:The sediment transfer network has become more centralized and vulnerable over time. The average path length for sediment transfer decreased by about 16%, indicating greater likelihood of direct sediment flow to the river channels. Critical nodes with high betweenness and centrality emerged, especially in sub-basins C and A, rendering these areas potential bottlenecks for sediment routing. Vulnerability is most acute in sub-basins with steep slopes, disrupted vegetation, and extensive agricultural development.Statistical Relationships:Regression and correlation results indicate that LULC changes, notably the expansion of croplands and built-up areas, are the dominant drivers of IC decline, explaining over 72% of the variance in IC reduction (Adjusted R²=0.72). While climate change (reduced precipitation and higher temperature) contributes to declining connectivity, its independent effect is less significant and often non-significant compared to human activities. The interplay between LULC and climate exacerbates connectivity loss in more than 60% of sub-basins, particularly where inappropriate management and environmental stress overlap. Notably, IC values plummet after the threshold of a 20% increase in agricultural areas is exceeded, and decline exponentially where expansion surpasses 40%.ConclusionThe integrated assessment conducted in the Zarrinehroud basin clearly demonstrates that land use change is the primary factor controlling geomorphic connectivity dynamics and sediment transfer risks. While climate change augments basin vulnerability, https://www.geomorphologyjournal.ir/article_232035.html Extended AbstractIntroduction The Lut Desert is one of the most prominent and significant desert regions located in southeastern Iran. Due to its unique climatic and geological conditions, it has attracted considerable attention in geomorphological and geological studies. This desert is known as one of the hottest and driest places on Earth, with extremely high temperatures and very low precipitation rates. Such harsh climatic conditions have led to the formation of distinctive landforms and surface features, which are the focus of many scientific investigations. Studying the surface sediments and geomorphology of the Lut Desert can provide valuable insights into erosional and depositional processes in arid and semi-arid environments. The Lut Desert lies within the Lut structural block in eastern Iran and plays a crucial role in understanding the geomorphological evolution of Iran’s desert regions. This area has been subjected to various tectonic systems, leading to the formation of igneous and metamorphic structures. Given that current tectonic activity in the region is minimal, aeolian (wind-driven) erosion and deposition have become the primary factors shaping the landscape. Detailed investigation of surface sediments and particle morphology offers a deeper understanding of the origins and processes behind sediment deposition. The Lut Desert experiences a hot and arid climate with annual precipitation rarely exceeding a few millimeters. Summer temperatures often surpass 50 degrees Celsius. Dominant winds in the region, especially the “120-day wind” blowing from the northwest to southeast, play a central role in transporting fine sand and dust particles. These winds contribute significantly to the erosion and formation of diverse geomorphological features such as yardangs (wind-carved ridges), sand dunes (barchans), and gravel plains.MethodologyIn this study, samples were collected from 19 different locations across the Lut Desert to represent its geomorphological diversity. Samples were prepared in the laboratory using wet sieving methods for particle size analysis. Using a shaker and standard sieves, particle size distributions were determined. For a more detailed analysis, particle morphoscopy was conducted using stereomicroscopy and electron microscopy to examine particle shape and surface texture. Statistical analysis was carried out with SPSS software to calculate parameters such as mean particle size, sorting, elongation, and skewness. These analyses helped distinguish between wind-driven (Aeolian) and water-driven (fluvial) sediments.Results and Discussion Particle size analysis showed that surface sediments of the Lut Desert include a wide range of grain sizes from coarse sand to fine silts and sandy silts. Generally, sediments showed moderate to poor sorting and a negative skewness, indicating a dominance of wind-derived sediments. Morphoscopic studies revealed many particles possess rough, angular surfaces consistent with short-distance aeolian transport and mechanical abrasion by wind. Some particles appeared semi-translucent and slightly rounded, suggesting secondary processes such as limited fluvial reworking. The evidence from the data indicates that aeolian erosion and deposition are the dominant processes shaping the surface of the Lut Desert. Prevailing winds transport sand particles from eastern sand seas towards western yardang fields. Although limited signs of fluvial activity were observed in some localities, their influence is considerably less than that of wind processes. This is especially evident in areas covered by hamada (Rocky desert pavements) and stone pavements, where wind is the main shaping agent. Mineralogical composition and particle morphology indicate that the source materials are primarily igneous and sedimentary rocks from adjacent regions, transported and deposited by wind over varying distances. The findings of this study contribute to a better understanding of erosional and depositional processes in desert environments and can be useful for environmental management, predicting geomorphological changes, and climatic studies. Furthermore, understanding aeolian sediment characteristics aids in evaluating surface mineral resources and environmental studies. Knowledge of these processes is also vital for addressing dust storm phenomena and their impacts on nearby human settlements and agriculture.ConclusionsAccording to the results of the studies, the most important surface features in the Yalan Sand include star-shaped dunes, wind holes or wind basins, irrigation holes, sand blades, longitudinal and saif hills, barkhans and kaluts. The erosion rate in the Lut Desert is very high due to the high wind speed, so that the trunks of Gaz and Taq trees are up to 120 cm outside the sediments.Based on the grain size analysis and statistical analysis of sedimentological parameters, the collected sediments indicate three types of sedimentary environments and two types of processes. Aeolian, playan and alluvial environments have been created by the activity of two types of wind and water processes. Based on the mineralogical and morphoscopy results, the dominant minerals in the sandy sediments of the Lut Desert and Yalan Sand include quartz, feldspar, calcite and clay minerals. In the Rigi Plain and the Kalut Zone, the simultaneous presence of particles with different roundness, opaque and transparent particles, as well as sediments with low mineralogical maturity in the aeolian sand samples indicates that sediment was supplied from multiple sources, with different intervals and processes in the past. The sources of aeolian sand outside the Kalut area include large alluvial fan deposits in the northern, northwestern, and western parts of the Lut Block, which are mostly igneous particles and alluvial fan deposits that are igneous, metamorphic, and sedimentary in the order of abundance. Given that the cobbles have lower chemical and mechanical resistance, it is not possible to make a definitive statement about the transport factors by studying the grain surface effects, so quartz grains are used to study the grain surface effects. In the coarser fractions, small rocks are more abundant, but in the medium fractions, quartz, detrital carbonate, feldspar, and heavy minerals are more abundant, and wind-blown quartz is more abundant in the finer fractions.Keywords: Geomorphological features, Sedimentology, Sedimentary environments, Aeolian deposits, Lut Desert https://www.geomorphologyjournal.ir/article_232801.html Introduction Landslides are among the most destructive geomorphological hazards, causing extensive damage to human lives, infrastructure, and natural environments, particularly in mountainous regions. Triggered by factors such as intense