Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

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dc.contributor.authorOzdemir, Adnan
dc.date.accessioned2020-03-26T18:17:29Z
dc.date.available2020-03-26T18:17:29Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km(2) (28.99%), 74.271 km(2) (19.906%), 101.203 km(2) (27.14%), and 90.05 km(2) (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions. (C) 2011 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.jhydrol.2011.05.015en_US
dc.identifier.endpage136en_US
dc.identifier.issn0022-1694en_US
dc.identifier.issn1879-2707en_US
dc.identifier.issue01.02.2020en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage123en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.jhydrol.2011.05.015
dc.identifier.urihttps://hdl.handle.net/20.500.12395/27037
dc.identifier.volume405en_US
dc.identifier.wosWOS:000293429200011en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIERen_US
dc.relation.ispartofJOURNAL OF HYDROLOGYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectGroundwater potentialen_US
dc.subjectSpringen_US
dc.subjectGISen_US
dc.subjectLogistic regressionen_US
dc.subjectThe Sultan Mountainsen_US
dc.titleUsing a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)en_US
dc.typeArticleen_US

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