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رمضانی مهریان, مجید, زرندیان, اردوان, آل‌محمد, سیده, بادام فیروز, جلیل. (1404). ارزیابی میزان اجتناب از دو فرایند فرسایش خاک و رسوب‌دهی و ارائه بینش‌های مدیریتی. سامانه مدیریت نشریات علمی, 39(4), 485-492. doi: 10.22092/ijsr.2026.371627.804
مجید رمضانی مهریان; اردوان زرندیان; سیده آل‌محمد; جلیل بادام فیروز. "ارزیابی میزان اجتناب از دو فرایند فرسایش خاک و رسوب‌دهی و ارائه بینش‌های مدیریتی". سامانه مدیریت نشریات علمی, 39, 4, 1404, 485-492. doi: 10.22092/ijsr.2026.371627.804
رمضانی مهریان, مجید, زرندیان, اردوان, آل‌محمد, سیده, بادام فیروز, جلیل. (1404). 'ارزیابی میزان اجتناب از دو فرایند فرسایش خاک و رسوب‌دهی و ارائه بینش‌های مدیریتی', سامانه مدیریت نشریات علمی, 39(4), pp. 485-492. doi: 10.22092/ijsr.2026.371627.804
رمضانی مهریان, مجید, زرندیان, اردوان, آل‌محمد, سیده, بادام فیروز, جلیل. ارزیابی میزان اجتناب از دو فرایند فرسایش خاک و رسوب‌دهی و ارائه بینش‌های مدیریتی. سامانه مدیریت نشریات علمی, 1404; 39(4): 485-492. doi: 10.22092/ijsr.2026.371627.804

ارزیابی میزان اجتناب از دو فرایند فرسایش خاک و رسوب‌دهی و ارائه بینش‌های مدیریتی

پژوهش های خاک
دوره 39، شماره 4، اسفند 1404، صفحه 485-492    اصل مقاله (1.86 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22092/ijsr.2026.371627.804
نویسندگان
مجید رمضانی مهریان1؛ اردوان زرندیان2؛ سیده آل‌محمد* 3؛ جلیل بادام فیروز4
1گروه مطالعات محیطی، پژوهشکده تحقیق و توسعه علوم انسانی (سمت)، تهران، ایران
2گروه ارزیابی و مخاطرات محیط‌زیست، پژوهشکده محیط زیست و توسعه پایدار، تهران، ایران.
3گروه نوآوری و پایداری، دانشکده حکمرانی، دانشگاه تهران، تهران، ایران
4گروه اقتصاد محیط‌زیست، پژوهشکده محیط زیست و توسعه پایدار، تهران، ایران.
چکیده
فرسایش خاک و تولید رسوب به‌عنوان یکی از مخاطرات اصلی، پایداری اکوسیستم‌ها و توسعه پایدار در حوضه‌های استان زنجان را تهدید می‌کند. این پژوهش، با هدف ارزیابی کمی خدمات اکوسیستمی نگهداشت رسوب انجام شد. برای دستیابی به این هدف، از چارچوب مدل نسبت تحویل رسوب در نرم‌افزار InVEST استفاده شد. در گام اول، پتانسیل فرسایش خاک با به‌کارگیری معادله اصلاح‌شده جهانی هدررفت خاک(RUSLE) ، برآورد شد که عوامل فرسایندگی باران، فرسایش‌پذیری خاک، توپوگرافی، پوشش اراضی و اقدامات حفاظتی را تلفیق می‌کند. در مراحل بعد، رسوب‌گذاری و رسوب‌دهی نهایی در پیکسل‌ها، بر حسب نسبت تحویل رسوب و شاخص اتصال هیدرولوژیکی، محاسبه شد و سپس این مقادیر در سطح حوضه‌ها تجمیع شد. نتایج، توزیع مکانی ناهمگون و تمرکز قابل‌توجه فرسایش و تولید رسوب را در برخی حوضه‌ها آشکار ساخت. ارائه بینش‌های مدیریتی در حوضه‌ها، بر اساس مقایسه منطقی دو معیار فرسایش و رسوب‌دهی، در سه سطح اولویت، صورت پذیرفت. این پژوهش با کمّی‌سازی نقش بازدارنده پوشش گیاهی موجود در جلوگیری از فرسایش خاک و ورود رسوب به شبکه‌های آبی، بر ارزش خدمات اکوسیستمی تأکید می‌نماید. نوآوری مطالعه حاضر، گذار از ارزیابی‌های صرفاً کمّی به سمت ارائه بینش‌های مدیریتی مکان‌محور در مقیاس حوضه‌ها است. این نتایج برای تخصیص بهینه منابع و هدایت هدفمند طرح‌های حفاظتی و آبخیزداری به سوی پهنه‌های بحرانی، کارآمد است. تکرار و پیگیری چنین مطالعاتی در کشور، می‌تواند به تکمیل یک سامانه اطلاعات جغرافیایی پشتیبان و قابل اتکا برای اتخاذ شیوه‌های مدیریت انطباقی در راستای حفاظت از منابع پایه خاک و آب بینجامد.
کلیدواژه‌ها
فرسایش خاک؛ نسبت تحویل رسوب؛ رسوب‌دهی؛ خدمت اکوسیستمی؛ استان زنجان
عنوان مقاله [English]
Quantifying Avoided Soil Erosion and Sediment Export and Deriving Managerial Insights
نویسندگان [English]
Majid Ramezani Mehrian1؛ Ardavan Zarandian2؛ Sayedeh Alemohammad3؛ Jalil Badam Firouz4
1Department of Environmental Studies, the Institute for Research and Development in the Humanities (SAMT), Tehran, Iran.
2Department of Environmental Assessment and Risks, Research Center of Environment and Sustainable Development, Tehran, Iran.
3Department of Innovation and Sustainability, Faculty of Governance, University of Tehran, Tehran, Iran.
4Department of Environmental Econoomics, Research Center of Environment and Sustainable Development, Tehran, Iran.
چکیده [English]
Objectives

