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:: Volume 32, Issue 4 (3-2018) ::
geores 2018, 32(4): 105-126 Back to browse issues page
Comparison of Gully Erosion Susceptibility Mapping Using Weight of Evidence and Frequency Ratio Models at Sanganeh Kalat Basin
Majid Ebrahim * 1, Abolghasem Amir Ahmadi 1, Mohammad Ali Zangeneh Asadi 1
1- Department of Geomorphology, Hakim Sabzevari University, Sabzevar, Iran
Abstract:   (1184 Views)
Gully erosion is the most advanced type of water erosion in watersheds that produces large volumes of sediment that and cause a lot of damage. Thus mapping susceptibility to gully erosion and identification of factors can help managers and decision-makers to reduce the risk of erosion. The objective of the present study is to assess the capability of weights-of-evidence (WofE) and frequency ratio (FR) models for spatial prediction of gully erosion susceptibility and characterizing susceptibility conditions at Sanganeh Kalat Basin. At first, a gully erosion inventory map is prepared through extensive field study, then raster maps of the variables affecting the Gully Erosion (lithology, land use, distance from river, slope degree, slope direction, plan curvature, topographic wetness index, drainage density and altitude) in a database and Geographic Information System (GIS) was created. In total, of the 46 gullies which have been identified, 32 (70 %) cases are random algorithm selected to build gully susceptibility models, while the remaining 14 (30 %) cases are used to validate the models. The effectiveness of gully erosion susceptibility assessment via GIS-based models depends on appropriate selection of the conditioning factors, which play an important role in gully erosion. Learning vector quantization (LVQ), one of the supervised neural network methods, is employed in order to estimate variable importance. Finally, validation of the gully dataset which has not been utilized during the spatial modeling process is applied to validate the gully susceptibility maps. The receiver operating characteristic curves for each gully susceptibility map are drawn, and the areas under the curves (AUC) are calculated. The results show that the gully erosion susceptibility map produced by the frequency ratio model (AUC = 86.32 %) functions well in prediction compared to the wofe model (AUC = 73.49 %). Furthermore, LVQ results reveal that drainage density, slope degree, distance from river and topographic wetness index are the most effective factors
Keywords: Gully erosion, Bivariate statistical Models, Learning Vector Quantization (LVQ), Sanganeh Kalat Basin
Full-Text [PDF 3098 kb]   (680 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/06/8 | Accepted: 2017/12/8 | Published: 2018/03/17
References
1. ­Achten, W.M.J., Dondeyne, S., Mugogo, S., Kafiriti, E., Poesen, J., Deckers, J. (2008), Gully Erosion in South Eastern Tanzania Spatial Distribution and Topographic Thresholds, Zeitschrift für Geomorphologie, Vol. 52, No. 2, pp. 225-235.
2. ­Agnesi, V., Angileri, S., Cappadonia, C., Conoscenti, C., Rotigliano, E. (2011), Multi-parametric GIS Analysis to Assess Gully Erosion Susceptibility a Test in Southern Sicily, Italy, Landform Analysis, Vol.7, pp.15-20.
3. ­Ahalt, SC., Krishnamurthy, AK., Chen, P., Melton, D.E. (1990), Competitive learning algorithms for vector quantization. Neural networks, Vol. 3, No. 3, pp. 277-290.
4. ­Amir Ahmadi, A., Ebrahimi, M., Zangeneh Asadi, M.A., Habibolahian, M. (2012), A Study of Geomorphologic Instability Slope Anbalang Method Using GIS (Case Study: Kalat Basin in the Heights of Hezar Masjed, Journal of Geographical Research, Vol. 29, No. 4, pp. 241-259, (in Persian).
5. ­Anabalagan, R. (1992), Landslide Hazard Evaluation and Zonation Mapping in Mountainous Terrain, Engineering geology, Vol. 32, pp. 269-277.
6. ­Baeza, C., Corominas, J. (2001), Assessment of Shallow Landslide Susceptibility by Means of Multivariate Statistical Techniques, Earth surface processes and landforms, Vol. 26, pp. 1251-1263.
