دوره 11، شماره 2 - ( 6-1403 )
جلد 11 شماره 2 صفحات 159-137 |
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Asgari S, Shirani K. Evaluation of the effective factors in gully erosion sensitivity using Dempster-Shafer. Journal of Spatial Analysis Environmental Hazards 2024; 11 (2) : 8
URL: http://jsaeh.khu.ac.ir/article-1-3433-fa.html
URL: http://jsaeh.khu.ac.ir/article-1-3433-fa.html
عسگری شمس اله، شیرانی کورش. ارزیابی عوامل موثر در حساسیت پذیری فرسایش گالی با استفاده از مدلهای دمپسترشیفر و آنتروپی. تحلیل فضایی مخاطرات محیطی. 1403; 11 (2) :137-159
1- ستادیار بخش تحقیقات منابع طبیعی و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران. ، Shamsasgari@yahoo.com
2- دانشیار پژوهشکده حفاظت خاک و آبخیزداری ، سازمان تحقیقات، آموزش و ترویج کشاورزی تهران، ایران.
2- دانشیار پژوهشکده حفاظت خاک و آبخیزداری ، سازمان تحقیقات، آموزش و ترویج کشاورزی تهران، ایران.
چکیده: (1066 مشاهده)
فرسایش گالی یکی از اشکال پیشرفته فرسایش خاک است که تحلیل و شناسایی آن در جهت حفاظت خاک ضرورت دارد. هدف این تحقیق تعیین آستانه عوامل موثر در فرسایش گالی می باشد بنابراین براساس سوابق تحقیقات دیگران عوامل تاثیر گذار بر فرسایش گالی انتخاب شدند. جهت دستیابی به هدف تحقیق از دو مدل معروف دمپستر شیفر و مدل آنتروپی استفاده شده است. جهت تعیین مهم ترین متغیرها از آزمون جک نایف و برای مشخص نمودن قدرت پیش بینی مدلها از منحنی ROC استفاده شد. با استفاده از تصاویر گوگل ارث و همچنین بازدیدهای میدانی 331 نقطه گالی شناسایی، ثبت و نقشه پراکنش گالی تهیه شد. داده‌های مکانی پراکنش فرسایش گالی در قالب دو دسته تصادفی آموزشی (70 درصد) و آزمایشی (30 درصد) تقسیم شدند. نتایج خروجی لایه ها، وزن دهی و کلاس بندی و تلفیق در دو مدل دمپستر شیفر و آنتروپی، استخراج نقشه پهنه بندی حساسیت فرسایش پذیری گالی و آستانه حساسیت فرسایش پذیری گالی برای هر عامل می‌باشد. بر اساس آزمون جک نایف به ترتیب متغیرهای شاخص کاربری اراضی 33درصد، شاخص تراکم آبراهه 17درصد، لیتولوژی 13درصد، اقلیم 10درصد، بارش 5 درصد شاخص پوشش گیاهی 4 درصد و شاخص ارتفاع 2 درصد که در مجموع 84 درصد می باشند، بیشترین تأثیر را در فرسایش خندقی داشتند. سطح زیر منحنی مشخصه عملکرد سیستم ROC و مساحت سطح زیر نمودار AUC مدل دمپستر شیفر با ضریب تبیین 934/0 و مدل حداکثر آنتروپی با ضریب تبیین 936/0 موفقیت هر دو مدل را نشان می دهد. نتایج علمی تحقیق قابل ترویج و آموزش می باشد و از لحاظ کاربردی دستگاه اجرایی ذی ربط جهت کنترل فرسایش گالی می تواند تمهیدات لازم را با استفاده از نتایج این تحقیق بکار گیرد.
شماره‌ی مقاله: 8
فهرست منابع
1. Ahmadpour H., Bazrafshan O., Rafiei-Sardooi E., Zamani H., Panagopoulos T. 2021. Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection. Sustainability, 13(18): 10110.
2. Alencar, P.H.L., Simplício, A.A.F., de Araújo, J.C., (2022). Entropy-based Model for Gully Erosion – A combination of probabilistic and deterministic components, Science of The Total Environment, 836(155629), 0048-9697, [DOI:10.1016/j.scitotenv.2022.155629.]