The primary objectives of this research were: 1) To conduct a spatial assessment and mapping of the sediment retention ecosystem service in the watersheds of Zanjan Province by quantifying avoided soil erosion and avoided sediment export. 2) To identify and delineate priority management areas at the watershed level and provide spatial strategies for enhancing the sediment retention service. The overarching goal was to bridge the gap between detailed biophysical evaluations and practical, location-specific decision-making for sustainable watershed management.

Methodology

The methodological core of this study was the Sediment Delivery Ratio (SDR) model implemented in the InVEST software suite. The process began with estimating soil erosion potential for each pixel using the RUSLE, which synthesizes data layers for rainfall erosivity (R), soil erodibility (K), the topographic length-slope factor (LS) derived from a 30m Digital Elevation Model (DEM), land cover (C), and conservation practices (P). Subsequently, the SDR for each pixel was calculated based on a hydrological connectivity index, balancing upslope resistance and downslope flow path factors. The sediment export from each pixel was then derived as the product of its USLE erosion potential and its SDR. Finally, the ecosystem services of "avoided erosion" (soil loss prevented at source by vegetation) and "avoided sediment export" (sediment prevented from entering streams) were quantified. All spatial data, including land use/land cover from Landsat 8 imagery, were standardized within a GIS environment to a consistent coordinate system and raster resolution for model execution.

Results

The application of the model across Zanjan Province revealed a highly heterogeneous spatial pattern of erosion and sediment dynamics. The total annual soil erosion potential and sediment export for the province were estimated, confirming the severity of the process. More importantly, the existing vegetative cover was quantified as providing a crucial ecosystem service by preventing a vastly greater amount of soil loss and sediment delivery to watercourses annually. Spatial aggregation of pixel-level results to the watershed scale enabled clear prioritization. Watershed 1 was identified as "Critical," contributing the dominant share to both total erosion potential and sediment export. watersheds 7 and 5 were categorized as "High Priority," while the remaining watersheds (2, 3, 4, 6) were classified as "Moderate to Low Priority." This stratification effectively pinpoints areas where management interventions would yield the highest return in terms of reducing sediment loads to vital water reservoirs.