rainfall, seismic activity, geological conditions, and human interventions, landslides have become increasingly frequent due to urbanization, deforestation, and climate change. In Iran, where mountainous terrains and tectonic activity dominate, landslides pose a persistent challenge, inflicting significant economic and social losses annually. Mapping landslide susceptibility is therefore essential for risk reduction, sustainable land-use planning, and hazard management. Recently, machine learning algorithms such as Random Forest (RF) and Support Vector Machine (SVM) have been widely adopted for landslide susceptibility mapping (LSM), owing to their ability to capture nonlinear and complex relationships among conditioning factors. Additionally, the use of Google Earth Engine (GEE) provides an efficient cloud-based platform for processing multi-source geospatial data, enhancing model scalability and accuracy. The Firouzabad watershed is located in the south of Ardabil province, covering an area of 1599 square kilometers of the province. This basin is located at a geographical location of 48 degrees 14 minutes to 48 degrees 32 minutes east longitude and 37 degrees 25 minutes to 37 degrees 54 minutes north latitude (Figure 1). The Firouzabad watershed is bounded by the Gharesu watershed from the north, the Qarnqu River watershed from the west, the Talesh Mountains from the east, and the foothills of the Qezel Ozan River from the south (Abadi et al., 2013). The Firuzabad watershed in Khalkhal County, as one of the landslide-prone areas in Ardabil Province, has been facing an increase in the occurrence of this phenomenon in recent years, and the identification and zoning of high-risk areas in this area is of great importance. Given the complexity of the factors affecting landslides and the nonlinear interactions between them, the use of classical methods alone in identifying high-risk areas cannot meet today's needs. In this regard, machine learning algorithms such as random forest (RF) and support vector machine (SVM) have attracted the attention of researchers as new and efficient tools in landslide hazard modeling due to their high accuracy and ability to analyze large and diverse data. Also, the use of Google Earth Engine (GEE) as a cloud computing platform for analyzing remote sensing data provides the basis for fast, accurate, and spatially based analyses and enables better modeling at different scales. Methodology This study was conducted in the Firoozabad watershed, Ardabil Province, northwestern Iran, which is highly prone to landslides due to its rugged topography, lithological diversity, heavy precipitation, and human-induced land-use changes. A landslide inventory containing 300 confirmed events was compiled from field surveys, Google Earth image interpretation, and official reports. Twelve conditioning factors were selected: slope, aspect, elevation, lithology, land use/land cover, NDVI, topographic wetness index (TWI), curvature, distance to roads, distance to rivers, distance to faults, and precipitation. These were derived from DEMs, remote sensing products, and climatic datasets. The dataset was divided into training (70%) and validation (30%) subsets. The RF and SVM algorithms were implemented using GEE, supplemented with statistical analyses in R. Both models generated susceptibility maps, which were classified into five categories (very low, low, moderate, high, and very high susceptibility). Model performance was assessed using the area under the ROC curve (AUC) and classification accuracy. Results and Discussion Both RF and SVM successfully delineated landslide-prone zones, though their predictive accuracies differed. The RF model classified approximately 1059.72 km² (66.31%) as very high risk and 132.32 km² (8.28%) as high risk. The SVM model similarly identified 1059.89 km² (66.32%) as very high and 133.53 km² (8.35%) as high risk. While spatial patterns were comparable, the models differed in factor importance. RF identified slope (14%) and elevation (11%) as the most influential variables, whereas SVM emphasized slope (34%) and precipitation (10%). Validation metrics confirmed the superiority of RF. The AUC value for RF was 0.895, compared to 0.798 for SVM, indicating higher predictive reliability. This aligns with prior research suggesting RF’s robustness in handling nonlinear relationships, multicollinearity, and overfitting, making it more effective than SVM in landslide hazard modeling. Conclusion The study highlights the effectiveness of machine learning algorithms in landslide susceptibility mapping, with RF outperforming SVM in predictive accuracy for the Firoozabad watershed. Scientifically, these findings confirm that advanced algorithms can capture the complex interactions among environmental factors influencing landslide occurrence. Practically, the susceptibility maps produced can guide policymakers and land managers in prioritizing preventive measures, including restricting construction in high-risk zones, slope stabilization, improved drainage systems, and vegetation reinforcement. The study also acknowledges limitations, including reliance on static datasets for precipitation and land use, as well as uncertainties introduced by IDW interpolation of rainfall. Future studies should integrate high-resolution, time-series datasets and explore ensemble or deep learning methods to enhance dynamic susceptibility modeling. Overall, this research demonstrates that combining multi-source geospatial data, machine learning, and cloud-based platforms provides a powerful framework for landslide risk assessment, supporting sustainable watershed management and disaster risk reduction in Iran and similar regions worldwide. https://www.geomorphologyjournal.ir/article_233710.html Introduction: Tourism is a fundamental element in the development of a region. Geotourism, as a novel approach within the tourism sector, examines the relationship between space, environment, culture, and tourism, aiming to enhance the connections among space, humanity, and culture in the context of tourism. It seeks to view tourism as an opportunity for the preservation and development of the environment and cultural heritage. In recent decades, geotourism has become one of the most significant forms of tourism worldwide due to its diverse applications. Notable applications of geotourism include its positive impact on local economies, environmental conservation, the promotion of cultural and historical significance of locations, enhancement of tourism infrastructure, and the creation of job opportunities. The study of geodiversity and geomorphosites represents an integrative concept that bridges tourism studies and earth sciences, facilitating a reevaluation and popularization of earth science concepts among the public. Research Methodology The research methodology employed in this study is a mixed-methods approach, integrating both quantitative and qualitative analyses with a practical objective. Initially, the geosites located on the northern slopes of the Bozqush Mountain range were identified through interviews and field observations. Subsequently, the value of these geosites was assessed using the Primary Geodiversity Assessment (PGA) method. The statistical population for this segment of the research comprised the opinions of 15 experts from the Department of Tourism and Cultural Heritage of East Azerbaijan Province, as well as the Cultural Heritage Department of Sarab County. To evaluate the geotourism potential of the northern slopes of Bozqush, a questionnaire was designed to weight the criteria based on the MACBETH model. Expert opinions were solicited from 15 faculty members of the Department of Geomorphology and Geology at Tabriz University, as well as specialists from the Water Department of Sarab County. In this questionnaire, participants were asked to provide scores for pairwise comparisons of the criteria and their importance on a scale from 0 to 6. In the third phase, hot springs were prioritized using a questionnaire based on the Simple Additive Weighting (SAW) model. In this questionnaire, expert opinions were gathered from 15 specialists from the Water Department of Sarab County, the Cultural Heritage Department of Sarab County, and the Regional Water Authority of East Azerbaijan Province. They were requested to rate the proximity of the criteria to