7. ­Bashari, M., Sadeghi, S.H., Rangavar, A. (2012), Comparison of Sediment Yield at Two North and South Facing Slopes ‎Using Small Plots, Watershed Engineering and Management, Vol. 3, pp. 134-140 (in Persian).
8. ­Bayati Khatibi, M., Karami, F. (2015), Estimation of Water Erosion and Soil Lose from Single Gully on Atashbeig Catchment Surface, Journal of Hydrogeomorphology, Vol. 3, No. 7, pp. 87-106, (in Persian).
9. ­Bonham-Carter, GF. (1991), Integration of Geoscientific Data Using GIS, In: Goodchild MF, Rhind DW, Maguire DJ (eds) Geographic information systems: principle and applications, Kingdom, London, pp. 171-184.
10. Bonham-Carter, GF. (1994), Geographic Information Systems for Geoscientists: Modeling with GIS, In Bonham-Carter F (ed), Computer methods in the Geosciences, Pergamon, Oxford.
11. ­Boukheir, R., Chorowicz, J., Chadi, A., Dhont, D. (2008), Soil and Bedrock Distribution Estimated from Gully form and Frequency: a GIS-based decision-tree model for Lebanon, Geomorphology, Vol, 93, pp. 482-492.
12. ­Casali, J., Lopez, J.J., Giraldez, J.V. (1999), Ephemeral Gully Erosion in Southern Navarra (Spain), Catena, Vol. 36, pp. 65-84.
13. ­Cevik, E., Topal, T. (2003), GIS-based Landslide Susceptibility Mapping for a Problematic Segment of the Natural Gas Pipeline, Hendek (Turkey), Environmental geology, Vol. 44, pp. 949-962.
14. ­Chaplot, V. (2013), Impact of Terrain Attributes, Parent Material and Soil Types on Gully Erosion, Geomorphology, Vol. 186, pp.1-11.
15. ­Chaplot, V., Giboire, G., Marchand, P., Valentin, C. (2005), Dynamic Modelling for Linear Erosion Initiation and Development Under Climate and Land-use Changes in Northern Laos, Catena, Vol. 63, pp. 318-328.
16. ­Choi, Y., Park, H., Sunwoo, C. (2008), Flood and Gully Erosion Problems at the Pasir Open Pit Coal Mine, Indonesia a Case Study of the Hydrology Using GIS, Bulletin of Engineering Geology and the Environment, Vol.67, pp.251-258.
17. ­Conforti, M., Aucelli, P.P.C., Robustelli, G., Scarciglia, F. (2010), Geomorphology and GIS Analysis for Mapping Gully Erosion Susceptibility in the Turbolo Stream Catchment (Northern Calabria, Italy), Natural hazards, Vol. 56, pp. 881-898.
18. ­Conoscenti, C., Angileri, S., Cappadonia, C., Rotigliano, E., Agnesi, V., Marker, M. (2014), Gully Erosion Susceptibility Assessment by Means of GIS-based Logistic Regression a Case of Sicily (Italy), Geomorphology, Vol. 204, No.1, pp. 399-411.
19. ­Conoscenti, C., Di Maggio, C., Rotigliano, E. (2008), Soil Erosion Susceptibility Assessment and Validation Using a Geostatistical Multivariate Approach a Test in Southern Sicily, Natural hazards, Vol. 46, pp. 287-305.
20. ­Dai, F.C., Lee, C.F., Li, J., Xu, Z.W. (2001), Assessment of Landslide Susceptibility on the Natural Terrain of Lantau Island, Hong Kong, Environmental Geology, Vol. 40, pp. 381-391.
21. ­De Vente, J., Poesen, J., Govers, G., Boix-Fayos, C. (2009), The Implications of Data Selection for Regional Erosion and Sediment Yield Modeling, Earth surface processes and landforms, Vol. 34, pp. 1994-2007.
