مدلسازی احتمال وقوع و بررسی اثر مکانی عوامل موثر بر فرسایش گالی با استفاده از رگرسیون درختی تقویت شده

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه خاکشناسی، دانشکده کشاورزی، دانشگاه تربیت مدرس، تهران، ایران

2 گروه مهندسی منابع آب ، دانشکده کشاورزی دانشگاه تربیت مدرس، تهران، ایران

چکیده

سابقه و هدف:
فرسایش گالی یکی از انواع فرسایش آبی محسوب میشود که در طی پیشرفت این نوع فرسایش، زمینهای کشاورزی به شکل غیرقابل استفاده درمیآیند. با در نظر گرفتن شرایط جغرافیایی و محیطی، عوامل متنوعی در ایجاد و گسترش فرسایش گالی تأثیر دارند. در تحقیق حاضر با توجه به گسترش شدید فرسایش گالی در منطقهی جعفرآباد مغان و آسیب رساندن به زمینهای کشاورزی و مرتعی مرغوب، به مدلسازی احتمال وقوع و بررسی عوامل تأثیرگذار در رخداد فرسایش گالی در منطقه پرداخته شده است.
مواد و روشها:
در این مطالعه که در منطقه جعفرآباد مغان (قره دره) انجام پذیرفت، تأثیر فاکتورهای شیب، جهت شیب، انحنای شیب، ارتفاع، درصد رس خاک افق A ،درصد رس افق B ،درصد شن افق A ،درصد شن افق B ،میزان ماده آلی خاک سطحی، فاصله از جادهها و فاصله از رودخانه ها با استفاده از مدل رگرسیون درختی تقویت شده مورد بررسی قرار گرفت و همچنین نقشه پیشبینی فرسایش گالی منطقه نیز تهیه گردید.
نتایج و بحث:
نتایج نشان داد که فاکتورهای فاصله از رودخانه، درصد شن افق A ،درصد رس افق A و همچنین میزان ماده آلی خاک سطحی بهترتیب با درصد تأثیر 16.3 ،13.1 ،11.4 و 10.4 ،بیشترین مشارکت را در احتمال رخداد فرسایش گالی داشتند. و همچنین کمترین تأثیر مربوط به جهت شیب و ارتفاع به ترتیب با5.4 و 5.5 درصد مشارکت بوده که میتواند بهدلیل نبود تغییرات ارتفاعی چشمگیر در منطقه باشد. براساس نقشه پیشبینی مشخص گردید که 10.63 درصد از مساحت منطقهی مورد مطالعه در طبقه حساسیت بسیار زیاد قرار گرفته است. مقدار AUC برای مدل رگرسیون درختی تقویت شده در این تحقیق0.81 محاسبه گردید که نشان دهنده تخمین خوب مدل در پیشبینی مناطق حساس به فرسایش گالی است
نتیجه گیری:
نتایج بهدست آمده از این تحقیق، نشان از تأثیر باالی ویژگی های سطحی زمین در شروع فرسایش گالی را دارد. با توجه به اینکه بیشترین تأثیر در احتمال رخداد فرسایش گالی مربوط به فاصله از رودخانه و ویژگی های خاک سطحی میباشد، میتوان با مدیریت آبراهه ها و گالی های رخ داده و همچنین افزایش دانش کشاورزان منطقه در مورد اهمیت مدیریت خاک و کشاورزی پایدار، میزان حساسیت زمینهای منطقه به فرسایش گالی را کاهش داد. نتایج بهدست آمده نشان از مناسب بودن مدل رگرسیون درختی تقویت شده برای انجام تحقیق های مشابه میباشد.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling the probability of gully occurrence and investigating the spatial effects of its drivers using the boosted tree regression

نویسندگان [English]

  • Hossein Talebi Khiavi 1
  • Hossein Shafizadeh Moghadam 2
  • Mostafa Karimian Eghbal 1
1 Department of Soil Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
2 Department of Water Resources Engineering, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
چکیده [English]

