انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 The Effect of Different Land Use Management Scenarios on Soil Erosion in Givi Chay Watershed تاثیر سناریوهای مختلف مدیریت کاربری اراضی بر میزان فرسایش خاک در حوزه آبخیز گیوی چای 1 19 213849 10.22034/gmpj.2025.482427.1525 FA صیاد اصغری گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. 0000-0002-5015-904X عقیل مددی گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. نازفر آقازاده گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. رئوف مصطفی زاده گروه آبخیزداری، دانشکده منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران. 0000-0002-0401-0260 Journal Article 2024 10 08 Introduction Soil 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). Methodology The 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 forest Data 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. Conclusion Soil 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. فرسایش خاک تابعی از قابلیت جداشدن ذرات و قابلیت انتقال آنها می‌باشد. برای تشکیل یک سانتی‌متر خاک بیش از ۳۰۰ سال زمان نیاز است. از این نظر جلوگیری از فرسایش خاک به‌منظور حفظ ثروت‌های ارزشمند طبیعی امری حیاتی به شمار می‌آید. فرسایش و‌ تولید‌‌ رسوب تابع پیچیده‌ای از عوامل مختلف از جمله، زمین‌شناسی، اقلیم، توپوگرافی، پوشش گیاهی و انسان است. فرسایش خاک فرایند طبیعی فیزیکی است که طی آن ذرات خاک از بستر اصلی خود جدا شده و به کمک یک عامل انتقال‌دهنده به مکانی دیگر حمل و رسوب‌گذاری می‌شود. در مطالعه حاضر، هدف تاثیر سناریوهای مختلف مدیریت کاربری اراضی بر میزان فرسایش خاک با استفاده از مدل G2 در حوزه گیوی چای استان اردبیل می‌باشد. که با بررسی 6 سناریوی مدیریت کاربری اراضی بر اساس الگوی استفاده از اراضی در محیط GIS تهیه شد. سپس داده‌های ورودی بر اساس داده‌های زمینی، کاربری اراضی و داده‌های مشاهداتی تهیه شد. بر اساس نتایج مدل، مقدار فرسـایش در سناریوی تبدیل مراتع ضعیف به متوسط و سناریو تبدیل مراتع متوسط به خوب و احداث باغ کاهش فرسایش را نشان داد و سناریو تخریب که در دو سناریو مطرح شد باعث افزایش فرسایش در کاربری زراعی رانشان می‌دهد. در این تحقیق، ابتدا داده‌های محیطی شامل نوع کاربری زمین، شیب، پوشش گیاهی و بارندگی جمع‌آوری شد. سپس با استفاده از مدل G2، میزان فرسایش خاک در هر یک از کاربری‌های مختلف (کشاورزی، مرتع، جنگل و مناطق مسکونی) محاسبه گردید. نتایج نشان داد که کاربری‌های کشاورزی با فرسایش بالاتری نسبت به دیگر کاربری‌ها مواجه هستند، درحالی‌که مناطق جنگلی به‌عنوان بهترین گزینه برای حفظ خاک و جلوگیری از فرسایش شناخته شدند. این یافته‌ها می‌تواند به تصمیم‌گیری‌های مدیریتی در زمینه حفاظت از خاک و توسعه پایدار کمک کند.

https://www.geomorphologyjournal.ir/article_213849_0332c980ac48ed9246c950336f90b47e.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Detection of Geomorphological Landforms Using the TPI Index and MLMSR, CMLSR, and SPSR Algorithms (Case Study: Southern Slopes of the Sahand Mountain Range آشکارسازی لندفرم‌های ژئومورفولوژی با استفاده از شاخص TPI و الگوریتم های MLMSR، CMLSR و SPSR (مطالعه موردی: دامنه جنوبی توده کوهستان سهند) 20 36 215592 10.22034/gmpj.2025.499686.1542 FA موسی عابدینی گروه جغرافیا طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. 0000-0002-4243-4670 ابوذر صادقی گروه جغرافیا طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. عقیل مددی گروه جغرافیا طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران. Journal Article 2025 01 13 Introduction Geomorphology, 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. Methodology The 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. Conclusion The 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. لندفرم‌ها بیانگر فرآیندهای تأثیرگذار بر عوارض سطح زمین درگذشته و حال هستند و اطلاعات مهمی در مورد ویژگی‌ها و پتانسیل‌های زمین فراهم می‌کنند پژوهش حاضر با هدف استخراج و تحلیل لندفرم‌های ژئومورفولوژیکی دامنه جنوبی توده کوهستان سهند، از شاخص موقعیت توپوگرافی (TPI) و سه الگوریتم پیشرفته MLMSR، CMLSR و SPSR بهره گرفته است. منطقه مورد مطالعه شامل حوضه‌های قلعه چای، صوفی چای، مردق چای، لیلان چای و بخشی از قرنقو است که به جز حوضه قرنقو بقیه حوضه‌ها از زیرحوضه‌های دریاچه ارومیه محسوب می‌شوند. در این مطالعه، مدل رقومی ارتفاع (DEM) با قدرت تفکیک ۳۰ متر برای تحلیل ویژگی‌های توپوگرافی منطقه به‌کار گرفته شد و بر این اساس، ۱۰ نوع لندفرم شناسایی گردید. نتایج نشان داد که توزیع لندفرم‌ها در منطقه متأثر از عوامل زمین‌شناسی، فرسایشی و تکتونیکی است. در مناطق کوهستانی، دره‌های باریک و زهکش‌های مرتفع گستردگی بیشتری دارند، درحالی‌که در مناطق هموارتر، دشت‌ها و تپه‌ها غالب هستند. مقایسه روش‌های مورد استفاده نشان داد که الگوریتم MLMSR در تشخیص اشکال پیچیده مانند دامنه‌های شیب‌دار و آبراهه‌ها کارایی بهتری دارد، درحالی‌که CMLSR در شناسایی نواحی مرتفع، قله‌ها و خط‌الرأس‌ها دقت بالاتری نشان داد. همچنین، SPSR در تفکیک مناطق مرتفع و دشت‌ها عملکرد مناسبی داشته، اما در شناسایی جزئیات شیب‌ها ضعیف‌تر از سایر الگوریتم‌ها بوده است. به‌طور کلی، این مطالعه نشان داد که ترکیب شاخص TPI با الگوریتم‌های MLMSR، CMLSR و SPSR می‌تواند رویکردی کارآمد برای استخراج و تحلیل لندفرم‌ها ارائه دهد و از این داده‌ها می‌توان برای مدیریت منابع طبیعی، برنامه‌ریزی منطقه‌ای، ژئوتوریسم و کاهش مخاطرات طبیعی استفاده کرد.

