The aim of this study is to investigate the performance of fifteen automatic thresholding methods, namely Huang and Wang's fuzzy thresholding method, inter-mode thresholding method, isodata thresholding method, Li and Tam's thresholding method, maximum entropy thresholding method, mean thresholding method, minimum error thresholding method, minimum thresholding method, moment-preserving thresholding method, Otsu's thresholding method, percentile (p-tile) thresholding method, Renyi's entropy thresholding method, Shanbhag's thresholding method, triangle thresholding method and Yen's thresholding method, for mapping open water body using Sentinel-2 data based on Normalized Difference Water Index (NDWI). Sentinel-2 data was acquired on 22 September 2018 and Lake Salda from Turkey was selected as a test site. Due to the lack of digital reference data of the test site, Support Vector Machine (SVM) classification was implemented to Sentinel-2 data and the classified image was utilized as reference data since previous studies proved that SVM classification provided better results than the thresholding methods. SVM classification results were evaluated using 1000 random points and the Overall Accuracy (OA) and Kappa coefficient were obtained 96.2% and 0.90, respectively. The thresholding methods were assessed using the statistical measures, namely OA, Kappa and Misclassification Error (ME). Considering the remote sensing perspective, all thresholding methods presented satisfying results having at least 92% OA for open water body extraction. The obtained accuracy results showed that minimum thresholding method was the best method among these fifteen algorithms with 0.000264 ME, 99.9355% OA and 0.9987 Kappa. On the other hand, p-tile and Shanbhag's thresholding method provided the worst accuracy results for open water body delineation.