the reality of the hot springs using a Likert scale ranging from 1 to 5. Conclusion: Geotourism, as a critical option in the tourism industry, aims to achieve objectives such as environmental sustainability, increased economic profitability, reduction of detrimental impacts resulting from the exploitation of geological and geomorphological resources, and minimal changes to natural ecosystems. The northern slopes of the Bozqush Mountain range in East Azerbaijan Province possess significant potential for geotourism development due to their unique characteristics, facilitating activities such as mountaineering, slope climbing, skiing, and hydrotherapy. This research aims to evaluate the geotourism capabilities of the northern slopes of the Bozqush Mountain range in Sarab County. To prepare maps of geotourism potential zones, 15 key criteria were initially identified, and corresponding maps for each criterion were developed using ARC GIS software. Subsequently, using the MACBETH model and considering the established priorities for geotourism development in the region, each criterion was weighted. The findings revealed that the elevations of Bozqush were identified as the most significant influencing criterion in this study. The northern slopes of the Bozqush Mountain range, due to their diverse and challenging routes for mountaineering and slope climbing, can attract tourists. Additionally, the potential for snow accumulation in winter provides suitable opportunities for the development of winter sports. This region, with its natural hot springs known for their therapeutic properties, can also be recognized as a health tourism destination. To optimize the utilization of the region's geotourism capabilities, it is essential to develop infrastructure, including the establishment and improvement of transportation, accommodations, and amenities for tourists. Ensuring the safety of mountaineers and slope climbers through the installation of signposts, creation of designated paths, and hiring of local guides is crucial. Furthermore, educating and promoting sustainable tourism to tourists and local communities to enhance awareness regarding the importance of natural resource conservation is necessary. Providing facilities and services for winter sports, such as skiing and snowboarding, including the establishment of ski slopes and provision of equipment, is also vital. The results of the zoning analyses indicate that 33.21% of the area is classified as highly suitable, 58.37% as suitable, 7.41% as relatively suitable, 1.01% as relatively unsuitable, and 0.006% as unsuitable. Activities such as mountaineering and slope climbing, as well as hydrotherapy, are prioritized over other activities. These findings emphasize the need to identify zones for potential geotourism locations adjacent to the hot springs of Asbfarushan, Allah Haq, Ardaha, Shalghon, Jaldeh Bakhan, and Narmiq. Given the high potential of the hot springs in enhancing the geotourism capabilities of the region, prioritization of these springs was conducted using the Simple Additive Weighting (SAW) model. The prioritization results indicate that the hot springs of Asbfarushan, Allah Haq, Ardaha, Shalghon, and Jaldeh Bakhan, along with Narmiq, are ranked highest in priority. This research demonstrates that the northern slopes of the Bozqush Mountain range possess significant potential for the development of geotourism activities. Planning for sustainable tourism development, particularly in mountaineering, slope climbing, and winter tourism, can substantially contribute to the conservation of the region's natural and geological resources while enhancing public awareness in this field. https://www.geomorphologyjournal.ir/article_234416.html Introduction Landslides are important natural hazards in mountainous areas that cause extensive human, financial and environmental losses by suddenly changing the land surface. This phenomenon destroys vegetation, agricultural lands and infrastructure and increases secondary destruction by intensifying erosion. Between 1995 and 2014, more than 3,876 landslides occurred in the world, resulting in thousands of injuries and more than 163,000 deaths. Identifying prone areas and zoning landslide susceptibility are effective solutions in reducing damage and managing the risk of this phenomenon. In this context, statistical methods and machine learning algorithms such as random forest and support vector machine can predict the occurrence of landslides with high accuracy. The aim of the present study is to zone landslide risk in the Samian watershed using machine learning algorithms and compare their performance in order to provide an accurate and reliable model for planning and reducing potential damages. Methodology This study aimed to map landslide risk in the Samian watershed using machine learning algorithms in the Google Earth Engine environment. First, topographic data (elevation, slope, direction, and curvature), geology (rock type), distance from river, road, and fault, and climatic and environmental variables (rainfall, soil moisture, NDVI, and land use) were collected and processed in a GIS environment. Field data included 55 landslide points and 55 non-slip points that were used to train and test the models. The layers were standardized using the fuzzification method to numerically represent the relative impact of each factor on slope instability. Three machine learning algorithms, including random forest (RF), support vector machine (SVM), and nearest neighbor (KNN), were implemented to generate a landslide probability map. Finally, the output of the models was converted into a hazard zoning map and categorized into five classes from very low to very high. The accuracy of the models was evaluated with AUC and comparison with real landslide data to determine the most accurate algorithm for the Samian basin. Results and Discussion The study of the distribution map of landslide and non-slip points in the Samian watershed showed that out of a total of 110 field-collected points, half were related to real landslides and were mainly concentrated in the western half of the basin, especially the slopes of the Sabalan heights and Nir county. This spatial distribution confirms the direct role of slope and high altitude in the occurrence of landslides. The analysis of the significance of the variables also showed that the slope factor with a share of 16.10% has the greatest impact on the occurrence of landslides, followed by altitude and rock type, which indicates the importance of morphometric features in controlling slope stability. At a spatial scale, the steep and high areas of the northwest of the basin (Sabalan heights) with slopes between 15 and 68 degrees and the southeastern part of the basin (Hire) have the highest potential for landslides due to the concentration of faults, high soil moisture, and abundant rainfall. In the southern part of the basin, especially in the Kuzeh Topraghi area, the northern slopes are more humid due to being in the shade of the sun, and long periods of frost and repeated cycles of freezing and thawing reduce the cohesion of the materials and increase instability. In the southwest of the basin (Nir) and along the Balikhlochay and Imamchay rivers, human activities such as road excavation and land use change have weakened the natural balance of the slopes and increased the risk of instability. In the northeast of the basin (Namin), despite dense vegetation, steep slopes and soil saturation during the rainy season have caused surface landslides. In contrast, the central areas of the basin with a tendency to the east (from Ardabil city to Abibiglou) are the least risky areas, which have higher stability due to their gentle slope, lower altitude, and less precipitation, and are in the low to very low risk class in all models. Conclusion A comparison of the performance of three machine learning algorithms (RF, SVM, and KNN) showed that all three are capable of predicting landslide-prone areas, but they have differences in sensitivity and accuracy. The accuracy index (AUC) for SVM, RF, and KNN was calculated to be 0.906, 0.864, and 0.848, respectively, indicating that SVM is more accurate in distinguishing landslide-prone and stable areas. Zoning results also showed that the total area of high and very high risk areas for RF, SVM, and KNN was 2222.1, 