Statistical estimation of Rosetta branch water quality using multi-spectral data

This research aimed at assessing the approaching of Multi-Spectral Remote Sensing (MS-RS) data for estimating water quality (WQ) of Rosetta branch (RB) using stepwise regression technique. The methodology was based on developing an algorithm for estimating WQ using the Worldview-2 bands reflectance. Results showed that the optical WQ parameters as total suspended solids (TSS) and chlorophyll-a (Chl-a) were acceptably estimated using MS-RS data with high confident. The optical WQ parameters are the most likely affecting the reflected radiation that sensed by the satellite. However, this research expanded to select non-optical WQ parameters such as pH value and biological demand (BOD) that is less likely affecting the radiation reflectance, nevertheless, still correlated to optical WQ parameters. The determination coefficient showed significant high values for ortho-phosphate (OP), total dissolved solids (TDS), Chl-a and pH with different mathematical formulations depending on pollution level. The results showed that, it is promising to perform routine WQ monitoring programs on different water bodies, even for those has relative narrow width as RB, using MS-RS data.