https://www.geomorphologyjournal.ir/article_215592_2e5464944c08461875b5c61736396daf.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Modeling the Geomorphological Development Stages of the Kaluts (Yardangs) in the Lut Desert World Heritage Site and Their Comparison with the Yardangs of the Aeolis Region on Mars مدل‌سازی مراحل توسعه ژئومورفولوژیکی کلوت های (یاردانگ‌های) میراث جهانی بیابان لوت و مقایسه آن با یاردانگ های منطقه آئولیس مریخ 37 58 222737 10.22034/gmpj.2025.512496.1553 FA عاطفه حصارکی زاد گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران. مهران مقصودی گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران. 0000-0002-4973-8327 Journal Article 2025 03 14 Extended Abstract Introduction The 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. Methodology In 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 Power The 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 Yardangs The 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 Yardangs Analysis 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 Yardangs The 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. Conclusion The 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. یاردانگ‌ها به‌عنوان یکی از برجسته‌ترین اشکال مورفولوژیکی در مناطق بیابانی شناخته می‌شوند و معمولاً به‌صورت تپه‌های فرسایش‌یافته‌ای مشاهده می‌شوند که توسط فرورفتگی‌های U شکل و با مجموعه‌ای از راهروها و پشته‌های ناهموار از یکدیگر تفکیک می‌شوند. بررسی ویژگی‌های مورفومتریک این سازه‌های زمین‌شناختی برای شناسایی شاخص‌های ژئومورفولوژیکی آن‌ها اهمیت بالایی دارد. در این پژوهش، یاردانگ‌های بیابان لوت ایران با یاردانگ‌های منطقه آئولیس در مریخ مقایسه شده‌اند. برای تحلیل یاردانگ‌های بیابان لوت، از تصاویر ماهواره‌ای لندست استفاده شده و داده‌های مربوط به فرکانس، سرعت و شدت بادهای غالب با استفاده از نرم‌افزار Global Mapper ارزیابی گردیده است. همچنین، برای مدل‌سازی مراحل تکامل یاردانگ‌ها و بازسازی سه‌بعدی آن‌ها، از نرم‌افزار Rhino و پلاگین Grasshopper بهره گرفته شده است. نتایج پژوهش نشان داد که یاردانگ‌های هر دو منطقه، تحت تأثیر فرسایش بادی، دارای ساختارهای تیز و باریک با شیارهای موازی هستند. علاوه بر این، جهت کشیدگی یاردانگ‌ها و دالان‌های میان آن‌ها در هر دو منطقه، شمال غربی - جنوب شرقی است. همچنین، یافته‌ها نشان داد که یاردانگ‌های بیابان لوت عمدتاً در مرحله بلوغ قرار دارند، درحالی‌که در آئولیس مریخ، یاردانگ‌های غالب از نوع "پشت‌ماهی" یا "گوژپشتی" بوده و در طبقه یاردانگ‌های میان‌سال دسته‌بندی می‌شوند. این تفاوت نشان می‌دهد که یاردانگ‌های منطقه آئولیس مریخ احتمالاً قدمت بیشتری نسبت به یاردانگ‌های بیابان لوت دارند.