22. ­Devkota, KC., Regmi, A.D., Pourghasemi, H.R., Yoshida, K., Pradhan, B., Ryu, I.C., Dhital, M.R., Althuwaynee, O.F. (2013), Landslide Susceptibility Mapping Using Certainty Factor, index of Entropy and Logistic Regression Models in GIS and their Comparison at Mugling-Narayanghat Road Section in Nepal Himalaya, Natural Hazards, Vol. 65, pp. 135-165.
23. ­Dramis, F., Gentili, B. (1977), Contributo Allo Studio Delle Acclivita Dei Versanti nell’Appennino Umbro, Marchigiano, Stud Geol Camerti, Vol. 3, pp. 153-164.
24. ­Dube, F., Nhapi, I., Murwira, A., Gumindoga, W., Goldin, J., Mashauri, D.A. (2014), Potential of Weight of Evidence Modelling for Gully Erosion Hazard Assessment in Mbire District-Zimbabwe, Physics and Chemistry of the Earth, Vol. 67, pp. 145-152
25. ­El Maaoui, M.A., Sfar Felfoul, M., Boussema, M.R, Snane, M.H. (2012), Sediment Yield from Irregularly Shaped Gullies Located on the Fortuna Lithologic Formation in Semi-arid Area of Tunisia, Catena, Vol. 93, pp. 97-104.
26. ­Entezari, M., Malaki, A., Moradi, K., Olfati, S. (2015), Erosion Gully Catchment Area of Deira Combination of WLC and SPI, Geographical Researches Quarterly Journal, Vol. 30, No. 3, pp. 297-312, (in Persian).
27. ­Faragzadeh, M., Afzali, A., Khalili, Y., Qalichi, A. (2013), Gully Erosion Susceptibility Assessment Using Multivariate Regression Model (Case Study: Kiasar, Southern Mazandaran Province), Environmental Erosion Research Journal, Vol. 2, No. 2, pp. 42-57, (in Persian).
28. ­Filippi, A.M., Jensen, J.R. (2006), Fuzzy Learning Vector Quantization for Hyperspectral Coastal Vegetation Classification, Remote Sensing of Environment, Vol. 100, pp. 512-530.
29. ­Flugel. W.A, Marker, M., Moretti, S., Rodolfi, G., Sidorchuk, A. (2003), Integrating Geographical Information Systems, Remote Sensing, Ground Truthing and Modelling Approaches for Regional Erosion Classification of Semi-arid Catchments in South Africa, Hydrology Process, Vol. 17, pp. 929-942.
30. ­Forests, Range and Watershed Management Organization. (2010), Digital files The countrywide land use coverage, September 2010, (in Persian).
31. ­Ghorbani Nejad, S., Falah, F., Daneshfar, M., Haghizadeh, A., Rahmati, O. (2016), Delineation of Groundwater Potential Zones Using Remote Sensing and GIS-based Data-driven Models, Geocarto International, Vol. 32, No. 2, pp. 167-187.
32. ­Golestani, G., Issazadeh, L., Serajamani, R. (2014), Lithology Effects on Gully Erosion in Ghoori Chay Watershed Using RS and GIS, International Journal of Biosciences (IJB), Vol. 4, No. 2, pp. 71-76.
33. ­Gomez, G.A., Schnabel, S., Felicısimo, A.M. (2009), Modelling the Occurrence of Gullies in Rangelands of Southwest Spain. Earth Surface Processes and Landforms, Vol. 34, No. 14, pp. 1894-1902.
34. ­Gomez-Gutierrez, A., Conoscenti, C., Angileri, S.E., Rotigliano, E., Schnabel, S. (2015), Using Topographical Attributes to Evaluate Gully Erosion Proneness (Susceptibility) in Two Mediterranean Basins: Advantages and Limitations, Natural Hazards, Vol. 79, No. 1, pp. 291-314.
35. ­Gorum, T., Gonencgil, B., Gokceoglu, C., Nefeslioglu, H.A. (2008), Implementation of Reconstructed Geomorphologic units in Landslide Susceptibility Mapping the Melen Gorge (NW Turkey), Natural Hazards, Vol. 46, No. 3, pp. 323-351.
