بررسی نقش لندفرم ها در میزان فرسایش خاک با مدل RUSLE و سامانه GEE ، مطالعه موردی: حوضه های دامنه جنوبی توده کوهستان سهند (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
این پژوهش با هدف بررسی نقش لندفرم ها در میزان فرسایش خاک در حوضه های دامنه جنوبی توده کوهستان سهند انجام شد. با استفاده از مدل اصلاح شده جهانی فرسایش خاک (RUSLE) و سامانه گوگل ارث انجین (Google Earth Engine)، عوامل مؤثر بر فرسایش شامل فرسایندگی بارش (R)، فرسایش پذیری خاک (K)، طول و شدت شیب (LS)، مدیریت پوشش گیاهی (C) و عملیات حفاظتی خاک (P) مورد ارزیابی قرار گرفت و طبقه بندی لندفرم ها نیز در این سامانه انجام گرفت. نتایج تحقیق نشان داد که مناطق با فرسایش خیلی زیاد و زیاد با مساحتی حدود 45/0 درصد معادل 33/17 کیلومترمربع را شامل می شود. این مناطق در بالادست حوضه که دارای ارتفاع بالا، میانگین بارندگی بیشتر و دارای پوشش گیاهی کمتری بوده رخ داده است. مناطق با فرسایش خیلی کم و کم مساحتی حدود 54/95 درصد معادل 11/3623 کیلومترمربع بوده است که در مناطق دارای پوشش گیاهی پر تراکم، بارندگی کم تر و در مناطق دشت ها و مسطح بوده است. علاوه بر این، تحلیل لندفرم های منطقه نشان داد که بیش ترین میزان فرسایش در لندفرم های آبراهه ها، پرتگاه ها و دره های باریک مشاهده می شود. در حالی که لندفرم های مسطح تر نظیر دشت ها و تراس های آبرفتی از فرسایش کمتری برخوردارند. استفاده از سامانه GEE در این پژوهش قابلیت بالای آن را در ترکیب و تحلیل داده های جغرافیایی مقیاس پذیر نشان داد و روشی مؤثر برای مدیریت پایدار اراضی و کاهش فرسایش خاک فراهم آورده شد. این یافته ها می توانند در برنامه ریزی های مدیریتی و اجرای عملیات حفاظتی در حوضه های آبخیز مشابه، توسط مسئولین و محققین مورد استفاده قرار گیرند.Investigating the Role of Landforms in Soil Erosion Rates Using the RUSLE Model and GEE System, Case Study: Basins of the Southern Slope of the Sahand Mountain Massif
This study aimed to investigate the role of landforms in soil erosion across the southern slope basins of the Sahand mountain range. Using the Revised Universal Soil Loss Equation (RUSLE) model and the Google Earth Engine (GEE) platform, key factors affecting erosion including rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), vegetation cover management (C), and soil conservation practices (P) were analyzed, and landforms were classified within this system. The results indicated that areas with very high and high erosion levels, covering approximately 0.45% of the total area, were predominantly located on steep slopes and at higher elevations, where increased rainfall and reduced vegetation cover led to severe erosion. Conversely, areas with low and very low erosion characterized by dense vegetation and gentle slopes accounted for more than 95% of the study area. Furthermore, the analysis revealed that landforms such as water channels, cliffs, and narrow valleys exhibited the highest erosion rates, whereas flatter features like plains and alluvial terraces experienced the least erosion. This study highlights the strong potential of GEE for large-scale geospatial analysis and presents an effective approach to sustainable land management and erosion mitigation. These findings can support policymakers and researchers in planning targeted protective measures for similar watersheds. Extended Abstract Introduction Soil erosion represents one of the most pressing environmental challenges, significantly impacting natural resources and hindering sustainable development. It depletes soil fertility, jeopardizes food security, threatens biodiversity, and disrupts the global carbon cycle. Several factors contribute to erosion, including climatic conditions such as intense rainfall, topographical elements like slope gradient, soil characteristics, and human activities such as land-use change, deforestation, and overgrazing. Landforms play a critical role in determining the severity and spatial distribution of soil erosion. Geomorphological analysis offers valuable insights into the interaction between natural processes and anthropogenic activities, thereby supporting sustainable land management. This study aims to assess the influence of landforms on soil erosion by applying the Revised Universal Soil Loss Equation (RUSLE) model in conjunction with the spatial data processing capabilities of Google Earth Engine (GEE). Study Area This research was conducted in the southern slope basins of the Sahand Mountain Range, located in East Azerbaijan Province, Iran. The study area includes the Qaleh Chay, Sufi Chay, Mardagh Chay, Lilan Chay, and parts of the Qaranqu basins. Elevation in the region ranges from 3964 meters in mountainous areas to 1236 meters in the plains, covering a total area of 3821.41 km². The region's diverse topography, variable precipitation, and heterogeneous vegetation make it an ideal case for examining the effects of landforms on soil erosion. Material and Methods The RUSLE model was used to estimate soil erosion. This model calculates average annual soil loss based on five factors: Rainfall erosivity (R): Represents the intensity and kinetic energy of rainfall. Soil erodibility (K): Indicates the vulnerability of soil to erosion. Slope length and steepness (LS): Reflects the topographic impact on erosion potential. Vegetation cover management (C): Accounts for the protective effects of land cover. Conservation practices (P): Evaluates the effectiveness of soil conservation methods. These factors were derived using long-term rainfall data, satellite imagery, digital elevation models (DEMs), and land-use maps, all processed through the Google Earth Engine (GEE) platform. Landform classification was performed using the Multi-Scale Topographic Position Index (MTPI) within GEE to identify and categorize distinct geomorphic units. Results and Discussion Erosion mapping revealed that soil loss in the study area ranged from 0 to 40 tons per hectare per year. Areas with very high and high erosion, making up only 0.45% of the total area, were mostly located on steep slopes at higher elevations, where rainfall intensity was greater and vegetation cover was sparse. In contrast, more than 95% of the area experienced low to very low erosion, typically found in flat plains and densely vegetated regions. Landform classification further showed that features such as water channels, cliffs, and narrow valleys exhibited the highest erosion rates, whereas flatter landforms like alluvial terraces and plains were associated with the lowest erosion levels. Conclusion This study demonstrates that the RUSLE model combined with GEE is a powerful tool for conducting large-scale soil erosion assessments. The integration of GEE enabled high-resolution spatial analysis, efficient data processing, and improved model accuracy. The findings indicate that very high and high erosion zones, covering approximately 17.33 km², are concentrated in upper watershed areas characterized by higher altitudes, greater rainfall, and limited vegetation cover. Conversely, low and very low erosion zones, accounting for about 3623.11 km², are located in flatter areas with dense vegetation. This research underscores the importance of incorporating landform analysis into natural resource management and soil conservation strategies. The outcomes provide essential insights for policymakers to prioritize vulnerable areas for conservation initiatives and promote sustainable land-use planning.
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