Introduction:
Gully erosion is a subtype of water erosion that makes agricultural lands impracticable during its development. Given the geographical and environmental conditions, various factors contribute to the development and expansion of gully erosion. In this study, due to the extensive expansion of gully erosion in Jafarabad Moghan, and damaging the agricultural lands and rangelands, the probability of gully occurrence and the spatial effects of its drivers has been investigated.
Material and methods:
In this study, using a boosted regression tree model, the effect of the following factors on the gully occurrence were investigated: slope, aspect, plan curvature, altitude, clay content of horizon A, clay content of horizon B, sand content of horizon A, sand content of horizon B, surface organic matter, distance from roads, and distance from rivers. Then, the susceptibility map of the gully erosion was created.
Results and discussion:
The results showed that the distance from river, the sand content of horizon A, the clay content of horizon A, and the surface organic matter with 16.3%, 13.1%, 11.4% and 10.7%. respectively, were the most important influential factors on gully occurrence. On the other hand, aspect (4.5%) and elevation (5.5%) were the least important ones, which could be due to the lack of significant elevation shift in the region. Based on the susceptibility map, 10.63% of the study area was classified as very sensitive to the gully erosion. The AUC value for the boosted tree regression model was 0.81, which indicated a good model performance in the prediction of areas sensitive to gully erosion.
Conclusion:
The results of this study showed the critical influence of surface soil properties on the gully erosion. Considering the fact that the greatest effect on the probability of gully erosion was related to distance from the river and surface soil properties, it is possible to manage the lands susceptible to gully erosion by effective management of streams and existing gullies, and also by training the farmers and increasing their knowledge regarding gully erosion, land management, and sustainable agriculture. The results indicated the suitability of the boosted regression trees for similar studies.

کلیدواژه‌ها [English]