https://www.geomorphologyjournal.ir/article_222737_ea58cc5133c3609cf7de9ddf14854312.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Evaluation of distribution of landslides of Ilam-Mehran area and their relationship with tectonics and geomorphologic indices ارزیابی پراکندگی و ارتباط زمین‌لغزش‌های گستره ایلام-مهران با زمین‌ساخت و شاخص‌های ژئومورفولوژی 59 83 224828 10.22034/gmpj.2025.529362.1566 FA فروزان ناصری گروه جغرافیای طبیعی، دانشکده علوم زمین، دانشگاه شهید بهشتی، تهران، ایران شهرام بهرامی گروه جغرافیای طبیعی، دانشکده علوم زمین، دانشگاه شهید بهشتی، تهران، ایران علیرضا صالحی پور میلانی گروه جغرافیای طبیعی، دانشکده علوم زمین، دانشگاه شهید بهشتی، تهران، ایران محسن احتشامی معین آبادی حوضه‌های رسوبی نفت، دانشکده علوم زمین، دانشگاه شهید بهشتی، تهران، ایران Journal Article 2025 06 09 Introduction Tectonic 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. Methodology In 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. Conclusion The 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. منطقه مورد مطالعه بخشی از زاگرس چین خورده در جنوب غربی ایران، شامل گستره ایلام-مهران است. هدف این تحقیق، شناسایی زمین‌لغزش‌ها و بررسی پراکندگی و ارتباط مکانی آن‌ها با پارامترهای زمین‌ساختی است. در این مطالعه، با استفاده از مطالعات میدانی و تصاویر ماهواره‌ای تعداد 257 زمین‌لغزش در منطقه مورد مطالعه شناسایی شد. جهت ارزیابی پراکندگی و ارتباط این زمین‌لغزش‌ها با زمین‌ساخت، شاخص‌های ژئومورفولوژی از جمله انتگرال هیپسومتری (Hi)، گرادیان طولی رودخانه (SL)، عدم تقارن حوضه (AF)، نسبت شکل حوضه (Bs)، پهنا یا عرض کف دره (Vfw) و سینوسیته جبهه کوهستان (Smf) برای حوضه‌های آبریز منطقه مورد مطالعه محاسبه گردید و با استفاده از شاخص Iat میزان فعالیت نسبی زمین‌ساختی منطقه به دست آمد. همچنین ارتباط کمی بین کانون زمین‌لرزه‌ها، گسل‌ها و فروانی زمین‌لغزش مورد بررسی قرار گرفت. نتایج به‌دست آمده از بررسی پراکندگی زمین‌لغزش‌ها نسبت به کانون زمین‌لرزه‌ها و گسل‌ها نشان می‌دهد که زمین‌لغزش‌ها بیشتر در مجاورت گسل‌های فعال و نزدیک به کانون زمین‌لرزه‌ها (با شعاع کمتر از 2 کیلومتر) متمرکز شده‌اند و نزدیکی به شکستگی‌های ساختاری و فعالیت‌های لرزه‌ای نقش مهمی در تحریک لغزش دامنه‌ها ایفا کرده است. بررسی شاخص‌های ژئومورفولوژیک و شاخص مورفوتکتونیک (Iat) نشان دهنده فعالیت زمین‌ساختی متوسط در حوضه‌های ایلام (2.16)، صالح آباد (2.33) و مهران 1 (2.33) و فعالیت زمین‌ساختی زیاد در حوضه مهران 2 (2) می‌باشد. نتایج نشان می‌دهد با افزایش انتگرال هیپسومتری (Hi) در زیرحوضه‌ها مقدار شاخص‌های تراکم زمین‌لغزش (LD) و نسبت مساحت زمین‌لغزش به مساحت کل حوضه (LA) افزایش می‌یابد. این موضوع نشان می‌دهد حوضه‌های جوان‌تر (با Hi بالاتر) و پرشیب‌تر، بیشتر مستعد وقوع زمین‌لغزش هستند. تلفیق داده‌های زمین‌ساختی، لرزه‌ای و مورفومتری حوضه‌ها، نشان می‌دهد که در زیرحوضه‌هایی با فعالیت زمین‌ساختی بالا، مساحت زمین‌لغزش‌ها نسبت به مساحت زیرحوضه افزایش می‌یابدو منطقه مورد مطالعه از نظر ژئودینامیک فعال بوده و زمین‌لغزش‌ها، تحت تأثیر فعالیت لرزه‌ای، گسل‌ها و شرایط زمین‌ساختی منطقه شکل گرفته‌اند.