1680.79, and 1890.39 square kilometers, respectively, which is equivalent to 53, 40, and 45 percent of the total area. These values indicate that the RF algorithm takes a more conservative view and identifies more areas as high-risk, while the SVM provides a more balanced approach but with higher accuracy. https://www.geomorphologyjournal.ir/article_234441.html در میان پدیده‌های طبیعی مخرب، فرونشست زمین در کنار زلزله، سیل و لغزش، از جمله ویرانگرترین مخاطرات ژئومورفیک ناشی از فرآیندهای زمین‌ساخت و فعالیت‌های انسانی به شمار می‌رود عوامل اصلی وقوع این پدیده عبارتند از: زلزله، سیل، بهره‌برداری بیش از حد از آب‌های زیرزمینی و کاهش آن، فعالیت‌های معدنی، ساخت تونل و غیره در میان همه این عوامل ممکن، بهره‌برداری از آب‌های زیرزمینی مهمترین مسئله در این زمینه است کاهش سطح آب‌های زیرزمینی بصورت یک فرایند کند و تدریجی عامل اصلی فرونشست زمین است برداشت بیش از حد از آبخوان ها به ویژه در مناطق کشاورزی و مسکونی، این مناطق را فرونشست زمین یکی از مخاطرات ژئومورفیک محسوب میشود که دارای حرکتی کند و بطئی بوده و آثار مخرب خود را در بلندمدت نشان می دهداز اثرات مخرب این مخاطره که مستقیم برزمین آسیب می زند میتوان به ایجاد ترک در ساختمان ها ، جاده هاو پل ها اسیب به زیر ساخت های حیاتی مانند خطوط لوله شبکه فاضلاب و تغییر در شبکه الگوهای آب شناسی منطقه اشاره و آسیب های غیر مستقیم آن عبارت اند از افزایش هزینه های نگهداری زیر ساخت ها، کاهش ارزش زمین واملاک، مهاجرت جمعیت از مناطق اسیب دیده، اختلال در فعالیت های اقتصادی (کندردهنوی،1403)بنابراین بنابراین فرونشست زمین در مقیاس فضایی و زمانی باعث چنین خسارت هایی در جهان میشود. این پدیده، که در نقاط مختلف جهان و به‌ویژه در ایران به وفور مشاهده می‌شود (جلینی و همکاران، 1396)، به یک بحران ملی تبدیل شده است. نرخ فرونشست در ایران به طور نگران‌کننده‌ای 34 برابر میانگین جهانی کشورهای توسعه‌یافته برآورد می‌شود. در حال حاضر، بیش از 300 دشت کشور درگیر این پدیده هستند که در برخی مناطق، همچون دشت کبوترآهنگ همدان، ورامین، نظرآباد، تهران، مشهد، نیشابور و دشت‌های استان‌های کرمان، اصفهان و قزوین، به مرحله بحرانی و تشکیل چاله‌های وسیع رسیده است (احمدی، 1401). در مناطق خشک و نیمه‌خشک، به ویژه در ایران، اصلی‌ترین عامل تشدید فرونشست، برداشت بی‌رویه از منابع آب زیرزمینی و نابودی و تدریجی آبخوان ها است (ریتب ابوتالیب،2020) و(فصاحیه وهمکاران،2025). کاهش سطح آب زیرزمینی منجر به کاهش فشار منفذی در لایه‌های ریزدانه آبرفتی، تحکیم و فشردگی غیرقابل برگشت این لایه‌ها، و در نتیجه، نشست دائمی سطح زمین می‌شود(مقیمی و همکاران،1400).به مستعدترین مناطق برای وقوع فرونشست زمین تبدیل کرده است. روش کار در این پژوهش، هدف پهنه بندی فرونشست با استفاده از شاخص های تاثیر گذار بر رخداد فرونشست و مدل حداکثر آنتروپی (مکسنت) در استان اصفهان است. این پژوهش بر سه مرحله اصلی استوار است (شکل 2). 1) شناسایی و آماده سازی داده‌ها: داده‌های مورد نیاز برای این پژوهش شامل نقاط وقوع فرونشست و شاخص‌های محیطی تأثیرگذار بر آن است. • الف) شناسایی موقعیت فرونشست‌ها: : موقعیت فرونشست‌ها از طریق بررسی‌های میدانی و استفاده از تصاویر ماهواره‌ای سنتینل 1 و گوگل ارث ثبت گردید. این نقاط به عنوان لایه رقومی فرونشست‌ها در محیط نرم‌افزار GIS تهیه شدند. ب) تهیه لایه‌های اطلاعاتی شاخص‌های تاثیرگذار پس از تهیه نقشه‌های شاخص‌های تأثیرگذار، نقاط فرونشست در سرتاسر استان رقومی شده و به عنوان لایه‌های ورودی به مدل MaxEnt استفاده گردید. 3)اعتبار سنجی مدل: برای ارزیابی و اعتبارسنجی مدل نهایی، از دو روش کلیدی استفاده شد: •الف) شاخص سطح زیر منحنی (AUC) برای منحنی (ROC): این شاخص برای ارزیابی دقت پیش‌بینی مدل به کار رفت. آزمون (Jackknife): این آزمون برای تعیین میزان تأثیر و اهمیت هر یک از شاخص‌ها به عنوان متغیرهای ورودی در مدل MaxEnt استفاده شد. نتیجه گیری نتایج حاصل از این مطالعه نشان داد که مدل MaxEnt با استفاده از 14 شاخص محیطی، توانایی بالایی در شناسایی مناطق مستعد فرونشست دارد. شاخص‌های شبکه کانال %41،ارتفاع %11، کاربری اراضی%10رطوبت خاک%9و بافت خاک%8.5 به ترتیب بیشترین تأثیر را در وقوع فرونشست در استان اصفهان ایفا می‌کنند. نقشه خطر فرونشست ، استان را به چهار طبقه خطر شامل کم خطر، متوسط،زیاد وبسیار زیادتقسیم کرده است. مناطق کم خطرمناطق با نرخ فرونشست ناچیزهستند که قسمت زیادی از استان را شامل میشود و مناطق که پرخطر هستند نرخ فرونشست بسیار بالا دارند.لازم به ذکر است که مناطق با خطر زیاد وبسیار زیاد منطبق هستند به آبخوان های اصلی استان از جمله ابخوان کوهپایه -سگزی ، برخوار، نجف آباد، بو ئین- میاندشت بحث اعتبارسنجی مدل با استفاده از منحنی ROC و مقدار AUC، دقت بالای مدل را تأیید کرد، به طوری که مقدار AUC برای نمونه تعلیمی 0.819 و برای نمونه آموزشی 0.807 بود. این مقادیر، که در محدوده "خیلی خوب" قرار می‌گیرند ، نشان‌دهنده قابلیت بالای مدل MaxEnt در پیش‌بینی و پهنه‌بندی مناطق مستعد فرونشست هستند. این نتایج حاکی از آن است که مدل توسعه‌یافته می‌تواند به عنوان یک ابزار قابل اعتماد برای ارزیابی ریسک فرونشست و برنامه‌ریزی‌های مدیریت زمین در استان اصفهان مورد استفاده قرار گیرد https://www.geomorphologyjournal.ir/article_234599.html Rivers are fundamental components of natural ecosystems, playing a vital role in maintaining environmental balance, recharging groundwater resources, supporting biodiversity, and fulfilling a wide range of human needs. They serve as dynamic systems that connect terrestrial and aquatic environments, regulate hydrological cycles, and provide essential services such as water supply, flood control, and habitat for diverse species. However, in recent decades, the rapid expansion of urbanization, uncontrolled development of residential areas, and unsustainable exploitation of natural resources have led to significant changes in the structure and function of river systems worldwide.The Alvand River, a prominent watercourse in western Iran, originates from the Zagros Mountains and flows through Sarpol-e Zahab County. In recent years, this river has undergone considerable transformations due to both anthropogenic and natural pressures. Key threats include encroachment on the riverbed and floodplain, land-use changes, excessive extraction of sand and gravel, and the construction of engineering structures along the river channel. These activities have disrupted the river’s natural morphology, reduced its ecological resilience, and imposed serious damage on its hydrogeomorphological integrity. This study aims to assess the hydrogeomorphological quality of the Alvand River within the urban stretch of Sarpol-e Zahab, specifically from the point where the river enters the city to the village of Qareh-Bolagh. To achieve this, the Hydrogeomorphological Quality Index (IHG) was employed—a multi-criteria assessment tool designed to evaluate the ecological and physical condition of river systems. The main channel was divided into seven distinct segments, and the IHG index was calculated for each segment using field observations, satellite imagery, and GIS-based spatial analysis. The IHG index evaluates nine parameters grouped into three main categories: (1) river functionality (including flow continuity, interaction with groundwater, and flow dynamics), (2) channel morphology (including cross-sectional shape, meandering patterns, and bed diversity), and (3) riparian vegetation (including density, diversity, and connectivity of plant cover). Each parameter is scored from 1 to 10, with higher scores indicating more natural conditions and better ecological performance. The total score for each segment reflects its overall hydrogeomorphological quality and provides a basis for comparison across different parts of the river. The results revealed that segments 1, 6, and 7 exhibit relatively favorable conditions. These areas are located outside the urban core and have experienced limited human interference. Natural riparian vegetation is largely intact, meandering patterns are preserved, and hydrological connectivity remains functional. In contrast, segments 3 and 4—located within the urban center—show very poor quality due to extensive human interventions. These include channelization, construction of engineering structures within the riverbed, disruption of flow continuity, and conversion of the floodplain into residential and agricultural land uses. Additionally, uncontrolled extraction of riverbed materials such as sand and gravel has led to bed degradation, loss of habitat diversity, and reduced ecological stability. Segments 2 and 5 fall into an intermediate category. Situated on the urban fringe, these segments show signs of disturbance but still retain some natural features. The river in these areas is semi-stable, and without proper management, they risk degradation similar to segments 3 and 4. Therefore, these transitional zones are critical for conservation planning and can serve as priority areas for restoration and protection efforts. Their