  • Modeling
  • Spatial effect
  • Gully erosion
  • Regression trees

مراجع

  1. Agnesi, V., Angileri, S., Cappadonia, Ch., Conoscenti, Ch. And Rotigliano, E. 2011. Multi-parametric GIS analysis to assess gully erosion susceptibility: a test in southern Sicily, Italy. Landform Analysis. 17, 15-20.
  2. Ahmadi, H. 1999. Apllied Geomorphology, 1, University of Tehran. Tehran.
  3. Basga, S. D., Tsozue, D., Temga, J. P., Balna, J. and Nguetnkam, J. P. 2018. Land use impact on clay dispersion/flocculation in irrigated and flooded vertisols from Northern Cameroon. International Soil and Water Conservation Research, 6(3), 237–244.
  4. Boix-Fayos, C., Calvo-Cases, A., Imeson, A. . and Soriano-Soto, M. 2001. Influence of soil properties on the aggregation of some Mediterranean soils and the use of aggregate size and stability as land degradation indicators. CATENA, 44(1), 47–67.
  5. Bouyoucos, G.J. 1962. Hydrometer method improved for making particle size analyses of soils. Agronomy journal. 54, 464-465.
  6. Bouyoucos, G.J. 1962. Hydrometer method improved for making particle size analyses of soils. Agronomy journal. 54, 464-465.
  7. Breiman, L., Friedman, J., Olshen, R. and Stone, C. 1984. Classification and Regression Trees. Chapman and Hall/CRC press. Boca Raton, FL.
  8. Choi, Y., Park, H. and Sunwoo, C., 2008. Flood and gully erosion problems at the Pasir open pit coal mine, Indonesia: a case study of the hydrology using GIS. Bull. Eng. Geol. Environ. 67, 251–258.
  9. Conforti, M., Aucelli, P. P. C., Robustelli, G. and Scarciglia, F. 2010. Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy). Natural Hazards, 56(3), 881–898.
  10. Conoscenti, C., Angileri, S., Cappadonia, C., Rotigliano, E., Agnesi, V. and Märker, M. 2014. Gully erosion susceptibility assessment by means of GIS-based logistic regression: a case of Sicily (Italy). Geomorphology 204 (1), 399–411.
  11. Douglas, I. and Pietroniro, A. 2003. Predicting road erosion rates in selectively logged tropical rain forests. In: de Boer, D., Froehlich, W., Mizuyama, T. (Eds.), Erosion Prediction in Ungauged Basins, Integrating Methods and Techniques. Proceedings of an International Symposium Sapporo, Japan, 8–9 July2003. IAHS Press, Wallingford, UK, pp. 199–205.
  12. Dube, F., Nhapi, I., Murwira, A., Gumindoga, W., Goldin, J. and Mashauri, D.A. 2014. Potential of weight of evidence modelling for gully erosion hazard assessment in Mbire District – Zimbabwe. Phys. Chem. Earth 67, 145–152.
  13. Esmaeili, R. and Shokati, R. 2015. Gully erosion susceptibility assessment using logestic regression in Salavat Abad basin of kurdistan province. Geographic studies of arid regions. 20, 91-104.
  14. Fernandez-Illescas, C.P., Porporato, A., Laio, F. and Rodriguez-Iturbe, I., 2001. The ecohydrological role of soil texture in a water-limited ecosystem. Water Resour. Res. 37 (12), 2863–2872.
  15. Gayen, A., Pourghasemi, H. R., Saha, S., Keesstra, S. and Bai, S., 2019. Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms. Science of The Total Environment. 668, 124-138.
  16. Ghahroodi, M. 2003. Danger zoning model due to the expansion of gully erosion. In Koloche Bijar watershed with GIS and RS. Ministry of Energy research project.
  17. Ghodousi, J. and Davari, M. 2005. The effect of soil physical an chemical properties on gully erosion and morphology of gully. 3rd Erosion and Sediment National conference 28 august, Tehran.
  18. Gholchin, A. 2016. Soil Organic Matter. Jahad Daneshghahi, Zanjan.
  19. Gyssels, G., Poesen, J., Nachtergaele, J. and Govers, G., 2002. The impact of sowing density of small grains on rill and ephemeral gully erosion in concentrated flow zones. Soil Tillage Res. 64 (3), 189–201.
  20. Igwe, C. A., Zarei, M., and Stahr, K. (2013). Stability of aggregates of some weathered soils in south-eastern Nigeria in relation to their geochemical properties. J. Earth Syst. Sci. 122(5), 1283-1294.
  21. Jafari Garzin, B. and Kavian, A. 2009. Estimation of Gully Erosion in Sorkh Abad watershed of Mazandaran using RS and GIS. Iran watershed management science and Engineering. 3, 55-58.
  22. Kay, BD. and Angers, DA. 1999. Soil Structure. In ME Sumner (ed) ”Handbook of Soil Science”. (CRC Press. Boca Raton USA).
  23. Maghsoudi, M., Shadfar, S. and Abbasi. M. 2012. Susceptibility mapping of gully erosion in Zavarian watershed. Quantitative geomorphology studies. 2, 35-52.
  24. Moore, I.D., Grayson, R.B. and Ladson, A.R., 1991. Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrological Processes. 5, 3–30.
  25. Morgan, Soil Erosion and Conservation, Alizadeh, Amin.
  26. Nguyen, N. M., Dultz, S., Kasbohm, J. and Le, D. 2009. Clay dispersion and its relation to surface charge in a paddy soil of the Red River Delta. Vietnam. Journal of Plant Nutrition & Soil Science 172, 477–486.
  27. Parkner, T., Page, M., Marden, M. and Marutani, T. 2007. Gully system Under Undisturbed indigenous forest East Coast Region New Zealand, Geomorphology. 84, 241-253.
  28. Poesen, J., Nachtergaele, J., Verstraeten, G. and Valentin C., 2003. Gully Erosion and Environment Change: Importance and Research Needs. Catena. 50, pp 91-133.
  29. Poesen, J., Vandaele, K. and Wesemael, B., 1998. Gully erosion: importance and model implications. In: Boardman, J., Favis-Mortlock, D. (Eds.), Modelling Soil Erosion by Water. Springer, Berlin, pp. 285–311.
  30. Pulice, I., Scarciglia, F., Leonardi, L., Robustelli, G., Conforti, M., Cuscino, M., Lupiano, V. and Critelli, S. 2009. Studiomultidisciplinare di forme e processi denudazionali nell’area di Vrica (Calabria orientale). Bollettinodella Societa ` Geografica Italiana 87(I–II):399–414.
  31. Rahmati, O., Tahmasebipour, N., Haghizadeh, A., Pourghasemi, H. R. and Feizizadeh, B., 2017. Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion. Geomorphology, 298, 118–137.
  32. Refahi, H. 2006. Water Erosion and coservation. 2298. University of Tehran press. Tehran.
  33. Sayadi, M. 2006. Investigation the Effect of some factors Affecting the Development of Gully Erosion in the Loess formation( case study of Emam Kakhi watershed in Golestan Province). M. Sc. Thesis. Gorgan university of Agricultural science and Natural Resources. Gorgan.
  34. VALENTIN C., Poesen J. and Li, Y. 2005. Gully erosion: Impacts, factors and control. Catena, 63, 132-153.
  35. VALENTIN, C., Poesen, J. and Li, Y., 2005. Gully erosion: Impacts, factors and control. Catena. 63, 132-153.
  36. Vandekerckhove, L., Poesen, J. and Govers, G., 2003. Medium-term gully headcut retreat rates in Southeast Spain determined from aerial photographs and ground measurements. Catena 50 (2), 329–352
  37. Voelkner, A., Holthusen, D. and Horn, R. 2015. Influence of anaerobic digestate amendment on the physicochemical properties of differently textured soils using homogenized residues. J. Plant Nutr. Soil Sci. 178 (2), 261–269.
  38. Walkley, A. and Black, l. A. 1934. An examination of the Degtjareff method for determining soil organci matter and a proposed modification of the chromic acid titration method. Soil Science. 37, 29-38.
فصلنامه علوم محیطی
دوره 18، شماره 3
مهر 1399
صفحه 167-183

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