Gully Erosion Hazard Zoning Using of Dempster-Shafer Model in The Gharnaveh Watershed, Golestan Province

Document Type : Research Article

Authors

1 PhD Student, Depatment of watershed management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

2 Depatment of watershed management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

3 Depatment of Desert management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

Abstract

The goal of this research is Gully Erosion Hazard zoning by using Dempster-Shafer Theory for the Garnaveh watershed (Golestan province). For this purpose, at first a gully erosion inventory map with the scale of 1:200000 (dependent variable) for the Gharnaveh watershed has been prepared using multiple field surveys and satellite pictures. From total gullies 70% of them have randomly selected for building gully erosion hazard zoning model while the residuals (30%) have used for validating the model. In the next stage, seven data layers contain slope percent, slope aspect, plan curvature, lithology, land use, distance from rivers and distance from roads have been selected as gully erosion conditioning factors (independent variables) and digitized in ArcGIS software. The amount of gully density in each factor class have calculated from combination of independent and dependent variables, and rating of classes have done based on Dempster-Shafer equations. Finally, the gully erosion hazard zoning map has drawn from summation of weighting maps. The results of model classification show that from total considered gully zones for model validating in the Gharnaveh watershed %68.06 are in the class of high and very high hazard. Also, the result of model validating with using the receiver operating characteristic (ROC) curves and areas under the curve (AUC) showed that Dempster-Shafer model is appropriate for gully erosion hazard zoning in the studied area with accuracy of %96.1 and standard deviation of 0.003