current condition offers an opportunity for proactive intervention before irreversible damage occurs. From a practical standpoint, the findings of this study provide a valuable foundation for decision-making in water resource management, river ecosystem conservation, and sustainable urban development. The IHG index, with its multi-dimensional approach, enables comparative analysis across different river segments and can be adapted for use in similar studies on other rivers in Iran and beyond. Moreover, the integration of GIS tools enhances the precision and interpretability of spatial data, supporting more informed environmental planning and policy-making. To improve the condition of the Alvand River within Sarpol-e Zahab’s urban stretch, the following measures are recommended: (1) legally define and enforce the river’s buffer zone to prevent construction within the floodplain, (2) regulate and reduce in-stream material extraction, replacing it with alternative sources outside the river corridor, (3) restore natural riparian vegetation and establish protective green belts, (4) redesign engineering structures to minimize disruption to natural flow patterns, and (5) engage and educate local communities in river stewardship and water conservation. In conclusion, this study demonstrates that the hydrogeomorphological quality of rivers is highly influenced by human activities. Without targeted management and conservation interventions, degradation will likely continue, leading to long-term ecological and social consequences. The Alvand River serves as a case study illustrating the challenges of balancing urban development with the preservation of natural resources. Therefore, adopting scientific, participatory, and data-driven approaches is essential for maintaining the ecological integrity of river systems and ensuring their long-term sustainability. https://www.geomorphologyjournal.ir/article_234800.html Introduction The last and shortest geological period is the Quaternary. One of the most important features of this period is irregular climate changes. The evidences and legacies of this unique period began and continues about 2.5 million years ago, and the last part of this period that has continued until now is the Holocene period.Today, Iran's playas are in arid conditions, but the geomorphological and sedimentological evidences of these areas have indicated significant changes in their climatic and natural conditions in the Quaternary. In this period glacial and interglacial condition in high latitudes and high mountains of mid-latitudes in areas far from the lands covered with ice, the level of lakes rose and there were lakes in the closed basins of arid or semi-arid areas today as well. Many studies conducted on the Holocene and Quaternary climate in Iran have pointed to dry and cold climatic conditions in the glacial period and relatively humid and warm in the interglacial period. Some authors have also proposed the event (rainy period) and assumed that the amount of precipitation is greater during the glacial period. Some scientists also attach importance to the increase in rainfall during that period and consider the changes in these areas to be caused by the cooling of the air and decrease in evaporation, and instead of rainy periods, they use the term cold periods. The simultaneity of rainy or cold periods of low latitudes with glacial or interglacial periods of high latitudes in different regions is one of the topics that is of interest to researchers. Methodology This research was carried out in Masileh,Depression which covers of Qom, Isfahan and Semnan provinces.The method of this research is the examination of geographical data and information, field studies, laboratory and remote sensing.The purpose of this research is to determine the extent of the Pluvial Lake of hill Mesileh including (Hoz-e-Sultan Basin, Mareh Basin and Salt Lake) based on geomorphological evidence (lacustrine terrace) in the Quaternary. In the field studies, the presence of a lake terrace in a specific area, the height of the levels was determined and samples were taken from their surface for laboratory analysis.This depression is located between the southern elevations of Middle Alborz in the north, the volcanic elevations in the west, the heights of Tafarsh and Kashan in the south and southwest, and the desert plain in the east of a large triangular area. Inside this triangle, there are basins and holes, which includes the salt lake, the Hoz-e-Sultan Basin, and the Marah basin. The maximum height of this basin is 3588 meters (Karkas peak) in the southern heights and the minimum is 800 meters in the salt lake. Results and discussion The studied watershed consists of 9 smaller sub-basins with an area of 18639 square kilometers. Hoz-e-Sultan playa with an area of 69.60 square kilometers, Hoz-e- Mereh with an area of 27.90 square kilometers and salt lake with an area of 1865 square kilometers are located in this basin. The exploratory terrace in Mesila basin at an altitude of 805 meters above sea level shows the extent of the paleo lake, which has an area of 6190 square kilometers, which includes each salt lake, Hoz-e- Mareh and Hoz-e- Sultan. This range shows that in the paleo climatic periods, when the dominance of rainy conditions was accompanied by a decrease in evaporation, these three basins were shared by a single lake. Based on these results, based on the height of its bottom, 802 meters above the sea level, the lake had 3 meters of water at the time of its expansion. Also, according to the height of the playa floor of Hoz-e- Sultan, which is 799 meters above sea level, this playa had 6 meters of water as a result of the extent of the said lake, and the salt lake with a floor height of 786 meters above sea level had 19 meters of water as a result of the extent of the said lake. The results of grain measurement and calcimetry analyzes of the sediments collected from the studied area have shown a peaceful sedimentation environment in the past and are proof of an ancient lake environment in this area. Conclusion Many studies conducted on the Holocene and Quaternary climate in Iran have pointed to dry and cold conditions in the glacial period and relatively humid and warm in the interglacial period. Some authors have also proposed the event (rainy period) and assumed that the amount of precipitation was greater during the glacial period. Some scientists also attach some importance to the increase in rainfall in that period and consider the changes in these areas to be caused by the cooling of the air and decrease in evaporation, and instead of rainy periods, they use the term cold periods. The simultaneity of rainy or cold periods of low latitudes with glacial or interglacial periods of high latitudes in different regions is one of the topics that is of interest to researchers. Mostofi and Feri's studies show that first the water enters the Mareh reservoir, and after it is filled, it enters the Hoz-e-Sultan reservoir from the last two reservoirs, and when the water rises a few meters in the Hoz-e-Sultan reservoir, it returns to the Mareh reservoir. The overflow of these two basins is discharged into the salt lake (Mostofi and Feri, 1959). These studies also confirm the possibility of the existence of this integrated lake, as well as Krinsley's studies also indicate the existence of Pluvial lakes in the central Iran regions in the past, which have led to the current situation and the loss of the lakes due to climate change and has left playas in central Iran. https://www.geomorphologyjournal.ir/article_234948.html Introduction Currently, using discharge-Eschle curves and measuring discharge in natural rivers is generally difficult and error-prone. Therefore, the use of new models plays an effective role in reducing the time and cost associated with hydrometry (Ahmad et al. 2021). Due to the importance of this phenomenon and because the use of physical models requires a large space, high cost, and long time to conduct experiments, many river engineering problems are investigated with mathematical models (Azizi et al., 2019). For this reason, to better understand these phenomena, numerical and computational fluid dynamics models should be used to simulate flow, which are more accurate than other simulation methods (Ildoromi et al. 2020). Bagheri (2023) evaluated the methods for