Conclusion

This study successfully moved beyond conventional erosion modeling by translating complex biophysical assessments into operational, priority-ranked maps at a management-relevant scale. By integrating the RUSLE and SDR models within the InVEST framework, it provided a scientifically robust and spatially explicit basis for optimizing the allocation of limited conservation resources. The proposed spatial prioritization enables a shift from uniform, dispersed management approaches to a targeted, evidence-based strategy focused on critical intervention areas. The methodology and findings not only offer a direct and practical tool for watershed managers in Zanjan Province but also establish a replicable framework for adaptive and intelligent decision-making in other watersheds across Iran. Ultimately, this approach supports the development of a dynamic, integrated spatial information system for the national-scale protection of fundamental soil and water resources.
کلیدواژه‌ها [English]
Soil Erosion, Sediment Delivery Ratio, Sediment Export, Ecosystem Service, Zanjan Province
مراجع
  1. Alewell, C., Ringeval, B., Ballabio, C., Robinson, D.A., Panagos, P. and Borrelli, P., 2020. Global phosphorus shortage will be aggravated by soil erosion. Nature Communications, 11(1), p.4546. https://doi.org/10.1038/s41467-020-18326-7
    2.  Andualem, T. G., Hewa, G. A., Myers, B. R., Peters, S. and Boland, J., 2023. Erosion and sediment transport modeling: a systematic review. Land, 12(7), p. 1396. https://doi.org/10.3390/land12071396
    3.  Aneseyee, A. B., Elias, E., Soromessa, T. and Feyisa, G. L., 2020. Land use/land cover change effect on soil erosion and sediment delivery in the Winike watershed, Omo Gibe Basin, Ethiopia. Science of the Total Environment, 728, p. 138776. https://doi.org/10.1016/j.scitotenv.2020.138776
    4.  Bayatikhatibi, M. and ali, I., 2025. Soil erosion spatial mapping with RUSLE model; A case study of Quetta Sub-basin (Pakistan). Journal of Hydrogeomorphology, 11(41), PP. 86-67. https://hyd.tabrizu.ac.ir/article_18214.html
    5.  Borrelli, P., Robinson, D.A., Panagos, P., Lugato, E., Yang, J.E. and Alewell, C., 2021. Land use and climate change impacts on global soil erosion by water (2015-2070). Proceedings of the National Academy of Sciences, 117(36), pp. 21994-22001. https://doi.org/10.1073/pnas.2001403117
    6.  Bozali, N., 2020. Assessment of the soil protection function of forest ecosystems using GIS-based Multi-Criteria Decision Analysis: A case study in Adıyaman, Turkey. Global Ecology and Conservation, 24, p. 01271. https://doi.org/10.1016/j.gecco.2020.e01271
    7.  Cvitanovic, C., Shellock, R. J., Mackay, M., van Putten, E. I., Karcher, D. B., Dickey-Collas, M. and Ballesteros, M., 2021. Strategies for building and managing ‘trust’ to enable knowledge exchange at the interface of environmental science and policy. Environmental Science & Policy, 123, 179-189. https://doi.org/10.1016/j.envsci.2021.05.020
    8.  Desmet, P. J. J. and Govers, G., 1996. A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. Journal of Soil and Water Conservation, 51(5), pp. 427–433. https://doi.org/10.1080/00224561.1996.12457102
    9.  Ebrahimzadeh, S. , Argany, M. and Mirdar Harijani, F., 2024. Modeling the rate of soil erosion and sediment yield using the RUSLE / SDR model in the Dizgaran watershed. Journal of Natural Environmental Hazards, 13(39), 1-24. http://doi.org/10.22111/jneh.2024.39109.1823
    10.  Ganasri, B.P. and Ramesh, H., 2016. Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), pp. 953-961. https://doi.org/10.1016/j.gsf.2015.10.007
