Volume 11, Issue 2 (8-2024)
Journal of Spatial Analysis Environmental Hazards 2024, 11(2): 137-159 |
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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-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3433-en.html
1- Assistant Prof, Soil Conservation and Watershed Management Research Department, Ilam Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran. , Shamsasgari@yahoo.com
2- Associate Professor , Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
2- Associate Professor , Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
Abstract: (1215 Views)
Gully erosion is one of the advanced forms of soil erosion, which needs to be analyzed and identified in order to protect the soil. In this research, according to the complex system of factors influencing the creation of ditch erosion, 23 factors were analyzed in the two famous Dempster-Schiffer models and the entropy model, and using Google Earth images and field visits, 331 ditch points were identified, recorded, and a ditch distribution map was prepared. Spatial data of gully erosion distribution were divided into two random training (70%) and experimental (30%) groups. In this research, two indicators of tolerance coefficient and variance inflation factor were used to check the collinearity test, and as a result, two indicators of waterway density and relative humidity index were removed and 21 factors were used in the modeling process. The output results of the layers, weighting and classification and integration in two Dempster-Schiffer and entropy models are the extraction of the zoning map of the gully's erodibility sensitivity. and 30% of the calibration and validation of the models, the area under the ROC system performance characteristic curve and the area under the AUC diagram of the Dempster-Schiffer model with an explanation factor of 0.934 and the maximum entropy model with an explanation factor of 0.936, both models have an acceptable percentage of the area under the curve were that this issue shows the high performance of both models in the region. Among other results of statistical analysis, the prioritization of the impact of 21 factors in causing ditch erosion in the region was determined. The scientific results of the research can be promoted and taught, and from the practical point of view, the relevant executive body to control ditch erosion can take the necessary measures using the results of this research.
Article number: 8
Keywords: Ilam basin, gully erosion, topographical indicators, maximum entropy model, Dempster Shafer model
Type of Study: Research |
Subject:
Special
Received: 2024/02/24 | Accepted: 2024/09/15 | Published: 2024/09/22
Received: 2024/02/24 | Accepted: 2024/09/15 | Published: 2024/09/22
References
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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