مدل‌سازی پتانسیل فرسایش و نرخ رسوب‌دهی حوضه آبریز گرگانرود

حوضه آبریز گرگانرود در استان گلستان، به دلیل شرایط خاص توپوگرافی و خاک‌های حساس، یکی از مناطق آسیب‌پذیر کشور در برابر فرسایش خاک محسوب می‌شود. تعیین پتانسیل فرسایش این حوضه در ارزیابی ریسک فرسایش و برآورد میزان تلفات رسوب اهمیت دارد. در این پژوهش، با استفاده از مدل پتانسیل فرسایش(epm) ، توزیع فضایی پتانسیل فرسایش خاک در 11 زیرحوضه حوضه آبریز گرگانرود مورد ارزیابی قرار گرفت. به‌منظور دستیابی به این هدف، از لایه‌های اطلاعاتی زمین‌شناسی، خاک‌شناسی، شیب، ارتفاع ، دمای سطح زمین، بارش و کاربری اراضی زمین در محیط gis استفاده شد. در ادامه، نسبت تحویل رسوب در هر زیرحوضه توسط سه روش مرسوم گاوریلوویچ، بویس و ویلیامز-برنت محاسبه و رابطه ریاضی بین این نسبت و ویژگی‌های حوضه‌ای مشخص شد. برای اعتبارسنجی نقشه پتانسیل رسوب حوضه، داده‌های متوسط بلندمدت رسوب ویژه 11 ایستگاه هیدرومتری در خروجی زیرحوضه های مورد مطالعه طی سال‌های 1345 تا 1396 محاسبه و نمودار مشخصه عملکرد محاسبه شد. سطح زیر منحنی مشخصه نتایج پتانسیل رسوب بر اساس معادله نسبت تحویل رسوب ویلیامز-برنت، گاوریلوویچ و بویس به ترتیب 0.78، 0.42و 0.75 بدست آمد. نتایج پژوهش نشان داد که بجز بخش های جنوب شرقی حوضه گرگانرود که شامل زیرحوضه‌های پل غزنوی و آق سو قوچمز که در کلاس شدت فرسایش شدید قرار دارند، سایر زیرحوضه‌ها در کلاس بسیار شدید قرار می‌گیرند. میزان فرسایش ویژه و رسوب ویژه کل حوضه به ترتیب 7656 و 862.26 مترمکعب در کیلومترمربع در سال برآورد شد. به منظور ارائه یک رابطه ریاضی نسبت تحویل رسوب برای حوضه آبریز گرگانرود، از فاکتورهای مساحت، محیط، شماره منحنی، طول آبراهه، بارش، دما، اختلاف ارتفاع و شیب متوسط زیرحوضه های مورد مطالعه در رگرسیون گام به گام استفاده شد. مدل رگرسیونی بدست آمده دارای ضریب تبیین 0.969 و خطای استاندارد 0.022، عملکرد بسیار خوبی در محاسبه مقدار sdr زیرحوضه های مور مطالعه نشان داد. متغیرهای شیب حوضه، طول آبراهه، دما و بارش به ترتیب بیشترین تاثیر را در برآورد sdr در حوضه گرگانرود داشتند. روش مورد استفاده در این تحقیق می تواند برای سایر حوضه های آبریز به منظور کمی سازی نرخ فرسایش کل و میزان رسوب خروجی از حوضه استفاده شود.

modeling the erosion potential and sedimentation rate of the gorganroud watershed

1-introductionthe erosion potential model (epm) is a widely used tool for estimating soil erosion and sediment yield in watersheds. it integrates multiple factors such as geological, topographic, climatic, and land use characteristics to predict erosion intensity and sediment transport. the model considers not only sheet and rill erosion but also gully erosion, wind, and tillage impacts. epm’s advantages include simplicity, low data requirements, and compatibility with geographic information systems (gis) for visualizing erosion-prone areas. soil erosion in iran, particularly in the golestan river basin, has been a growing concern due to population growth, land use changes, and poor water and soil management. the golestan basin has experienced severe erosion in several sub-basins, leading to increased sedimentation and damage to fertile soil. previous studies have applied epm in this region, estimating soil loss and sediment yield. this study aims to evaluate the application of epm alongside three sediment delivery ratio (sdr) equations in the golestan river basin to provide more accurate erosion assessments.2- methodologythe study employed a comprehensive set of spatial and hydrometric data for modeling erosion and sedimentation in the golestan river basin. data sources included meteorological, topographic, land use, geological, soil, geomorphological, and hydrometric information. meteorological data, covering the period from 1981 to 2024, were sourced from the chirps dataset. topographic data, derived from a 30-meter spatial resolution digital elevation model (dem), were used to assess the impact of slope and elevation on erosion. land use maps, based on sentinel-2 satellite images, tracked changes in vegetation and urban development from 2000 to 2022. geological maps, soil maps, and geomorphological data were used to assess factors like soil permeability, texture, and basin morphology. hydrometric data from 11 stations provided sediment concentration data to validate the model’s predictions. the study also applied regression analysis to identify the relationship between variables (e.g., area, perimeter, slope, precipitation) and sediment production. all data were processed in gis software, including arcgis, global mapper, and saga gis, allowing for spatial analysis and the generation of erosion potential maps.3-resultsthe study revealed significant variations in sediment yield across the sub-basins of the gorganroud watershed, depending on the selected erosion model. for example, the gavrilovich model predicted higher sediment yields (e.g., 2.465 in the onq lghi sub-basin) compared to the bois and williams-brent models, which yielded lower estimates (e.g., 0.15726 in bois). the differences suggest that the gavrilovich model is more suitable for regions with steep slopes and severe erosion, while the bois and williams-brent models are more appropriate for flatter, less erosive areas. regression analysis identified several key factors influencing sediment production: area, perimeter, river length, slope, curve number, temperature, elevation difference, and rainfall. these variables, particularly slope and rainfall, were found to have a strong correlation with erosion intensity and sediment yield. areas with steep slopes, high rainfall, and low soil permeability were identified as the most vulnerable to erosion.4- discussion & conclusions the results demonstrated that the epm is an effective tool for estimating erosion and sediment yield in the gorganroud watershed. climatic factors, especially temperature and precipitation, played a significant role in erosion processes, with intense rainfall events leading to increased surface runoff and sediment transport. the topography of the watershed, particularly its steep gradients, also contributed to higher erosion rates. the average slope of the watershed was 21.39%, with some areas exceeding 40%, leading to significant sediment loss. key factors like curve number (cn) and elevation differences were found to influence runoff intensity and soil permeability. areas with high cn values and large elevation differences experienced greater erosion due to higher runoff and soil displacement. human activities, including overgrazing and land conversion for agriculture, were identified as additional contributors to erosion. the modeling results revealed that most sub-basins experienced extreme erosion intensity (class v), while only a few showed severe erosion (class iv). the model demonstrated a high level of accuracy, with a coefficient of determination (r²) of 0.969 and a standard error of 0.022. validation using hydrometric data and statistical methods like roc and auc confirmed the model’s reliability in predicting erosion and sediment yield. in conclusion, the epm model proved to be a valuable tool for identifying areas of high erosion risk and understanding the factors contributing to sediment production. however, the accuracy of the model is highly dependent on the quality of input data. in areas with insufficient data, model predictions may be less reliable. to mitigate erosion and improve sediment conditions in the watershed, the study recommends integrating epm into land management strategies, such as vegetation restoration and sustainable water resource management. by considering the specific characteristics of each sub-basin and selecting the most appropriate erosion model, policymakers and land managers can better address soil erosion challenges and develop effective strategies for soil conservation in the golestan river basin.