Life on Earth depends on water, and nature maintains its constant cycle. Thus, resource management and water quality maintenance are essential. The spectral quality index method is the most widely used of several multispectral image-based water quality mapping techniques. For mapping regional water quality, Sentinel-II data, which is freely available and often accessed, is extremely important because it provides great spatial resolution. In order to determine the water quality features, this study used stepwise discriminant analysis (SDA) for band selection. Using specific bands, new models and statistical regression equations were developed for the following variables: electrical conductivity (EC), temperature, pH, calcium, turbidity, magnesium, total alkalinity, total hardness, dissolved oxygen (DO), and biochemical oxygen demand (BOD). Google Earth Pro was used to determine and verify the water color. The accuracy of the BOD validation was 83.57%. Based on pond water validation datasets, the revised regression equations for temperature, total alkalinity, DO, pH, total hardness, EC, calcium, turbidity, and magnesium showed accuracies of 82.62%, 83.04%, 92.595%, 96.09%, 86.16%, 95.91%, 89.91%, 83.91%, and 97.53%, respectively. With the exception of DO and total hardness, which need minor changes for the best fish production, other metrics were generally satisfactory. As a result, every pond in the research region was judged appropriate for fish culture in the 2019–2020 monsoon, premonsoon, and postmonsoon seasons. An intensive fish production system was identified using the Aquaculture Production Intensity Scale (APIS), which gave adjacent land cover a score of −7 for all seasons.