https://www.geomorphologyjournal.ir/article_224828_43174d6e1d2f2791af4925de27e813af.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Comparative evaluation of geomorphosites of Li Li Gorge, Gahar Lake and Bisheh Waterfall towards the geotourism development in Dorud County ارزیابی کمّی ژئومورفوسایت‌های دریاچه گهر، آبشار بیشه و تنگه لی‌لی به‌منظور توسعه ژئوتوریسم شهرستان دورود 84 104 228486 10.22034/gmpj.2025.528957.1565 FA مرضیه دلیخون گروه جغرافیا و گردشگری، دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، کاشان، ایران. 0009-0004-2705-9886 سید حجت موسوی گروه جغرافیا و گردشگری، دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، کاشان، ایران. 0000-0003-1818-439X Journal Article 2025 06 07 Introduction Geotourism, 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. Methodology According 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. Conclusion In 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. امروزه اقتصاد روبه‌رشد زمین گردشگری، اهمیت جاذبه‌های ژئوتوریسمی و ویژگی‌های منحصر‌به‌فرد میراث زمین، توجه به ژئوتوریسم و ارزیابی ژئومورفوسایت‌ها را بیش از پیش ایجاب کرده است. لذا پژوهش حاضر با هدف ارزیابی کمّی ژئومورفوسایت‏های آبشار بیشه، دریاچه گهر و تنگه لی‌لی انجام شد که به لحاظ نوع، کاربردی و از نظر روش، تحلیلی است. بدین منظور از مدل پرالونگ استفاده شد که توانمندی گردشگری ژئومورفوسایت‌ها را بر پایه چهار شاخص زیبایی، علمی، فرهنگی و اقتصادی، و ارزش بهره‌وری آنها را ازطریق شاخص‌های میزان و کیفیت بهره‌برداری ارزیابی می‌کند. براین اساس پرسشنامه‌های تخصصی مدل پرالونگ تدوین و توسط 60 متخصص به صورت مجزا برای هر ژئومورفوسایت تکمیل شد. علاوه‌براین پرسشنامه عمومی برای بررسی رفتار گردشگران، امکانات و خدمات، و حفاظت‌از ژئومورفوسایت‌ها تهیه و توسط 100 گردشگر تکمیل شد. نتایج نشان داد آبشار بیشه، دریاچه گهر و تنگه لی‌لی به‌ترتیب با کسب امتیاز گردشگری ۶۳/0، 6/0 و 57/0، و امتیاز بهره‌وری ۶۲/0، 48/0 و 56/0 در رتبه‌های اول تا سوم قرار دارند. دراین‌بین، آبشار بیشه از نظر عیارهای زیبایی و اقتصادی به‌ترتیب با کسب امتیاز 85/0 و ۷۵/0 رتبه نخست را دارد که بیانگر بیشترین جذابیت و دسترسی مطلوب این ژئومورفوسایت از طریق جاده با سطح اهمیت ملی است. سایر ژئوسایت‌‌ها نیز نیازمند توسعه راه‌های دسترسی و همچنین افزایش سطح تمهیدات حفاظتی و بهره‌وری هستند. ازنظر عیار علمی دریاچه گهر با امتیاز ۶۲/0 در رتبه اول قرار گرفت که نشانگر قابلیت علمی و آموزشی این سایت برای توسعه ژئوتوریسم است. عیار فرهنگی در ارزیابی ژئومورفوسایت‌ها، امتیاز بسیار پایینی را کسب کرد که حاکی از نبود رخدادهای فرهنگی و هنری است و توجه بیشتری را می‌طلبد. این نتایج می‌تواند به توسعه پایدار ژئوتوریسم در سایت‌های مورد مطالعه کمک کند و شرایط ایجاد تجربه‌ی مطلوب برای گردشگران فراهم آورد.

https://www.geomorphologyjournal.ir/article_228486_1c7df12d1fcd48c7e2fbd417b9f200cf.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Analyzing the role of geometric characteristics of active and inactive surfaces of alluvial fans in the evolution of the gully erosion pattern(case study: the southern slopes of Aladag) تحلیل نقش ژئومتری سطوح فعال و غیرفعال مخروط افکنه‌های دامنه‌های جنوبی آلاداغ در تحول الگوی فرسایش گالی 105 127 229113 10.22034/gmpj.2025.528739.1563 FA امین برابریان گروه جغرافیا، دانشکده ادبیات و علوم انسانی، دانشگاه فردوسی مشهد، مشهد، ایران. ندا محسنی گروه جغرافیا، دانشکده ادبیات و علوم انسانی، دانشگاه فردوسی مشهد، مشهد، ایران. 0000-0003-0691-9408 Journal Article 2025 06 06 Introduction Alluvial 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. Methodology The 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. Conclusion In 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. هدف اصلی پژوهش حاضر ارائه یک مدل مفهومی برای شناسایی فاکتورها و مکانیزم‌های موثر بر دینامیک الگوی فرسایش گالی روی سطوح مختلف مخروط افکنه‌ها می‌باشد. سطوح مختلف 60 مخروط افکنه‌ در دامنه‌های جنوبی آلاداغ تفکیک و ژئومتری هر یک اندازه‌گیری شد. الگوی گالی هر مخروط ارزیابی و در نهایت ارتباط بین تحول مخروط افکنه‌ها، تغییرپذیری در ژئومتری سطوح و الگوی فرسایش گالی تعیین شد. گالی زایی در سطوح فعال ۲.۵ برابر بیشتر از سطوح غیرفعال بوده است. این تفاوت‌ها می‌تواند ناشی از در معرض قرارگیری سطوح فعال نسبت به فرایندهای سیلابی و مساحت کوچک‌تر آن‌هادر مقایسه با سطوح غیر فعال باشد. افزایش معنادار میانگین طول گالی در سطوح فعال بیانگر انرژی بیشتر جریان‌ و تداوم فرآیندهای فرسایشی می‌باشد. افزایش معنادار میانگین عرض گالی در سطوح غیرفعال ناشی از فرآیندهای تخریب دیواره گالی، فرسایش جانبی و پرشدگی نسبی در طول زمان است. نسبت طول به عرض گالی به طور معناداری در مخروط‌افکنه‌های فعال بیشتر از سطوح غیرفعال بوده است. وجود رسوبات به شدت هوادیده و دور بودن از فرایندهای سیلابی در سطوح غیرفعال با ایجاد خاک‌های تکامل یافته‌تر و ریزدانه، زمینه توسعه عرضی و عمقی گالی‌ها را فراهم می‌آورند. همبستگی مثبت عرض گالی با قدرت جریان، نشان‌دهنده غالبیت فرسایش کناری و عریض‌تر شدن گالی‌های تکامل‌یافته نسبت به سطوح فعال است. در سطوح فعال، انرژی اولیه جریان، توسعه شبکه زهکشی و شرایط ارتفاعی، مهم‌ترین فاکتورهای مؤثر به نظر می‌رسند. در مخروط‌افکنه‌های غیرفعال، افزایش شاخص رطوبت توپوگرافی، زبری سطحی و وضعیت تثبیت‌شده سطوح، اهمیت بیشتری در الگوی فرسایش گالی می‌یابند. مراحل تکاملی مخروط‌افکنه‌ها با تغییر ژئومتری آن‌ها، اهمیت نسبی عوامل توپوگرافیک مؤثر بر توسعه گالی را در نسل‌های مختلف علی‌رغم وجود برخی عوامل مشترک تغییر می‌دهد. راهکارهایی مانند احداث استخرها در بالادست برای جمع‌آوری رواناب، احیای پوشش گیاهی، کاهش اتصال هیدرولوژیک و روش‌های بیولوژیک برای کنترل فرسایش گالی اتخاذ گردد.