36. ­Hongchun, Z.H.U, Guoan, T., Kejian, Q., Haiying, L. (2014), Extraction and Analysis of Gully Head of Loess Plateau in China Based on Digital Elevation Model, Chinese geographical science, Vol. 24, No. 3, pp. 328-338.
37. ­Hosseinzadeh, M.M., Sarvati, M.R., Mansori, A., Mirbaghari, B., Khazri, S. (2009), Zoning the Risk of Mass Movement Coccurrences Using Logistic Regression Model Case Study in vicinity of Sanandaj- Dehgolan road, Iranian Journal of Geology, Vol. 3, No. 11, pp. 27-37, (in Persian).
38. ­Hughes, A.O, Prosser, I.P., Stevenson, J., Scott, A., Lu, H., Gallant, J., Moran, C.J. (2001), Gully Erosion Mapping for the National Land and Water Resources Audit, Csiro Land and Water Technical Report, Canberra, Technical Report, Vol. 26, pp. 1-20.
39. ­Jaafari, A., Najafi, A., Pourghasemi, H.R., Rezaeian, J., Sattarian, A. (2014), GIS-based Frequency Ratio and Index of Entropy Models for Landslide Susceptibility Assessment in the Caspian Forest, northern Iran, Environmental Earth Sciences, Vol. 75, No. 9.
40. ­Kakembo, V., Xanga, W.W., Rowntree, K. (2009), Topographic Thresholds in Gully Development on the Hillslopes of Communal Areas in Ngqushwa Local Municipality, Eastern Cape, South Africa, Geomorphology, Vol. 110, No. 3-4, pp. 188-194.
41. ­Kohonen, T., Hynninen, J., Kangas, J., Laaksonen, J., Torkkola, K. (1996), Learning Vector Quantization. Technical Report A30. Helsinki University of Technology, Laboratory of Computer and Information Science, Espoo.
42. ­Kuhnert, PM., Henderson, A.K., Bartley, R., Herr, A. (2010), Incorporating Uncertainty in Gully Erosion Calculations Using the Random Forests Modelling Approach, Environmetrics, Vol. 21, pp. 493-509.
43. ­Le Roux, J.J., Sumner, P.D. (2012), Factors Controlling Gully Development Comparing Continuous and Discontinuous Gullies, Land Degradation Development, Vol. 23, No. 5, pp. 440-449.
44. ­Luca, F., Conforti, M., Robustelli, G. (2011), Comparison of GIS-based Gullying Susceptibility Mapping Using Bivariate and Multivariate Statistics: Northern Calabria, South Italy, Geomorphology, Vol. 134, pp. 297 308.
45. ­Maharaj, R. (1993), Landslide Processes and Landslide Susceptibility Analysis from an Upland Watershed a Case Study from St Andrew, Jamaica, West Indies Engineering Geology, Vol. 34, pp. 53-79.
46. ­Malaki, A., Miladi, B. (2012), Simulation of Creating of Gully Appropriate Regions Using SPI in River Basins Mereg, Quantitative Geomorphological Researches, Vol. 3, No. 1, pp. 23-38, (in Persian).
47. ­Manap, M.A., Nampak, H., Pradhan, B., Lee, S., Sulaiman, W.N.A., Ramli, M.F. (2014), Application of Probabilisticbased Frequency Ratio Model in Groundwater Potential Mapping Using Remote Sensing Data and GIS, Arabian Journal of Geosciences, Vol. 7, No. 2, pp. 711-724.
48. ­Marker M, Pelacani, S., Schroder, B. (2011), A Functional Entity Approach to Predict Soil Erosion Processes in a Small Plio-Pleistocene Mediterranean Catchment in Northern Chianti, Italy, Geomorphology, Vol. 125, pp. 530-540.