3. Azareh, A., Rahmati, O., Rafiei-Sardooi, E., Joel B. Sankey, J.B., Lee, S., Shahabi, H., Ahmad, B., (2019) Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models, Science of The Total Environment, 655(0048-9697): 684-696, [DOI:10.1016/j.scitotenv.2018.11.235.]
4. Bernini, Alice, Alberto Bosino, Greg A. Botha, and Michael Maerker. 2021. "Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa" ISPRS International Journal of Geo-Information 10, no. 11: 729. [DOI:10.3390/ijgi10110729.]
5. Castillo C., Gómez J. A. 2016. A century of gully erosion research: Urgency, complexity and study approaches. Earth-Science Reviews, 160: 300-319. [DOI:10.1016/j.earscirev.2016.07.009]
6. Conforti, Massimo, and Fabio Ietto. 2024. "Testing the Reliability of Maximum Entropy Method for Mapping Gully Erosion Susceptibility in a Stream Catchment of Calabria Region (South Italy)" Applied Sciences 14, no. 1: 240. [DOI:10.3390/app14010240.]
7. Dube F., Nhapi I., Murwira A., Gumindoga W., Goldin J., Mashauri D.A. 2014. Potential of weight of evidence modeling for gully erosion hazard assessment im Mbire Distract- Zimbabwe. Physics and Chemistry of the Earth 67-69:145-152.
8. Gayen.A, Pourghasemi.H. R, Saha.S, Keesstra.S, Bai.S. 2019. Gully erosion susceptibility assessment and management of hazardprone areas in India using different machine learning algorithms, Science of the Total Environment, 668:124-138. [DOI:10.1016/j.scitotenv.2019.02.436.]
9. Kalehhouie M., Kavian A., Gholami L., Jafarian Z. 2020. Influence of Start Time and Coefficient of Runoff to Application of Organic Mulch under Small Laboratory Plots. Iranian Journal of Watershed Management Science and Engineering, 13(47): 9-17. (In Persian)
10. Kou M., Jiao J., Yin Q., Wang N., Wang Z., Li Y., Yu W., Wei Y., Yan F., Cao B. 2016. Successional trajectory over 10 years of vegetation restoration of abandoned slope croplands in the hill‐gully region of the Loess Plateau. Land Degradation & Development, 27(4): 919-932.
11. Madadi, A., Asghari Saraskanroud, S., Negahban, S., Marhamat, M. (2022). 'Evaluation of Gully Erosion Sensitivity using Maximum Entropy Model in Shoor River Watershed (Mohr Township)', Journal of Geography and Environmental Hazards, 11(3), pp. 123-145. doi: 10.22067/geoeh.2022.76707.1228.
12. Maerker M., Que´ne´herve.G. Bachofer. F., Mori S. 2015 A simple dem assessment procedure for gully system analysis in the lake manyara area, northern tanzania.79:235–253.
13. mohamkhan, S., pirani, P., riahi, S., geravand, F. (2020). 'Evaluation of entropy model efficiency in erosion zoning of kand watershed with geomorphologic approach', Geographical Planning of Space, 9(34), pp. 85-98. doi: 10.30488/gps.2019.100315.
14. Obrien, R. M., 2007. A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41: 673-690.
15. Poesen J., Nachtergaele J., Verstraeten G., Valentin, C. 2003. Gully erosion and environmental change: importance and research needs. Catena, 50(2-4): 91-133.
16. Saber chenari, K., Bahremand, A., Sheikh, V. B., Komaki, C. B. (2016). 'Gully Erosion Hazard Zoning Using of Dempster-Shafer Model in The Gharnaveh Watershed, Golestan Province', Iranian journal of Ecohydrology, 3(2), pp. 219-231. doi: 10.22059/ije.2016.59663.
17. Saeediyan, H., shirani, K., salajegheh, A., ahmadi, R. (2023). 'Investigating the performance of the entropy maximum model in determining the importance of effective environmental factors in creating gully erosion in semi-arid areas', Journal of New Approaches in Water Engineering and Environment, 2(1), pp. 129-144. doi: 10.22034/nawee.2023.407297.1047
18. Shahbazi K, Khosrowshahi M, Heshmati M, Ghietury M. 2020. Effects of Geological and Topographical Factors on Determining Gully Erosion Thresholds. Journal of Watershed Management Research, 11 (21): 259-268. (In Persian)
19. Shahbazi, K., parvizi, Y., Kalehhouei, M. (2022). 'Morphometric factors affecting gully erosion development and its climatic zoning in Kermanshah Province, Iran', Watershed Engineering and Management, 14(4), pp. 528-548. doi: 10.22092/ijwmse.2022.356146.1919.