https://www.geomorphologyjournal.ir/article_229113_9f81da4518607c9a25276b5e9c40138b.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Identification and classification of desert landforms using the random forest algorithm in the Garmsar region شناسایی و طبقه‌بندی زمین‌شکل‌های بیابانی مبتنی بر الگوریتم جنگل تصادفی در شرق شهرستان گرمسار 106 123 230956 10.22034/gmpj.2025.532717.1569 FA فاطمه عمادالدین گروه ژئومورفولوژی، دانشکده جغرافیا، دانشگاه خوارزمی، تهران، ایران علی احمدآبادی گروه ژئومورفولوژی، دانشکده جغرافیا، دانشگاه خوارزمی، تهران، ایران 0000-0002-3623-6192 عزت اله قنواتی گروه ژئومورفولوژی، دانشکده جغرافیا، دانشگاه خوارزمی، تهران، ایران Journal Article 2025 07 05 Introduction Geomorphological 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. Methodology This 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). Conclusion Landform 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. نقشه‌های ژئومورفولوژی ابزارهای مهمی در ارزیابی فرآیندهای ژئومورفولوژیکی، هیدرولوژیکی، و مدیریت منابع طبیعی هستند. روش‌های سنتی نقشه‌برداری لندفرم‌ها، که شامل مشاهدات میدانی و تصاویر هوایی می‌شود، به دلیل زمان‌بر بودن و هزینه‌های بالای اجرایی محدودیت‌هایی دارند. در این پژوهش، از الگوریتم یادگیری ماشین جنگل تصادفی برای تولید نقشه‌های لندفرم در منطقه بیابانی ده نمک و آرادان استفاده شد. برای این منظور، از داده‌های ماهواره‌ای سنتینل 2آ سال 2023و شاخص‌های مورفومتری شامل رطوبت توپوگرافیک، انحنا کلی و ناهمواری زمین به همراه مدل رقومی ارتفاع 10 متر استفاده گردید. در این مطالعه، دو مدل شامل مدل اپتیک استفاده از داده‌های سنتینل 2آ به‌تنهایی و مدل اپتیک-مورفومتریک ترکیب داده‌های سنتینل 2آ با شاخص‌های مورفومتری برای طبقه‌بندی لندفرم‌ها بررسی شد. نتایج نشان داد که مدل ترکیبی دقت بالاتری در شبیه‌سازی مرزهای لندفرم‌ها و شناسایی لندفرم‌های با تغییرات شدید ارتفاعی مانند تپه ماهور، کوهستان با دامنه منظم و هوگ بک ارائه داد. همچنین، مدل ترکیبی توانست مناطق دشتی و کوهستانی را به‌طور مؤثری از یکدیگر تفکیک کند. علاوه براین، استفاده از شاخص‌های مورفومتری به‌طور چشمگیری دقت طبقه‌بندی لندفرم‌ها را افزایش داده است. به‌طوری‌که با افزایش دقت کلی از ۷۸ درصد به ۸۵ درصد و ارتقاء شاخص کاپا از 74/0 به 82/0، توانست تفکیک دقیق‌تری از واحدهای لندفرمی ارائه دهد. این روش می‌تواند زمان و هزینه‌های نقشه‌برداری لندفرم‌ها را به‌طور قابل‌توجهی کاهش دهد و دقت نقشه‌های ژئومورفولوژیکی را بهبود بخشد. نتایج این پژوهش به‌ویژه در زمینه‌های مدیریت منابع آب، پایش تغییرات محیطی و برنامه‌ریزی کاربری اراضی کاربرد دارد و پیشنهاد می‌شود که در مطالعات آتی از ترکیب داده‌های مورفومتری و ماهواره‌ای برای بهبود تفکیک لندفرم‌ها استفاده شود.