calculating the discharge-Eschle curve based on bedform resistance relations at the Ablo Nekarud hydrometric station in Mazandaran and showed that the Einstein-Barbarossa method has the lowest absolute error compared to other methods. Mohammadi et al. (2023) showed in estimating the discharge-echel curve in natural rivers with unsteady flow that with a new method based on constant velocity meters, the discharge-echel curve of unsteady flow and depth and discharge hydrographs can be tracked.Kim et al. (2023) evaluated the sedimentation and erosion of riverbanks and channels in the Mekong Delta using the MK-BEHI index and showed that differences in bank stress and riverbank structures cause changes in the erosion rate and riverbank load.Boustani et al. (2023) studied the distribution of bed shear stress using numerical simulation and compared the results of Ansys Fluent and Flow-3D, showing that the numerical results of the Fluent model were closer to the experimental data compared to the Flow 3D model. Methodology The Yalfan River is located in the Ekbatan Dam watershed in the northern part of Alvand, 10 kilometers southeast of Hamedan city. In this study, open channel flow in a one-dimensional stable has been investigated.manner in channels with conventional rectangular and trapezoidal cross-sections in the Yalfan River of Ekbatan Dam, Hamedan, Given that the shape of the sides of the channel cross-section has an important effect on the discharge-Ecshle relationships, and the distribution of runoff in channels with different cross-section shapes and surfaces has an important effect on causing erosion and instability of the riverbed.Therefore, numerical values of runoff advance in rectangular and trapezoidal sections were calculated at different times and compared with experimental results for different turbulence models and percentage of error of each turbulence model was calculated and compared with each other.In this research, the second-order discretization method of the Fluent model was used to separate the load and the effect of rectangular and trapezoidal sections to investigate the propagation of runoff flow in scour and edge erosion, and the Reynolds stress numbers were used to determine the movement threshold and to analyze the movement pattern and settling of sediment particles in different flow tubes in a laboratory glass channel, using Fluent software. Results and Discussion The results showed that in a rectangular cross section, runoff distribution and pressure are distributed almost equally across the channel surface, and the flow rates do not show significant changes.In a trapezoidal channel with a closed cross-section, discharge - Eschle's measurements showed that the spread of runoff with higher velocity and pressure at the bottom of the channel causes increased erosion at the bottom.The results of the study in a trapezoidal channel with an open cross-section, the values of the discharge - Eschle and the histograms of pressure and diffusion velocity, showed that the pressure and diffusion velocity are higher on the sides of the channel and the erosion rate is higher on the sides.The results of the assessment of the discharge-Ecshle relationships showed that the more closed the trapezoidal channel opening is, the higher the pressure at the bottom and the lower the pressure at the channel wall, and as a result, the greater the erosion rate at the bed.Conversely, the more the trapezoid opening is opened, the greater the runoff pressure on the sides of the bed and, consequently, the greater the erosion rate.The results showed that due to the change in the relationship between the discharge-Ecshle and the flow velocity and pressure at different sections, the rate of erosion and sedimentation changes drastically.The study of runoff distribution showed that the channel shape has an important effect on creating riverbed instability and causes meandering and shifting of the river course over time, which should be considered in river engineering works. Conclusion Comparison of the output results of the Fluent hydraulic model shows that this model has good ability to estimate changes in river cross sections.The results show that changes in the channel sections of the Yalfan River along the longitudinal profile of the river cause changes in bank erosion and bank erosion.So that at the beginning of the flow with a trapezoidal cross-section, due to changes in flow propagation speed and pressure, erosion and foaming are greater than at the sides.While in rectangular sections in the middle and end of the stream, lateral erosion and bed sedimentation are observed, which must be carefully considered in the location and design of appropriate river engineering control and protection structures.The results showed that modeling the runoff propagation phenomenon in the Fluent environment has acceptable accuracy, but generating the geometry file and solution field network in Gambit software for study using topographic maps requires a lot of time.Therefore, it is recommended that other software be used to create geometry and modeling for modeling in large watersheds, and that the Fluent model be used for modeling in small watersheds that require high accuracy. Keywords: Erosion, Cross Sections, Model, Flow Velocity, Fluent https://www.geomorphologyjournal.ir/article_235561.html Land subsidence is increasingly recognized as one of the most significant geomorphological hazards in arid and semi-arid regions worldwide, primarily driven by the compaction of subsurface layers resulting from excessive groundwater extraction and the overexploitation of aquifers. This phenomenon presents substantial challenges to sustainable water resource management and environmental protection, as it leads to deformation of the ground surface, structural damage to infrastructure, reduction in aquifer storage capacity, disruption of natural drainage systems, and threats to ecological stability. Understanding the mechanisms, spatial distribution, and temporal trends of subsidence is essential for developing effective mitigation strategies and ensuring long-term water security in vulnerable regions. The present study investigates land subsidence in the Mahidasht plain, with a particular focus on the role of declining groundwater levels as a primary driver of surface deformation. To achieve this, piezometric data collected from observation wells over a six-year period (2017–2022) were integrated with high-resolution Sentinel-1 radar imagery and the Interferometric Synthetic Aperture Radar (InSAR) technique. This combination enabled a comprehensive spatiotemporal analysis of subsidence patterns and allowed for precise quantification of both the magnitude and rate of surface settlement across the plain. Results indicate a substantial decrease in groundwater levels, with the piezometric surface dropping by approximately seven meters during the study period. The InSAR analysis revealed annual subsidence rates ranging from 3 to 14 centimeters, with the highest rates observed in the central and northwestern areas of the plain. Spatial correlation analysis further demonstrated a strong, direct relationship between groundwater depletion and the intensity of land subsidence, confirming that anthropogenic groundwater withdrawal is the dominant factor driving surface deformation in the region. Further investigations suggest that geological and hydrogeological conditions, such as sediment composition and the thickness of unconsolidated alluvial layers, modulate the severity and spatial variability of subsidence. Regions characterized by loose, unconsolidated sediments exhibited higher susceptibility to settlement, whereas areas underlain by more consolidated deposits or bedrock experienced comparatively lower rates of subsidence. The observed patterns indicate that areas subject to intensive groundwater extraction are particularly vulnerable, and without proper management interventions, continued subsidence could exacerbate structural and environmental risks. Beyond direct impacts on infrastructure, subsidence also has significant environmental and socio-economic consequences, including disruption of natural drainage patterns, increased flooding risk, soil degradation, decreased agricultural productivity, and long-term ecological imbalance. The study highlights the effectiveness of integrating remote sensing