49. ­Marzolff, I., Poesen, J., The Potential of 3D Gully Monitoring with GIS Using High-resolution Aerial Photography and a Digital Photogrammetry System, Geomorphology, 2009 Oct, 1, Vol. 111, No. 1, pp. 48-60.
50. ­Moghaddam, D.D., Rezaei, M., Pourghasemi, HR., Pourtaghie, Z.S., Pradhan, B. (2013), Groundwater Spring Potential Mapping Using Bivariate Statistical Model and GIS in the Taleghan Watershed, Iran, Arabian Journal of Geosciences, Vol. 8, No. 2, pp. 913-929. DOI:10.1007/s12517-013-1161-5.
51. ­Mohammady, M., Pourghasemi, H.R., Pradhan, B. (2012), Landslide Susceptibility Mapping at Golestan Province, Iran a Comparison Between Frequency Ratio, Dempster-Shafer, and weights-of-evidence models, Journal of Asian Earth Sciences, Vol. 61, pp. 221-236.
52. ­Naghibi, S.A., Pourghasemi, H.R., Dixon, B. (2016), GIS-based Groundwater Potential Mapping Using Boosted Regression Tree, Classification and Regression Tree, and Random Forest Machine Learning Models in Iran, Environmental monitoring and assessment, Vol.188, No.1, DOI:10.1007/s10661-015-5049-6.
53. ­Orkhzlo, H.S., Emami, H., Haqniya, Q.H., Esmali, A. (2016), Comparison of Two Methods of Hierarchical Analysis and Fuzzy Logic for Mapping the Risk of Gully Erosion in Three Regions of the Province, Environmental Erosion Research Journal, Vol. 21, No. 1, pp. 1-16 (in Persian).
54. ­Patel, A.K., Chatterjee, S. (2016), Computer Vision-based Limestone Rock-type Classification Using Probabilistic Neural Network, Geoscience Frontiers, Vol. 7, No. 1, pp. 53-60.
55. ­Pavel, M., Nelson, J.D., Fannin, R.J. (2011), An Analysis of Landslide Susceptibility Zonation Using a Subjective Geomorphic Mapping and Existing Landslides, Computers Geosciences, Vol. 37, No. 4, pp. 554-566.
56. ­Poesen, J., Nachetergaele, J., Verstraeten, J., Valentin, C. (2003), Gully Erosion and Environmental Change: Importance and Research Needs, Catena, Vol. 50, No. 2-4, pp. 91-133.
57. ­Poudyal, C.P., Chang, C., Oh, H.J., Lee, S. (2010), Landslide Susceptibility Maps Comparing Frequency Ratio and Artificial Neural Networks a Case Study from the Nepal Himalaya, Environmental Earth Sciences, Vol. 6, pp. 1049-1064.
58. ­Pourghasemi, H.R., Kerle, N. (2016), Random Forests and Evidential Belief function-based Landslide Susceptibility Assessment in Western Mazandaran Province, Iran, Environmental Earth Sciences, Vol. 75, No. 3.
59. ­Pourtaghi, Z.S., Pourghasemi, H.R. (2014), GIS-based Groundwater Spring Potential Assessment and Mapping in the Birjand Township, Southern Khorasan Province, Iran, Hydrogeology, Vol. 22, pp. 643-662.
60. ­Pradhan, B. (2010), Landslide Susceptibility Mapping of a Catchment Area Using Frequency Ratio, Fuzzy Logic and Multivariate Logistic Regression Approaches, Journal of the Indian Society of Remote Sensing, Vol. 38, No. 2, pp. 301-320.
61. ­Qilin, Y., Jiarong, G., Yue, W., Bintian, Q. (2011), Debris Flow Characteristics and Risk Degree Assessment in Changyuan Gully, Huairou District, Beijing, Procedia Earth and Planetary Science, Vol. 2, pp. 262 -271.
62. ­Rahmati, O., Zeinivand, H., Besharat, M. (2015), Flood Hazard Zoning in Yasooj Region, Iran, Using GIS and Multi- Criteria Decision Analysis, Geomatics, Natural Hazards and Risk, Vol. 7, No. 3, pp. 1000-1017.