https://www.geomorphologyjournal.ir/article_230956_13a92d6eded2da97f023ef951b57dc10.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Multitemporal Land Use and Land Cover Change Detection via Foundation Model Embeddings (AlphaEarth): A Pixel-Wise Similarity Framework in a Rapidly Urbanizing Semi-Arid Region (Alborz, Iran 2017–2024) تشخیص چندزمانه تغییرات کاربری و پوشش زمین بر پایه بردارهای نهفته مدل بنیادین آلفاارث: چارچوب شباهت پیکسل‌محور در منطقه‌ای نیمه‌خشک با شهرنشینی شتابان (۲۰۱۷–۲۰۲۴، البرز، ایران) 124 149 243595 10.22034/gmpj.2026.566714.1594 FA ابوالقاسم گورابی گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران. 0000-0002-2787-8687 مصطفی کریمی احمدآباد گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران. 0009-0005-6551-3418 آرین الله ویسی گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران 0009-0008-6609-4771 Journal Article 2025 12 17 Extended Abstract Introduction Land use and land cover change (LULCC) in arid and semi-arid regions has emerged as a critical challenge for sustainable land management, particularly in areas experiencing rapid urbanization and socio-economic transformation. In Iran, accelerated population growth, industrial expansion, and infrastructure development have intensified land conversion processes, often in environmentally sensitive landscapes. Reliable detection of such changes is essential for spatial planning, environmental governance, and risk mitigation. However, conventional LULCC detection approaches, including supervised classification and spectral index–based methods such as the Normalized Difference Vegetation Index (NDVI), suffer from fundamental limitations. These methods typically depend on extensive local training data, are prone to cumulative classification errors, and primarily capture vegetation dynamics rather than structural or functional land-use transformations. Recent advances in foundation models for Earth observation provide a new paradigm for land change analysis. Pre-trained on massive, globally representative datasets, these models encode high-level semantic and structural information in latent feature spaces, enabling transferable and scalable analyses. Among these, the AlphaEarth foundation model offers dense, pixel-wise latent embeddings that summarize multi-spectral, spatial, and contextual characteristics of the land surface. This study leverages AlphaEarth embeddings to propose a pixel-based, multitemporal similarity framework for analyzing patterns of land use and land cover change without reliance on local training samples. The rapidly urbanizing semi-arid province of Alborz, Iran, is selected as a representative case study for the period 2017–2024.. Methodology The methodological framework is based on the extraction and analysis of 64-dimensional AlphaEarth latent embeddings at a native spatial resolution of 10 m for annual composites spanning 2017 to 2024. To ensure spatial consistency with auxiliary datasets, all outputs were resampled to 30 m resolution. Change analysis was conducted using a pixel-wise similarity approach rather than categorical classification, thereby reducing the risk of error propagation associated with multi-class labeling. Four complementary similarity metrics were computed for each pair of temporal embeddings: cosine similarity, Pearson correlation coefficient, dissimilarity (1 − cosine similarity), and the Structural Similarity Index Measure (SSIM). Each metric captures a distinct aspect of change, including directional similarity in latent space, linear association, magnitude of divergence, and spatial–textural variation. This multi-metric strategy improves the interpretability and consistency of latent-space change analysis and supports the identification of both subtle and abrupt changes. Spatial analyses included hotspot and coldspot identification based on statistically derived similarity thresholds, as well as three-class and five-class stability classifications to represent varying intensities of change. To support decision-making at administrative levels, similarity values were aggregated at the county scale, enabling comparative stability ranking across Alborz Province. Temporal trend analysis was conducted for seven consecutive annual intervals, from 2017–2018 to 2023–2024, using linear regression and the non-parametric Mann–Kendall test to identify long-term tendencies and anomalous periods. Finally, results were conceptually and operationally compared with NDVI-based change detection and with findings from previous studies employing traditional machine learning and deep learning approaches. Results and discussion The results reveal pronounced overall stability in land use and land cover across Alborz Province during the study period. Approximately 77.78% of the provincial area, equivalent to 4,030.40 km², exhibited high similarity values, indicating persistent land-use conditions. In contrast, only 2.36%, equivalent to 122.30 km², experienced intense changes, forming spatially concentrated hotspots rather than diffuse patterns. These hotspots were primarily located in the counties of Nazarabad, Eshtehard, Fardis, and parts of Charbagh, closely aligned with industrial corridors, transportation axes, and zones of suburban expansion. The provincial mean cosine