technologies, such as InSAR, with ground-based hydrogeological measurements for monitoring land deformation over time. This integrated approach not only provides a detailed understanding of the magnitude and distribution of subsidence but also offers a valuable tool for identifying high-risk zones, evaluating temporal trends, and informing decision-making processes related to urban development, infrastructure planning, and water resource management. Continuous monitoring using advanced remote sensing techniques is critical for early detection of emerging subsidence hotspots and for the implementation of timely mitigation strategies. The findings emphasize the necessity of adopting sustainable groundwater management practices to reduce subsidence rates and mitigate associated risks. Potential interventions include controlled and regulated groundwater extraction, artificial recharge of aquifers, soil compaction management, land-use planning, and the establishment of protective policies for critical infrastructure. In addition, the development of early-warning systems, risk maps, and adaptive management frameworks can facilitate proactive responses and prioritization of interventions in areas most affected by subsidence. The results underscore that a multidisciplinary approach combining hydrogeology, remote sensing, geotechnical analysis, and environmental management is essential for addressing the complex challenges posed by land subsidence in semi-arid regions. In conclusion, land subsidence in the Mahidasht plain is predominantly driven by anthropogenic activities, particularly excessive groundwater extraction, while geological characteristics influence the severity and spatial distribution of the phenomenon. The integration of InSAR with piezometric measurements provides a robust methodology for detecting, quantifying, and mapping subsidence patterns, offering critical insights for policymakers, water resource managers, engineers, and environmental planners. The study reinforces the importance of sustainable groundwater management, continuous monitoring, and the application of advanced remote sensing technologies to mitigate subsidence risks. Furthermore, the implications of this research extend beyond the Mahidasht plain, offering valuable lessons for other semi-arid regions around the world facing similar challenges of water scarcity, intensive groundwater use, and land subsidence. By understanding the mechanisms, drivers, and consequences of subsidence, decision-makers can implement more effective, evidence-based strategies to protect infrastructure, maintain agricultural productivity, preserve ecological systems, and enhance the resilience of human and natural systems to ongoing environmental change. Ultimately, this study demonstrates that proactive, integrated management of groundwater resources, combined with cutting-edge monitoring technologies, is critical for reducing land subsidence, safeguarding environmental and socio-economic assets, and promoting sustainable development in arid and semi-arid regions globally. The findings contribute to a deeper scientific understanding of subsidence processes, provide a foundation for policy development, and emphasize the need for coordinated efforts between scientists, planners, and decision-makers to ensure the long-term sustainability and resilience of vulnerable landscapes. https://www.geomorphologyjournal.ir/article_236046.html Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances. This region, due to its unique geomorphological characteristics, has not previously been independently subjected to fractal analysis. To this end, during the winter of 2024, 403 surface microforms were imaged, of which 208 with distinct boundaries were selected, and their area and perimeter were precisely measured. The fractal dimension (DAP) for each form was calculated and analyzed using the logarithmic relationship between perimeter and area. The results showed that DAP values range from 1.60 to 1.90, indicating a high level of geometric turbulence and structural complexity in the region. The mean DAP value of 1.75 and a high correlation coefDeserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.Deserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities. Among these, the Eshtehard Plain, identified by the Ministry of Energy's reports as one of the critically restricted plains due to its groundwater resource conditions, is highly sensitive to active geomorphological processes and surface changes. This study aims to analyze the geometric patterns and degree of turbulence in clay microforms of the Eshtehard Plain using the perimeter-area fractal model as a tool for simulating unstable surface disturbances.eserts, playa lakes, and similar landforms in many arid and semi-arid regions have experienced disturbance and turbulence due to human activities.mong these, the Eshtehard Plain, identified by theficient (above 0.96) confirm the model's validity and the data's alignment with the region's unstable conditions. https://www.geomorphologyjournal.ir/article_238029.html Introduction: Sand dunes, especially barchan dunes, represent some of the most visually striking and dynamically responsive landforms in Earth’s arid and semi-arid landscapes. Characterized by their crescentic shape, sharp horns, and steep slip faces, barchan dunes form under conditions of limited sand supply and unidirectional wind regimes. Their mobility and morphological plasticity make them sensitive indicators of environmental change, serving as natural recorders of wind patterns, sediment availability, and surface roughness. In regions such as the Kalateh Mazinan area in northeastern Iran — situated within the expansive arid belt of Razavi Khorasan Province — barchan dunes are not merely passive features but active agents of landscape transformation. Monitoring their behavior is critical not only for advancing fundamental geomorphological knowledge but also for practical applications including desertification control, infrastructure planning, agricultural zoning, and ecological conservation. Despite their significance, comprehensive, high-resolution spatiotemporal analyses of barchan dune dynamics in Iran — and particularly in the Kalateh Mazinan region — remain scarce. Most previous studies have relied on coarse-resolution satellite imagery or infrequent field surveys, which often fail to capture the subtle yet critical micro-scale changes in dune morphology and position. This study addresses this gap by employing cutting-edge unmanned aerial vehicle (UAV) photogrammetry to generate precise, time-series digital elevation models (DEMs) and orthophotos, enabling detailed quantification of dune migration and structural evolution over a 29-month interval (May 2022 to October 2024). Materials and Methods: The methodological framework of this research integrates advanced remote sensing techniques with classical geomorphometric analysis. Two high-resolution aerial surveys were conducted using a DJI Phantom 4 Pro drone, capturing overlapping nadir and oblique imagery under optimal lighting and wind conditions to minimize motion blur and shadowing. The imagery was processed using industry-standard photogrammetric software — Agisoft Metashape and Pix4Dmapper — to reconstruct 3D point clouds, orthomosaics, and DEMs with centimeter-level accuracy. Five morphologically distinct barchan dunes were selected as representative samples based on their spatial distribution, isolation from neighboring features, and clarity of form. For each dune, a suite of 12 quantitative parameters was extracted: planimetric area, perimeter, mean and maximum elevation, volume, windward and leeward slope angles, lengths of both horns (arms), inter-arm width, and crestline orientation. Crucially, displacement was measured by tracking three fiducial points — the tips of the windward and leeward arms, and the apex of the crest — across the two epochs. The arithmetic mean of these three displacement vectors was taken as the representative migration distance for each dune. Results: Results indicate a wide spectrum of dune mobility and morphological response. Total displacement ranged from 9.47 meters (Dune 5) to 27.76 meters (Dune 4), yielding a regional average migration rate of 20.57 meters over the study period — equivalent to approximately 8.5 meters per year. Dunes 1, 2, and 3 exhibited moderate