    11.  Hamel, P., Chaplin-Kramer, R., Sim, S. and Mueller, C., 2015. A new approach to modeling the sediment retention service (InVEST 3.0): Case study of the Cape Fear catchment, North Carolina, USA. Science of the Total Environment, 524, pp. 166-177. https://doi.org/10.1016/j.scitotenv.2015.04.027
    12.  Haregeweyn, N., Tsunekawa, A., Nyssen, J., Poesen, J., Tsubo, M. and Tsegaye Meshesha, D., 2017. Comprehensive assessment of soil erosion risk for better land use planning in river basins: Case study of the Upper Blue Nile River. Science of the Total Environment, 574, pp. 95-108. https://doi.org/10.1016/j.scitotenv.2016.09.019
    13.  Hosseinalizadeh, M., Alinejad, M., Mohammadian Behbahani, A., Khormali, F., Kariminejad, N., Pourghasemi, H.R. (2020). A Review on the Gully Erosion and Land Degradation in Iran. In: Shit, P., Pourghasemi, H., Bhunia, G. (eds) Gully Erosion Studies from India and Surrounding Regions. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-23243-6_26
    14.  Hosseini Mofrad, S. M. R. , Ahmadi, H. , Mehrabi, A. A. and Motamedvaziri, B., 2023. Investigating the effect of the construction of the new Hashtgerd - Taleghan road in Alborz province on the amount of erosion and sediment production using the WARSEM model. Journal of Range and Watershed Managment, 76(3), 237-251. http//doi.org/10.22059/jrwm.2023.354414.1694
  2. 15.  Iacona, G. D., Sutherland, W. J., Mappin, B., Adams, V. M., Armsworth, P. R., Coleshaw, T. and Possingham, H. P., 2023. Standardized reporting of the costs of management interventions for biodiversity conservation. Conservation Biology, 32(5), 979-988.  https://doi.org/10.1111/cobi.13195
    16.  IPBES, 2018. The IPBES assessment report on land degradation and restoration. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. https://www.ipbes.net/assessment-reports/ldr
    17.  Jafari, M., Tahmoures, M., Ehteram, M., Ghorbani, M. and Panahi, F., 2022. Soil erosion control in drylands (pp. 649-700). Springer. https://link.springer.com/book/10.1007/978-3-031-04859-3
    18.  Ji, C., Cao, Y., Li, X., Pei, X., Sun, B., Yang, X. and Zhou, W., 2024. A review of the satellite remote sensing techniques for assessment of runoff and sediment in soil erosion. Journal of Hydrology and Hydromechanics, 72(2), pp. 252-267. https://doi.org/10.2478/johh-2024-0009
    19.  Mahmood, S., Naeem, N., Ahamad, M. I., Tariq, Z. and Song, J., 2024. Spatial modeling of soil erosion potential in the Panjkora Basin, Eastern Hindu Kush: integrated RUSLE and geospatial approaches. Environment, Development and Sustainability, pp. 1-22. https://doi.org/10.1007/s10668-024-05709-9
    20.  Matomela, N., Li, T., Ikhumhen, H. O., Raimundo Lopes, N. D. and Meng, L., 2022. Soil erosion spatio-temporal exploration and Geodetection of driving factors using InVEST-sediment delivery ratio and Geodetector models in Dongsheng, China. Geocarto International, 37(26), pp. 13039-13056. https://doi.org/10.1080/10106049.2022.2076912
    21.  Mohammadi, S. , karimzadeh, H. , pourmanafi, S. and Soltani, S., 2018. Spatial and Temporal Evaluation of Soil Erosion using RUSLE model Landsat satellite image time series (Case Study: Menderjan, Isfahan). Journal of Range and Watershed Managment, 71(3), 759-774. https://doi.org/10.22059/jrwm.2018.221162.1073 (In Persian)
    22.  Motamedirad, M. , Zangane Asadi, M. A. and Ajam, H., 2023. Investigating the rate of soil erosion and sediment production using the RUSLE model and the modified method PSIAC (case study: kal basin of Ismail , Shahrood city, Semnan province). Quantitative Geomorphological Research, 11(4), 147-165. http://doi.org/10.22034/gmpj.2022.360813.1374 (In Persian)