20. Vosoghi, S., Zakerinejad, R., entezari, M. (2023). 'Prediction of Gully Erosion and identifying factors affecting it using the Maximum Entropy Model and BCC-CSM2-MR climate change models for the years 2020-2040 (case study: Alamarvdasht watershed)', Journal of Geography and Planning, (), pp. -. doi: 10.22034/gp.2023.57572.3169.
21. Tadesual, A., Setargie, M., Ebabu, K., Nzioki, B. and Meshesha, T.M., 2023. Random Forest–based gully erosion susceptibility assessment across different agro-ecologies of the Upper Blue Nile basin, Ethiopia. Geomorphology, 431, p.108671. [DOI:10.1016/j.geomorph.2023.108671.]
22. Teimurian, T., Nazari Samani, A., Feiznia, S., Ahmadaali, K., Soleimanpour, S. M. (2022). 'Determining the Spatial Distribution of Gully Erosion Probability Using the MaxEnt Model', Watershed Management Research Journal, 35(2), pp. 2-15. doi: 10.22092/wmrj.2021.354647.1415.
23. Yousefi Mobarhan E, Shirani K. (2023). Assessment of Maximum Entropy (ME) to identify Effective Factors on Gully Erosion and Determination of Sensitive Areas in Alaa Semnan Watershed. J Watershed Manage Res. 14(28), 37-54. Doi: 10.61186/jwmr.14.28.37
24. Ahmadpour H., Bazrafshan O., Rafiei-Sardooi E., Zamani H., Panagopoulos T. 2021. Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection. Sustainability, 13(18): 10110.
25. Alencar, P.H.L., Simplício, A.A.F., de Araújo, J.C., (2022). Entropy-based Model for Gully Erosion – A combination of probabilistic and deterministic components, Science of The Total Environment, 836(155629), 0048-9697, [DOI:10.1016/j.scitotenv.2022.155629.]
26. Azareh, A., Rahmati, O., Rafiei-Sardooi, E., Joel B. Sankey, J.B., Lee, S., Shahabi, H., Ahmad, B., (2019) Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models, Science of The Total Environment, 655(0048-9697): 684-696, [DOI:10.1016/j.scitotenv.2018.11.235.]
27. Bernini, Alice, Alberto Bosino, Greg A. Botha, and Michael Maerker. 2021. "Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa" ISPRS International Journal of Geo-Information 10, no. 11: 729. [DOI:10.3390/ijgi10110729.]
28. Castillo C., Gómez J. A. 2016. A century of gully erosion research: Urgency, complexity and study approaches. Earth-Science Reviews, 160: 300-319. [DOI:10.1016/j.earscirev.2016.07.009]
29. Conforti, Massimo, and Fabio Ietto. 2024. "Testing the Reliability of Maximum Entropy Method for Mapping Gully Erosion Susceptibility in a Stream Catchment of Calabria Region (South Italy)" Applied Sciences 14, no. 1: 240. [DOI:10.3390/app14010240.]
30. Dube F., Nhapi I., Murwira A., Gumindoga W., Goldin J., Mashauri D.A. 2014. Potential of weight of evidence modeling for gully erosion hazard assessment im Mbire Distract- Zimbabwe. Physics and Chemistry of the Earth 67-69:145-152.
31. Gayen.A, Pourghasemi.H. R, Saha.S, Keesstra.S, Bai.S. 2019. Gully erosion susceptibility assessment and management of hazardprone areas in India using different machine learning algorithms, Science of the Total Environment, 668:124-138. [DOI:10.1016/j.scitotenv.2019.02.436.]
