Performance evaluation of Dempster-Shafer model for erosion potential mapping in Kakareza watershed, Lorestan province

Subject Areas : Geospatial systems development

Samira  Ghorbaninejad ¹ (MSc. Student of Watershed Management, Department of Agriculture and Natural Resources, Lorestan University)
Hossein  Zeinivand ² (Assoc. Prof. College of Watershed Management, Department of Agriculture and Natural Resources, Lorestan University)
Ali  Haghizadeh ³ (Assist. Prof. College of Watershed Management, Department of Agriculture and Natural Resources, Lorestan University)
Naser  Tahmasebi ⁴ (Assist. Prof. College of Watershed Management, Department of Agriculture and Natural Resources, Lorestan University)

Received: 2017-02-23 Accepted : 2018-07-04 Published : 2018-10-23

Keywords: Erosional points, Receiver operating characteristic (ROC) curve, Soil conservation, Kakareza watershed,

Abstract :

Identifying susceptible areas for erosion can be considered as one of the most important soil conservation measures. In this study, the capability of Dempster-Shafer (DS) model for mapping potential areas for erosion was investigated in Kakareza watershed in Lorestan province. First thematic layers of influential factors in soil erosion, including altitude, slope, slope, aspect, plan curvature, lithology, land use, distance from the river, soil and topographic wetness index were prepared. In addition, 29 eroded positions in the study area that their positions were obtained from GPS and Google earth on 10 July 20016 were mapped and then were divided into a training (70%) and testing (30%) points. The layers of environmental variables were classified into different classes according to and then based on the density of eroded points in the study area and DS analysis, the weight of each class was determined and the potential map of vulnerable areas to erosion was obtained according to the DS model. The accuracy of a generated map was also investigated using testing points and receiver operating characteristic (ROC) curve. The result showed that the produced map has the success rate of 21%, that means the poor capability of the DS model for mapping susceptible areas of erosion. In addition, according to the DS map, areas with the highest potential to surface erosion are located in the central and eastern part of the study area. Therefore, it can be indicated that this model has a poor ability in identifying potential and vulnerable areas to surface erosion compared to other phenomena such as flood and gully erosion.

References:

رجایی، ع. ا.  1373. ژئومورفولوژی کاربردی در برنامه ریزی عمران ناحیه ای تهران، نشر قومس. چاپ اول، 328 صفحه.

رحیمی شهید، م.، ف. کارگران و ن. رحیمی. 1394. تهیۀ نقشه زون­های لرزه­ای گستره اصفهان با استفاده از داده­های سنجش از دور و سیستم اطلاعات جغرافیایی. سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 6(4): 47-59.

طهماسبی پور، ن.، ا. رحمتی  و س. قربانی نژاد. 1395. پیش بینی حساسیت به فرسایش آبکندی منطقۀ سیمره براساس مدل عامل قطعیت و تعیین اهمیت عوامل مؤثر بر آن. اکوهیدرولوژی، 3(1): 83-93.

رفیعیان، ا.، س. ع. ا. میر راضی، ع. ا. پورنجیبه و ا. گلابی. 1393. انتخاب مناطق مستعد طبیعت گردی پناهگاه حیات وحش کیامکی به روش تصمیم گیری چندمعیاره. سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 5(4): 95-108.

قدوسی. ج. و م. داوری. 1384. تاثیر خصوصیات فیزیکی و شیمیایی خاک در رخداد فرسایش خندقی و مرفولوژی خندق ها. سومین همایش ملی فرسایش و رسوب، تهران، مرکز تحقیقات حفاظت خاک و آبخیزداری کشور، 6 الی 9 شهریور، 382 – 389.

گودرزی، ل.، ع. م. آخوندعلی و ح. زارعی. 1392. تعیین مکان مناسب برای تغذیه مصنوعی با استفاده از سیستم اطلاعات جغرافیایی و روش تحلیل سلسله مراتبی (مطالعة موردی: دشت اشترینان). سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 4(2): 53-67.

ماه گلی، آ.، م. چیت‌سازان و ی. میرزایی. 1390. پتانسیل‌یابی آب زیرزمینی در سازندهای سخت با استفاده از GIS و سنجش‌ازدور (مطالعۀ موردی: شمال حسینیه). همایش ژئوماتیک، تهران، سازمان نقشه‌برداری کشور، 25 الی ۲۹ اردیبهشت، 1559 صفحه.

نسرین نژاد، ن.، ک. رنگزن، ن. کلانتری و ع. صابری. 1393. پهنه بندی پتانسیل سیل­خیزی حوزه آبریز باغان با استفاده از روش تحلیل سلسله مراتبی فازی (FAHP). سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 5(4): 15-34.

هاشمی، س. م.، ر. قربانی و ب. کاوه‌ای. 1383. تحلیل منحنی‌های ROC  برای مقایسه تست‌های تشخیص پزشکی. مجله علمی دانشگاه علوم پزشکی سمنان، 6(2): 145-150.

یعقوبی، ث.، م. فرامرزی، ح. کریمی، ح و ج. سروریان. 1395. ارزیابی کارایی شبکه عصبی مصنوعی در پیش بینی روند بیابان زایی با استفاده از سیستم اطلاعات جغرافیایی GIS (مطالعه موردی: دشت دهلران، ایلام). سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 7(3): 61-77.

Chmelová R, Sarapatka B. 2002. Soil erosion by water: contemporary research methods and their use. Geographica, 37: 23-30.

Dabral P, Baithuri N, Pandey A. 2008. Soil erosion assessment in a hilly catchment of north eastern India using USLE, GIS and remote sensing. Water Resources Management, 22(12): 1783-1798.