63. ­Rangavar, A.S., Abasi, A., Zagiabadi, M. (2007), Gully Erosion and Assess the Economic Damage Caused by it (Case Study: Sanganeh Kalat Basin, Khorasan Razavi), 4th National Seminar on Watershed Management, Karaj, pp. 16-23, (in Persian).
64. ­Razandi, Y., Pourghasemi, H.R, Samani Neisani, N., Rahmati, O. (2015), Application of Analytical Hierarchy Process, Frequency Ratio, and Certainty Factor Models for Groundwater Potential Mapping Using GIS, Earth Science Informatics, Vol. 8, No. 4, pp.867-883. DOI:10.1007/s12145-015-0220-8.
65. ­Regmi, A.D., Devkota, K.C., Yoshida, K., Pradhan, B., Pourghasemi, H.R., Kumamoto, T., Akgun, A. (2013), Application of Frequency Ratio, Statistical Index, and Weights-of-evidence Models and their Comparison in Landslide Susceptibility Mapping in Central Nepal Himalaya, Arabian Journal of Geosciences, Vol. 7, No. 2, pp. 725-742. DOI:10.1007/s12517-012-0807z.
66. ­Saber chenari, K., Bahremand, A., Sheikh, V.B., Biram Komaki, C. (2016), Gully Erosion Hazard Zoning Using of Dempster-Shafer Model in The Gharnaveh Watershed, Golestan Province, Journal of Ecohydrology, Vol. 3, No. 2, pp. 219-231 (in Persian).
67. ­Sadeghi, H.R., Bashari Seghaleh, M., Rangavar, A.S. (2008), Comparing the Sediment Variation with Hillside Direction and Plot Length in Storm Wise Soil Erosion, Journal of Water and Soil, Vol. 22, No. 2, pp. 230-239, (in Persian).
68. ­Scheidegger, A.E. (2012), Theoretical Geomorphology, Springer Science Business Media, 2012 Dec.
69. ­Shahrivar, A., Shadfar, S., khazae, M., Behzad, A. (2017), Assessment of Gully Erosion Zonation Methods (Case Study: Abgendi Watershed), Journal of Ecohydrology, Vol. 4, No. 1, pp. 119-132, (in Persian).
70. ­Snelder, D.J., Bryan, R.B. (1995), The Use of Rainfall Simulation Tests to Assess the Influence of Vegetation Density on Soil Loss on Degraded Rangelands in the Baringo District, Kenya, Catena, Vol. 25, No. 4, pp. 105-116.
71. ­Stotle, J., Liu, B., Ritsema, C.J., Van, H.G.M., Den Elsen, R., Hessel, R. (2003), Modeling Water Flow and Sediment Processes in a Small Gully System on the Loess Plateau in China, Catena, Vol. 54, pp.117-130.
72. ­Svoray, T., Michailov, E., Cohen, A., Rokah, L., Sturm, A. (2012), Predicting Gully Initiation: Comparing Data Mining Techniques, Analytical Hierarchy Processes and the Topographic Threshold, Earth Surface Processes and Landforms, Vol. 37, No. 6, pp. 607-619.
73. ­Tayebi, M.H., Tangestani, M.H. (2015), Sub Pixel Mapping of Alteration Minerals Using SOM Neural Network Model and Hyperion Data, Earth Science Informatics, Vol. 8, No. 2, pp. 279-291.
74. ­Tehrany, M.S., Pradhan, B., Jebur, M.N. (2014), Flood Susceptibility Mapping Using a Novel Ensemble Weightsof- evidence and Support Vector Machine Models in GIS, Journal of hydrology, Vol. 512, pp. 332-343.
75. ­Tien Bui, D., Pradhan, B., Lofman, O., Revhaug, I., Dick, O.B. (2012), Spatial Prediction of Landslide Hazards in Vietnam a Comparative Assessment of the Efficacy of Evidential Belief Functions and Fuzzy Logic Models, Catena, Vol. 96, pp. 28-40.