similarity of 0.9569 falls within the upper range of values reported in related change detection studies, suggesting that latent-space similarity analysis provides a scalable framework for representing broad patterns of land-use stability and potential structural transformation. Among the four metrics, cosine similarity and Pearson correlation showed strong spatial and statistical convergence, indicating the consistency of the detected patterns across vector-based similarity measures. SSIM exhibited higher variability, reflecting its sensitivity to local structural and textural changes, particularly in heterogeneous urban environments. Temporal analysis identified a statistically significant increase in overall stability over the 2017–2024 period, interrupted by a distinct decline in 2020–2021. This decline represents an anomalous interval within the multiyear similarity pattern and indicates a temporary increase in land-use volatility. The subsequent recovery in similarity values during 2021–2022 suggests a return to relative stability, although identifying the specific drivers of this temporal fluctuation requires further investigation using ancillary environmental and socio-economic data. Comparison with NDVI-based change maps revealed important conceptual differences. NDVI primarily captured vegetation and biomass fluctuations, particularly in mountainous and vegetated northern areas, which were identified as relatively stable by the AlphaEarth-based framework. Conversely, several urban and industrial transformation zones exhibited limited NDVI change but appeared as hotspots in latent-space analysis. This contrast suggests that vegetation-based spectral indices and latent embeddings capture different but complementary dimensions of land-surface change. NDVI is more sensitive to vegetation phenology and biomass variability, whereas AlphaEarth embeddings can provide complementary evidence of patterns consistent with non-vegetative and structural–functional land-use transformations. Conclusion This study shows that multitemporal similarity analysis of foundation model embeddings can provide a scalable, training-free, and complementary framework for land use and land cover change analysis in semi-arid regions. By operating directly in latent feature space, the proposed approach reduces dependence on local training data and avoids the error propagation commonly associated with repeated categorical classification. Its main contribution lies in representing patterns of land-use stability and identifying areas potentially consistent with structural and functional land-use transformations beyond vegetation dynamics. The application to Alborz Province reveals a land-use system characterized by broad stability, interrupted by localized and policy-relevant hotspots of transformation. These findings highlight the potential of foundation models such as AlphaEarth to support continuous land monitoring, early-warning applications, and evidence-based spatial planning, particularly in data-scarce environments. Nevertheless, because latent embeddings are not directly equivalent to ground-truth land-use classes, the results should be interpreted as complementary analytical evidence rather than definitive proof of land-use conversion. Future research should integrate socio-economic drivers, in situ validation, official land-use maps, predictive modeling, and explainable artificial intelligence approaches to further enhance the interpretability, validation, and policy relevance of latent-space change detection. تغییرات کاربری و پوشش زمین در مناطق خشک و نیمه‌خشک ایران، به‌ویژه نواحی با شهرنشینی سریع، چالش اصلی مدیریت پایدار سرزمین است. روش‌های سنتی مانند طبقه‌بندی نظارت‌شده و شاخص NDVI به‌دلیل وابستگی به داده‌های محلی، تجمیع خطاها و ناتوانی در تمایز تغییرات گیاهی از تحولات ساختاری، محدودیت‌های جدی دارند. این پژوهش چارچوبی نوین پیکسل‌محور و چندزمانه بر پایه تحلیل شباهت بردارهای نهفته مدل AlphaEarth ارائه می‌دهد تا بر این کاستی‌ها غلبه کند. بردارهای ۶۴بعدی با تفکیک ۱۰ متری برای ۲۰۱۷–۲۰۲۴ استخراج شد و چهار معیار شباهت (کسینوسی، همبستگی پیرسون، عدم شباهت و SSIM) پیکسل‌به‌پیکسل محاسبه گردید. تحلیل‌ها شامل شناسایی خوشه‌های تغییر (Hotspot/Coldspot)، طبقه‌بندی پایداری چندسطحی، تجمیع شهرستانی و روند زمانی بود. نتایج با NDVI و مطالعات پیشین مقایسه شد. یافته‌ها حاکی از پایداری بالای ۷۷.۷۸٪ مساحت استان البرز (۴۰۳۰.۴۰ کیلومترمربع) است، در حالی که ۲.۳۶٪ از مساحت استان (۱۲۲.۳۰ کیلومترمربع) تغییرات شدید را تجربه کرده؛ این تغییرات عمدتاً در شهرستان‌های نظرآباد، اشتهارد، فردیس و چهارباغ متمرکز بوده‌اند. میانگین شباهت کسینوسی استانی ۰.۹۵۶۹، در دامنه بالای مقادیر گزارش‌شده در مطالعات مشابه قرار می‌گیرد و نشان‌دهنده قابلیت مناسب چارچوب پیشنهادی در بازنمایی پایداری و الگوهای سازگار با تحولات ساختاری–کارکردی اراضی است. تحلیل روند زمانی، افت پایداری در دوره ۲۰۲۰–۲۰۲۱ و بازگشت نسبی پایداری در دوره بعدی را نشان می‌دهد. برخلاف NDVI که عمدتاً نوسانات پوشش گیاهی و زیست‌توده را بازتاب می‌دهد، این رویکرد می‌تواند شواهد مکملی از الگوهای سازگار با تحولات ساختاری–کارکردی کاربری اراضی، به‌ویژه در پهنه‌های شهری، صنعتی و کم‌پوشش گیاهی، فراهم سازد. این چارچوب بدون نیاز به داده‌های محلی و با مقیاس‌پذیری بالا، ابزاری کارآمد برای پایش تغییرات در مناطق خشک فراهم می‌آورد و می‌تواند مبنایی علمی برای برنامه‌ریزی آمایش سرزمین و سیاست‌گذاری محیطی فراهم سازد.

