Turbidity (TB), an important factor that determines water quality, can influence the water supply of reservoirs. Using a submerged optical sensor, the TB of a body of water can be observed. This study aims to use remote sensing (RS) technology in order to examine TB variations of the water in reservoirs. In general, previous studies have focused on evaluating the relationships among a number of single-spectrum bands and in situ data. In this study, we included the Normalized Difference Vegetation Index (NDVI) among the TB monitoring methods for reservoirs and investigated its practical utility. The ratio of NDVI is between -1 and 1. A negative value indicates water or snow; a value of 0 indicates rock or bare soil; and a positive value indicates a vegetative cover. We consider the value of NDVI to be close to -1 in clean water and close to 0 in turbid water. TB, which is the scattering degree of incident light into water, is observed using a submerged optical sensor. Water appears turbid if floating material or suspended solids are found. Therefore, we use NDVI in this study in an attempt to estimate TB concentration. Images from the Landsat-7 ETM+ satellite were used to observe several important reservoirs in northern Taiwan, and multiple linear regression (MLR) was used for analysis. This study examines the data of 47 samples and found the gaps between the 3 days of the in situ date and the date the images were taken. We found that the NDVI has a negative correlation with TB. After including the NDVI in our model, its explaining ability and improvement rate increased by 11.2 and 8.72 %, respectively. Therefore, using the NDVI can provide additional reflective information, as well as improve the model's accuracy.