76. ­Umar, Z., Pradhan, B., Ahmad, A., Jebur, M.N., Tehrany, M.S. (2014), Earthquake Induced Landslide Susceptibility Mapping Using an Integrated Ensemble Frequency Ratio and Logistic Regression Models in West Sumatera Province, Indonesia, Catena, Vol. 118, pp. 124-135.
77. ­Valentin, C., Poesen, J., Yong, L. (2005), Gully Erosion: Impacts, Factors and Control Catena, Vol. 63, pp.132-153.
78. ­Vandaele, K., Poesen, J., Govers, G., Wesemael, B. (1996), Geomorphic Threshold Conditions for Ephemeral Gully Incision, Geomorphology, Vol. 16, pp. 161-173.
79. ­Wang, L., Wei, S., Horton, R., Shao, M. (2011), Effects of Vegetation and Slope Aspect on Water Budget in the Hill and Gully Region of the Loess Plateau of China, Catena, Vol, 87, No. 1, pp. 90-100.
80. ­Williams, R.N., Souza. J.R, Jones, E.M. (2014), Analysing Coastal Ocean Model Outputs Using Competitivelearning Pattern Recognition Techniques, Environ Modell Softw, Vol. 57, pp. 165-176.
81. ­Yesilnacar, E.K. (2005), The Application of Computational Intelligence to Landslide Susceptibility Mapping in Turkey, Ph. D Thesis Department of Geomatics the University of Melbourne, pp. 423.
82. ­Youssef, A.M., Pourghasemi, H.R., El-Haddad, B.A, Dhahry, B.K. (2015), Landslide Susceptibility Maps Using Different Probabilistic and Bivariate Statistical Models and Comparison of their Performance at Wadi Itwad Basin, Asir Region, Saudi Arabia. Bulletin of Engineering Geology and the Environment, Vol. 75, No. 1, pp. 63-87.
83. ­Zakerinejad, R., Maerker, M. (2015), An Integrated Assessment of Soil Erosion Dynamics with Special Emphasis on Gully Erosion in the Mazayjan basin, southwestern Iran, Natural Hazards, Vol. 79, No. 1, pp. 25-50.
84. ­Zare, M., Pourghasemi, H.R., Vafakhah, M., Pradhan, B. (2013), Landslide Susceptibility Mapping at Vaz Watershed (Iran) Using an Artificial Neural Network Model a Comparison Between Multilayer Perceptron (MLP) and Radial Basic Function (RBF) Algorithms, Arabian Journal of Geosciences, Vol. 6, No. 8, pp. 2873-2888.
85. ­Zheng. F. (2006), Effect of Vegetation Changes on Soil Erosion on the Loess Plateau, Pedosphere, Vol. 16, No. 4, pp. 420-427.
86. ­Zhu, A., Wang, R., Qiao, J., Qin, C., Chen, Y., Liu, J., Du, F., Lin, Y., Zhu, T. (2014), An Expert Knowledge-based Approach to Landslide Susceptibility Mapping Using GIS and Fuzzy Logic, Geomorphology, Vol. 214, pp. 128-138.
87. ­Zinck, J.A., Lopezb, J., Metternichtc, G.I., Shresthaa, D.P., Vazquez-Selemd, L. (2001), Mapping and Modeling Mass Movements and Gullies in Mountainous Areas Using Remote Sensing and GIS Techniques, International Journal of Applied Earth Observation and Geoinformation, Vol. 3, No. 1, pp. 43-53.
88. ­Zucca, C., Canu, A., Della Peruta, R. (2006), Effects of Land use and Landscape on Spatial Distribution and Morphological Features of Gullies in an Agropastoral Area in Sardinia (Italy), Catena, Vol. 68, pp. 87-95.
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Ebrahim M, Amir Ahmadi A, Zangeneh Asadi M A. Comparison of Gully Erosion Susceptibility Mapping Using Weight of Evidence and Frequency Ratio Models at Sanganeh Kalat Basin. geores. 2018; 32 (4) :105-126
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