Keywords

Main Subjects


 
[1]. Bou Kheir, R, Wilson J, Deng Y. Use of terrain variables for mapping gully erosion susceptibility in Lebanon. Earth Surf. Process. Landforms. 2007; 32(12):1770–1782.
[2]. Conoscenti C, Angileri S, Cappadonia C, Rotigliano E, Agnesi V. Märker, M. Gully erosion susceptibility assessment by means of GIS-based logistic regression: a case of Sicily (Italy). Geomorphology. 2014; 204:(399–411.
[3]. Nigel R, Rughooputh SDDV. Soil erosion risk mapping with new dataset: An improved prioritization of high erosion risk area, Catena. 2010;82(3):191-205.
[4]. Conoscenti C, Agnesi V, Angileri S, Cappadonia C, Rotigliano E, Märker M. A GIS-based approach for gully erosion susceptibility modelling: a test in Sicily, Italy. Environmental Earth Science. 2013; 70(3):1179–1195.
[5]. Li Y, Poesen J, Yang JC, Fu B, Zhang JH. Evaluating gully erosion using 137Cs and 210Pb/137Cs ratio in a reservoir catchment. Soil Tillage Resources. 2003;69(1-2):107–115.
[6]. Poesen J, Vandekerckhove L, Nachtergaele J, Oostwoud Wijdenes D, Verstraeten, G, Van Wesemael B. Gully erosion in dryland environments. In: Bull, L.J., Kirkby, M.J. (Eds.), Dryland Rivers: Hydrology and Geomorphology of Semi-Arid Channels. Wiley & Sons, Chichester, England. 2002; pp. 229–262.
[7]. Poesen J, Nachtergaele J, Verstraeten G, Valentin C. Gully erosion and environmental change: importance and research needs. Catena. 2003;50(2-4):91–133.
[8]. USDA-SCS. Procedure for determining rates of land damage, land depreciation, and volume of sediment produced by gully erosion. Technical Release No. 32. US GPO 1990-261-419:20727/SCS.US Government Printing Office, Washington, DC. 1966.
[9]. Damavandi MZ. Study morphological features of loss deposits in the western part of Gorgan city. Report of Research projects. Gorgan University of Agricultural Sciences & Natural Resources. 2006; p.45. [Persian]
[10]. Report design of flood and sediment control structures in the Gharnaveh watershed. Kavosh Pay Mashhad Consulting Engineers Company. P.2-10. [Persian]
[11]. Esfandyaridorabad F, Beheshtijavid A, Ftahi MH. Gully erosion Susceptibility Evaluation using fuzzy logic model (Case study: Golestan dam watershad-Ghornave River). 2th international conf. on environmental hazards. Kharazmi University. 2013. [Persian]
[12]. Nohegar A, Heydarzadeh M, The study of physical - chemical characteristics and morphometery of gullying area (case study: Gezir, Hormozgan province). Environmental Erosion Research Journal. 2011;1(1) :29-44. [Persian]
[13]. Dewitte O, Daoudi M, Bosco C, Eeckhaut MVD. Predicting the susceptibility to gully initiation in data-poor regions, Geomorphology journal. 2015; 228:101-115.
[14]. Entezari M, Maleki A, Moradi Kh, Olfati S. Zoning of Gully Erosion in Catchment of Dyreh by Analytical Hierarchy Process (AHP). Journal of Spatial Planning. 2014; 17(4). 63-86. [Persian]
[15]. Pourghasemi HR, pardhan B, gokceoglu C, dylami moezzi K. Comparative assessment of prediction capabilities of Dempster–Shafer and Weights-of-evidence models in landslide susceptibility mapping using GIS", Geomatics, Natural Hazards and Risk. 2013; 4(2):93–118.
[16]. Tangestani MH. A comparative study of Dempster–Shafer and fuzzy models for landslide susceptibility mapping using a GIS: An experience from Zagros Mountains, SW Iran. Journal of Asian Earth Sciences. 2009;35(1):66–73.
[17]. Shadfar S. Application of fuzzy logic operators for investigation of Gully erosion using GIS (Case study: Troud watershed basin). Geography information Journal. 2015; 23(92): 35-42. [Persian]
[18]. Yamani M, Zamanzadeh SM, Ahmadi M. Analysis of Factors Affecting the Formation and Development of Gully Erosion: A Case Study of Kahoor Plain in Fars Province. journal of Geographical explorations deserts areas. 2013; 1(1): 53-84. [Persian]
[19]. Farajzadeh M, Afzaly A, Khalili Y, Ghelichi A. Gully Erosion Susceptibility Assessment using Multivariate Regression Model (Case Study: Kiasar, Southern Mazandaran Province). Environmental Erosion Research Journal. 2012; 2(2):42-57. [Persian]
[20]. Maghsoodi M, Shadfar S, Abasi M. Gully erosion Susceptibility zoning in the Zavarian watershed, Qum province. Journal of Quantitative Geomorphological researches. 2012; 1(2):35-52. [Persian]
[21]. Dube F, Nhapi I, Murwira A, Gumindoga W, Goldin J, Mashauri DA. Potential of weight of evidence modelling for gully erosion hazard assessment in Mbire District-Zimbabwe. Physics and Chemistry of the Earth, Parts A/B/C. 2014;67:145–152.
[22]. Conforti M, Aucell C, Robustelli G, Scarciglia F. Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy). Nat Hazards. 2011;56(3):881-898.
[23]. Achten WMJ, Dondeyne S, Mugogo S, Kafiriti E, Poesen J, Deckers J, et al. Gully Erosion in South Eastern Tanzania: Spatial Distribution and Topographic Thresholds, Zeitschrift für Geomorphologie. 2008;52(2):225-235.
[24]. Mendel JM. Fuzzy Logic Systems for Engineering. Proceedings of IEEE. 1995; 83:345-377.
[25]. Hughes AO, Prosser I. Gully erosion prediction across a large region: Murray–Darling Basin, Australia, Soil Research. 2012;50(4):267-277.
[26]. Rahmati O, Haghizadeh A, Pourghasemi HA, Noormohamadi F. Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison. Natural Hazards. 2016;82(2);1231–1258.
[27]. Shadfar S. Investigation of Gully Erosion by using the Analytical Hierarchy Process Model Case study: Roudbar, Gilan Province. Iran. Environmental Erosion Research Journal. 2011;1(3) :16-30. [Persian]
[28]. Dempster AP. Upper and lower probabilities induced by a multi valued mapping. The Annals of Mathematical Statistics. 1967; 38:325–339.
[29]. Shafer G. A mathematical theory of evidence. Princeton University Press, ISBN 0-608-02508-9. 1976.p. 314.
[30]. An P, Moon WM, Bonham-Carter GF. Uncertainty management in integration of exploration data using the belief function. Nonrenewable Resources. 1994;3(1):60–71.
[31]. Park NW. Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis. Environmental Earth Science. 2010;62(2):367-376.
[32]. Saber Chenari K, Salmani H, Mohammadi M. Landslide Hazard Assessment Using Information Value and LNRF Models. Eco-Hydrology Journal. 2015; 2(1): 105-116. [Persian]
[33]. Devkota KC, Regmi AD, Pourghasemi HR, Yoshida K, Pradhan B, Ryu IC, et al. 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. Nat Hazards. 2013;65(1):135–165.
[34]. Yesilnacar EK. The application of computational intelligence to landslide susceptibility mapping in Turkey. Ph.D Thesis Department of Geomatics the University of Melbourne; 2005. p.423.
[35]. Makhdoom Frakhondeh M. Fundamental of land use planning. 1nd ed. Tehran: University of Tehran Press; 2010. P.289. [Persian]
[36]. Maleki A, Ahmadi M, Miladi B, Simulation Gully Prone areas using of SPI method in the Mereg River Watershed. Journal of Quantitative Geomorphological researches. 2013;1(3): 23-38. [Persian]
[37]. Ghahroodi M. Hazard zoning model of gully erosion using of RS & GIS in the Abkand Kloche Bijar watershed. Research projects of Ministry of Energy. 2003; p.52-53. [Persian]
[38]. Dai FC, Lee CF, Xu ZW. Assessment of landslide susceptibility on the natural terrain of Lantua sland, Hong Kong. Environment Geology.2001;40(3):381-391.
[39]. Zucca C, Canu A, Della Peruta R. Effects of land use and landscape on spatial distribution and morphological features of gullies in an agro-pastoral area in Sardinia (Italy). Catena. 2006;68(2-3):87–95.
Volume 3, Issue 2
June 2016
Pages 219-231
  • Receive Date: 03 August 2016
  • Revise Date: 08 November 2016
  • Accept Date: 11 November 2016
  • First Publish Date: 11 November 2016
  • Publish Date: 21 June 2016