32. Kalehhouie M., Kavian A., Gholami L., Jafarian Z. 2020. Influence of Start Time and Coefficient of Runoff to Application of Organic Mulch under Small Laboratory Plots. Iranian Journal of Watershed Management Science and Engineering, 13(47): 9-17. (In Persian)
33. Kou M., Jiao J., Yin Q., Wang N., Wang Z., Li Y., Yu W., Wei Y., Yan F., Cao B. 2016. Successional trajectory over 10 years of vegetation restoration of abandoned slope croplands in the hill‐gully region of the Loess Plateau. Land Degradation & Development, 27(4): 919-932.
34. Madadi, A., Asghari Saraskanroud, S., Negahban, S., Marhamat, M. (2022). 'Evaluation of Gully Erosion Sensitivity using Maximum Entropy Model in Shoor River Watershed (Mohr Township)', Journal of Geography and Environmental Hazards, 11(3), pp. 123-145. doi: 10.22067/geoeh.2022.76707.1228.
35. Maerker M., Que´ne´herve.G. Bachofer. F., Mori S. 2015 A simple dem assessment procedure for gully system analysis in the lake manyara area, northern tanzania.79:235–253.
36. mohamkhan, S., pirani, P., riahi, S., geravand, F. (2020). 'Evaluation of entropy model efficiency in erosion zoning of kand watershed with geomorphologic approach', Geographical Planning of Space, 9(34), pp. 85-98. doi: 10.30488/gps.2019.100315.
37. Obrien, R. M., 2007. A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41: 673-690.
38. Poesen J., Nachtergaele J., Verstraeten G., Valentin, C. 2003. Gully erosion and environmental change: importance and research needs. Catena, 50(2-4): 91-133.
39. Saber chenari, K., Bahremand, A., Sheikh, V. B., Komaki, C. B. (2016). 'Gully Erosion Hazard Zoning Using of Dempster-Shafer Model in The Gharnaveh Watershed, Golestan Province', Iranian journal of Ecohydrology, 3(2), pp. 219-231. doi: 10.22059/ije.2016.59663.
40. Saeediyan, H., shirani, K., salajegheh, A., ahmadi, R. (2023). 'Investigating the performance of the entropy maximum model in determining the importance of effective environmental factors in creating gully erosion in semi-arid areas', Journal of New Approaches in Water Engineering and Environment, 2(1), pp. 129-144. doi: 10.22034/nawee.2023.407297.1047
41. Shahbazi K, Khosrowshahi M, Heshmati M, Ghietury M. 2020. Effects of Geological and Topographical Factors on Determining Gully Erosion Thresholds. Journal of Watershed Management Research, 11 (21): 259-268. (In Persian)
42. Shahbazi, K., parvizi, Y., Kalehhouei, M. (2022). 'Morphometric factors affecting gully erosion development and its climatic zoning in Kermanshah Province, Iran', Watershed Engineering and Management, 14(4), pp. 528-548. doi: 10.22092/ijwmse.2022.356146.1919.
43. Vosoghi, S., Zakerinejad, R., entezari, M. (2023). 'Prediction of Gully Erosion and identifying factors affecting it using the Maximum Entropy Model and BCC-CSM2-MR climate change models for the years 2020-2040 (case study: Alamarvdasht watershed)', Journal of Geography and Planning, (), pp. -. doi: 10.22034/gp.2023.57572.3169.
44. Tadesual, A., Setargie, M., Ebabu, K., Nzioki, B. and Meshesha, T.M., 2023. Random Forest–based gully erosion susceptibility assessment across different agro-ecologies of the Upper Blue Nile basin, Ethiopia. Geomorphology, 431, p.108671. [DOI:10.1016/j.geomorph.2023.108671.]
45. Teimurian, T., Nazari Samani, A., Feiznia, S., Ahmadaali, K., Soleimanpour, S. M. (2022). 'Determining the Spatial Distribution of Gully Erosion Probability Using the MaxEnt Model', Watershed Management Research Journal, 35(2), pp. 2-15. doi: 10.22092/wmrj.2021.354647.1415.
46. Yousefi Mobarhan E, Shirani K. (2023). Assessment of Maximum Entropy (ME) to identify Effective Factors on Gully Erosion and Determination of Sensitive Areas in Alaa Semnan Watershed. J Watershed Manage Res. 14(28), 37-54. Doi: 10.61186/jwmr.14.28.37
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