Dabral P, Pandey A. 2008. Morphometric analysis and prioritization of eastern Himalayan river basin using satellite data and GIS. Asian Journal of Geoinformatics, 7(3): 3-14.

Dempster AP. 2008. Upper and lower probabilities induced by a multivalued mapping. In: Yager RR, Liu L (eds) Classic Works of the Dempster-Shafer Theory of Belief Functions. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 57-72.

Dube F, Nhapi I, Murwira A, Gumindoga W, Goldin J, Mashauri D. 2014. 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, 67: 145-152.

Edet A, Okereke C, Teme S, Esu E. 1998. Application of remote-sensing data to groundwater exploration: a case study of the Cross River State, southeastern Nigeria. Hydrogeology Journal, 6(3): 394-404.

Galton F. 1889. Narrative of an explorer in tropical South Africa: Being an account of a visit to Damaraland in 1851, vol 2. Ward, Lock and Company, 320 pp.

Gayen A, Saha S. 2017. Application of weights-of-evidence (WoE) and evidential belief function (EBF) models for the delineation of soil erosion vulnerable zones: a study on Pathro river basin, Jharkhand, India. Modeling Earth Systems and Environment, 3(3): 1123-1139.

George T, Pal NR. 1996. Quantification of conflict in Dempster-Shafer framework: a new approach. International Journal Of General System, 24(4): 407-423.

He B, Cui Y, Chen C, Chen J, Liu Y. 2011. Uncertainty mapping method for mineral resources prospectivity integrating multi-source geology spatial data sets and evidence reasoning model. In: Geoinformatics, 2011 19th International Conference on. IEEE, pp 1-5.

Khosrokhani M, Pradhan B. 2014. Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS. Geomatics, Natural Hazards and Risk, 5(3): 252-270.

Kim S-M, Choi Y, Suh J, Oh S, Park H-D, Yoon S-H. 2012. Estimation of soil erosion and sediment yield from mine tailing dumps using GIS: a case study at the Samgwang mine, Korea. Geosystem Engineering, 15(1): 2-9.

Lal R. 1994. Soil erosion research methods. CRC Press, 352 pp.

Lal R, Blum WE, Valentin C, Stewart BA. 1997. Methods for assessment of soil degradation, vol 9. CRC press, 576 pp.

Mogaji K, Lim H, Abdullah K. 2015. Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Dempster–Shafer model. Arabian Journal of Geosciences, 8(5): 3235-3258.

Naqvi HR, Mallick J, Devi LM, Siddiqui MA. 2013. Multi-temporal annual soil loss risk mapping employing revised universal soil loss equation (RUSLE) model in Nun Nadi Watershed, Uttrakhand (India). Arabian journal of geosciences, 6(10): 4045-4056.

Nigel R, Rughooputh S. 2010. Soil erosion risk mapping with new datasets: An improved identification and prioritisation of high erosion risk areas. CATENA, 82(3): 191-205.

Oh H-J, Lee S. 2011. Integration of ground subsidence hazard maps of abandoned coal mines in Samcheok, Korea. International Journal of Coal Geology, 86(1): 58-72.

Perreault LM, Yager EM, Aalto R. 2017. Effects of gradient, distance, curvature and aspect on steep burned and unburned hillslope soil erosion and deposition. Earth Surface Processes and Landforms, 42(7): 1033-1048.

Pham HT. 2009. Soil erosion risk modeling within upland landscapes in Vietnam using remotely sensed data and the RUSLE model. Dalhousie University, Canada, PhD. Thesis, 87 pp.,

Rahmati O, Haghizadeh A, Pourghasemi HR, Noormohamadi F. 2016. Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison. Natural Hazards, 82(2): 1231-1258.

Rozos D, Skilodimou HD, Loupasakis C, Bathrellos GD. 2013. Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece. Environmental Earth Sciences, 70(7): 3255-3266.

ShafapourTehrany M, Shabani F, Javier DN, Kumar L. 2017. Soil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratio. Geomatics, Natural Hazards and Risk, 8(2): 1695-1714.

Shafer G. 1976. A mathematical theory of evidence, vol Volume 42 of Limited paperback editions. Princeton University Press, 297 pp.

Tangestani M. 2004. Landslide susceptibility mapping using the fuzzy gamma approach in a GIS, Kakan catchment area, southwest Iran. Australian Journal of Earth Sciences, 51(3): 439-450.

Wright D. 1996. VHMS favourability mapping with GIS-based integration models, Chisel Lake-Anderson Lake area. Extech i: A multidisciplinary approach to massive sulphide research in the rusty lake-snow lake greenstone belts, manitoba, 339: 387-401.

Yetemen O, Istanbulluoglu E, Duvall AR. 2015. Solar radiation as a global driver of hillslope asymmetry: Insights from an ecogeomorphic landscape evolution model. Water Resources Research, 51(12): 9843-9861.

Zeinivand H. 2009. Development of spatially distributed hydrological WetSpa modules for snowmelt, soil erosion, and sediment transport. Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Brussels, Belgium, PhD Thesis, 178 pp.,

Zeinivand H, Ghorbani Nejad S. 2018. Application of GIS-based data-driven models for groundwater potential mapping in Kuhdasht region of Iran. Geocarto International, 33(6): 651-666.

Zhang Y, Degroote J, Wolter C, Sugumaran R. 2009. Integration of modified universal soil loss equation (MUSLE) into a GIS framework to assess soil erosion risk. Land Degradation & Development, 20(1): 84-91.