Accurate and frequent update of surface water has been made possible by remote sensing technology. Index methods are mostly used for surface water estimation which seprates the water and nonwater bodies based on a threshold. Generally thresholds have fixed value but are challenging in case of shades, hills, forest and urban areas. In such case, determination of threshold is done manually which is subjective and can cause a lot variation in area. In order to widen the difference between water and non water class and ease the threshold selection, a combination of muntiple water index can be used. This could widen the gap between classes and the threshold sensitivity can be minimized. In this study, we combined Normalized Difference Water Index (NDWI), Modified NDWI, Water Ratio Index and Normalized Difference Vegetation Index to form a new raster and explore the efficiencty of thresholding compared to individual indices on Landsat 8 Operational Land Imager (OLI) image of Nepal. The combined index shows much better separation of water with it is background and can be further used for automated binary classification of surface water. The process could be very useful in mapping surface water accurately.