volumetric growth (ranging from +3% to +7%) and elongation along the dominant northwest–southeast axis, suggesting sediment accumulation and forward propagation under consistent wind forcing. Dune 4, the most mobile feature, displayed morphological signs of coalescence with a neighboring dune, including flattening of the inter-dune depression and merging of slip faces — a phenomenon indicative of dune field maturation and potential transition toward transverse or barchanoid ridge forms. In contrast, Dune 5 remained relatively static, with minimal displacement and unchanged volume, possibly due to local topographic sheltering, higher soil moisture retention, or the presence of sparse vegetation anchoring the surface sediment. Correlation analysis revealed that displacement rate was positively associated with initial dune volume and windward arm length in three of the five dunes, aligning with theoretical models that link dune size to mobility under constant wind stress. However, Dune 5’s anomalous behavior — large size yet low mobility — underscores the influence of localized environmental controls, such as microtopography, sediment cohesion, or anthropogenic barriers. Slope asymmetry (steeper leeward faces) was consistent across all dunes and aligned with the regional wind regime, further validating the unidirectionality of aeolian transport in the study area. Discussion: The discussion contextualizes these findings within broader aeolian geomorphology literature. The observed migration rates fall within the expected range for mid-latitude desert dunes under moderate wind regimes (cf. Baddock et al., 2011; Zhang et al., 2020). The detection of dune merging processes adds empirical support to conceptual models of dune field evolution, wherein isolated barchans progressively interact, coalesce, and reorganize into more complex morphologies. Methodologically, this study demonstrates that UAV-based photogrammetry offers unparalleled spatial and temporal resolution compared to traditional techniques, enabling detection of sub-meter-scale changes and facilitating process-based interpretation rather than mere descriptive mapping. Conclusion: In conclusion, this research provides a robust, replicable framework for monitoring barchan dune dynamics using low-cost, high-efficiency UAV platforms. The findings confirm the dominant control of regional wind patterns on dune form and migration in Kalateh Mazinan, while also highlighting the modulating role of local factors. These insights are vital for predictive modeling of desert landscape evolution and for designing targeted interventions to mitigate dune encroachment on human settlements and agricultural lands. Future research should expand the temporal scope of monitoring, integrate in-situ meteorological data (particularly wind speed and direction), and explore seasonal variations in dune activity to build more comprehensive predictive models under scenarios of climatic variability and land-use change. https://www.geomorphologyjournal.ir/article_239173.html Introduction The slopes overlooking the metropolitan area of Tabriz are at high risk of landslides due to a combination of natural factors, including the presence of weak formations such as marl, steep slopes, and sufficient rainfall, as well as human factors such as urban development and road construction on unstable slopes. This phenomenon can lead to disastrous consequences, including casualties, extensive financial losses, and damage to infrastructure. Therefore, the main objective of this research is to prepare a landslide susceptibility zoning map for the slopes overlooking the metropolitan area of Tabriz using the MEREC (Method based on the Removal Effects of Criteria) multi-criteria decision-making method within a Geographic Information System (GIS) environment. This study aims to identify and prioritize areas with high potential for landslide occurrence by considering key effective criteria, including geological formations (especially weak marls), slope, rainfall, distance from faults and rivers, as well as human development indicators such as distance from roads and land use. The results of this research provide essential and necessary information for risk management, sustainable urban development planning, and the implementation of landslide mitigation measures in this sensitive region. Methodology The study area of the present research is the slopes overlooking the metropolis of Tabriz. The study area is located at latitudes between 38° 02΄ and 38° 10΄ North, and at longitudes between 46° 11΄ and 46° 23΄ East. The present study was conducted with the aim of preparing a landslide susceptibility zonation map for the slopes overlooking the metropolitan city of Tabriz, using the MEREC method and GIS. To this end, twelve effective criteria were employed, including lithology, slope, aspect, elevation, precipitation, land use, vegetation cover, distance from fault, distance from road, distance from river, Stream Power Index (SPI), and Topographic Wetness Index (TWI). The data were extracted from various sources such as the Digital Elevation Model (DEM), geological maps, Landsat 8 satellite imagery, and precipitation data, and were prepared in the form of information layers. Results and Discussion The results of the criteria weighting process indicate that the lithology criterion, with a relative weight of 0.164, is the most determining factor in slope instability and the occurrence of landslides in the region. Subsequently, the criteria of distance from road (0.124), mean annual precipitation (0.118), and slope (0.112) were ranked. In contrast, the aspect and stream power index criteria were identified as the least influential factors in this analysis. To produce the final landslide susceptibility map, the effective informational layers, after being assigned relative weights for each criterion, were integrated within the Geographic Information System (ArcGIS) environment. Based on the final map analysis, the northern slopes of Tabriz, particularly the Einali highlands, fall within the high and very high-risk categories. This situation is attributed to the presence of weak and unstable formations, such as marls in these zones, coupled with the steep slope gradients, which have significantly reduced the natural stability of the land. On the other hand, human activities have also played a significant role in increasing the landslide risk. The construction of the Pasdaran Highway at the foot of these slopes has caused a loss of slope equilibrium and intensified instability along its path. Conclusion The results indicated that weak formations such as marls, the steep slopes of northern Tabriz, and human activities including road construction are among the most important factors of instability in this region. Analyses performed on twelve key criteria clearly revealed the prominent role of geological and human factors in the instability of the region's slopes. The most significant finding of this study was the identification of lithology as the most influential criterion (with a weight of 0.164). The presence of weak and erodible formations, particularly marls on the northern slopes of Tabriz, has provided the primary foundation for landslide occurrence. Subsequently, the criteria of distance from roads (0.124), precipitation (0.118), and slope (0.112) were ranked next, indicating the combined influence of construction activities and natural factors in exacerbating this hazard. The construction of roads and highways such as the Pasdaran Highway has disrupted slope equilibrium by creating slope cuts and altering the natural drainage pattern. On the other hand, regional precipitation acts as a triggering factor; by infiltrating weak subsurface layers, it increases pore water pressure and reduces slope stability. The final susceptibility map clearly revealed the spatial distribution of high-risk areas. The concentration of high and very high hazard zones in the northern highlands of the city, particularly in the Einali (Aun-bin-Ali) Mountain range, poses a serious warning for the future development of the city and the safety of residents in these areas. The significant concordance between recorded historical landslides (such as those along the Pasdaran Highway) and the high-risk zones identified in this research strongly confirms the accuracy and validity of the presented model.