عنوان مقاله [English]
The lack of information on the majority of catchment areas has motivated scholars to use spatial analysis of Geographical Information System (GIS) for hydrological studies and potential detection of the groundwater resources. This paper is focused on studying the performance and efficiency of the evidential belief function (EBF) method for groundwater potential mapping in Alshtar plains, Lorestan province. Moreover, parameters of slope, elevation, land use, curvature, Topography Wetness index (TWI) and Stream Power Index (SPI) were utilized. The digital maps of the all parameters were obtained via AcrGIS 10.1 and SAGA GIS 2 software with Raster Format. The geographical location of 28 wells within the region was provided. These points were randomly divided into the groups consist of 20 wells (70%) and 8 wells (30%) for modelling process (calibration) and validation, respectively. The results indicated that the EBF method possesses a proper efficiency for potential detection of the groundwater resources. With regard to the final zoning map, it can be deduced that the western parts of the plain have the higher potential and the center of the plain has the low groundwater potential.
Application of an evidential belief function model in landslide susceptibility mapping. Computer and Geosciences. 44: 120-135.
Carranza,E.J.M and Hale,M. 2003. Evidential belief functions for data-driven geologically constrained mapping of gold potential, Baguio district, Philippines. Ore Geology Reviews. 22.1: 117-132.
Chenini,I, Mammou,A.B. 2010. Groundwater recharge study in arid region: An approach using GIS techniques and numerical modeling, Camputer and geoscience. 36.6:801-817.
Davoodi Moghaddam,D., Rezaei,M., Pourghasemi, H.R., Pourtaghie,Z.S and Pradhan,B. 2015. Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan watershed, Iran. Arabian Journal of Geosciences. 8 .2: 913-929.
Jebur,M., Pradhan,B., Tehrany,M. 2014. Manifestation of LiDAR-derived parameters in the spatial prediction of landslides using novel ensemble evidential belief functions and support vector machine models in GIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8.2:674 – 690.
Lee,M.J., Kang,J.E and Jeon,S. 2012. Application of frequency ratio model and validation for predictive ﬂooded area susceptibility mapping using GIS. In: Geoscience and Remote Sensing Symposium (IGARSS), Munich. 895–898.
Lee,S., Kim,Y.S., Oh,H.J. 2012. Application of a weights- of -evidence method and GIS to regional groundwater productivity potential mapping. Journal of Environmental Management. 96.1: 91-105.
Nampak,H., Pradhan,B., Manap,M.A. 2014. Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. Journal of Hydrology. 513 Model. Softw. 15: 101-124.
Oh,H.J., Kim,Y.S., Choi,J.K., Park,E and Lee,S. 2011. GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. Journal of Hydrology. 399. 158-172.
Oh,H.J., Pradhan,B. 2011. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Computer and Geoscience. 37: 1264-1276.
Ozdamir,A. 2011. GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison. Catena, 431:255-268
Pourghasemi,H.R and Beheshtirad,M. 2014. Assessment of a data-driven evidential belief function model and GIS for groundwater potential mapping in the Koohrang Watershed, Iran. Geocarto International. 31: 628-646.
Pourghasemi,H.R., Moradi,H.R., Fatemi Aghda,S.M., Gokceoglu,S and Pradhan,B. 2012. GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran). Arabian journal of geosciences. 7: 1857-1878.
Pourtaghi,Z.S., Pourghasemi,H.R. 2014. GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeology Journal. 22: 643-662.
Pradhan,B. 2009. Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. Journal of Spatial Hydrology. 9: 1-18
Pradhan,B., Hagemann,U., Shafapour Tehrany,M., Prechtel,N. 2014. An easy to use ArcMap based texture analysis program for extraction of flooded areas from Terra SAR-X satellite image. Computers & Geosciences Journal. 63: 34-43.
Rahmati,O., Pourghasemi,H.R, Melesse,A.M. 2016. Application of GIS-based data driven random forest and maximumentropy models for groundwater potential mapping, Catena. 5:215-230.
Razandi,Y., Pourghasemi,H.R., Samani,N., Rahmati,O. 2015. Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS, Earth Science Informatics, 8.4:867-883.
Tehrany,M.S., Pradhan,B and Jebur,M.N. 2013. Spatial prediction of ﬂood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology. 504: 69-79.
Tehrany,M.S., Pradhan,B and Jebur,M.N. 2014. Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology. 512: 332-343.
Tehrany,M. Pradhan,Sh.B., Mansor,S.H and Noordin,D. 2015. Flood susceptibility assessment using GIS-based support vector machine model with different kernel types. Catena. 125: 91-101.
UN. 2003. Water for people, water forlife. The UN World WaterDevelopment Report (WWDR), UNESCO, Publishing and Berghahn Books, UK, pp 34.