https://www.geomorphologyjournal.ir/article_243595_13ba209c5c0541fdf82a7943b41a2d33.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 The role of earthquakes in the occurrence of landslides on the Tefin-Dagaga axis in Kurdistan province using radar interferometry techniques نقش زمین لرزه در وقوع زمین لغزش های محور تفین-دگاگا در استان کردستان با استفاده از تکنیک‌های تداخل سنجی راداری 125 146 217108 10.22034/gmpj.2025.486482.1530 FA امید ابراهیمی گروه ژئومورفولوژی، دانشگاه تبریز، ایران. 0009-0001-0019-1607 سید اسداله حجازی گروه ژئومورفولوژی، دانشگاه تبریز، ایران. شهرام روستایی گروه ژئومورفولوژی، دانشگاه تبریز، ایران. Journal Article 2024 11 01 Extended Abstract Introduction In 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. Methodology In 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. Conclusion In 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. زمین لغزش از جمله مخاطرات طبیعی، تاثیرات بسیار ویرانگر جانی و مالی به ویژه در مناطق کوهستانی ایران وجهان به همراه داشته است. لذا تمهیدات لازم برای کاهش خسارات ناشی از وقوع زمین لغزش، ضروری است . دراین پژوهش هدف نقش زمین لرز ه در تعیین میزان جابجایی زمین لغزش در محور تفین-دگاگا در استان کردستان با استفاده از تکنیک-‌های تداخل سنجی راداری می باشد.در این مطالعه، از داده‌های تصاویر ماهواره‌ای سنتینل-1 برای اندازه‌گیری جابجایی زمین در طول سال‌های 2017 تا 2019 استفاده شد. به این منظور تصاویر راداری در بازه‌های زمانی مختلف جمع‌آوری و در فرآیند آنالیز تداخل‌سنجی راداری (InSAR) پردازش شده و سپس تغییرات ارتفاعی زمین، نشست‌ها و لغزش‌ها با دقت ارزیابی و محاسبه شدند. نتایج حاصل از این روش نشان داد که داده‌های جابجایی زمین نشان‌دهنده تغییرات مهمی در وضعیت زمین در مسیر جاده تفین به داگاگا هستند.در سال 2018، جابجایی‌های زمین بیشتر به صورت نشست‌های جزئی گزارش شدند، با میانگین جابجایی -0.0235 متر در ماه اوت که نشان‌دهنده بهبود نسبی وضعیت زمین نسبت به سال 2017 بود.در نتیجه، مقایسه داده‌های جابجایی نشان می‌دهد که منطقه مورد مطالعه، به ویژه در مسیر جاده تفین به داگاگا، در معرض تغییرات مستمر زمین‌شناسی و تکتونیک منطقه(گسل اصلی زاگرس) قرار دارد. در حالی که سال 2018 بهبود نسبی در وضعیت زمین نشان می‌داد، داده‌های سال 2019 از بازگشت نشست‌های شدیدتر و ناپایداری گسترده‌تر خبر می‌دهند. این امر نشان می‌دهد که نظارت مداوم و دقیق به همراه اقدامات حفاظتی فوری برای جلوگیری از خطرات بیشتر در این منطقه ضروری است.

https://www.geomorphologyjournal.ir/article_217108_6055ee96d58a46d9bf9258fbd01ce5b7.pdf

انجمن ایرانی ژئومورفولوژی پژوهشهای ژئومورفولوژی کمّی 22519424 14 3 2025 12 22 Analysis of the dynamics of geomorphic continuity under the influence of climate and land use change in the Zarrineh Rud basin, northwestern Iran تحلیل پویایی پیوستگی ژئومورفیک تحت تأثیر تغییر اقلیم و کاربری زمین در حوضه زرینه‌رود، شمال‌غرب ایران 166 147 231149 10.22034/gmpj.2025.532441.1568 FA مریم ایلانلو گروه جغرافیا، واحد ماهشهر، دانشگاه آزاد اسلامی، ماهشهر، ایران. Journal Article 2025 07 03 Introduction In 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. Methodology This 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%. Conclusion The 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, در سال‌های اخیر، پیوستگی ژئومورفیک به عنوان مفهومی کلیدی برای درک نحوه انتقال رسوب و انرژی در حوضه‌های آبخیز، اهمیت ویژه‌ای یافته است. پژوهش حاضر با هدف تحلیل پویایی شاخص پیوستگی ژئومورفیک (IC) تحت تأثیر تغییرات اقلیمی و کاربری زمین در حوضه زرینه‌رود، شمال‌غرب ایران، طی بازه زمانی ۲۰۰۰ تا ۲۰۲۵ انجام شده است. در این راستا، داده‌های مکانی شامل مدل رقومی ارتفاع، تصاویر لندست و لایه‌های کاربری زمین همراه با داده‌های اقلیمی جمع‌آوری و پردازش شدند. طبقه‌بندی تصاویر ماهواره‌ای با دقت بالایی صورت گرفت و روند تغییر کاربری اراضی به ویژه افزایش اراضی کشاورزی و توسعۀ سکونتگاه‌ها به‌عنوان عوامل اصلی تخریب پیوستگی شناسایی گردید. شاخص IC با استفاده از روش Cavalli و همکاران محاسبه و تغییرات آن در طول دوره مورد بررسی قرار گرفت. نتایج نشان می‌دهد که مقدار IC طی سال‌های مورد نظر کاهش چشمگیری داشته، به‌ویژه پس از عبور از آستانه ۲۰ درصد افزایش در اراضی کشاورزی، افت واضحی در مقدار IC ایجاد شده است. تحلیل گراف‌نظری شبکه زهکشی نیز نشان داد تمرکز انتقال رسوب در چند زیرحوضه خاص افزایش یافته و آسیب‌پذیری شبکه تشدید شده است. نتایج رگرسیونی بیانگر آن است که نقش تغییرات انسانی، به‌ویژه در کاربری اراضی، به مراتب مهم‌تر از نوسانات اقلیمی در افت پیوستگی ژئومورفیک بوده است. یافته‌ها بر ضرورت مدیریت یکپارچه و بازنگری سیاست‌های کاربری زمین جهت حفظ پایداری ژئومورفیک منطقه تأکید دارند.

https://www.geomorphologyjournal.ir/article_231149_073ae4434b75a5aa1527bf28578c5686.pdf