    23.  Nasir, N. and Selvakumar, R., 2018. Influence of land use changes on spatial erosion pattern, a time series analysis using RUSLE and GIS: the cases of Ambuliyar sub-basin, India. Acta Geophysica, 66(5), pp. 1121-1130. https://doi.org/10.1007/s11600-018-0186-2
    24.  Panagos, P., Standardi, G., Borrelli, P., Lugato, E., Montanarella, L. and Bosello, F., 2022. Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models. Land Degradation & Development, 33(3), pp.459-471. https://doi.org/10.1002/ldr.2879
    25.  Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., & Alewell, C., 2014. Soil erodibility in Europe: A high-resolution dataset based on LUCAS. Science of the Total Environment, 479–480, 189–200. https://doi.org/10.1016/j.scitotenv.2014.02.010
    26.  Poesen, J., 2021. Soil erosion in the Anthropocene: Research needs. Earth Surface Processes and Landforms, 46(1), pp.5-13. https://doi.org/10.1002/esp.4250
    27.  Qurishi, S. M., 2024. Exploring the major watershed basins all around the world: a meta-analysis for basins characteristics. AUIQ Technical Engineering Science, 1(2), p. 9. https://doi.org/10.70645/3078-3437.1018
    28.  Redhead, J. W., Stratford, C., Sharps, K., Jones, L., Ziv, G., Clarke, D. and Bullock, J. M., 2016. Empirical validation of the InVEST water yield ecosystem service model at a national scale. Science of the Total Environment, 569, pp. 1418-1426. https://doi.org/10.1016/j.scitotenv.2016.06.227
  3. 29.  Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., & Yoder, D. C., 1997. Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook No. 537. https://directives.nrcs.usda.gov/sites/default/files2/1712932574/28651.pdf
    30.  Sadeghi, S. H. , Hashemi Ariyan, Z. , Vafakhah, M. and Karimi, Z., 2018. Comparison of Spatial Variations of Soil Erosion at Gonbad Representative and Treated Watersheds in Hamadan Province. Journal of Range and Watershed Managment, 71(2), 405-417. https://doi.org/10.22059/jrwm.2018.202889.984 (In Persian)
    31.  Sadeghi, S. H. R., 2017. Soil erosion in Iran: state of the art, tendency and solutions. Poljoprivreda i Sumarstvo, 63(3), 33-37. http://doi.org/10.17707/AgricultForest.63.3.04
    32.  Sharp, R., Douglass, J., Wolny, S., Arkema, K., Bernhardt, J., Bierbower, W., and Wyatt, K., 2020. InVEST User’s guide. The natural capital project, Standford university, University of Minnesota, the nature conservancy, and World Wildlife Fund: Standford, CA, USA. https://storage.googleapis.com/releases.naturalcapitalproject.org/invest/3.9.0/userguide/index.html
    33.  Vigiak, O., Borselli, L., Newham, L., McInnes, J. and Roberts, A., 2012. Comparison of conceptual landscape metrics to define hillslope-scale sediment delivery ratio. Geomorphology, 138 (1), pp. 74- 88. https://doi.org/10.1016/j.geomorph.2011.08.026
    34.  Williams, B. K.  Brown, E. D., 2016. Technical challenges in the application of adaptive management. Biological Conservation, 195, pp. 255-263. https://doi.org/10.1016/j.biocon.2016.01.012
    35.  Zarandian, A., Ramezani Mehrian, M., Mohammadyari, F., Mousazadeh, R., Azizi, N., 2024. Assessment and Economic Valuation of Ecosystem Services for Soil Erosion Prevention and Sediment Retention in the Khorkhoran International Mangrove Wetland. Iranian Journal of Applied Ecology, 13 (4), pp. 1-20. http://ijae.iut.ac.ir/article-1-1251-fa.html
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تعداد مشاهده مقاله: 47
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